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David Tomé Bartolomeu Simões

Metamorphosis of the Waves: a parallel draw between BECTS and developmental dyslexia with an AERP study

TESE DE DOUTORAMENTO Psicologia

2015

UNIVERSIDADE DO PORTO FACULDADE DE PSICOLOGIA E DE CIÊNCIAS DA

EDUCAÇÃO

Metamorphosis of the Waves:

A parallel draw between BECTS and developmental dyslexia

with an AERP study

David Tomé Bartolomeu Simões

January 2015

This dissertation is submitted for the degree of Doctor in Psychology at the Faculty of Psychology and Educational Sciences, University of Porto, under the supervision of Professor Doutor João Marques-Teixeira and Professor Doutor Fernando Barbosa

v

Chaos is an unintelligible order

O Caos é uma ordem indecifrável

José Saramago – The Double

vii

Resumo

Este estudo teve como objectivo geral investigar o processamento auditivo em

perturbações do neurodesenvolvimento como a dislexia desenvolvimental e a epilepsia

centro-temporal benigna da infância (ECTBI) em crianças de idade escolar.

Está reportado na literatura a existência de défices neurolinguísticos e de

aprendizagem nestas duas perturbações que ocorrem em idade escolar. Embora

consideradas perturbações do neurodesenvolvimento, pouco se sabe sobre possíveis

resultados em técnicas neurofuncionais objectivas na avaliação desses mesmos défices.

A alta resolução temporal de medidas como os potenciais evocados auditivos

relacionados com eventos (PEARE) permite a captação e estudo de processos neuronais

que ocorrem na ordem dos milisegundos, como o processamento auditivo e linguístico.

Como método, recorreu-se ao uso de PEARE, nomeadamente os componentes

N1, N2 e o mismatch negativity (MMN), elicitados por dois paradigmas oddball auditivo

contendo estímulos tonais e estímulos consoante-vogal (CV) em 8 crianças com ECTBI

e 7 crianças com dislexia desenvolvimental, comparadas com um grupo controlo (n=11).

Os resultados foram interpretados considerando o significado funcional dos

componentes analisados e tendo em conta o mais recente modelo neurocognitivo de

processamento auditivo de frases.

Sem descurar a influência de possíveis artefactos metodológicos, é discutida a

possibilidade de os resultados obtidos reflectirem a ocorrência de défices perceptivos

para estímulos tonais e CV (pré-atencionais e de discriminação auditiva) na dislexia

desenvolvimental, relacionados com uma reduzida amplitude de N1. Estes achados

suportam a hipótese de défice de âncora para explicação dos défices neurolinguísticos na

dislexia. O grupo com ECTBI não revelou resultados significativos para o N1, no

entanto, verificaram-se amplitudes aumentadas de N2b que podem estar relacionadas

com um potencial défice dos mecanismos inibitórios dos neurónios piramidais,

recentemente justificados pelo processo de epileptogénese.

Os componentes dos PEARE são medidas heurísticas para o estudo

neurofuncional de perturbações do neurodesenvolvimento como a dislexia

desenvolvimental e a ECTBI. São ainda necessários, mais estudos empíricos que

viii

permitam sustentar a ligação do significado funcional dos componentes aos défices

neurolinguísticos.

Palavras-chave: PEARE, processamento auditivo, neurodesenvolvimento, dislexia

desenvolvimental, epilepsia centro-temporal benigna da infância.

ix

Abstract

This study had the overall objective to investigate the auditory processing in

neurodevelopmental disorders such as developmental dyslexia and benign epilepsy with

centro-temporal spikes (BECTS) in school-age children.

Several authors reported the existence of language and learning impairments in

these two childhood disorders. Although considered neurodevelopmental disorders, little

is known about possible results to objective neurofunctional techniques regarding the

abve stated deficits. Auditory event-related potentials (AERPs) high temporal resolution,

are adequate measures to capture and study neural processes that occur in the order of

milliseconds, such as the auditory and language processing.

As a method, N1, N2 and MMN components, from the AERPs, were elicited by

two auditory oddball paradigm with pure-tone and consonant-vowel stimuli (CV) in 8

children with ECTBI and 7 children with developmental dyslexia, compared with a

control group (n=11). The results were interpreted taking into account the functional

significance of the components enlightened by the neurocognitive model of auditory

sentence processing.

Considering the influence of possible methodological bias, results revealed

perceptual deficits both for pure-tone and CV stimuli (pre-attentional and auditory

discrimination) in developmental dyslexia, related to N1 reduced amplitude. These

findings support the anchor-deficit hypothesis for explanation of neurolinguistic deficits

in dyslexia. The BECTS group revealed no significant results for N1, however, there

have been increased by N2b amplitude which can be related to a potential lack of

inhibitory mechanisms of pyramidal neurons, recently justified by the epileptogenesis

process.

The AERPs components are heuristic measures for the neurofunctional study of

neurodevelopmental disorders such developmental dyslexia and BECTS. However, more

empirical studies are necessary to strengthen the causal link neurofunctional components

and neurolinguistic deficits.

Keywords: AERPs, auditory processing, neurodevelopment, developmental dyslexia,

benign epilepsy centro-temporal spikes.

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Résumé

Ce étude à tenu comme objectif principale rechercher le processement auditif en

perturbations de le neurodéveloppment comme la disléxie du développment et la

épilepsie centro-temporal benigne de l’enfance (ECTBE) chez les enfants d’âge scolaire.

Sont rapportés dans la littérature léxistence de déficits neurolinguistiques et de

l’apprentissage dans ces deux troubles qui se produisent à l’âge scolaire. Bien que

considérés comme des troubles du développement neurologique, on en sait peu sur les

résultats possibles sur les techniques neurofonctionnels objectives lors de l’évaluation de

ces deficits. La haute resolution temporelle de mesures comme les potentiels évoquée

auditifs liés aux événements (PEALE) peut capturer et étudier les processus neuronaux

qui se produisent dans l’ordre de milliseconds, comme le traitement auditif et la langue.

Comme procédé, on a eu recours à l’utilisation du PEALE, comprenant des

composants N1, N2 et le mismatch negativity (MMN), provoquée par deux paradigmes

oddball auditives contenant stimuli sonores et stimuli consonne-voyelle (CV) dans 8

enfants atteints de ECTBE et 7 enfants avec disléxie du développment, par rapport au

groupe témoin (n=11). Les résultats ont été interprétés compte tenu de l’importance

fonctionnelle des composants analysé et en tenant compte du dernier modèle

neurocognitif de traitment auditif des phrases.

Tout en considérant l’influence de possibles artefacts méthodologiques, on

discute de la possibilité de les résultats obtenus reflètent l’apparition de déficits

perceptifs pour les sons et CV (pré-attentionnel et la discrimination auditive) en la

disléxie du development, associée à une amplitude réduite du N1. Ces résultats

soutiennent l’hypothèse déficit-anchor pour l’explication des deficits neurolinguistiques

dans la dyslexie. Le groupe avec ECTBE révélé aucun résultat significatif pour N1,

cependant, il ya une augmentation des amplitudes N2b qui peut être lié à un écart

potential de les mécanismes inhibiteurs des neurons pyramidaux récemment justifié par

processus d’épileptogenèse.

Les composants de PEALE sont mesures heuristiques pour l’étude

neurofuncionnal des perturbations de le neurodevelopment comme la disléxie du

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development et la ECTBE. Il reste à plus études empiriques pour renforcer la

signification fonctionnelle des composants avec des deficits neurolinguistiques.

Mot-clé: PEALE, traitement auditif, neurodéveloppment, disléxie du développment,

épilepsie centro-temporal benigne de l’enfance.

xiii

Prologue

The work described within this thesis was conducted at the Laboratory of

Neuropsychophysiology, Faculty of Psychology and Educational Sciences, University of

Porto, Portugal, during the period 2009–2014 under the supervision of Prof. Doutor João

Marques-Teixeira and Prof. Doutor Fernando Barbosa.

The content of this thesis reflects the views, the work and the author's

interpretations at the time of delivery. This thesis may contain inaccuracies, both

conceptual and methodological, that may have been identified at a later time from

delivery. Therefore, any use of their content should be exercised with caution.

By submitting this thesis, the author states that it is the result of his own work,

contains original contributions and all sources used are recognized, finding such sources

properly cited in the text and identified in the reference section. The author states that

does not disclose in this thesis any content for which reproduction is prohibited by

copyright or industrial property without proper authorization, as specifically indicated in

text and Addendum.

This dissertation follows the 6th edition of the Publication Manual of American

Psychological Association, except the published and submitted articles.

This dissertation does not exceed the limit of length prescribed by the Doctor of

Psychology Degree Scientific Council. The copyright of this thesis rests with the author.

No quotation from it should be published without his prior written consent and

publication of information derived from it should acknowledge the original source.

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Acknowledgements

First, I would like to express my gratitude to my supervisors, Prof. Doutor João

Marques-Teixeira and Prof. Doutor Fernando Barbosa, for their invaluable support,

insight, and guidance throughout this project. Providing constructive criticisms, feedback

on time, and always showing appreciation and respect for my work.

Not least, I want to thank all participants; in particular the children, for revealing

such patience, responsability, and maturity. Their participation was vital to the

achievement of this work.

Secondly, I wish to thank my friends and colleagues from ESTSP-IPP and

FPCEUP who helped me, in different ways, for their constant encouragement and

support during this path; in particular, Paula, Diana, Ana Rita, Paulo, Carina, Ana

Sucena, Vasco, and Andreia.

A special gratitude for their professional contribution: Brígida Patrício, Maria

Celeste Vieira, José Mendes-Ribeiro, Ilídio Pereira, Kamila Nowak, Mafalda Sampaio,

and Pedro Moreira.

Finally, I would like to express my deepest gratitude to my wife Teresa. Though

our courtship last the same time of this work, our love shall last forever.

Part of this research was made possible by a grant generously provided by the

School of Allied Health Technologies, supported by the Polytechnic Institute of Porto

(Portugal). Express my gratitude to Prof. Doutor Agostinho Cruz, Prof. Doutor António

Marques, Drª. Carla Saraiva, and my colleagues Professor Paula Lopes, Professor Paulo

Cardoso do Carmo, Drª. Natália Oliveira, and Drª. Ana Barbosa.

xvii

This work is dedicated to a generation of young Portuguese, who needed to leave

their country to follow and achieve their dreams

Este trabalho é dedicado a toda uma geração de jovens portugueses, que necessitou

de sair do seu país para seguir e concretizar os seus sonhos

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List of Original Publications

I. Tomé, D., Cudna, A., Barbosa, F., Marques-Teixeira, J. (submitted). Auditory event-

related potentials in an idiopathic generalized epilepsy case study and relatives: a

putative endophenotype?

II. Tomé, D., Barbosa, F., Nowak, K., Marques-Teixeira, J. (2014). The development of

the N1 and N2 components in auditory oddball paradigms: a systematic review with

narrative analysis and suggested normative values. Journal of Neural Transmission,

121(7). doi:10.1007/s00702-014-1258-3

III. Tomé, D., Marques-Teixeira, J., & Barbosa, F. (2012). Temporal Lobe Epilepsy in

Childhood – a study model of auditory processing. Journal of Neurology &

Neurophysiology, 3(2). doi:http://dx.doi.org/10.4172/2155-9562.1000123

IV. Tomé, D., Patrício, B., Barbosa, F., Marques-Teixeira, J. (submitted). Mismatch

negativity and N2 elicited by pure-tone and speech sounds in anomic aphasia: a case

study

V. Tomé, D., Moreira, P., Marques-Teixeira, J., Barbosa, F., Jääskeläinen, S. (2013).

Mismatch Negativity in Temporal Lobe Epilepsy in Childhood: a proposed

paradigm for testing central auditory processing. Journal of Hearing Sciences, 3(2):

9-15

VI. Tomé, D., Sampaio, M., Mendes-Ribeiro, J., Barbosa, F., Marques-Teixeira, J.

(2014). Auditory event-related potentials in children with benign epilepsy with

centro-temporal spikes. Epilepsy Research, 108, 1945-1949.

doi:http://dx.doi.org/10.1016/j.eplepsyres.2014.09.021

VII. Tomé, D., Vieira, C., Barbosa, F., & Marques-Teixeira, J. (in preparation). Auditory

event-related potentials in BECTS and developmental dyslexia: a progressive

insight.

1

TABLE OF CONTENTS

Resumo ......................................................................................................................... vii

Abstract ........................................................................................................................... ix

Résumé ........................................................................................................................... xi

Prologue ....................................................................................................................... xiii

Acknowledgements ....................................................................................................... xv

List of Original Publications ........................................................................................ xix

Abbreviations ................................................................................................................... 5

List of Symbols .............................................................................................................. 11

List of Figures ................................................................................................................ 13

List of Tables ................................................................................................................. 15

INTRODUCTION ....................................................................................................... 17

CHAPTER I – THE PROBLEM ............................................................................... 27

The Research Problem .............................................................................................. 29

Biomarkers and Endophenotypes.............................................................................. 37

Paper I ....................................................................................................................... 46

CHAPTER II – LANGUAGE .................................................................................... 59

Auditory Processing: anatomy and physiology ........................................................ 61

The Conceptualization & Neurodevelopment of Language ..................................... 72

So, What Was Language’s Function? ................................................................ 75

But What is Language? ...................................................................................... 78

Is Language Neurolaterality and Handedness Related? ..................................... 87

CHAPTER III – NEUROPSYCHOPHYSIOLOGY OF AUDITORY

PROCESSING ............................................................................................................. 91

The Auditory Evoked Brain Responses: short, middle, and long latency ................ 94

2

Auditory Evoked Potentials Ethnicity ................................................................ 96

The N1 wave .................................................................................................... 100

The P2 wave ..................................................................................................... 101

The N2 wave .................................................................................................... 101

The MMN wave ............................................................................................... 102

The P3 wave ..................................................................................................... 104

Other Late AERPs ............................................................................................ 105

Paper II .................................................................................................................... 113

Psycholinguistic Models and Language Processing ............................................... 150

Clinical Models for Understanding and Applying: conceptus et constructus from

Temporal Lobe Epilepsy, Aphasia, and Dyslexia ................................................... 159

Dyslexia ............................................................................................................ 161

The Phantom of Comorbidity ........................................................................... 168

Paper III ................................................................................................................... 171

Paper IV .................................................................................................................. 181

CHAPTER IV – METHODOLOGY ....................................................................... 199

Aims of the Work .................................................................................................... 201

Methodology ........................................................................................................... 202

Participants .............................................................................................................. 203

Experimental Design and Procedures ..................................................................... 204

Paper V .................................................................................................................... 211

CHAPTER V – RESULTS ....................................................................................... 229

The Results .............................................................................................................. 231

Amplitude ................................................................................................................ 236

Latency .................................................................................................................... 237

3

Paper VI .................................................................................................................. 243

CHAPTER VI – DISCUSSION ................................................................................ 255

Discussion of Findings ............................................................................................ 256

Implications and Further Research ......................................................................... 261

Conclusion .............................................................................................................. 266

REFERENCES .......................................................................................................... 269

ADDENDUM

5

Abbreviations

A1 – left earlobe electrode position

A2 – right earlobe electrode position

ABR – auditory brainstem response

AED – antiepileptic drugs

AEP – auditory evoked potential

AERP – auditory event related potential

ADHD – attention-deficit hyperactivity disorder

ALLR – auditory long latency response

AMLR – auditory middle latency response

APD – auditory processing disorders

ASHA – American Speech-Language-Hearing Association

BECTS – benign epilepsy with centro-temporal spikes

BIAP – Bureau International D’Audiophonologie

Ca2+ – calcium

CAE – childhood absence epilepsy

CANS – central auditory nervous system

CAP – central auditory processing

6

CAPD – central auditory processing disorder

CBZ – carbamazepine

CG – control group

cit. – citatum

Cl- – chlorine

cm – centimeter

cm3 – cubic centimeter

CNS – central nervous system

Cz – vertex electrode position

dB - deciBel

dB HL – deciBel Hearing Level

dB SPL – deciBel Sound Pressure Level

DSI – diffusion spectrum imaging

DSM – Diagnostic and Statistical Manual of Mental Disorders

DTI – diffusion tensor imaging

ECoG – electrocorticography

EEG – Electroencephalography

e.g. – exempli gratia (for example)

7

EG – experimental group

EOG - electrooculogram

EPSP – excitatory postsynaptic potential

ESTSP-IPP – School of Allied Health Technologies, Polytechnic Institute of Porto

et al. – et alli (and others)

fMRI – functional magnetic resonance imaging

Fpz – forehead midline electode position 10% distance above the nasion

Fz – frontal midline electrode position

GABA – gamma aminobutyric acid

IBE – International Bureau for Epilepsy

IC – inferior colicullus

ICD – International Classification of Diseases

ICF – International Classification of Functioning, Disability and Health

ICIDH – International Classification of Impairments, Disabilities and Handicaps

i.e. – id est (that is/to say)

iEEG – intracranial electroencephalography

ILAE – International League Against Epilepsy

IPSP – inhibitory postsynaptic potential

8

IQ – intelligence quotient

ISI – interstimulus interval

JAE – juvenile absence epilepsy

JME – juvenile myoclonic epilepsy

K+ – potassium

LGN – lateral geniculate nucleus

M – mean

M1 – left mastoid electrode position

M2 – right mastoid electrode position

MEG – magnetoencephalography

MGB – medial geniculate body

MMN – Mismatch Negativity

MRI – magnetic resonance imaging

ms – milisseconds

mV – milivolts

Na+ – sodium

OEA – otoacoustic emission

Oz – electrode position 10% distance above the inion

9

p – p-value

PANS – peripheral auditory nervous system

PET – positron emission tomography

RATP – rapid auditory temporal processing theory

RD – reading disorders

SC – superior colliculus

SD – standard deviation

SOA – stimulus onset asynchrony

SOC – superior olivar complex

SRT – Speech Reception Threshold

STG – superior temporal gyrus

STP – supratemporal planum

TLE – temporal lobe epilepsy

VEP – visual evoked potential

WHO – World Health Organization

µV – microvolts

11

List of Symbols

= is equal to

> greater-than

< less-than

≥ equal or greater-than

≤ equal or less-than

% percent

+ plus

13

List of Figures

Figure 1. a | Cut-away view of the human inner ear. b | Section of the cochlear spiral

showing the organ of Corti, which contains the hair cells. c | Auditory pathways and

centres in the brain. (Ng, Kelley & Forrest, 2013).

Figure 2. Auditory pathways (First Years, 2012).

Figure 3. Subdivisions of auditory cortex and processing streams in primates (Kaas &

Hackett, 2000).

Figure 4. Auditory evoked potentials.

Figure 5. Language’s three dynamical systems operating on three different timescales:

individual, cultural and biological evolution (Kirby, 2007).

Figure 6. The basic design of language (Berwick et al., 2013; with permission,

appendix 7).

Figure 7. Neurocognitive model of auditory sentence processing (adapted from

Friederici, 2002; with permission, appendix 8).

Figure 8. The cortical language circuit, schematic view of the left hemisphere

(Friederici, 2012; courtesy, appendix 9).

Figure 9. Design scheme of stimuli presentation for both experiments.

Figure 10. Electrode’s placement with ground electrode at Oz (left figure), young

participant comfortably sitted in an armchair after data acquisition in the laboratory

(right figure).

http://www.pnas.org/search?author1=Jon+H.+Kaas&sortspec=date&submit=Submit

14

Figure 11. Schematic representation of an ERP waveform, indicating different

procedures for component quantification and measure after stimulus onset: peak

latency, peak-to-peak, base-to-peak and area (Fabiani et al., 2007).

Figure 12. Grand average deviant waveforms for pure-tone (a) and consonant-vowel

(CV; b) paradigm for the BECTS group (red solid line), the control group (blue solid

line), and the dyslexia group (black solid line). Grand average MMN difference

waveforms are represented in the right column.

Figure 13. N1 mean amplitude across electrodes for CV (right) and pure-tones (left)

(error bars represent a 95% confidence interval).

Figure 14. N2b mean latency for electrode and participant group (control,

BECTS/Epilepsy and dyslexic).

Figure 15. N2b mean latency across electrodes for CV (right) and pure-tones (left)


Figure 16. MMN mean latency across electrodes for CV (right) and pure-tones (left)


Figure 17. Topographic voltage map of grand average deviant waveforms to pure-

tones in a 141 ms time window [113-254 ms].

Figure 18. Topographic voltage map of grand average deviant waveforms to

consonant-vowel stimuli in a 141 ms time window [117-258 ms].

Figure 19. Topographic voltage map of MMN to pure-tones in a 140 ms time window

[102-242 ms].

Figure 20. Topographic voltage map of MMN to consonant-vowel stimuli in a 140 ms

time window [102-242 ms].

15

List of Tables

Table 1. Auditory processing structures and its evoked response: assessment and

dysfunction (adapted from Bailey (2010), with permission; see appendix 6).

Table 2. Clinical characteristics, medications and outcome of each participant group.

Table 3. Mean peak-to-peak amplitude and peak latencies of the N1, N2 and MMN

wave in Fpz, Fz and Cz, for the BECTS, dyslexia and the comparison/control group to

pure-tone and speech (consonant-vowel) paradigms.

17

Introduction

18

There are eight major transitions in the evolution of life in our planet that signal

radical changes in the way evolution works. For example, the replicating molecules

changed to populations of molecules, the RNA emerged in DNA, solitary individuals

to colonies, etc., and the 8th major transition concerns to the emergence of Language

(Maynard-Smith & Szathmáry, 1997).

All the transitions underlie some type of new mechanism for the transmission

of information. Language provided a novel mechanism, essentially enabling a system

of cultural transmission and storage of complex information with unlimited

transgerational and heredity transmission. It allows us to transcend our communication

limits in space and time. Once something is written down, it can be preserved, copied

and distributed. Though with no causal relation, this might be one explanation for the

primate societies change to human societies (Kirby, 2007). We acquired large amounts

of knowledge at a high speed, and thus learnt from other’s successes and failures.

Consequently, proficient literacy has become an essential prerequisite to obtain social

and economic success in our knowledge-technology based society (Froyen, 2009).

Since then, a structured education of language revealed that some children can

have difficulties in acquiring different skills. Whether in auditory memory, auditory

attention, sequencing, or higher order language processes including reading or writing

(Bailey, 2010). A crucial phase during the development towards successful acquisition

of reading and writing skills is learning the associations between letters and speech

sounds (Froyen, 2009; Vellutino, Fletcher, Snowling, & Scanlon, 2004), i.e. the

smallest units of respectively written and spoken language. Moreover, it is suggested

that difficulties with associating letters and speech sounds are a cause of difficulties in

learning to read in neurodevelopmental disorders such as developmental dyslexia

(Snowling, 1980). In addition, language impairments started to be observed in a wider

range of clinical conditions (e.g., neurology and psychiatry) such as ADHD, epilepsy,

autism, or even schizophrenia. Therefore, language as a mental process that affects

behavior, underpinned and dynamically emerged by different neural processes such as

attention, memory, perception, and metacognition, started to be seen has a highly

important human ability for “today’s modern society” that required methods and tools

to assess it.

19

Right from birth, our brain is highly structured, to quickly acquire sophisticated

representations inherited from our evolution. We developed the concepts of objects, of

space, of time, of number, of linguistic structures and of social relations. Reading,

writing or arithmetic are human inventions. Most children, with the right training at the

right time, acquire language and learn to read with apparent ease (McArthur, Atkinson,

& Ellis, 2009). However, some children with neurodevelopmental disorders such as

bening epilepsy with centro-temporal spikes and dyslexia may find it difficult to learn

their native language and learn new skills in general. Behavioural measures lack to

discriminate language impairments between different disorders, differentiate the

underlying processes of reading and speech, and underpinne theoretical models of

language and brain development entailing several levels of brain organization.

An approach that provides a more direct measurement of brain function is the

use of psychophysiological measures. Two measures of brain activity have been used

that are derived from electrical potential activity occurring on the scalp: the

electroencephalogram (EEG) and scalp-recorded event related potentials (ERPs).

Recent years have seen a growing use of electrophysiological techniques in research

on the neurobiological mechanisms underlying language-learning disorders. Event-

related potentials (ERPs) provide sensitive neurophysiological measures of the timing

and cortical utilization of different stages of cognitive processing, and thus are well

suited for the study of normal cognitive development, as well as in the investigation of

cognitive disturbances in childhood (e.g., Banaschewski & Brandeis, 2007; Habib,

2000; Martineau et al., 1992; Stauder, Molenaar, & van der Molen, 1993).

Furthermore, longitudinal studies confirm that infants’ AERPs to speech sounds also

predict (in a statistical sense) their subsequent language development, such as verbal

memory at age five (Guttorm et al., 2005) or reading skills at age eight (Molfese,

2000).

Deficient letter–speech sound associations are considered to be the link

between often observed phonological deficits and difficulties with learning to read

(Snowling, 1980; Vellutino et al., 2004). However, direct experimental evidence for

this assumption is currently lacking. Thus, auditory processing deficits in rapid

temporal processing, formation of stable representations in the brain and mapping

phonemes on to letters are being pointed as possible causal risk factors to speech

20

language impairments (SLI), speech sound disorder (SSD), specific reading disability

(SRD), and developmental dyslexia (McArthur, Atkinson, & Ellis, 2009).

Studies in developmental dyslexia have provided mixed findings in AERPs,

thus with different components interpretation. The MMN seems to be the most

consistent and with consensual interpretations. Abnormalities of the MMN correlated

with the degree of phonological impairment (Baldeweg, Richardson, Watkins, Foale,

& Gruzelier, 1999; Kraus et al., 1996), pointing to a selective processing deficit at an

earlier phonetic level as a possible source of the difficulties in learning to read, while

at a later lexical level information seems to be processed normally (Bonte & Blomert,

2004a). However, MMN findings seem to not completely explain the very single

sound unit processing and discrimination in early stages.

Regarding benign epilepsy with centro-temporal spikes (BECTS) the studies

are scarce but with consistent results, indicating a neocortical excitability, however

none explain how can AERPs be clinically useful.

A feasible protocol diagnosis and treatment monitoring method is still lacking.

Further, very few studies actually investigated the central auditory processing with

AERPs in these disorders, much less in children and between disorders. In clinical

practice very similar EEG curves, are reported among school-aged children with

rolandic epilepsy and and children with other developmental disorders such as dyslexia

and autism (Canavese et al., 2007; Oliveira, Neri, Capelatto, Guimarães, & Guerreiro,

2014; Spence & Schneider, 2009). To our knowledge, no studies have established a

comparison of passive AERPs between developmental dyslexia and BECTS discussed

with a neurocognitive auditory sentence-processing model to interpret and explain the

neurophysiological findings.

In clinical areas such as Audiology and Neurology, the neurophysiological

rational of brains’ funtion is limited by the so-called evoked potentials. Mainly, in the

assessment of brain funtions such as attention, memory, and cognition by different

sensory modalities (e.g., auditory and visual). Event-related potentials largely

underpinned and construed by Psychology, can be highly valuable in assessing the

different stages of auditory and language processing for a better diagnosis, prognosis

and treatment strategies in neurodevelopmental disorders, e.g., dyslexia, epilepsy,

autism, and ADHD. But also, in other clinical conditions such as aphasia, epilepsy,

21

schizophrenia, dementia, and depression. Moreover, research in translational medicine

may test and verify theorical neurofunctional models.

The overall aim of this research was to investigate (describe and explain)

auditory event-related potentials (N1, N2b, and MMN) in a passive auditory oddball

paradigm, and their clinical usefulness (predict) in neurodevelopmental disorders, such

as BECTS and developmental dyslexia, and hypothesize as neurophysiological

endophenotypes or biomarkers of auditory processing dysfunction. Furthermore, we

will discuss putative neurophysiological deficits in developmental dyslexia as a

possible explanation for phonological deficit hypothesis and the anchoring-deficit

hypothesis, ocurring in the very early stages of cortical auditory processing.

Along in this work we will answer the following hypothesis and objectives

(summarized in Chapter IV):

1. Examine and investigate AERPs as possible endophenotypes or biomarkers

for auditory processing dysfunction due to neuronal systems disorders

(epilepsy, aphasia, and dyslexia);

2. Investigate and document putative changes in AERPs components (N1, N2b,

and MMN) in a group of children with BECTS;

3. Suggest normative values for the development of N1 and N2 components

across the lifespan;


and MMN) in a group of children with developmental dyslexia;

5. Discuss and relate the neurophysiopathological mechanisms of language

deficits (developmental dyslexia) explained by anchoring-deficit hypothesis,

phonological defict hypothesis, and RAPT deficit by AERPs results;

6. Discuss an eventual neuropsychophysiological parallel between two school

age neurodevelopmental disorders (BECTS and developmental dyslexia).

These are comprehensive and transversal subjects that require an unanimously

approach, methodology, and discussion.

Chapter I provide the necessary background, review some of the relevant

literature, and introduce the specific research questions that we addressed and that

motivated this work. Moreover, we will hypothesize and suggest AERPs as possible

biomarkers and endophenotypes in a case study of generalized epilepsy in order to

22

illustrate the theorical background, and arouse future empirical research (Paper;

objective 1).

The first part of Chapter II is a general description of the human ear anatomy

and function, essential for the neuroanatomical basis of this thesis. Hearing loss is

normaly the first problem to be screened before diagnosing a neurodevelopmental

disorder. The last part of Chapter II explores the concept of Language and its inherent

neurodevelopmental processes, focusing on its function, importance, and wide

dynamic complexity in neuroscientific approach.

The Chapter III focuses on electroencephalogram as a non-invasive technique

and auditory event-related potentials as a measure of brain response to auditory stimuli

and its underlying components. This chapter discusses the importance in assessing

central auditory processing, AERPs components’ contribution to auditory and

language processing models, and a narrative review on N1 and N2 development across

lifespan and possible normative values (Paper II; objective 3). Afterwards, the main

focus, will be explaining the processes that take place in language cortex during

auditory sentence processing. Lastly, the chapter ends with a discussion and inference

on clinical models such as temporal lobe epilepsy (Paper III; objective 1), dyslexia,

and a case study of anomic aphasia (Paper IV; objective 1) to the understanding of

putative changes in AERPs and as promising clinical indexing measure in the

assessment of central auditory processing among different clinical conditions and

populations.

Case studies are criticized because data collected cannot necessarily be

generalised to the wider population, and because it is also very difficult to draw a

definite cause/effect. The two case studies above stated were conducted, because case

study design is deeper, thus more appropriate to scientists adapt ideas and produce

novel hypotheses which can be used for later testing (Boyd, 2014). Moreover, they

required a thorough and idiosyncratic approach to each clinical case. And intended to

suggest AERPs as heuristic measures to endorse future translational empirical studies

on endophenotypes and biomarkers. Though this was not the ultimate purpose of this

work, we aspire to research this issue in a close future.

The procedures and inclusion/exclusion criteria were identical for all case and

empirical studies within this thesis. A detailed description is made in Chapter IV, were

23

we specify the aims of this thesis, hypothesis addressed by the technique and measures

used, we describe the experimental design, procedures, and inclusion/exclusion

criteria. This chapter ends with Paper V, whose purpose was a peer-validation and

publishing of the procedures.

Chapter V presents the results of the empirical studies (objectives 2 and 4), and

statistical tests used. In addition, results and discussion regarding BECTS were timely

published in a specialized journal (Paper VI; objective 2).

Finally, Chapter VI provides the overall discussion, main conclusions, study

limitations, implications and further research. Specifically, results are interpreted

enlightened by the neurocognitive auditory sentence-processing model in order to

achieve a deep discussion regarding the above stated dyslexia’s deficit hypothesis

theories relating to AERPs components meaning. This chapter main content will form

Paper’s VII base discussion (in preparation; objectives 4, 5, and 6). We can advance

that though AERPs are not pathognomonic, they can identify auditory perceptual

deficits and reveal neocortical excitability processes.

One of the main challenges that ERPs face at the moment is the transposition to

clinical practice, with a high risk of some erroneous transduction of meaning.

In Psychology, the dimensions of sensitivity and specificity are related but not

synonymous with those used in either signal detection theory or clinical decision

analysis. Sensitivity, in this context, refers to likelihood that a physiological response

will covary with any psychological element. Specificity, in contrast, refers to the

probability that a physiological response will be linked to a particular psychological

element or set of elements (Cacioppo, Tassinary, & Berntson, 2007).

The larger social, cultural, and interpersonal contexts are recognized as

powerful determinants of brain and behavior. Therefore, the physiological and

psychological domains are studied bearing in mind the context dependency, in order to

establish a correct psychophysiological relationship. This led to four categories of

psychophysiological relationships (Cacioppo, Tassinary, & Berntson, 2007): the

outcome (is a situation-specific or context-dependent relationship, defined as a many-

to-one, meaning two or more psychological elements are associated with the same

subset of elements in the physiological domain); marker is defined as a one-to-one,

one psychological element is related to one physiological element of the set, and

24

context-dependent; concomitant (or correlate/coexists) is defined as a many-to-one,

cross-situational (context-independent); and invariant relationship, refers to an

isomorphic (one-to-one), context-independent (cross-situational) association.

Only the relations one-to-one and many-to-one allow a formal specification of

psychological elements as a function of physiological elements (Cacioppo &

Tassinary, 1990). But, if we consider the context, the main goal would be the search to

establish one-to-one relationship, specially an invariant. However, this is not the only

way to acess new information and clinical knowledge. Physiological concomitants,

markers, and outcomes can also provide important, unattainable and sometimes

unexpected information about elements in the psychological domain. They are all valid

steps for science, some are small and others bigger, but they are all steps.

The relationships between the physiological data and theoretical construct

(psychological event) have a limited range of validity, because the relationship is clear

only in certain well-prescribed assessment contexts. Therefore, the ERPs have the

major advantage to simplify and limit the relation between psychological and

physiological phenomena in a more interpretable form within specific assessment and

controlled contexts.

On the other hand, in clinical context, sensitivity and specificity are statistical

measures of the performance (classification function). Sensitivity (also called the true

positive rate) of a test/procedure, measures the proportion of positives that are

correctly identified as such by that test/procedure (e.g., sick people correctly diagnosed

as sick). Specificity (sometimes called the true negative rate) measures the proportion

of negatives, which are correctly identified as such (e.g., the percentage of healthy

people who are correctly identified as not having the condition).

The sensitivity and specificity of a quantitative test are dependent on the cut-off

value above or below which the test is positive. In general, the higher the sensitivity,

the lower the specificity, and vice versa. Positive and negative predictive values are

useful when considering the value of a test to a clinician. They are dependent on the

prevalence of the disease in the population of interest (Lalkhen & McCluskey, 2008).

Many clinical tests are used to confirm or refute the presence of a disease or

further the diagnostic process. Ideally, such tests correctly identify all patients with the

disease, and similarly correctly identify all individuals who are disease free. Most

25

clinical tests fall short of this ideal, but economic impositions mainly, always require

and allow the implementation of tests/procedures with a high rate of positive

predictive value. ERPs are sometimes unfairly included in this sieve.

As a secondary goal of this work, we intend to show that AERPs components

are valuable measures to explain and assess language impairments in

neurodevelopmental disorders such as developmental dyslexia and BECTS.

27

Chapter I

The Problem

29

This Chapter provides the necessary background, reviews some of the relevant

literature, and introduces the specific research questions that we addressed and that

motivated this work. Moreover, we hypothesize the advantages and surplus value of

endophenotype’s and biomarker’s research in neurodevelopmental disorders. Paper I,

at the end of this chapter, will explore and hypothesize in a case study format, AERPs

as putative neurophysiologic endophenotypes in generalized epilepsy. Exploring and

testing the hypothesis that AERPs are adequate measures, with high temporal

resolution, to study neurophysiological disorders.

The Research Problem

The last century was considered the century of Language and Communication.

Now it seems we live in the decade of social networks, online telegraphic writing and

quick interpretations of content and emotional states of various contacts or “Facebook

friends”, per minute. A different form of communication, but still we need more than

ever to communicate and acquire this capacity in the very first years of life. Most of

the learning and development takes place by taking in information through the sense of

hearing using our ears, through the sense of vision using our eyes and through touch

and movement. Of all the senses, these, more than any of the other senses, determine

how well we develop from a newborn baby to a well-adjusted adult that can function

successfully in life (Goldfeld, 1997).

As a natural born language learning specie, during childhood, almost all

learning take place through interaction with the senses and in particular, by the speech

through hearing and by visual interaction through the eyes. The interaction, integration

and complementarity of these two senses allow us to hear and distinguish the

surrounding sounds, assigning an association and visual representation that will

progressively facilitate the interaction with the environment as well as the acquisition

and development of language (as an ability), which in turn acquiesces the acquisition

and the use of more complex communication systems (human language) (Musiek &

Rintelmann, 2001). Despite the new technological advances, the written word (written

language) continues to form the foundation of our communication and development.

30

If these key senses do not operate effectively, then learning will be

compromised. However, ineffective hearing or vision does not necessarily mean

hearing loss or the need to wear glasses. Today's modern education and child care

ascribe to much emphasis and focus on what the child cannot do, to assign the fastest

possible diagnosis, rather than what is happening or can the child do in other context.

For, example in ADHD often the child can concentrate on a task under certain

circumstances, but fails to so in the school or when required to do homework.

This is common in neurodevelopmental disorders, were sensory information (e.g.,

hearing and vision) have normal input, but the signal from peripheral organs (e.g., eyes

and cochlea) to the brain is not being correctly processed, thus causing a wide

spectrum of learning, cognitive, and/or social behavior difficulties.

People working, caring or investigating neurodevelopmental childhood

disorders should always bear in mind that while an adult mostly manages to perceive

and describe what is going wrong with himself, from a child this rarely happens. A

child does not know what is wrong with her, because she has not yet grasped labeled

normal behaviors. The suspicious of language deficits, starts in preschool with

language delay or maladaptive behavior. Already during school age, the latter deficits

are perceived by difficulties in concentrating and acquisition of new knowledge.

It is possible that language arised from the joint evolution of gestures and

vocalizations, which may explain the correlation between handedness, verbal language

and the signs predominantly processed in the left hemisphere. A wider cortical left

temporal area was already found in Homo erectus (between 300 000 and 500 000

years), compared to right hemisphere, currently resulting in the language dominant left

hemisphere in about 90% of cases (Knecht et al., 2000). This dominance manifests

itself in many other areas such as the processing of information in identifying,

decoding and encoding symbolic/linguistic elements and codes. On the other hand, the

right hemisphere is more specialized for elements or “affective” components of

language (implemented in speech) as prosody, tone, rhythm, intonation and melody of

speech. Certain aspects of language acquisition, including the time of its inception, are

universal and innately determined, while others - such as language, dialect and accent -

are determined and influenced by individual, social and environmental factors (Plaja,

Rabassa, & Serrat, 2006).

31

In evolution, Nature seems to demand always a trade (e.g., having wings to fly

one cannot swim, living in the deep bottom of the oceans means one cannot see the

sunlight), except for Darwinian Demon (Law, 1979). Such is the rule of balance and

natural order. According to Crow (1998) due to underlying hemispheric

differentiation, brain function abnormalities may occur as the disruption of the

mechanism of “indexicality” that allows the speaker to distinguish his thoughts from

the speech output that he generates and the speech input that he receives and decodes

from others. The nuclear symptoms of schizophrenia. This is “the price that Homo

sapiens pays for language” (Crow, 1997, p.127). The disadvantage associated with this

biological predisposition should then be balanced with an adaptive advantage - the

ability to develop Language.

Keeping the above in mind, neurodevelopmental disorders such as dyslexia,

temporal lobe and rolandic epilepsy, ADHD, and autism could also be part of our

“debt” for acquiring and use a complex system of communication (Done, Crow,

Johnstone, & Sacker, 1994; Leask, Done, & Crow, 2002). In an illiterate society there

should be no dyslexia and ADHD would probably be considered misbehavior.

Several studies have reported neurolinguistic deficits in children with

neurodevelopmental disorders. Today is the unanimous that above stated disorders can

be a barrier to neurolinguistic development (Schlindwein-Zanini, Izquierdo, Portuguez,

& Cammarota, 2009). However, neurobiology presents a difficult problem for

linguistics. Biology imposes a number of constraints on our understanding of cognitive

processes and limits the plausibility of cognitive models that remain agnostic to

biological instantiations (Kiggins, Comins, & Gentner, 2012). As a result, today we

have various cognitive and psycholinguistic models for language acquisition, language

processing, auditory processing, speech processing and speech production, but with

fragile underpinning when applied to clinical practice, to comorbidity cases or

different techniques results (e.g., EEG/ERP, MEG and fMRI). The inconsistencies

between theoretical and behavioral linguistics are longstanding.

Social behavior, interactions, and quality of life can also be affected in

neurodevelopmental disorders. The Holistic Theory of Health, perspectives “Man” as a

socially integrated being, which performs a number of daily activities, engaging in

different personal and institutional relationships. In this perspective, a person is

32

healthy if it feels functional in its relational context (Nordenfelt, 1995). The “ability” is

the central term in defining health. Nordenfelt (1995) defines it:

“An individual is healthy iff the individual has the (mental and physical) ability

to reach his or her vital goals, given acceptable circumstances” (p. 97).

That is, someone who feels that is showing its own value – health is

nomopoiesis, a situation in which an individual imposes to herself/himself to behave in

compliance with a general primary rule. Thus correlated with life quality. For example,

epilepsy is a neurological disorder that can manifest itself in various types of seizures,

making it the most dramatic situation when we refer to epileptic syndromes that

developed in childhood.

Because some seizures are accompanied by brain injuries, many patients have

restricted daily activities, such as the inaccessibility of some professions or vehicle

driving ban, affecting self-esteem and therefore quality of life (for a deeper view on

this issue see appendix 1). In children, the restrictions can be bathing or swimming

always accompanied, no cycling, cannot climb trees or walls, or other similar games.

These restrictions are often misunderstood and perceived as “unfair” by children. In

these cases, parents and educators should keep in mind that too many prohibitions can

led to over protected and dependent children, with future consequences for their

psychological development and social life.

Quality of life in epilepsy, as in other areas, is multifactorial, suffering

influences of different aspects. Globally, the main factors that condition these patients

and their daily lives relate to the type and frequency of seizures, the side-effects of

anti-epileptic medication, cognitive and/or intellectual deficits, the relational

dynamics, stigma and social exclusion (Williams et al., 2003). Sillanpää (2004)

conducted a study in order to analyse the occurrence of learning disabilities in adults

with childhood epilepsy onset and their likely medical and social results. The results

showed that 66% of patients had some type of learning difficulty. From patients with

less severe epilepsy, 19% had problems in reading, 18% in writing and 15% to the

level of discourse.

At the time of choosing the AED for seizure control, cognitive and behavioral

impacts should be taken into account, as they can have serious consequences for the

33

intellectual and psychomotor development in children and quality of life in adults,

mainly (Aldenkamp & Bodde, 2005).

The epileptic syndromes that commonly present language impairments are the

Landau-Kleffner syndrome, temporal lobe epilepsy and rolandic epilepsy (atypical).

The Landau-Kleffner syndrome is the most studied epilepsy syndrome

associated with childhood aphasia. Acquired in childhood (between three and eight

years of age), has an acute or insidious onset, it is also characterized by an altered EEG

(bilateral spike waves during sleep) although it can occur without seizures (Wilfong,

2009), as well temporal lobe epilepsy. Both are associated with an auditory aphasia,

and there are also frequently documented hyperactivity, memory deficits and

impairments of neuropsychological functions such as attention, language, executive

functions and constructive praxis (Schlindwein-Zanini, Izquierdo, & Cammarota,

2009). Temporal lobe epilepsy is characterized by the existence of complex partial

seizures with automatisms, postural changes or subjective feelings and experiences as

déjà vu, illusions, hallucinations, depersonalization, dreamlike states, confusion,

forced thinking (rare epileptic phenomenon), dizziness, amnesia, mood swings and

aggressive behavior (also referred to as the syndrome of interictal behavior in which

many authors believe that it is a consequence of limbic epileptic discharge, however

the neurophysiological mechanism remains unclear). The automatisms are normally

simple type, such as chewing, groping, fumbling, look around and grumble, lasting

early seconds to one minute, during which the individual is unanswerable. The final

phase consists of loss of consciousness, and the total episode lasts from one to 30

minutes (Farrell, 1993).

In 2006, Meneguello, Leonhardt and Pereira concluded in a sample of eight

patients with temporal lobe epilepsy (TLE) aged between 22 and 51 years, that they

had poorer performance on tests of duration pattern, dichotic digits and dichotic non-

verbal. In the continuity of the work, similar results to non-verbal tests with a sample

of 38 children and adolescents aged between seven and 16 years with neurological

diagnosis of idiopathic epilepsy were reported (Ortiz, Pereira, Borges, & Vilanova,

2009). In another study, Bocquillon and his team at the Department of

Neurophysiology, University of Lille (France), in 2009, observed differences in

34

morphology, latency and localization of P300 (P3b) in ten adult patients with TLE

compared to a control group.

More commonly, rolandic epilepsy or benign epilepsy with rolandic or centro-

temporal spikes (BECTS) is the most common form of idiopathic epilepsy in children,

with age of seizure onset between 3-14 years, representing 8-23% of epilepsies under

the age of 16 and is more common in boys than girls (Bernardina et al., 1992).

However, several studies have questioned the benign nature of BECTS reporting

neuropsychological deficits in many domains (Liasis, Bamiou, Boyd, & Towell, 2006;

Myatchin, Mennes, Wouters, Stiers, & Lagae, 2009). This seems to be related with the

atypical form of BECTS, characterized by the presence of neurological deficits,

continuous spike wave during sleep, atypical absences, speech delay, and intellectual

deficits (Wong, Gregory, & Farrell, 1985).

Developmental dyslexia was first described in 1896 by W. Pringle Morgan, in

an article published in the British Medical Journal (Snowling, 2004). This article

marked the beginning of the study of dyslexia, initially by ophthalmologists with

Hinshelwood in 1917, to call it the verbal and congenital blindness. From the very first

time, dyslexia was seen has a having a neurological origin. The French neurologist

Jules Dejerine, in 1891, reported that damage to the left inferior parieto-occipital

region (in adults) results in a specific, more or less severe, impairment in reading and

writing, suggesting that this region, namely the left angular gyrus, may play a special

role in processing the optic images of letters (Habib, 2000). Orton, in 1925, defined it

as “a disorder of the occipital cerebral dominance of one hemisphere over the other”

(Guardiola, 2001, p.10). After Orton, the study of dyslexia, which until then was under

the domain of the medical class, started to be equally studied by psychologists and

educators. This gave rise to numerous definitions and theories in an attempt to its

characterization and definition. However, is in the 60s that dyslexia research has an

exponential growing interest that continues today.

The dyslexia was the target of numerous definitions, only until the turn of the

century a consensus was reached.

The definition of the International Dyslexia Association working group has the

largest gathering consensus (Lyon, Shaywitz, & Shaywitz, 2003):

35

“Dyslexia is a specific learning disability that is neurobiological in origin. It is

characterized by difficulties with accurate and/or fluent word recognition and

by poor spelling and decoding abilities. These difficulties typically result from

a deficit in the phonological component of language that is often unexpected

in relation to other cognitive abilities and the provision of effective classroom

instruction. Secondary consequences may include problems in reading

comprehension and reduced reading experience that can impede growth of

vocabulary and background knowledge” (p. 1).

Today is considered a specific developmental disorder in learning to read,

which is not the direct result of impairments in general intelligence, gross neurological

deficits, uncorrected visual or auditory problems, emotional disturbances or inadequate

schooling (DSM IV-TR, American Psychiatric Association, 2002; ICD-10, World

Health Organization, 2007).

According to the phonological deficit hypothesis, is a prevalent cognitive-

level explanation, dyslexia is revealed in a continuum of specific learning difficulties,

related to the acquisition of basic skills in reading, spelling, writing and / or calculation

(Vellutino et al., 2004). Due to information processing deficits, such as in the short-

term verbal memory, verbal appointment, and phonetic individual words decoding

reflecting insufficient phonological processing skills, often unexpected in relation to

age or other cognitive abilities. These difficulties do not come from a developmental

disability or a sensory or motor impairment (Ramus, 2004). There is a high correlation

between difficulties in connecting the sounds of language to letters and reading delays

or failure in children. The phonological deficit hypothesis, also considers that reading

failure is due to a functional or structural deficit in left hemispheric brain areas

associated with processing the sounds of language (Ramus, 2001). Critics of the

phonological hypothesis argue that much of the evidence for the theory is based on

circular reasoning, in that phonological weakness is seen as both a defining symptom

of dyslexia and as its underlying cause, but also that other symptoms such as small

motor coordination and visual difficulties remain to explain (Uppstad & Tønnessen,

2007).

Dyslexia is one of the most common causes of learning difficulties, estimating

its prevalence between two and 10% of school-age population (Katusic et al., 2001;

36

Shaywitz, 1998). The difficulties of acquiring literacy are explained by only one

symptom, which characterizes its complex framework. There are documented several

difficulties in visual processing, auditory processing, motor coordination and the

existence of comorbidity, where sometimes dyslexia arises associated with attention

deficit, dyspraxia, dyscalculia, specific language disorders or hyperactivity (Nicolson

& Fawcett, 1999; Palesu et al., 2001; Wrigth, Bowen, & Zecker, 2000). It occurs in all

known languages (Lindgren, DeRenzi, & Richman, 1985; McBride-Chang et al.,

2008). Socioeconomic status and family factors are known to influence the

development of reading abilities, but are not causally related to dyslexia (Vellutino et

al., 2004).

Aside from reading and spelling deficits, a number of neurophysiological

studies have revealed altered auditory event-related potentials (AERPs) in both

children and adults with dyslexia when passively discriminating between two

phonemes or two tone stimuli, though with some contradictory results or unclear

explanations (for review see Bishop, 2007; Näätänen, Paavilainen, Rinne, & Alho,

2007; Schulte-Korne & Bruder, 2010).

Although the mass investigations on these two school age disorders (epilepsy

and dyslexia), a feasible protocol diagnosis and treatment monitoring method is still

lacking. Further, there are scarcely studies that actually investigate the central auditory

processing with AERPs in these disorders, much less in children and between

disorders. In clinical practice, very similar EEGs are reported among school-aged

children with rolandic epilepsy and children with other developmental disorders such

as dyslexia and autism (Canavese et al., 2007; Oliveira et al., 2014; Spence &

Schneider, 2009). This finding is very pertinent, it actually fomented the idealization

of the very construct of the sui generis work in this thesis, and gave rise to questions

such as of what are the limits, continuities and parallelism in auditory processing and

development between two neurodevelopmental disorders in children with the same age

and no cognitive impairments. Further, can the AERPs detect and explain putative

erroneous auditory processing that occurs in a highly temporal resolution dimension?

And therefore, can AERPs be a reliable clinical tool to early distinguish between these

disorders?

37

The AERPs are changes in the ongoing EEG, which are time-locked and phase-

locked to perceptual, cognitive, and motor processes involved in language processing

and production. In addition, its components reflect synchronized postsynaptic

potentials of aligned neurons such as pyramidal cells in cortex (Banaschewski &

Brandeis, 2007). With a high temporal resolution, they are important to measure covert

processes, and to distinguish cause and effect. AERPs are a promising tool to study

putative auditory processing deficits that may underpinne language impairments in

neurodevelopmental disorders, but also as potential predictors of clinical treatment

responses.

More incisive research to document and explain these mechanisms is required.

To prove, complement and even innovate etiological theories and neurophysiological

models. Consequently, the methods and techniques of therapeutic approaches and

intervention improved.

In this work, we will illustrate the current state of the art of AERPs results and

meaning in developmental dyslexia and benign epilepsy with centro-temporal spikes,

two of the most common neurodevelopmental disorders. Further, we will counterpoint

the meaning of electrophysiological components with the recent and renewed findings

on neurocell network processing, such as the cell assembly model theory, and the

neurocognitive model of auditory sentence processing.

Biomarkers and Endophenotypes

In the last decades, the research in biomarker’s field provided high feasible

methods and protocols. We can see in our daily life, how they become wide used tools

in clinical practice: diagnosis of myocardial infarction, diagnosis and management of

heart failure, inflammatory conditions in general and particularly systemic infections

(Mueller, Müller, & Perruchoud, 2008).

We have a genetic code with about 30 thousand genes, the term “genetics”

appeared in 1902 by William Bateson and the term “gene” by Wilhelm Johanssen in

1909. The phenotype represents observable characteristics in an organism, resulting

from genetic and environmental influences; the genotypes are measurable with

38

molecular biology techniques, and useful as indicators of disease prediction

(Gottesman & Gould, 2003, p.636). One must kept in mind, that the phenotype is not a

precise or perfect representation of one individual genetic code, this explains our

unique appearance in seven billion people in the world.

Although there is no widely accepted definition of what constitutes a biomarker

or “bioindicator”, the National Institute of Environmental Health (NIEH, 2011)

defined them as “key molecular or cellular events that link a specific environmental

exposure to a health outcome”. This is in accordance with the Biomarkers Definitions

Working Group, committed to the following definition: biomarkers are “measurable

and quantifiable biological parameters which serve as indices for health – and

physiology related assessments, such as disease risk, psychiatric disorders,

environmental exposure and its effects, disease diagnosis, metabolic processes,

substance abuse, pregnancy, cell line development, epidemiologic studies, etc.”

(Ritsner & Gottesman, 2009, p.5). Biomarker is an indicator of the presence or extent

of a biological process that is directly linked to the clinical manifestations and outcome

of a particular disease, therefore may not be specifically embedded in the causal chain

for the disease (Biomarkers Definitions Working Group, 2001).

There can be different types of biomarkers (Lenzenweger, 2013; Ritsner &

Gottesman, 2009): antecedent markers (evaluation of risk to a disorder); screening

markers (early detection of diseases); diagnostic markers (identification of a disorder);

biomarker signatures (indicators of a disease state that are usually linked to an ongoing

pathophysiology); prognostic markers (predict the likely course of the disease);

stratification markers (predict the likelihood of a drug response, plays a prominent role

in use of pharmacogenetics, pharmacogenomics and pharmacoproteomics for

development of personalized medicine).

The illness dynamics lead researchers to consider two concepts in markers: trait

and state. This is particularly important in research areas of psychology, psychiatry

and neurology. A state marker reflects the status of clinical manifestations in patients

and a trait marker represents the properties of the behavioral, neuropsychological and

biological processes that play an antecedent role in the pathophysiology of the

neuropsychiatric disorder (Fridhandler, 1986).

39

Endophenotype is an important kind of heritable trait marker, which relates

only to genetically influenced phenotypical characteristics of patients. Yet are not

directly related to symptoms of the disease or disorder in question and are not typically

considered in the diagnosis and screening (Gottesman & Gould, 2003; Ritsner &

Gottesman, 2009). Several authors suggest that the link between endophenotypes and

genes is stronger than that between genes and the phenotype. Thus, being more closely

related to the genotype, endophenotypes might explain the etiological processes

(Lenzenweger, 2013). Originally, endophenotype was defined as an internal

phenotype, not obvious to the unaided eye that lies intermediate between the gene and

the disease itself (Gottesman & Shields, 1973).

The term “endophenotype” was first used by John and Lewis (1966) to explain

geographic distribution and genetics of insects (Marques-Teixeira, 2005, p.21). In fact,

their work was adapted into the “endophenotype strategy” of Gottesman and Shields

(1973) in order to reduce the heterogeneity and complexity of research and establish

useful criteria for the identification of endophenotypes. Thus, in the early 1970s the

endophenotype concept as an unobservable latent entity, applied to psychopathology,

was proposed by Shields and Gottesman (1973, p.172). Notably, this view is consistent

with the “hypothetical construct model”: a theoretical concept can exist at a latent level

and not be directly observable (only with appropriate technology or tests) but be

plausibly related via a nomological and natural network to observable and measurable

characteristics (Lenzenweger, 2013, p.186; MacCorquodale & Meehl, 1948).

To solve and clarify these issues, it has been given a lot of emphasis on

research in the field of biomarkers with significant evolution. This strategy consists of

decomposing the genetic complexity of pathologies in more homogeneous subtypes,

and genetically less complex. Thus, proceeding to phenotypic complexity reduction,

allows achieving simplified genetic transmission mechanisms.

This approach is being applied to schizophrenia (Freedman, Adler, & Leonard,

1999; Gur et al., 2007), major depression and bipolar disorder (Benes, 2007; Hasler et

al., 2006; Lenox, Gould, & Manji, 2002), ADHD (Waldman, 2005), autism (Belmonte

et al., 2004), alcohol dependence (Dick et al., 2005), and other complex conditions.

The concept of endophenotype is continuously changing with new discoveries.

In this work, we will consider it as a set of quantitative, heritable, trait-related deficits

40

typically assessed by biochemical, endocrine, neuroanatomical, neurophysiological,

neuropsychological, and other methods (Cannon & Keller, 2006; Turetsky et al.,

2007).

Endophenotype is a laboratory measure that should reflect the action of genes,

and in turn predispose the individual to a specific pathology (Ritsner & Gottesman,

2009). Tandon, Nasrallah and Keshavan (2009) state that endophenotypes play a key

role here in establishing the relationship between the neurobiological processes

underlying pathological mechanisms and clinical expression. In turn, the

endophenotypes can help defining better treatment strategies.

An endophenotype, to be distinguished from biomarkers, has to be: (1)

associated with illness (general population); (2) heritable; (3) state-independent (illness

active/inactive); (4) familial co-segregation with illness (higher prevalence among

family members with the marker); (5) found in some unaffected relatives at a higher

rate than the general population; and (6) the endophenotype should be a trait that can

be measured reliably, and ideally is more strongly associated with the disease of

interest than with other neuropsychiatric conditions. These six points were designed to

direct clinical research in psychiatry toward genetically and biologically meaningful

conclusions (Gould & Gottesman, 2006; Lenzenweger, 2013).

In addition, we may find in the literature the term “intermediate phenotype”. It

has been used in genetics for decades for describing incomplete or partial dominance

(Meyer-Lindenberg & Weinberger, 2006). A clear example of this, given by

Lenzenweger (2013) is a white flower and a red flower give rise to a pink flower.

Although intermediate phenotype indicates a predictable path from gene to behavior or

even half way between endophenotype and biomarker, its technical definition applied

to psychopathology, neurology and other clinical areas still predates all discussions.

In sum, endophenotypes and biomarkers are distinct entities. But “all

endophenotypes are, by definition, biomarkers, but not all biomarkers are

endophenotypes” (Lenzenweger, 2013, p.187).

In the past fifteen years several endophenotypes and biomarkers have been

studied: neuropsychological, neurophysiological, endocrinological, neuroimaging and

neuroanatomical, metabolic and peripheral, molecular and genetic. A MEDLINE

database search carried out by Ritsner and Gottesman (2009) between 2000-2007

41

concerning publications in the biomarker field revealed that the number of articles

nearly doubled for: heart failure, Alzheimer's disorder, multiple sclerosis,

inflammatory conditions, schizophrenia, mood disorders, and epilepsy.

The advantages brought by endophenotype concept are particularly important if

we think in the diagnosis, monitoring and treatment of neurodevelopmental disorders

such as dyslexia, epilepsy, autism, CAPD, and ADHD. Further, endophenotype

approach could help clarify and clinically support treatment decisions when there is

existence of comorbidity.

Similarly to the above work, we made a PubMed search between 2000-2014

using the terms “biomarker” or “epilepsy” or ”dyslexia” or “autism” or “central

auditory processing disorder” or “ADHD”. Results revealed a total of 2336

publications: 1283 were related to epilepsy (54.9%), 644 to autism (27.6%), 291 to

ADHD (12.4%), 60 to dyslexia (2.6%) and 58 were related to central auditory

processing disorder (2.5%). These results clearly reveal the importance given to each

disorder in the field of biomarkers research. Dyslexia, ADHD and CAPD have the

lowest publications, this is probably due to high variability of epigenetic input and an

indefinable comorbidity limits normally seen in these neurodevelopmental disorders.

The first step is to identify and validate potential endophenotypes (Braff &

Light, 2005). The identification of phenotypes can be obtained through complementary

strategies, particularly subject’s description and the identification of vulnerability

traces in non-affected family members of individuals with the disease under study. So,

the first approach should be the identification of candidate symptoms to distinct

clinical features that are most likely associated with a genotype of the disease, thus

being theoretically a simpler pattern of transmission. The second strategy emphasizes

the need to use wider approaches, such as biochemical or neurophysiological, to

identify sub-clinical characteristics in non-affected subjects but carrying genes of

vulnerability. These subclinical traces association may be useful in identifying

common alleles with nonspecific or moderate effect on the risk for developing the

disease. However, considering that endophenotypes originate from genetic

polymorphisms and knowing that genes initiate the neurobiological expression and

regulation during embryo conception it must be taken into account that they are mainly

studied on adulthood. Therefore, its expression may be altered by non-genetic factors,

42

such as developmental events, aging, traumatic injuries, drugs administration or drug

use.

The final step, after endophenotype identification, would be the validation of

protocol/method or test used. The latter, should be designed to achieve a high

specificity, sensitivity, and reliability. Whether it is a biochemical,

electrophysiological, or other type of technique.

The fact that many neurological and developmental syndromes present the

same pattern regarding cognitive and social deficits in childhood, followed by

psychotic symptoms years later, suggests that the factors that lead to the onset of

psychosis are not specifically related to the disease but time-dependent instead

(Weinberger, 1987; 1995).

The work within this thesis, may contribute to a depth analysis and discussion

of ERPs components contribution to better understand neurodevelopment in

childhood. This may open new perspectives on the origin of adult disorders.

Without straying from the main subject, is relevant to highlight a possible link

to be studied regarding schizophrenia as a neurodevelopmental disorder. The model

emerging from this neurodevelopmental perspective is the possibility that a

developmental lesion influences a pathway or a regulatory process, such as the fine-

tuning of excitatory and inhibitory synapses in the prefrontal cortex, which may have

only subtle effects until a precise balance is required in late adolescence. This lesion in

early development that does not manifest until a much later developmental stage when

compensatory changes can no longer suffice with the emergence of psychosis in late

adolescence or early adulthood (Insel, 2010; Thompson & Levitt, 2010). Although we

still do not know how to map the trajectory of schizophrenia as a neurodevelopmental

disease, it seems to exist a developmental continuum with other behavioral disorders

that arise in childhood (e.g., autism, mental retardation or epilepsy) from overlapping

biological risk factors with several covariates.

Epilepsy is probably the neurological disorder closer related to psychiatry, even

historically. For example epilepsy patients were admitted to hospitals for mental

diseases in the nineteenth and beginning of the twentieth century.

Patients with epilepsy have a higher prevalence of psychiatric disorders and

psychological conditions compared with the general population (Rai et al., 2012). With

43

special emphasis to depression, anxiety, psychosis (mainly schizophrenia), social

phobia and ADHD (de Boer, Mula, & Sander, 2008). According to WHO, depression,

psychosis and anxiety disorders are the most common feature after surgery to control

seizures.

In a close past, renewed interest has occurred in finding common denominators

in both “diseases” for the different types of psychiatric disturbances reported

frequently in epileptic children and adults: depression, psychosis, autism, personality

disorders and ADHD (Ritsner & Gottesman, 2009). However, the relation between

epilepsy and psychiatric disorders (brain- and non-brain-related) is not yet clear. Many

genes have been identified for monogenic epilepsy syndromes but not in psychiatry,

especially psychosis like schizophrenia and bipolar disorders (Swinkels, Kuyk, van

Dyck, & Spinhoven, 2005). This discrepancy is especially intriguing in view of the

frequent co-occurrence of epilepsy and psychiatric disorders. The answer probably

relies on the differences in etiological complexity, the use of different strategies for

endophenotyping, the wide variation in population genetic background, which may

play a role in the frequently contradicting or inconsistent results, and also studies of

small sample sizes with a prior low statistical power for successful detection of

susceptibility loci (Pinto, Trenité, & Lindhout, 2009).

Dyslexia is also a disorder with a complex and heterogeneous genetic basis.

There have been identified four genes that are expressed in cortical brain regions that

are part of the complex neuronal network for reading (Neuhoff et al., 2012; Shaywitz

& Shaywitz, 2008). Curiously, the genes are involved in the development of the

cerebral neocortex, either in terms of axonal guidance (ROBO1; Hannula-Jouppi et al.,

2005) or neuronal migration (KIAA0319; Cope et al., 2005; DCDC2; Meng et al.,

2005; and DYX1C1; Taipale et al., 2003). Further, some studies found an attenuated

late MMN to speech sounds (Alonso-Bua, Diaz, & Ferraces, 2006; Maurer, Bucher,

Brem, & Brandeis, 2003; Roeske et al., 2011; Schulte-Kӧrne, Deimel, Bartling, &

Remschmidt, 2001), and in relatives of dyslexic individuals, who therefore have a

genetic risk for dyslexia, but have not developed reading and/or spelling disorders

(Neuhoff et al., 2012; Roeske et al., 2011). Thus, an attenuated late MMN is recently

being suggested as an endophenotype for dyslexia. However it remains unclear how

44

genetics impact brain function and how these areas are related to reading and spelling

phenotypes.

The use of endophenotypes in the neurodevelopmental disorders mentioned is

probably still far from reality. Its genetics are complex, with various gene-by-gene and

gene-by-environment interactions leading to activation of multiple neuronal circuits,

which results in phenotypic variations (Pinto et al., 2009). This is complicated by the

knowledge that there can be more than one pathway to a given phenotype, for example

the common language deficits in temporal lobe epilepsy (TLE), benign epilepsy with

centro-temporal spikes (BECTS) and developmental dyslexia.

At least in a close future, the endophenotype approach seems to offer great

promise as an alternative or complement to the studies of categorical disease ILAE

phenotypes (e.g., neuroimaging). It is known that most patients have a normal

neurological examination and brain imaging studies are essential to reveal gross

structural cerebral abnormalities. However, it is unknown whether patients may have

subtle regional cytoarchitectural abnormalities. Neuroanatomical measures, as assessed

by MRI, are shown to be highly heritable in large twin-studies and show considerable

variation in the general population (Posthuma et al., 2000; Thompson et al., 2001).

Furthermore, there is emerging evidence that electrical, neuroimaging, and molecular

changes in spike-wave seizures do not involve the entire brain homogenously in all

idiopathic generalized epilepsy (IGE) patients (Koepp, 2005; Meschaks, Lindstrom,

Halldin, Farde, & Savic, 2005).

In sum, although overlapping, endophenotype and biomarker concepts refer to

different biological properties. Both are measurable, the biomarkers point out a

dysfunction or morphological feature strongly linked to physical illness but which may

not be hereditary. For example, the genetic markers are useful in diagnosis and

prognosis. Given that are present from birth, theoretically allow to establish preventive

measures.

Endophenotypes may preclude us to identify subjects with genes of a particular

illness not having any symptoms yet. This could raise the statistical power of genetic

analysis (Marques-Teixeira, 2005). However, this area is especially in need of the

improved delimitation of homogeneous endophenotypes (whether defined

categorically or dimensionally) that psychophysiology, neurology and psychiatry may

45

foster, as discussed above. The fewer the number of pathways that give rise to an

endophenotype, the better the chances of efficiently discovering its genetic and

neurobiological underpinnings.

Particularly promising is the ability of psychophysiology to define the

endophenotype in psychopathology, the manifestation of a disorder via anomalies not

observable by diagnostic interview or observation of overt behavior. This may prove to

be crucial, for example, for identification of affected individuals in genetic linkage

studies (Edgar, Keller, & Miller, 2007).

While the use of endophenotypes is not yet a fully validated approach, it

remains a highly promising concept. Endophenotypes represent more defined and

quantifiable measures that are envisioned to involve fewer genes, fewer interacting

levels and ultimately activation of a single set of neuronal circuits. So far, there is no

standardization in the selection of endophenotypes in genetic research, but several

criteria for valid and useful endophenotypes have been previously proposed

(Gottesman & Gould, 2003; Gould & Gottesman, 2006; Leboyer et al., 1998).

Inherent benefits of endophenotypes include more specific disease concepts and

process definitions. For example, the process of language acquisition and language

development, inherent to the most common developmental disorders. The study of

endophenotypes can transcend the limits of conventional diagnoses and receive new

patterns of association between symptoms, personality traits or other behavioral

aspects. In this context, identifying endophenotypes not directly observable could help

solve complex issues about the etiological models of mental and neurodevelopmental

disorders.

Regarding neurophysiologic endophenotypes, would they represent

dysfunction, susceptibility or both?

Paper I will explore and hypothesize in a case study format, AERPs as putative

neurophysiologic endophenotypes in generalized epilepsy. Namely, N1, N2b, and P3

components are discussed to be possible traits of neocortical excitability circuits.

46

Paper I

Auditory event-related potentials in an idiopathic generalized epilepsy case

study and relatives: a putative endophenotype?

David Tomé1,2, Ana Rita Cudna1, Fernando Barbosa2, João Marques-Teixeira2

aLaboratory of Neuropsychophysiology, Faculty of Psychology and Educational Sciences,

University of Porto, Portugal bDepartment of Audiology, School of Allied Health Technologies, Polytechnic Institute of Porto, Portugal

(submitted)

47

Abstract

Introduction: several endophenotypes candidates have been proposed in the last

fifteen years to different types of epilepsy, from genes, neuroimaging, photosensitivity,

and neurocognitive. Very scarcely is known concerning auditory event-related

potentials (AERPs) as possible endophenotypes. Despite being considered to provide

objective measures of central auditory processing.

Objective: our aim is to study the auditory N1 and N2b components in an idiopathic

generalized epilepsy case and first cousins.

Methods: we elicited N1 and N2b with a speech and pure-tone auditory oddball

paradigms, in a young adult with IGE since childhood compared to his first cousins

and a control group.

Results: the results revealed higher peak-to-peak amplitudes for IGE subject and

cousins compared to control group.

Conclusions: our findings indicate that increased amplitude of N1 and N2b from Cz

and Fz for pure-tone and speech stimuli paradigms, respectively, are strong candidates

to endophenotypes of IGE. Further studies are required to establish the relationship

between neurobiological processes, pathological mechanisms and the clinical

expression found. Finally, N1 and N2b increased amplitude are traits of neocortical

excitability circuits in affected subjects and a predisposition in unaffected family

members. The study of these endophenotype candidates might define a faster and

accurate diagnosis, prognosis and treatment strategies in the future.

Keywords: endophenotype · epilepsy · N1 · N2b · neuroexcitability · relatives

48

Introduction

Endophenotype is an important kind of heritable trait marker, which relates only to

genetically influenced phenotypical characteristics of patients. Yet are not directly

related to symptoms of the disease or disorder in question and are not typically

considered in the diagnosis and screening [1,2]. Several authors suggest that the link

between endophenotypes and genes is stronger than that between genes and the

phenotype. Thus, being more closely related to the genotype endophenotypes might

explain the etiological processes [3].

The current criteria for an endophenotype, to be distinguished from biomarkers, it

has to be (1) associated with illness (general population), (2) heritable, (3) state-

independent (illness active/inactive), (4) familial co-segregation with illness (higher

prevalence among family members with the marker), (5) found in some unaffected

relatives at a higher rate than the general population and (6) the endophenotype should

be a trait that can be measured reliably, and ideally is more strongly associated with

the disease of interest than with other neuropsychiatric conditions. These 6 points were

designed to direct clinical research in psychiatry toward genetically and biologically

meaningful conclusions [3,4].

In epilepsy, the last fifteen years revealed an exponential growth in endophenotype

and biomarkers research field. The main goal seems to establish the relationship

between neurobiological processes underlying pathological mechanisms and clinical

expression [5]. In turn, the endophenotypes can define better treatment strategies.

However, these primary objectives have proved to be more complex than we thought.

Genetics of epilepsy disorders is complex, many genes may interact at many levels

(gene-by-gene and gene-by-environment), and leading to activation of multiple

neuronal circuits which results in phenotypic variations [6].

Until today, several endophenotypes candidates have been proposed to different

types of epilepsy. Many genes have been identified to play a role in disease

susceptibility, being related to non-ion and ion-channels gating: generalized epilepsy

with febrile seizures (SCN1A, SCN2A, SCN1B, GABRG2 and MASS1), juvenile

myoclonic epilepsy (CLCN2, CACNB4, JRK/JH8, EFHC1), childhood absence

epilepsy (CLCN2, GABRG2, CACNA1H, JRK/JH8), temporal lobe epilepsy (LGI1, IL-

49

1ß, PDYN, ApoE, GABBR1, PRNP, BDKRB1, BDKRB2, CCL3, CCL4, 5HT-1B,

SCN3A, SCN3B, GRIN1, C3, SCN1A, SCN1B, ABCB1_4, SLC6A4, KCNA1, KCNA4,

KCNAB1, ADAM22, LGI4, 5HT-2c, GRM1, GRM4, and GABRA1) [for review see 7-

11]. These are only the most studied, the possibility that many polymorphisms

contribute minor effects to a single phenotype or interact with multiple genetic loci

raises the problems of locus heterogeneity and variable expressivity [12,13].

Thwarting the utility of genetic testing for epileptic syndromes for now.

The photoparoxysmal response is also considered as a potential endophenotype for

idiopathic generalized epilepsies. Also known as photosensitivity is found in up to

50% of IGE syndromes, 10–40% of subjects with myoclonic epilepsies of infancy, in

30–40% of subjects with juvenile myoclonic epilepsy (JME) and in 13–18% of

subjects with absence epilepsies of childhood (CAE) or juvenile onset (JAE). This

high degree of co-morbidity compared to a 0.5–7.6% prevalence in the general

population [14-16]. Despite de efforts, none of the genes mentioned above have yet

been associated with photosensitivity.

Regarding neuroimaging endophenotypes, it is known from large twin studies that

cytoarchitectural abnormalities are highly heritable [17,18]. JME has the largest

number of neuroimaging endophenotypes: neurotransmitter changes in the cerebral

cortex demonstrated by positron emission tomography (PET) [19], abnormalities of

cortical gray matter in medial frontal areas revealed by magnetic resonance imaging

(MRI) [20], thalamic dysfunction shown by H-magnetic resonance spectroscopy

(MRS) [21], and more recently an attenuated deactivation of the motor system and

increased functional connectivity between fronto-parietal cognitive networks and the

motor cortex during functional MRI working memory task [22].

Neurocognitive endophenotypes are also starting to be proposed and sustained with

past evidence. For rolandic epilepsy or benign epilepsy with centro-temporal spikes

(BECTS) there is evidence for an endophenotype associated with neurocognitive

impairments, which may involve auditory processing deficits, attentional function and

consequently language impairments [23-25]. Finally, a battery of neuropsychological

tests sensitive to frontal lobe dysfunction (nonverbal reasoning, verbal generativity,

sustained attention, and working memory impairments) are possible endophenotypes

for IGE syndromes [26].

50

What about auditory event-related potentials (AERPs)? The EEG has proved to be a

valuable tool for diagnosing some forms of epilepsy but mainly to indicate seizures

type, susceptibility and severity. Though, EEG features are considered biomarkers.

Our hypothesis is based on ERPs high temporal resolution, enabling the detection of

the imbalance of exciting and inhibiting currents in neurons that underpin epilepsy.

Our aim is to present probably the very first link between cortical excitability and N1

and N2 components in a subject with IGE and two unaffected first cousins.

Subjects and Methods

We present a case study of a young adult with IGE since childhood (age = 23; length

of Portuguese education = 12 years) with primary generalized tonic-clonic seizures

generally lasting 1 minute, triggered by stressful situations. Interictal EEG patterns

indicate epileptic activity in temporal lobes, suggesting a neocortical IGE. He is

seizure free for the last 2 months, currently with anticonvulsant medication of

carbamazepine 400 mg/day. This subject was compared with two unaffected first

cousins (a man and a woman with 24 and 22 years old, respectively) and a matched

control group (n = 4; 2 male; M = 22.0 years; SD = 5.03). All participants were right

handed, had normal hearing and vision, no ear malformation, and no neurological

(except IGE subject) or mental deficits reported.

The experimental procedures followed the tenets of the Declaration of Helsinki.

Written informed consent was obtained from all participants.

The AERPs provide objective measures of central auditory processing. We elicited

the N1 and N2 components. These scalp recorded potentials reflect activation of

different neuronal populations that are suggested to contribute to auditory

discrimination (N1) [27], attention allocation, inhibition control and phonological

categorization (subcomponent N2b) [28]. The latter is particularly important for the

study of phonological activation processes and cell assemblies’ organization in

perisylvian cortices for phonological word forms and memory traces [29].

During EEG recording (32 channel bio-amplifier Refa32, ANT Neuro, Netherlands)

participants were presented with two active auditory oddball paradigms: a block of

51

pure-tone stimuli (std: 1000Hz; dev: 1100Hz; created in Audacity software v2.0.0) and

other of consonant-vowel (CV digitalized rate of 44100Hz with 175ms duration,

spoken by a male Portuguese voice; std: /ba/ 118 Hz (F0); dev: /pa/ 127 Hz (F0),

recorded with Nuendo software v4.3.0) with a stimulus onset asynchrony (SOA) of

800 ms, to a proximal sound level of 75 dB SPL. In both blocks (300 trials), standard

stimuli comprised 80% of all trials, while deviant stimuli comprised 20%. Recordings

were obtained from the following montage of cup-shaped silver chloride (Ag-AgCl)

electrodes: Cz, Fz, Fpz, M1, M2 and Oz (ground), referenced to averaged ear lobes

(A1 and A2). An electrode was attached above right eye to monitor the

electrooculogram (EOG). Impedance between the electrodes and skin were kept below

10 kΩ at all sites. Stimuli were presented using Presentation® software

(Neurobehavioral Systems, Inc.) via closed headphones while the participants where

comfortably seated in an armchair and instructed to keep alert with eyes-open,

passively listening to auditory stimuli and focused on a small cross in the center of a

computer screen during recording. The EEG data was recorded with ASA software

v4.0.6.8 (ANT Neuro, Netherlands). The sampling rate was 512 Hz for each channel

and the recording bandwidth between 0.05 Hz and 100 Hz. Preprocessing included

band-pass filtering [0.3-30] Hz, entire sweep linear detrending and a baseline

correction of individual epochs (200 ms).

The N1 and N2b waves were obtained from the Fpz, Fz, Cz, M1 and M2 electrodes,

being identified as the two largest negative peaks occurring between 100 and 300 ms.

Results

The N1 and N2b auditory ERP components were present in all participants for both

pure-tones and CV conditions. Mean peak-to-peak amplitude and peak latencies of the

N1 and N2 wave in Fpz, Fz and Cz, for the IGE subject, family and the comparison

group are shown in Table 1. Cohen’s effect sizes were obtained with nonparametric

Mann-Whitney test Z value.

52

The results revealed higher amplitudes for IGE subject and cousins as seen in

Figure 1. However, in order to more feasibly interpret results we decided to analyze

peak-to-peak amplitudes.

Pure-tones. The most relevant finding was a moderate to strong effect size (r>0.65)

for N2b amplitude from Fz electrode. With the IGE subject having the highest

amplitude and its relatives an intermediate result compared to control group (Fig.1).

Regarding latency, the same effect size was also found for Fz, diminished compared to

control group, but with no difference between IGE subject and cousins (Table 1).

Consonant-vowel. For speech stimuli paradigm, results revealed the highest amplitude

of N1 from Fpz and Cz for the IGE subject, followed by his cousins, and lastly control

group. Regarding N1 latency, there was a similar strong effect size, but delayed

contrary to pure-tone stimuli and compared to control group (Table 1).

Table 1 Mean peak-to-peak amplitude and peak latencies of the N1 and N2b wave in Fpz, Fz and Cz, for the

IGE subject, family and the comparison group

IGE subject Family (median/SD) Control group (median/SD)

Pure-tone

μV / ms μV / ms μV / ms

N1

Fpz -2.57 / 113 -2.28 (0.13) / 109 (2.83) -1.95 (1.59) / 120 (17.87)

Fz -5.87 / 110 -7.23 (0.66) / 113 (4.65) -6.90 (2.01) / 121 (4.62)

Cz -5.17 / 109 -6.07 (0.19) / 117 (5.66) -3.74 (1.70) / 121 (4.61)

Fpz -2.06 / 230 -2.48 (0.81) / 219 (8.48) -0.94 (0.58) / 232 (10.06)

N2b Fz -5.02 / 220 -3.74 (0.09) / 221 (8.47) -1.82 (1.09) / 244 (13.09)

Cz -3.56 / 219 -3.05 (0.49) / 227 (2.12) -2.92 (1.86) / 225 (8.61)

Speech


Fpz -2.60 / 160 -2.05 (0.45) / 152 (6.36) -0.83 (0.67) / 113 (9.24)

N1 Fz -6.14 / 152 -6.81 (4.26) / 121 (5.66) -2.9 (2.29) / 133 (16.86)

Cz -7.76 / 141 -6.26 (2.14) / 121 (5.65) -4.24 (1.66) / 125 (4.61)

Fpz -1.51 / 250 -1.73 (0.84) / 234 (10.61) -1.12 (0.89) / 258 (16.65)

N2b Fz -5.25 / 245 -3.39 (0.11) / 221 (8.49) -4.89 (1.89) / 242 (19.67)

Cz -4.01 / 246 -2.32 (1.09) / 231 (4.95) -6.02 (1.42) / 238 (18.46)

IGE = idiopathic generalized epilepsy; Family group (n = 2); Control group (n = 4); μV: microvolts (amplitude);

ms: milliseconds (latency). Effect size, r > 0.65 (moderate-strong difference, compare with control group).

54

unaffected family members (at least first cousins), state-independent (IGE is stable,

had no seizures recently) and there is familial co-segregation with illness. Regarding

anti-epileptic drug effect’s on AERPs, although IGE subject was on medication only

P300 seems to be affected by carbamazepine [30]. This effect is clearly seen in an

increased amplitude of P300 to both stimuli, but mainly to speech (Fig.1).

From the endophenotypical point of view, the high amplitude of N1 and N2b could

be seen as a trait of neocortical excitability circuits in affected subjects and a

predisposition in unaffected family members. However, this is probably the first

neuropsychophysiological approach. The results justify the upgrade of the study to a

clinical level with significant number of participants, homogenous groups and genetic

testing included.

The advantages brought by endophenotype concept are particularly important if we

think in the diagnosis, monitoring and treatment of neurodevelopmental disorders such

as dyslexia, epilepsy, autism, CAPD, and ADHD. Further, endophenotype approach

could help clarify and clinically support treatment decisions when there is existence of

comorbidity.

The AERPs components occur in the same temporal dimension of the dysfunctional

neuronal circuits and the electrodes can be considered close to its biological origin.

Though, homogeneous sample studies still need to be made in order to achieve a high

specificity, sensitivity, and reliability.

Conflicts of interest statement

None of the authors has any conflict of interest to disclose.

Acknowledgements

The first author’s work was supported by a scholarship for Advanced Graduation from

School of Allied Health Technologies, Polytechnic Institute of Porto (ESTSP-IPP).

Regarding the other authors, there are not any financial, relationship and

organizational conflict of interests that may bias any of the establishment of the

hypotheses discussed in this article.

55

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Chapter II

Language

61

Hearing is the primary sense for acquiring Language. Therefore, different types

and levels of hearing loss may originate different language impairments. This chapter

provides a general description of the human ear anatomy and function, in order to

illustrate the complexity of hearing and the need for detecting hearing loss in

neurodevelopmental disorders before performing AERPs. Lastly, the concept of

Language and its inherent neurodevelopmental processes are explored and related to

neuronal maturation. This will elucidate the complexity of assessing language, and is

an introduction of its subdisciplines, such as phonology, that underpinne one of the

most accounted theories for the developmental dyslexia – the phonological deficit

hypothesis. Discussed further down in this work.

Auditory Processing: anatomy and physiology

The language is one of the human capacities that require astonishing features

and integrity of neuronal systems. To its acquisition the sense of hearing is highly

important, being part of a specialized system of communication, involves more than

just the peripheral sensitivity. This complex sense, allows the identification, location

and processing of sounds, from enjoying Beethoven’s 9th symphony to the simple

understanding of speech. For this function to be used in its maximum efficiency, it is

necessary the integrity of the whole auditory route, from the outer ear to the central

auditory pathways and temporal cortex in a hierarchical way (Fukushima & Castro,

2007).

The ear as a sensory organ is far more complex than other sensory organs.

The ear is the organ that allows us to perceive and interpret sound waves in

intensities between 0 dB and 130 dB, at a range of frequencies between 20 and 20000

Hz (Rattay, Gebeshuber, & Gitter, 1998). Furthermore, it is also responsible for our

balance. For both functions, transduces biomechanical energy into bioelectrical stimuli

at cellular level, sending the latter via vestibulocochlear nerve to the brain (Hunter &

Shahnaz, 2014; Martin, 2005).

The nervous system is divided into central and peripheral parts. The central

nervous system (CNS) consists of the spinal cord and the brain (medulla, brainstem,

62

midbrain, the cerebellum, the diencephalon and the cerebral hemispheres) (Møller,

2013). The peripheral nervous system in evolutionary terms is older than CNS,

consists of the skeletal nervous system and the autonomic nervous system

(sympathetic and parasympathetic nervous systems), in other words, the nerves that go

between the CNS and other parts of the body (Webster, 1999).

The auditory system is divided into peripheral and central. The peripheral

auditory system is composed by the outer ear, middle ear, inner ear and the auditory

nerve (Figure 1a). The central auditory nervous system (CANS) is formed by the

neural pathways and the auditory cortex (Figure 1c).

Figure 1. a | Cut-away view of the human inner ear. b | Section of the cochlear spiral showing the organ of Corti, which contains the hair cells. c | Auditory pathways and centres in the brain.

Abbreviations: RM, Reissner's membrane; SM, scala media; ST, scala tympani; SV, scala vestibule. (Ng, Kelley, & Forrest, 2013)

The processes involved in the detection, analysis, and interpretation association

of sound stimuli occur at peripheral auditory nervous system (PANS) and CANS level.

The nerve impulse, the consequent transformation of the sound stimulus, runs the

pathway between the cochlea and the temporal lobe, generating action potentials in the

cochlear branch of the vestibulocochlear nerve, which are forward to the temporal

neocortex. The entire network of nerve fibers, cores and relay stations involved in this

process is often referred to as CANS (Bess & Humes, 1998).

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Before a cortical interpretation of the meaning of the incoming signal can

occur, all sounds, both speech and non-speech, are analyzed at subcortical levels for

characteristics of frequency (pitch), duration, intensity (loudness), and interaural

timing differences (Bailey, 2010).

The afferent auditory pathways of the central auditory system, originate in the

cochlear nucleus complex, located posteriorly to the pontomedular junction. From

there the signal travels both ipsi- and contralaterally through a series of relay stations

until it reaches the primary, or core, auditory cortex.

Throughout this ascending course, several cores will contribute to the

processing and forwarding of auditory message, among which include the superior

olivary complex (SOC; deep pons), the lateral lemniscus cores (upper pons), the

inferior colliculus and lateral lemniscus (dorsal midbrain or mesencephalon), and the

medial geniculate body (MGB; dorsal and caudal thalamus). In addition, medial

geniculate body projections take different subcortical paths toward the cortex (Musiek

& Rintelmann, 2001). It then travels ipsilaterally through the core and belt regions of

the auditory cortex, and contralaterally via the corpus callosum to the opposite

auditory cortex for further processing.

The spatial layout of frequencies in the cochlea along the basilar membrane is

repeated in other auditory areas in the brain. This is called tonotopic organization. It is

known that at least the cochlear nucleus, the inferior colliculus, and even primary

auditory cortex are organized tonotopically.

The first relay station is the cochlear nucleus. Here, the auditory pathway is

divided into two, the primary or contralateral and the secondary or ipsilateral. The

primary auditory pathway is contralateral, is faster (large myelinated fibers) and

consisting of 2/3 of the auditory fibres, and ends in the primary auditory cortex (Figure

2). The ipsilateral or non-primary auditory pathway has less fibers (~1/3), and small

fibers connect with the reticular formation where the auditory message joins all other

sensory messages (e.g., vestibular, somesthesic, visual). The main function of this non-

primary auditory pathway, also connected to wake and motivation thalamic centers as

well as to vegetative and hormonal systems, is to select the type of sensory message to

be firstly analyzed in secondary auditory cortex; this process is called selective

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auditory attention (Fuentes, Malloy-Diniz, Camargo, & Cosenza, 2008). It ends in the

polysensory (associative) cortex (Figure 3).

Figure 2. Auditory pathways. Auditory nerve fibers terminate in the cochlear nuclei. The superior olive is where input from both ears first converges. From there, the major output is via the lateral lemniscus, which terminates in the inferior colliculus (First Years, 2012)

The three constituent nuclei of the cochlear nucleus (dorsal, anteroventral, and

posteroventral cochlear nucleus) receive this information, respond selectively to

speech-specific frequencies, assist in sound localization, and relay it to different parts

of the next steps in the pathway. They are the first to analyze the information arriving

from the auditory nerve, concerning frequency, intensity and duration, forwarding the

analysis to the SOC, which is the anatomical basis for binaurality (Møller, 2013).

65

Figure 3. Subdivisions of auditory cortex and processing streams in primates. Major cortical and subcortical regions are color coded. Subdivisions within a region have the same color. Solid black lines denote established connections. Dashed lines indicate proposed connections based on findings in other mammals. Joined lines ending in brackets denotes connections with all fields in that region. (From: Kaas & Hackett, 2000). Abbreviations of subcortical nuclei: AVCN, anteroventral cochlear nucleus; PVCN, posteroventral cochlear nucleus; DCN, dorsal cochlear nucleus; LSO, lateral superior olivary nucleus; MSO, medial superior olivary nucleus; MNTB, medial nucleus of the trapezoid body; DNLL, dorsal nucleus of the lateral lemniscus; VNLL, ventral nucleus of the lateral lemniscus; ICc, central nucleus of the inferior colliculus; ICp, pericentral nucleus of the inferior colliculus; ICdc, dorsal cortex of the inferior colliculus; ICx, external nucleus of the inferior colliculus; MGv, ventral nucleus of the medial geniculate body; MGd, dorsal nucleus of the medial geniculate body; MGm, medialymagnocellular nucleus of the medial geniculate body; Sg, suprageniculate nucleus; Lim, limitans nucleus; PM, medial pulvinar nucleus. Abbreviations of cortical areas: AI, auditory area I; R, rostral area; RT; rostrotemporal area; CL, caudolateral area; CM, caudomedial area; ML, middle lateral area; RM, rostromedial area; AL, anterolateral area; RTL, lateral rostrotemporal area; RTM, medial rostrotemporal area; CPB, caudal parabelt; RPB, rostral parabelt; Tpt, temporoparietal area; STS, superior temporal sulcus; TS1,2, superior temporal areas 1 and 2. Frontal lobe areas numbered after the tradition of Brodmann and based on the parcellation (Preuss & Goldmann-Rakic, 1991): 8a, periarcuate; 46d, dorsal principal sulcus; 12vl, ventrolateral area; 10, frontal pole; orb, orbitofrontal areas.

Basically, SOC analysis the difference in time of arrival of a sound at the two

ears (the physical basis for directional hearing in the horizontal plane) together with

http://www.pnas.org/search?author1=Jon+H.+Kaas&sortspec=date&submit=Submit

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the difference in intensity of the sound at the two ears. This process is termed binaural

fusion and integration. The lateral superior olive contains neurons that are selective to

interaural intensity differences and the medial superior olive contains neurons that are

selective for interaural timing differences. If the central pathway is compromised at

this level, there can be noticeable difficulty localizing sounds, particularly in the

presence of background noise (Shield & Dockrell, 2004).

Then, the auditory information goes through the lateral lemniscus to the inferior

colliculus (IC) where multidimensional location and spatial sound representation

occurs, existing in these nuclei specialized neurons to process interaural phase

differences. However, some literature considers that the function of the lateral

lemniscus is not well understood. Contralateral spatial representation from the afferent

fibers is preserved and possibly enhanced. Disruptions at this level result in

localization difficulties and in central deafness (Bailey, 2010).

Following, the information reaches the MGB of thalamus were there are

neurons that respond to dynamic characteristics of sound (modulation of intensity,

frequency and amplitude) and the capacity of phonetic composition analysis of

auditory message (discrimination specific to speech). Temporal and frequency

information regarding localization and lateralization of sound is more finely analyzed.

Afterwards, fibers are projected to the insula subcortex. At this level sound begins to

be separated into speech and non-speech sounds. In other words, it is detected which

type of information contains the auditory message; the speech information is sent to

the dominant language hemisphere and the non-verbal information to the non-

dominant hemisphere (Fuentes et al., 2008). It is unclear the extent to which fibers

connect with the arcuate fasciculus and are involved in auditory signal and language

processing.

Integration and interhemispheric transfer is made by corpus callosum.

Currently, the details of these routes are still not completely known. The

hearing message reaches the last resort, the auditory cortex, located bilaterally on the

superior temporal plane, within the lateral fissure and comprising parts of Heschl's

gyrus and the superior temporal gyrus, including planum polare and planum temporale

– roughly Brodmann areas 41, 42, and partially 22 (Pickles, 2012), Figure 3.

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Current terminology uses the image of a core with at least two concentric areas

around the core (Heschl’s gyrus), the belt (neighboring sulci) and the parabelt (Figure

3). At this level the tonotopic arrangement continues. Timing differences as short as

0.8 ms can be distinguished. Both, ipsi and contralateral fibers reach the cortical areas.

The frontal lobe and the inferior parietal lobe are also described as areas that respond

to acoustic stimulation.

Along the CANS there are several points at which several of the ascending

auditory fibers (afferent) intersect and follow contra-laterally, thereby increasing

system redundancy. For example, at SOC occurs the first main intersection and upper

at corpus callosum auditory fibers establish a connection between the two auditory

cortexes (Katz, 1999).

One must bear in mind, that other so-called nonclassical pathways exist and

complement the central auditory processing. Another pathway, known as the auditory

cortico-cerebellar thalamic loop mapped in a close past, appears to have a role in

auditory attention and the integration of behavioral responses to auditory and visual

inputs (Pastor et al., 2008; Sens & de Almeida, 2007). The basal ganglia have been

identified as having a role in processing auditory signal aspects of speech, particularly

timing (Kotz, Schwartze, & Schmidt-Kassow, 2009). All these pathways bypass the

thalamo-cortical portion of the classical pathway, and proceed to the auditory cortex

by different pathways.

The final part of the auditory system also includes descending auditory

pathways (efferent) that follow in parallel the afferent pathways from the cortex to the

peripheral auditory system, specifically both cochleas. The fibers have both ipsi and

contralateral paths, featuring an anatomical journey similar to the ascending auditory

fibers (Musiek & Rintelmann, 2001). The olivocochlear efferent fibers influence the

function of outer hair cells and, thereby, affect the otoacoustic emissions (OAE)

(Zheng et al., 2000). Its exact function is still controversial. Efferent pathways, thought

to be part of a feedback loop that involves spatial orientation, helping the listener move

toward or away from the perceived stimuli. They contribute to basic awareness and

attention (Parvizi & Damasio, 2001).

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The most frequent complaint of auditory system dysfunction is the hearing loss.

Can be acquired or hereditary, stationary or progressive, unilateral or bilateral,

perceived by the own or the surrounding people.

Regarding degrees of hearing loss, the most widely used classification at

European level is the recommended by BIAP 02/1 bis (Bureau International

d'Audiofonologie, 2003), with the following criteria:

1. Normal hearing – the hearing levels less than 20 dB HL in the audiogram;

2. Mild hearing loss – between 21 and 40 dB HL, which involves hearing

problems in relation to low voice or in noisy environments; in children,

language development is normal, however small defects in speech

articulation can become significant as loss increases;

3. Moderate hearing loss – average tone loss between 41 to 55 dB HL (1st

degree) and 56-70 dB HL (2nd degree), which implies difficulty in hearing

normal voice; Speech is perceived if the voice is loud; The subject

understands better what is being said if he can see his/her interlocutor.

Some daily life noises are still perceived; problems arise in language

acquisition, phonetics and phonology is affected;

4. Severe hearing loss – average tone loss between 71 to 80 dB HL (1st

degree) and 81-90 dB (2nd degree). There are many difficulties in hearing

normal voice; Speech is perceived is the voice is loud and close to the ear.

Only loud noises are perceived. In cases of children oral

language/communication is not acquired without specific aid;

5. Profound/very severe hearing loss – exceeding 90 dB; 91-100 dB HL (1st

degree), 101-110 dB (2nd degree), 111 to 119 dB (3rd degree); This level of

deafness implies that the subject only listen very intense sounds, and word

discrimination usually is done with the help of other inputs (e.g., visual,

tactile). There is no oral language development, the consequence of this

situation may entail social maladjustment and adversely influence the

cognitive development of the child;

6. Cophosis/total hearing loss – loss equal to or greater than 120 dB HL, nothing

is perceived, there is not any auditory sensation.

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Another type of classification of hearing loss/deafness is the time of onset

regarding language acquisition (Goldfeld, 1997):

1. Prelocutive (0-3 years) - before language acquisition;

2. Perilocutive (3-5 years) - during language acquisition;

3. Postlocutive (> 5years) - after the acquisition of language.

During the periods referred above, the existence of hearing loss / deafness can

result in several complications, depending on age of onset have different implications

at various levels, e.g., reduction of acoustic-spatial perception (time, intensity);

decreased sensory stimulation; neocortical decreased stimulation (neuroplasticity);

decrease of communicative interaction (social, work and family); implications in

language, speech and cognition; psychosocial, social, professional and family

implications (Campiotto et al., 1997).

The last twenty years are marked by major advances in several areas related to

the study of the brain, with special emphasis on anatomy and neurophysiology of

hearing that in some American and British universities, originated the branch of

Neuroaudiology, which aims to study all neuronal processes that involve the

processing of speech and non-speech stimuli (Fuentes et al., 2008).

The central auditory processing (CAP) refers to a series of auditory operations

conducted to interpret detect sound vibrations. In a technical report the American

Speech and Hearing Association (ASHA, 2005) identified seven central auditory

processing mechanisms: (a) sound localization, (b) lateralization, (c) discrimination,

(d) pattern recognition, (e) temporal aspects of audition, including temporal

integration, temporal discrimination (e.g., temporal gap detection), temporal ordering,

and temporal masking, (f) auditory performance in competing acoustic signals

(including dichotic listening), and (g) auditory performance with degraded acoustic

signals (e.g., speech in noise). Other author consider different terms and concepts for

CAP capacities: auditory selective attention (the ability to select stimuli), detection

(ability to perceive and identify the presence or absence of sound), discrimination (to

differentiate between two or more stimuli), recognition (identifying sound and sound

source with the ability to classify or name what heard), to associate (ability to establish

correspondence between a non-language sound and its source) and comprehensiveness

(establishing relations between sound stimuli, other events and the environment own

70

behavior) (Carmo, 1998; Martins & Magalhães, 2006). An auditory processing

disorder (APD) is present when an individual has significant difficulty in one or more

of these processing mechanisms as demonstrated by abnormal performance on one or

more tests of central auditory processes (ASHA, 2005; Chermak, 2007).

The auditory or central auditory processing disorder (CAPD) translates into an

inability to perceive and understand the information contained in auditory stimulation,

even with normal audiometric tests, being a different concept or entity not associated

with hearing loss. This is due to possible flaws in the transduction of the stimulus,

slowing or failure in synaptic transmission, synaptic desynchronization, CANS injury

pathways and / or the cortical areas responsible for auditory information processing,

deficits in interhemispheric transfer and hemispheric asymmetries result of

neurobiological dysfunctions (Jerger et al., 2002; Kraus et al., 1996).

Chermak and Musiek (1997) estimated that CAPD occurs in 2 to 3 % of

children, with a 2:1 ratio between boys and girls, while Cooper and Gates (1991)

estimated the prevalence of adult APD to be 10 to 20 %. For these authors, CAPD

interferes with both the input and integration of verbal information, and results in a

potentially permanent cognitive dysfunction during the developmental period of

acquisition of language.

The impairment is not due to a disorder of attention, cognition, or language,

although these may be comorbid. When there is comorbidity, the auditory processing

deficit or dysfunction is not caused by the other disorder(s), although different views

and perspectives exist among clinicians. In light of this definition, a CAPD is not a

discrete diagnostic entity but a term of convenience that alerts the clinician to the

presence of one or more processing dysfunctions in one of the auditory processing

mechanisms (Bailey, 2010).

There is no ICD-10 code for APD (National Center for Health Statistics,

2009). Furthermore, this disorder is not recognized as a unique entity affecting school-

aged children in Diagnostic and statistical manual of mental disorders (DSM-IV-TR,

American Psychiatric Association, 2002). It seems there is insufficient scientific

evidence.

In Germany, Ptok and colleagues put forward a consensus definition, which

stressed that auditory processing disorders (APDs) are primarily based on deficits in

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the hierarchical processing of acoustic signals in the afferent nervous system (2000,

cit. in Neijenhuis, 2003). In addition, they made a proposal to classify APDs according

to the International Classification of Impairments, Disabilities and Handicaps (ICIDH).

In the International Classification of Functioning, Disability, and Health:

Children & Youth Version (ICF-CY), it is only considered the central auditory

processing capacities as part of the auditory function, but again, CAPD is not

considered as a diagnostic entity (WHO, 2007).

Based on the possible etiology of CAPD have been described (Carmo, 1998;

Pereira, 1997): repeated otitis in early childhood (respiratory allergic conditions such

as rhinitis and sinusitis, are usually associated); small lesions in the auditory afferent

pathways; deprivation of sound stimulation during childhood; neurological disorders

(e.g., neurodegenerative diseases, changes caused by anoxia, seizures); anatomical

changes of the CNS (gray matter - direct effect on auditory function; white matter -

interference with sound transmission); staying for more than 48 hours in neonatal

intensive care; preterm birth (birth weight < 1.5 kg); congenital problems (rubella,

syphilis, cytomegalovirus, toxoplasmosis and herpes); hereditary factors, and

cognitive deficits.

The CAP assessment should be performed whenever the subject has behavioral

and clinical manifestations. Behavioral symptoms are evidenced primarily by

difficulties of understanding in noisy environments, speech and language impairments,

writing and reading impairments, maladaptive social behaviors, attention deficit,

difficulties in following a conversation, and auditory memory impairment. Clinical

manifestations show failure in sound localization, decreased auditory memory but

normal audiometric thresholds. The evaluation should be done after the basic

audiological evaluation (pure-tone audiometry, speech audiometry and

tympanometry).

The CAP is assessed through special behavioral tests, such as: speech test with

white noise, filtered speech and binaural fusion test, binaural consonant-vowel test,

with competitive non-verbal sounds, among others (Filho, 1997). Moreover, there is no

clear acceptance of a "gold standard" test battery for evaluating this disorder.

Current studies aim at comparing and correlating between behavioral

psychoacoustic evaluations and electrophysiological. Although electrophysiological

72

measures demonstrate good correlations with behavioral measures for distinguishing

APD as a separate diagnostic entity (McArthur, Atkinson, & Ellis, 2009), in

neurodevelopment disorders or comorbid conditions seems to have low reliability and

sensitivity. Mainly, because many of these behavioral tests of central auditory function

were originally based on adult site of lesion studies and rarely consider the new

developments and discoveries in brain research techniques. Further, it is quite difficult

to have good collaboration with young children with tests with such complexity level

of performance. We shall call it the clinical hiatus, when researchers and

neuroscientists found it difficult to see its discoveries and groundbreaking methods

implemented and accepted in clinical practice, even by its colleagues.

If we are talking on neurodevelopment disorders such as dyslexia, epilepsy,

ADHD, autism or even brain injuries such as aphasia, passive objective measures are

required to assess disordered neuronal systems. We believe that ERPs might be the

answer, but with specific and validated paradigms.

The AERPs components occur in the same temporal dimension of the

dysfunctional neuronal circuits and the electrodes can be considered close to its

biological origin. Though, new homogeneous sample studies still need to be made in

order to achieve a high specificity, sensitivity, and reliability.

The Conceptualization & Neurodevelopment of Language

Language is a uniquely human cognitive faculty: no other animal has this

capacity to productively create signs that link a form and a meaning, and to combine

these signs into sentences. The latter capacity may have an exception for some

chimpanzees and orangutangs (Savage-Rumbaugh, Rumbaugh, & McDonald, 1985;

Savage-Rumbaugh, McDonald, Sevcik, Hopkins, & Rupert, 1986). There are more

than 5000 human languages in the world, representing a huge reservoir of phonemes,

morphemes, words, and syntax. With all this variety, what do human languages share

that the communication systems of other animals lack? According to Hockett (1960)

there are thirteen design features of language for primates. The human language is

distinguished by the last four: we are capable to combine and recombine morphemes

73

(duality of patterning); the sounds and speech-words we produce are rarely

predictable, only the onomatopoeia words (he called this – arbitrariness); we have the

capacity to combine and recombine the morphemes, words and sentences in different

ways and individual thoughts (generative capacity); and lastly the same words can be

combined in an endless variety of sentences (recursion). Hockett later added

prevarication, reflexiveness, and learnability. This cognitive capacity is due to some

set of anatomic and physiological properties in the human brain, but also a unique

human vocal tract, that even a chimpanzee goes beyond the complexity of a 2-year-old

human child (Wade, 1980).

But the main question therefore arises as to how the human brain got that

capacity, how it evolved, and why a functional and anatomical asymmetry is acquired.

Theories about the origin of language differ concerning their basic assumptions

about what language is. Communication is ubiquitous among animals, but only

humans seem to possess language. The uniqueness of modern language among animal

communication systems has raised several inquiries regarding our evolutionary origins

along with attempts to define a subset of unique, language-specific cognitive abilities

(Terrace, 2011). In this field we are probably discussing what defines us as humans.

There are continuity-based theories, deeming that language is so complex that it

must have evolved from earlier pre-linguistic systems among our ancestors. On the

other hand, we have discontinuity-based theories, stating that language is such a

unique human trait that it cannot be compared to anything found among non-humans

and that it must therefore have appeared suddenly in the transition from pre-hominids

to early man, thus being genetically encoded.

The first explanation for the origin of different languages, not the Language,

can be found in the Book of Genesis of the Bible with the story of the Tower of Babel

(from Hebrew: “Migdal Bavel”; Genesis 11: 4–9). In the story, there was only one

language in the world. However, a Lord wanted to reach Heaven and started to build a

huge tower and city. God came down to look at the city and tower, and remarked that

as one people with one language, nothing that they sought would be out of their reach.

God went down and confounded their speech, so that they could not understand each

other, and scattered them over the face of the earth, and they stopped building the city

and the tower.

http://en.wikipedia.org/wiki/Reflexiveness

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Only in 16th century the theme had a reborn. Descartes stated that humans’

capacity for language is due to the different nature of their âme (“mind/soul”),

compared to other animals. We use language to think creatively and discuss ideas.

Thus, language becomes part of an argument for both the existence of God and the

immortality of the soul. Our reasoning mind cannot originate from the mechanistic

power of matter but from a being that is not material – God (Bouchard, 2013).

Moreover, since the âme is entirely independent from the mechanistic body, the human

âme is not subject to dying with the body: it is immortal. From this point of view,

language was a blessing and was related to our species status – sons of God. Curiously,

it was in this same period (Renaissance) that the Flemish painter Pieter Brueghel

painted “The Tower of Babel” (1563; can be seen at Kunsthistorisches Museum,

Vienna).

From an evolutionary anthropology point of view, Li and Hombert (2002) give

four communication-aided activities that they correlate with the emergence of

language:

- the explosion of human population 60000 to 40000 years ago because

language facilitated all aspects of human activity and social interaction;

- the “big bang” of art 40000 years ago, because language facilitates

intellectual capabilities;

- the diversification and specialization of Upper Paleolithic tools starting 50–

40000 years ago, which they attribute to the communicative skills of language

(Greenfield, 1998);

- and the population of Australia 60000 years ago, which involved crossing

100 km of deep, fast-moving ocean water.

All this is correlated with language, because it required social organization,

collaborative effort, sophisticated planning, skills, and equipment for navigation. Their

explanation for the uniqueness of language in humans is that, in a flash of creative

innovation, an early hominid invented a communicative signal symbolizing an object,

and taught this to the social group (Li & Hombert, 2002).

Correlations between language and improved human activities in art and tool

making are very frequent, but not well founded when examined in detail (Bouchard,

http://en.wikipedia.org/wiki/The_Tower_of_Babel_%28Bruegel%29

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2013). The tools and cave patings can fossilize but not the so-called protohuman

language. This concept is one the main mysteries to be solved. It presupposes

monogenesis of all known languages, but not a common ancestor. The first serious

scientific attempt to establish the reality of monogenesis was that of Alfredo Trombetti

in 1905, estimating that the common ancestor of existing languages had been spoken

between 100000 and 200000 years ago in African continent (Ruhlen, 1994). Which is

in agreement with Homo sapiens age. In the opinion of other authors, the ability to

produce complex speech only developed some 50000 years ago with the appearance of

modern man or Cro-Magnon man (upper Palaeolithic; Klein & Edgar, 2002).

So, What Was Language’s Function?

The main obvious reason seems communication, much a matter for debate

whether communication is the function of language that drove its evolution (Kirby,

Smith, & Brighton, 2004). Other possible functions more commonly discussed are

internal “speech” (Chomsky, 2002), social grooming (Dunbar, 1993), sexual display

(Miller, 2000), and alliance-forming (Dessalles, 2000).

According to Chomsky (2005), the answer lies on the two key innovations of

language in the sudden emergence of the human intellectual capacity: “the core

semantics of minimal meaning-bearing elements and the principles that allow infinite

combinations of symbols, hierarchically organized, which provide the means for use of

language in its many aspects” (p.4). If we can explain why language evolved with

these two basic properties, we may know its very first function.

On the basis of adaptation by natural selection “the language faculty evolved

gradually in response to the adaptive value of more precise and efficient

communication in a knowledge-using, socially interdependent lifestyle” (Pinker &

Jackendoff, 2005, p.223).

Although Chomsky (2011) accepts that pressures to communicate may have

played a role, as a language of thought and externalization, he claimed that at its

origin, language could not have evolved due to communicative pressures because this

raises a problem. The Luria/jacob problem (Bouchard, 2013): How can a mutation that

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brings about a better communication system provide any survival advantage to the first

single individual who gets it? Burling (2005) says, “If no one else was around with the

skills to understand, what could the first speaker have hoped to accomplish with her

first words? The puzzle dissolves as soon as we recognize that communication does

not begin when someone makes a meaningful vocalization or gesture, but when

someone interprets another’s behavior as meaningful” (p.20).

Evolutionary neuroscience criticises investigation lines that focused largely on

whether language exists along some continuum with other communication systems, or

is categorically distinct (Fitch, Hauser, & Chomsky, 2005; Hauser, Chomsky, & Fitch,

2002; Pinker & Jackendoff, 2005; Terrace, 2011), and attempted to dichotomize

cognitive processes into those that are or are not “human-like” (Pinker & Jackendoff,

2005). Further, evolutionary neuroscientists and linguistics propose that there is more

to be learn about the neurobiology and evolution of language by studying mechanisms

that are shared by other species such as birds, rather than those that are unique

(Kiggins, Comins, & Gentner, 2012). On the basis, those mechanisms should be

present in protolanguages and/or ancestral hominids.

It is possible that language gave birth from the joint evolution of gestures and

vocalizations, which would explain the strong correlation between handedness and

verbal language located in the left hemisphere.

As we mentioned before, one of the difficulties is that language does not

fossilise, though we are able to infer some things from the skeletal remains of our

hominid ancestors, but only static elements not the active dynamic that language

requires. The only way is to look for living fossils and trace a plausible evolutionary

trajectory that will take us from this protolanguage to full modern human language.

Furthermore, evidence from existing languages does not support the view that

language is primarily an internal system for organizing thought and that externalization

is a secondary property (Bickerton, 1995; Kirby, 2007). From the evolutionary

perspective there has to be intermediate stages. Regarding this point, the movie Youth

Without Youth (Coppola, 2007), provides us an astonishing journey in the search for

the origins of language.

In other perspective, Rizzolatti and Arbib started to look at neurobiological

properties of human brains that differ from those of the brains of species in our closest

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lineage, and proposed the Mirror System Hypothesis (Arbid, 2005; Rizzolatti & Arbib

1998). It all started with the discovery of mirror neurons in the F5 zone of the brain of

monkeys. What is so special about these neurons is that they are activated when

individuals produce a sound/noise, a gesture of prehension or break an object but also

when they see a conspecific producing these same actions (Perrett, Rolls, & Cann,

1982). Some regions of F5 belong to Broca’s area homologs, controlling oro-

laryngeal, orofacial, and brachio-manual movements. Thus, Rizzolatti and Arbid

(1998) suggested the possibility that mirror neurons played a role in the evolution of

language, allowing individuals to recognize types of actions in themselves as well as in

conspecifics, facilitating the parity between the sender and the receiver of a message.

Moreover, it seems that mirror neurons system enables individuals (neuronal

structures/systems and body movements) self-modeling and modeling the behavior of

others, predict actions and consequences of actions performed by others (Arbid, 2002).

Some sort of beginning, the kind of empathy required in communication at the level of

human language (Gallese, Eagle, & Migone, 2007). However, the Mirror System

Hypothesis raises some doubts, mainly because mirror neurons code no more than just

a sensorimotor association having a limited function to a small subset of physical

actions, thus leaving all other events (physical and non-physical) without any internal

representation (Hickok, 2009).

The difference from our closest primate’s lineage is in the way some human

neuronal systems function.

A recent critique to the above mentioned theory is that language should not be

seen as a system of communication nor a system for organizing thought with a natural

selection pressure, but a system of signs instead (Bouchard, 1996; 2013). Language

would have evolved as a side effect of human brain and neuronal systems evolution.

We progressively acquired the capacity to link concepts and percepts, due to an

increase in synaptic interactions triggered by several factors (Bouchard, 2013)

probably genetic, environmental, nutritional, for example. Thus, the main difference is

that human neuronal systems can be activated in the absence of stimuli, in other words

the individual does not have to see or hear an action for these neuronal systems to be

activated. These are called Offline Brain Systems, triggered by representations of

events instead of the events themselves, and produce representations of events with no

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brain-external realization (Bouchard, 2013). This new concept seems to fit and

complement our Theory of Mind – understanding the thoughts of others, and the

ability to interpret and predict others’ behavior by the attribution of mental states, such

as beliefs, desires, feelings, etc. (Garfield, Peterson, & Perry, 2001) – phonological

development – language-specific capacity for phoneme perception, representation and

categorization (Dehaene-Lambertz & Baillet, 1998) – essential for language

acquisition.

Language is an object of study for many different sciences and different

currents of thoughts. There are three components to a comprehensive study of

language: a theory of what language is; the theory’s account of the way language

evolved in the human brain; and the theory’s explanation of the properties of language

(Bouchard, 2013). In this work, we believe it is relevant to emphasize how language

evolved in the human brain with sustained knowledge and new findings regarding

anatomical and physiological neuromaturation.

But What is Language?

As an object of linguistic study, “language” has two primary meanings: an

abstract concept, and a specific linguistic system, e.g., “Portuguese”. Language is the

human ability to acquire and use complex systems of communication, and a

“language” is any specific example of such a system. The Swiss linguist Ferdinand de

Saussure, who defined the modern discipline of linguistics, first explicitly formulated

the distinction using the French word langage for language as a concept, langue

(mother tongue) as a specific instance of a language system, and parole (speaking) for

the concrete usage of speech in a particular language (Lyons, 1981).

Being also a specific structured linguistic system, the language allows us to

map the space between concepts and articulation or perception (Origgi & Sperber,

2000). Traditionally, the study of the structure of language has been divided into a

number of subdisciplines, each of which tackles a different aspect of this mapping

system (Kirby, 2007):

1. Phonetics: the production and perception of sounds/manual gestures;

http://en.wikipedia.org/wiki/Human

http://en.wikipedia.org/wiki/Communication

http://en.wikipedia.org/wiki/Ferdinand_de_Saussure

http://en.wikipedia.org/wiki/Ferdinand_de_Saussure

http://en.wikipedia.org/wiki/Langue_and_parole

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2. Phonology: the systematic behavior of the sounds of language;

3. Morphosyntax: the system for combining the basic meaningful units of

language into words and sentences (sometimes this is divided into

morphology and syntax, is most clearly the study of the aspects of language

that govern how concepts and articulation/perception are connected);

4. Semantics: the meaning of words and sentences in isolation;

5. Pragmatics: the system for relating word/sentence meaning to

communicative intention in the context of communication.

From an evolutionary view there are four basic components of auditory

cognition for which the basic behavioral and neurobiological groundwork has already

been laid (Kiggins, Comins, & Gentner, 2012). We believe the importance of their

reference:

1. Segmentation: a fundamental aspect for perceiving complex

communication signals such as speech and language. The ability to

segment a sound into temporally distinct auditory objects. Human infants

are remarkably good at detecting word boundaries in speech (phonemic,

syllabic, and morphemic boundaries), at only 8 months of age through

transition statistics and prosodic cues (Jusczyk, 1999; Saffran, Aslin, &

Newport, 1996);

2. Serial expertise: sensitivity to the ordering of linguistic units across time.

This is vital to language comprehension, not only which elements occur in

a sequence, but also where they occur. Further, it requires sufficient

memory to store multiple items after a signal fades and to represent the

serial arrangement of those items. This reminds us the “problem of serial

order” (Lashley, 1951) and the chaining models for sequence-encoding of

Watson (2009) and Skinner (1934), stating that a given element’s location

in a sequence is encoded by association with both the preceding and

succeeding element. Accordingly, the sequence ABCD would be encoded

(most simply) as a sequence of pairwise associations, such as A–B, B–C,

C–D, where the recall of a single item initiates the recall of a subsequent

item. However, the pairwise concept cannot be related to MMN generation

model;

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3. Categorization: human linkage between acoustic information with

linguistic representations. This process is complex, starting with the

mapping of a component of the speech signal to the most elementary

linguistic unit – the phoneme. The notion of categorical perception in

speech was classically demonstrated by the work of Liberman and

colleagues (reviewed in Liberman, Cooper, Shankweiler, & Studdert-

Kennedy, 1967). Infants (6 to 8-month-old) rapidly and spontaneously

assess distributional patterns of auditory stimuli to determine categories

(Maye, Werker, & Gerken, 2002), as we shall see later;

4. Relational abstraction: the ability to apprehend and generalize relationships

between perceptual events is a fundamental component of human cognition

and a crucial capacity for language comprehension and production (for

review, see Hauser, Chomsky, & Fitch, 2002).

Keeping Hockett’s (1960) language features in mind, all the cognitive

characteristics stated above made possible the existence of a flexible lexicon. Lexicon

is essentially a catalogue of a language’s words (its wordstock). Must not confuse with

grammar, a system of rules that allows the combination of those words into

meaningful sentences. This aspect really sets human language apart as a uniquely

powerful tool for the unbounded transmission of cultural information with high fidelity

(Kirby, 2007). In addition, the lexicon is not the sole locus of variation in language, as

the phonological structure of languages varies, as does their syntax. This becomes

clearer when linguistics examine and compare in detail different languages or even

historically different languages. It is still a matter of controversy what these constraints

on variation indicate (e.g., are they innate?; or they could result from universal

properties of the way language is used) (Kirby, 2001; Newmeyer, 1998). In any case,

in this work we will only focus on language biological endowment.

Basic auditory functions are routinely screened in Audiology, Pediatric, ENT

and Neurology departments, by auditory brainstem evoked potentials in both preterm

and term infants (Hall, 2007). Despite normative data, at least to distinguish normal

from abnormal electrophysiological responses, the full extent and description of the

auditory maturational curve for children and adolescents has yet to be determined

(Bailey, 2010).

http://en.wiktionary.org/wiki/wordstock

http://en.wikipedia.org/wiki/Grammar

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It has gone nearly 40 years since Huttenlocher (1979) published is work in

which he described that synaptic density in neonatal brains is already high in the range

seen in adults in frontal lobe. However, synaptic morphology differed, due to

immature profiles that have an irregular presynaptic dense band instead of the separate

presynaptic projections seen in mature synapses. Further, he observed that synaptic

density reach a maximum at age 1-2 years which was about 50% above the adult

mean, and the decline in synaptic density observed between ages 2-16 years was

accompanied by a slight decrease in neuronal density. The number of synapses per one

neuron with age increases. However the number of neurons with age decreases. Thus

the total number of synapses decreases with age too (Nunez, 1995). This might be

related to ERPs amplitude over age. Though there is still be some doubts for a direct

connection or even quantification, relevant and deeper discussion as recently been

made (see Paper III).

Auditory processes do not develop linearly (Musiek & Baran, 2007). Human

cerebral cortex is one of a number of neuronal systems in which loss of neurons and

synapses appears to occur as a late developmental event. Some auditory processes are

well developed at birth, while others continue to mature into late adolescence. Similar

maturation processes occur in auditory cortex. The brainstem auditory pathway is

relatively mature at the time of birth (Moore, 2002; Ponton, Moore, & Eggermont,

1996), but an infant is able to hear even before birth. Newborns have at least three

months of experience of listening to their mothers’ sounds and environmental sounds.

Although the quality is not optimal due to smothering by tissues, liquid and mothers’

internal sounds, this prenatal stimulation is very important. Newborns possess the

ability to discriminate rhythm, intonation, frequency variation and phonetic

components of speech, thus recognising their mothers’ voices (Northern & Downs,

1991). This is proven by highly detailed neuroanatomical studies.

Moore carried out a developmental work in the neuroanatomical laboratory at

the University of Southern California in 2001. Traced the maturation of the human

auditory cortex from midgestation to young adulthood, using immunostaining of

axonal neurofilaments to determine the time of onset of rapid conduction. The study

identified three developmental periods, each characterized by maturation of a different

axonal system (perinatal period, early childhood and late childhood; Moore, 2002).

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During the perinatal period (3rd trimester to 4th postnatal month), neurofilament

expression occurs only in axons of the marginal layer (layer 1) of the cortex. These

axons drive the structural and functional development of cells in the deeper cortical

layers, but do not relay external stimuli although play an important stimulatory role of

large number of apical dendritic tufts for long distances (Moore, 2002; Moore & Guan,

2001). Brainstem auditory axons develop an adult-like content of neurofilaments

between 16th and 28th fetal weeks. Myelination of the axons first occurs between the

26th and 28th weeks of development, and by the 29th fetal week, the presence of click-

evoked brainstem auditory potentials indicates that rapid synchronous conduction is

already occurring (Moore, Perazzo, & Braun, 1995; Sarnat, 1998). In the first 6

months of life, babies gradually become better at distinguishing among high

frequencies as the brainstem and middle ear continue to mature (Bailey, 2010). Many

studies have shown that infants in the first months can accurately distinguish speech

sounds from different speakers (Hohne & Jusczyk, 1994; Jusczyk, Pisoni, &

Mullennix, 1992; Kuhl, 1979, 2011), what evolutionary neuroscientists call

“segmentation” as above stated.

Progressively, by age 6 months og age, babies can discriminate among higher

frequencies as well as adults, while the ability to distinguish among low frequencies

takes several more years to mature. Preschool children have difficulty separating

foreground from background sounds. Infants begin to listen significantly longer to

monosyllables that have a high probability of occurrence in their ambient language

(Jusczyk, Luce, & Charles-Luce, 1994), at the same time there is reduced

discrimination of sounds of a foreign language. In a classical study of MMN, involving

6 and 12 months of age Finnish children, the amplitude of the MMN increased to

contrasts in native phonemes, but decreased to contrasts between non-native (Estonian)

phonemes (Cheour et al., 1998). This categorisation ability refines by developing a

preference for the phonological contrasts of mother’s tongue, this is called the

“perceptual magnet effect”, becoming tuned to the auditory features of the language

before speaking the first words between 12 and 18 months of age (Kuhl, 2011).

At this stage, we are able to hear from 12-24 months of age children a type of

communication that does not share all the features of fully-modern language, with

minimal structure (e.g., “fix it”, “more cookies”). This stage of language development

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is considered a living fossil of protolanguage (Bickerton, 1995), probably representing

an early evolutionary stage of our full modern language.

In parallel, during early childhood (6 months to 5 years of age), maturing of

thalamocortical afferents to the deeper cortical layers are the first source of input to the

auditory cortex from lower levels of the auditory system. Neurofilament-expressing

axons first appear in the white matter core of the temporal lobe, with axons radiating

up into the deeper layers 4, 5, and 6, becoming clearly vertical and horizontal by 2

years of age, and progressively denser by 5 years (Moore, Perazzo, & Braun, 1995;

Moore, 2002). Again, this is consistent with Huttenlocher’s (1979) work regarding

development of synaptic density in human frontal cortex.

By 6 years of age (later childhood), children have generally reached adult

capacity to cooperate in a behavioral audiometric testing, although they are still prone

to becoming easily distracted by competing sounds (Bailey, 2010). Later, between the

ages of 7 and 10 during primary structured education, children become better able to

ignore irrelevant sounds and to maintain focus in an environment with competing

signals. However, not until after age 12 (years) are children able to discriminate as

finely as adults among consonant categories (Bailey, 2010). As a result, they rely more

on multiple sources of cues for this information than do adults (Werner, 2007). This is

coincident with the emergence of mature axons in cortical layers 2 and 3, with an

equivalent density compare to adults (Moore, 2002). This represents corticocortical

connections, in other words the maturation of commissural and association axons in

the superficial cortical layers, allowing communication between different subdivisions

of the auditory cortex, thus forming a basis for more complex cortical processing of

auditory stimuli (intra and interhemispheric). This enables the perception of speech

distorted by binaural switching, interruption, filtering, perception of sound in noise,

masked or degraded auditory stimuli, which are the basis of behavioural CAP tests to

study sensory (bottom-up) pathways but not linguistic (top-down) processing

(Chermak & Musiek, 1997; Eisenberg et al., 2000; Emanuel, 2002).

Children’s ability to identify consonant sounds accurately varies with the

quantity and quality of the listening environment. This ability does not reach adult

levels until about 14 years of age, as adolescents are confronted with noise-plus-

reverberation conditions more often (Johnson, 2000). Considering the auditory N1

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component, a preattentive auditory ERP, as indexing auditory perception and

discrimination with tonotopic organization in auditory cortex, or its magnetic

equivalent (M100), this confirms the assumptions that the maturation of the frontal N1

is not yet completed at the age of 9–12 years due to incomplete frontal myelination

(Bruneau, Roux, Guérin, Barthélémy, & Lelord, 1997). Thus, the above mentioned

high perceptual skills acquired by 12-14 years of age, mediated by intrinsic cortical

connections with high intracortical processing representing the final stage in the

maturation of the human auditory cortex (Moore, 2002), might be related with

N1/M100 generators maturation.

In addition, some authors consider that higher pathways involved in auditory

processing, such as corpus callosum and its fibre connections to cortex, mature much

later at about 15-20 years of age (Boothroyd, 1997; Ponton, Eggermont, Kwong, &

Don, 2000). Keeping the above in mind, this might justify the difficulties in assessing

behaviourally central auditory processing in children, especially under adolescence

age.

Remembering Bickerton’s “protolanguage” concept (1995), the described

maturational and neurodevelopmental processes might fill the lacking transition from

protolanguage to full human language. Despite these biological evolution

underpinnings, it is still not clear how language became cultural…or was it the other

way around? This is a further aspect of the question and one that will certainly be

considered in greater depth in future linguistic studies, in the light of parallels such as

the process of creolisation whereby children innovate a full human language after

exposure to a pidgin (Kirby, 2007).

Lastly, we cannot end this section without referring the hemispheric

asymmetries, as a sort of requirement for language acquisition. Throughout the history

of neuroscience lot of knowledge about the biological foundations of human behavior

have appeared closely linked to the concept of hemispheric lateralization or cerebral

dominance, in other words, the functional and anatomical differences between the two

hemispheres of the brain.

The very first study of the brain as a non uniform mass was developed by the

Austrian physician and anatomist Franz J. Gall in 1796. He is considered the founder

of Phrenology, a very popular pseudoscience in 19th century, based on the studying the

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shape of the human skull in order to draw conclusions about particular character traits

and mental faculties (Koenigs, Tranel, & Damasio, 2007).

Later, Marc Dax (cit. in Caldas, 2000) reported the association of aphasia and

paralysis of the right arm muscles in thirty patients, although it has not set any theory

or framed any scientific movement. Few decades after, in 1861, Paul Broca presented

eight cases of subjects who had a lesion in the posterior portion of the frontal gyrus of

the left hemisphere (LH), showing that this injury was associated with aphasia.

Further, he proposed that LH was language dominant and considered that both speech

and the use of the right hand were attributable to congenital superiority of LH in right-

handed people. According to this hypothesis, left-handed subjects would have a

dominance of the right hemisphere for both speech (language) and handedness (Plaja,

Rabassa, & Serrat, 2006). Three years later, in 1864, based on Brocas’s work, the

English neurologist John Hughlings Jackson highlighted the importance of the right

hemisphere in visual-spacial processing and in 1870, Hugo Karl Liepmann, shown that

LH controlled language and some severe apraxias may be associated with LH lesions

(Pearce, 2009).

Few years later, in 1876, Karl Wernicke found that the injury to a different part

of the brain in the LH, also caused language problems mainly at expression level rather

than understanding. This area now known as “Wernicke’s area” is located in the

posterior part of the temporal lobe and is connected to Broca’s area through a set of

nerve fibers known as arcuate fasciculus (Catani, Jones, & Ffytche, 2005), although

these fibers have already been described long time ago by Reil in 1809 and named

“Fasciculus Arcuatus” by Bouchard in 1822, both german neuroanatomists (Catani &

Mesulam, 2008). Wernicke’s disconnection syndrome – conduction aphasia – was to

become the prototype for all other types. Furthermore, he believed cognitive functions,

in contrast to movements and perceptions, are not localized in specific regions, but

emerge from associative connections linking areas where images of motor and sensory

memories reside (Catani & Mesulam, 2008).

During the World War II, clinicians started to see the surgical sectioning of

corpus callosum as a possible treatment of epileptic patients. In 1940, William Van

Wagenen performed the first surgical intervention sectioning of the corpus callosum

(split-brain). Later in 1959, Penfield and Roberts discovered that surgical removal

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affect certain functions lateralized to the left or right (Hamberger & Cole, 2011). This

line of thought prevailed decades, standing out the work of Roger Sperry during the

60’s, observing the differentiation and hemispheric lateralization of various functions

such as language, visuo-perceptual abilities and emotions (Sperry, 1982). He saw his

work recognised by winning the Nobel Prize in Physiology or Medicine in 1981 (The

Nobel Foundation, 1981).

Contemporaneous to Sperry, Norman Geschwind in 1965 initiates the study of

cerebral asymmetries in an anatomical and morphological perspective, correlating

them with known functional asymmetries from previous studies (Geschwind &

Levisky, 1968). This American neurologist upthrusted the neurobiological foundations

of cerebral dominance, targeting it as a neuroscience research field.

A wider cortical left temporal area, compare to that of the right hemisphere,

was found in Homo neardenthalensis (between 30 000 and 50 000 years ago) and

already in Homo erectus (between 300 000 and 500 000 years), this might justify the

currently dominant left hemisphere in speech at around 90% of cases for Homo

sapiens (Plaja et al., 2006). This could be the anatomical fossil that at least proof the

existence of protolanguage.

This left dominance for speech processing includes content identifying,

decoding symbolic/linguistic elements and coding. On the other hand, the right

hemisphere is more specialized for processing the prosody, tone, rhythm, intonation

and melody of speech. Certain aspects of language acquisition, including the time of

its inception, are universal and innately determined, while others - such as language,

dialect and accent - are determined and influenced by individual, social and

environmental factors (Plaja, Rabassa, & Serrat, 2006).

The anatomy of the infant Homo sapiens brain already shows hemispheric

asymmetries comparable to those found in adults, notably in the temporal lobes

(Witelson & Pallie, 1973). Further, functional asymmetry indicating superior

processing of short syllables in the left hemisphere involving arousal and attention-

orienting processes, which can be activated in less than one second, has been shown to

ERPs (Dehaene-Lambertz & Dehaene, 1994; Nelson & deRegnier, 1992). Thus,

suggesting a left-hemispheric advantage for language in infants rather than a sharp

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division of functions, probably affected by asymmetries in brain morphology such as

the orientation of the left and right sylvian fissures (Bertoncini et al., 1989).

It is known that left-hemisphere lesions cause impairments in the processing of

temporal but not spectral information in speech (Ilvonen et al., 2004; Robin, Tranel, &

Damasio, 1990). Thus, the left hemisphere is predominant in processing rapid acoustic

changes associated with language functions (Nicholls, 1996). On the other hand, right-

hemisphere lesions cause problems in perception and production of emotional prosody

(Alcock, Wade, Anslow, & Passingham, 2000; Bowers, Coslett, Bauer, Speedie, &

Heilman, 1987), which partly depend on the pitch-processing ability in order to

understand the emotional content of speech. Further, the right temporal lobe is more

sensitive to frequency variations, and thus being specific to spectral resolution

processing (Zatorre, Evans, Meyer, & Gjedde, 1992; Paper I).

Is Language Neurolaterality and Handedness Related?

Handedness is a better performance or individual preference for use of a hand.

Came to be regarded as the simplest and most obvious manifestation of “cerebral

dominance”. The left hemisphere, that directs the fine motor skills of the right hand,

constitutes for most of the population the dominant hemisphere for this activity as well

for language (with Broca’s and Wernicke’s area in the dominant hemisphere, linked by

a white matter fiber tract – arcuate fasciculus). This “language loop” can occasionally

be found in the right hemisphere of right-handed (Knecht et al., 2000).

Handedness is not a discrete variable (right or left), but a continuous one that

can be expressed at levels between strong left and strong right. This concept became

clear the development of questionnaires and other instruments for measuring

handedness as is the case of Edinburgh Handedness inventory, among others, which

have been imposed as simple tools in daily practice (Oldfield, 1971). Studies

conducted in several countries, point to the likelihood of the right-handed account for

over 90% of individuals, whatever their cultural background although only 70% of the

population seems to be “strong right-handed” (who make all acts exclusively with the

right hand), this finding allowed the emergence of some theories of "biological origin"

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of this distribution (Habib, 2003). Regarding language laterality, 95% of right-handed

people have left-hemisphere dominance for language, 18.8% of left-handed people

have right-hemisphere dominance for language function, and 19.8% of the left-handed

have bilateral language functions (Schönwiesner, Rübsamen, & von Cramon, 2005).

Furthermore, various language functions (e.g., semantics, syntax, prosody) may differ

of dominance may differ (Medland et al., 2009). The relation between language

laterality and handedness is not strict.

In fact, studies already in the 60s with the Wada test, or “Intracarotid Sodium

Amobarbital Procedure (ISAP)” technique, invented in 1949 by Juhn Wada, that

momentarily interrupts the function of a particular brain region when is injected a

solution of sodium amytal directly into the artery that irrigates that brain region, show

that the organization of the lefty brain (Wada & Rasmussen, 2007), far from being the

mirror image of the right-hander, has its own functional characteristics, rather than the

absence of mechanisms present in the latter (van Emde Boas, 1999).

These findings are now confirmed by modern neuroimaging techniques such as

functional magnetic resonance imaging (fMRI) and positron emission tomography

(PET), showing that the left hemisphere is responsible for the processes of language in

the vast majority of right-handed but also in more than half of the left-handed and

ambidextrous (Matthews et al., 2003). Therefore, “right handedness and lateralization

of language in the left hemisphere are phenomena that often go hand in hand but

whose commonality is not a functional relationship but rather two independent

genetically determined characteristics” (Caldas, 2000).

As mentioned before, Geschwind’s work was also important to establish a

possible relation between hemispheric morphology asymmetries and handedness. In an

anatomic working with 100 dissected brains of normal individuals, in order to analyse

the sylvian fissure, Norman Geschwind and his team studied the triangular surface

located behind the primary listening area, the planum temporale (posterior to the

primary auditory cortex, Heschl's gyrus), and showed that this was clearly more

developed in the left of 65% of the brains. In other cases, in turn, this structure was

somewhat symmetrical or slight asymmetrical for the right side (Geschwind &

Levisky, 1968). Furthermore, Geschwind’s theory postulates that planum temporale

morphological asymmetry is related to language functional asymmetry and

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hemispheric dominance, based on the argument that increased fetal testosterone levels

modify neural development, immune development, and neural crest development

(Geschwind & Galaburda, 1985; McManus & Bryden, 1991).

Nowadays, the brain is seen as a chaotic unit composed of several

interconnected systems, whose maturation and neuropsychophysiological development

occurs from the womb to adulthood. The history and research of hemispheric

lateralization is not over yet. However, we may conclude, for now, that there is no

“dominant” hemisphere and a lower or “dominated”. Instead, we have two

complementary hemispheres that need each other to carry out tasks from the simplest

reflex activities to more elaborate reasoning or acts of artistic creation.

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Chapter III

Neuropsychophysiology of Auditory Processing

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In the first half of this chapter we will clarify the differences between

Audiological and Psychological classification of evoked and event-related potentials.

One based on latency and anatomical aspects, the other on functional meaning. This

approach is important in order to achieve a consensus between research and clinical

practice. Furthermore, the so-called auditory evoked potentials rational has limitations

in assessing and interpreting neurofunctional processing. Event-related potentials

largely underpinned and construed by Psychology, can be highly valuable in assessing

the different stages of auditory and language processing for a better diagnosis,

prognosis and treatment strategies in neurodevelopmental disorders. This chapter

reviews AERP’s state of art, auditory functional meaning, and intends to impel its

clinical use. We review the auditory processing structures, its components, assessment

and dysfunction, summarized in Table 1. In addition, Paper II suggests normative

values for N1 and N2 components in order to be considered by clinicians and

researchers in assessing central auditory processing.

The second half relates language processing with the most recent

neurocognitive auditory processing model, underpinned by ERPs and imaging studies.

Allowing a better understanding of how we can assess language impairments in

disorders such as epilepsy, dyslexia, and aphasia. But also, what does the mentioned

disorders tell us about language and auditory processing. Paper III hypothesizes TLE

in childhood as a unique model to study topographic and functional central auditory

processing, due to its limited affection of temporal lobe. Paper IV presents a case study

of a Broca’s aphasia that evolved to an anomic aphasia. In this case, we analyse the

contribution of MMN and N2b to explain and assess the underlying language deficits

but also as AERPs components representing sensory memory and phonological

processing.

Evoked and event-related potentials are changes in electrical potential that are

specifically related in time to the preparation or response to stimuli or events. These

potentials, recorded in the electroencephalogram in response to a variety of stimuli,

include motor and cognitive long latency potentials (e.g., mental processing). Allow

assessment of brain physiology while the subject is performing a cognitive task, thus

providing a non-invasive technique for neurofunctional evaluation, fairly economic,

and with excellent temporal resolution.

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The Auditory Evoked Brain Responses: short, middle and long latency

Since the enunciation of Cell Theory in 1830, stating that all parts of both

plants and animals are made up of cells and the product of cells, Theodor Schwann

concluded that the nervous system was an exception, it just looked different to

microscopes of the time (cit. in Shepherd, 1991). Only several decades later, based on

the Reticular Theory of Camillo Golgi in 1873 and on the work of the German

anatomist Wilhelm Waldeyer in 1891, the Spanish neuroanatomist Santiago Ramón y

Cajal formulated the Neuron Doctrine stating that each neuron is a separate cell (all.

cit. in Webster, 1999). Subsequently, the latter transmit information in only one

direction, always away from the cell body – Dynamic Polarization of Neurons.

However, this second law of Cajal has important exceptions, because dendrites can

serve as synaptic output sites of neurons and axons can receive synaptic inputs

(Djurisic, Antic, Chen, & Zecevic, 2004).

In electrophysiology it is essential an understanding of the nature of electricity

and the behavior of charged particles with one fundamental principle – like charges

repel and opposite charges attract (Sinclair, Gasper, & Blum, 2007).

We cannot say that our brain has AC (alternate current; the flow of electric

charge periodically reverses direction) or DC (direct current; the flow of electric

charge is only in one direction), though it is similar to AC.

The human brain contains more than 100 billion neurons starting its electric

activity around the 17-23 weeks of prenatal development (Williams & Herrup, 1988).

It is assumed that at birth the full number of neural cells is already developed, roughly

1011

neurons (100 billion), the majority of which have the ability to influence many

other neurons (Nunez, 1995; Ullian, Sapperstein, Christopherson, & Barres, 2001).

They can be functionally divided in (Smith & Kosslyn, 2007): sensory or afferent

neurons, activated by input from sensory organs such as the eyes and ears; motor or

efferent neurons, responsible for stimulating muscles; and interneurons, the vast

majority of the neurons in the brain, stand between sensory and motor neurons or

between other interneurons forming vast networks of neuronal ensemble of circuits. It

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is through this communication process, termed signaling, that electrical activity is

generated, resulting in the human EEG.

If the excitatory input reaching a neuron is sufficiently greater than the

inhibitory input, the neuron will produce an action potential. That is, it will “fire”,

neurons obey an all-or-none law: either they fire or not. Depolarization during the

action potential is very large, but very brief, lasting only 1 ms. Thus, only EEG,

evoked and event-related potentials can detect and register these processes, due to high

temporal resolution. However, only large populations of active neurons can generate

electrical activity recordable on the head surface (Tyner & Knott, 1989).

If there is depolarization of the membrane, the potential is termed an excitatory

postsynaptic potential (EPSP), whereas, if there is hyperpolarization, the potential is

called an inhibitory postsynaptic potential (IPSP; Holmes & Khazipov, 2007). EEG

measures mostly the currents that flow during synaptic excitations of the dendrites of

ten of thousands of synchronously activated pyramidal neurons in the cerebral cortex.

Differences of electrical potentials are hypothesized to be caused by summed

postsynaptic graded potentials from pyramidal cells that create electrical dipoles

between soma (body of neuron) and apical dendrites (neural branches). The orientation

of their dendritic trunks (parallel to each other and perpendicular to the cortical

surface) allows summation and propagation to the scalp surface (Nunez & Silberstein,

2000).

More precisely, regarding scalp recorded EEG oscillations, and mainly ERPs

polarity, negative potentials at the surface can arise either due to superficial EPSPs

(excitation at apical dendrites) or from deep IPSPs (inhibition of the soma).

Conversely, positive potentials at the surface can arise either due to superficial IPSPs

(inhibition at apical dendrites) or from deep EPSPs (excitation of the soma; Pizzagalli,

2007; Speckmann, Elger, & Altrup, 1993).

It is important to mention that deeper structures, such as the hippocampus,

thalamus, or brainstem, do not contribute directly to the surface EEG; only cortical

macrocolumns (Baillet, Mosher, & Leahy, 2001; Fisch, 1999). However, transmission

of electrical impulses from distant sites has substantial effects on the surface EEG. For

example, thalamocortical connections are critical in the synchronization of electrical

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activity, such as sleep spindles, and subcortical contributions to scalp-recorded EEG

have been reported (Holmes & Khazipov, 2007; Lopes da Silva, 2004).

With 140 years of history, since the discovery of electrical currents in the brain

by the English physician Richard Caton in 1875, the electrophysiology and

encephalography have undergone massive progress. One historical landmark was in

1924, when Hans Berger, a German neurologist, used his ordinary radio equipment to

amplify the brain's electrical activity measured on the human scalp, using the word

electroencephalogram as the first for describing brain electric potentials in humans

(Bronzino, 1995; Pizzagalli, 2007). Nowadays, clinical neurophysiological studies are

based on the recording of both spontaneous electrical activity, as with the EEG, or

with stimulated responses, such as evoked potentials. Mind notice, that there is also the

electrocorticography (ECoG), or intracranial EEG (iEEG), as the practice of using

electrodes placed directly on the exposed surface of the brain to record electrical

activity from the cerebral cortex (Palmini, 2006). This is an invasive procedure, in this

work we will refer to the non-invasive classical EEG.

Auditory Evoked Potentials Ethnicity

With the development and application of evoked potentials to clinical practice,

several classifications have been proposed across different areas and disciplines. In

spite of different evoked potentials to different types of stimuli, in this section we will

only analyse the auditory evoked potentials. The latter are changes in brain electrical

activity caused by auditory stimulation. Since they are embedded in the background

EEG activity, a large number of potentials can be collected, filtered and averaged to

enhance the signal-to-noise ratio and to obtain a clear evoked potential (Musiek &

Rintelmann, 2001).

In Audiology, the auditory evoked potentials are classified in short, middle and

long latency (ALLR). In other words, based on latency, auditory pathway length and

automatic sensory/perception parameters. From a psychological point of view, it is

more convenient to distinguish in (Fabiani, Gratton, & Federmeier, 2007): sensory or

exogenous (largely controlled by the physical properties of an external eliciting event);

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endogenous (largely determined by the nature of the interaction between the person

and the event, other can be elicited in the absence of an external eliciting event); and

mesogenous (sensitive to both the physical properties of the stimulus and the nature of

the interaction between the subject and the event, e.g., whether the event is to be

attended or not). Figure 4 clarifies both points of view and the transition from

automatic sensory processing to attention dependent/orienting cognitive processing.

Figure 4. Auditory evoked potentials (n.d.).

The first human AEP was recorded by the Russian scientist Vladimirovich

Pravdich-Neminsky in 1913. Since then, the evolution of the AEPs was parallel to

technological development (McPherson & Ballachanda, 2000). Non-invasive

measurement of electrophysiology and sensory evoked potentials, immediately

assumed great importance and applicability in research, differential diagnosis,

evaluation neurotology assessment, auditory neonatal screening and intraoperative

monitoring, contributing to a better topographical and functional understanding of

hearing and central auditory disorders.

In a normal subject, BAEPs or ABR occur from 1-10 ms being the waves

classified with Roman numerals (I, II, III, IV, V, VI and VII; Jewett & Williston,

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1971). BAEPs have been used in clinical medicine from the 1970s for the diagnosis of

brainstem pathology and audiological dysfunction (Musiek & Rintelmann, 2001;

Zaidan et al., 2007). In fact, they are the most frequently used AEPs in the clinic. Due

to their exogeneity, BAEPs are unaffected by subjective variables and good predictors

of cochlear sensitivity and the retrocochlear status of the auditory pathway from

cochlea to the brainstem (Cummings & Harker, 1986). Monaural click stimuli and

contralateral white noise are generally used. Each wave has a main generator, though it

is known that other close sources contribute (Table 1).

The MLAEPs or AMLR were first described by Geisler, Frishkopf and

Rosenblith (1958). However, due to lack of data that could confirm its effectiveness,

this potential has been attributed to a myogenic artifact, making it difficult to accept as

a clinical procedure for hearing evaluation. Later, in 1974, Piction described the

various components of AEPs, including the MLAEPs (Schochat, Rabelo, & Loreti,

2004). At this stage AEPs are named according to their polarity (P for positive and N

for negative): Po, Na, Pa, Nb, and Pb or P1, and are still considered exogenous (P50, at

least according to montage – Fpz, Cz, C7; McPherson & Ballachanda, 2000). Studies

of P50 are typically composed of a paired-click paradigm, in which a pair of auditory

stimuli (S1, S2) are presented, with an ISI of 500 ms. This positive wave, indexes the

auditory sensory gating, which is a neurological processes of filtering out redundant or

unnecessary stimuli in the brain from all possible environmental stimuli (Freedman et

al., 1987). For normal auditory sensory gating, if a person hears a pair of clicks within

500 ms of one another, the person will gate out the second click because it is perceived

as being redundant. In other words, in normal subjects the first stimulus that the

subject hears inhibits the neurophysiological processing of the second stimulus in 80-

90% (McPherson & Ballachanda, 2000; Wan, Friedman, Boutrous, & Crawford,

2008).

During the last decade, these potentials have been seen as one of the most

promising electrophysiological tests to evaluate changes in CANS (e.g., dyslexia,

epilepsy, schizophrenia, stroke, cochlear implant candidate user, and deep anaesthesia

monitoring) and its clinical and scientific contribution is important for health

professionals, such as otolaryngologists, audiologists, neurologists,

neuropsychologists, among others. These potentials are synchronized and rapid

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auditory evoked responses after presentation of an acoustic stimulus, occurring

between 10 and 80 ms, and can be evoked by clicks, tone pips, tone bursts or logon.

This is an advantage, because enables frequency evaluation, since central auditory

connections can preserve the tonotopy observed in the cochlea, and MLAEPs reflect

the activation of the thalamocortical pathway and the primary auditory areas

(Fukushima & Castro, 2007).

The long latency auditory evoked response potentials occurring at and after 200

ms are mostly considered endogenous, in other words, are evoked by internal mental

processes and reflect higher cortical functions such as discrimination, pre-attentive,

attention, phonological categorization, sensory memory, target detection and working

memory regarding central auditory processing (N2, P3a, P3b, N400; Bailey, 2010;

Katz, Medwetsky, Burkard, & Hood, 2009; Salo et al., 2002). Although the

exogenous/endogenous distinction provides a useful method for classifying many ERP

components, there are potentials that possess characteristics that are intermediate

between these two groups, and are therefore called mesogenous (e.g., P1, N1, P2, and

MMN).

In this work, we will refer to the sensory auditory event-related potentials

(AERPs), time-locked components from the EEG signal, elicited from auditory

oddball paradigms and considering a psychological and neuroscience interpretation.

Some authors consider the following classification (Fabiani, Gratton, & Federmeier,

2007; Näätänen & Picton, 1986): early cognitive components (P1, N1, and P2),

middle-latency cognitive (N2 and MMN), and late cognitive ERPs (P3, N400, P600).

In auditory novelty processing experiments, the experimental paradigm that

seems the most feasible is the above mentioned oddball paradigm. The oddball

paradigm, as a signal-detection paradigm was first described by Ritter and Vaughan

(1969). In the auditory modality, it was first used in 1975 by Squires, Squires and

Hillyard at the University of California, San Diego, USA (Squires, Squires, &

Hillyard, 1975). In this paradigm, physically deviant stimuli (silence included) are

randomly presented among repetitive streams of homogenous sounds – standard

stimuli (Donchin, 1981; Jääskeläinen, 2012; Näätänen, 1975; Näätänen, Gaillard, &

Mäntysalo, 1978). Thus, providing a measure of functional brain neuroelectric activity

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that occurs within a given time period on a significant event, reflecting successive

stages of processing information (Fabiani & Friedman, 1995).

The N1 wave

The electrically recorded N1 or N100 in auditory oddball stimulation is a

fronto-centrally negative wave response, which peaks about 100 ms after stimulus

onset and lasts for approximately 100 ms, generated bilaterally mainly in the auditory

cortices (May & Tiitinen, 2010; Näätänen & Picton, 1987; Tiitinen, May, Reinikainen,

& Näätänen, 1994). However, multiple sources have been identified to generate N1

wave. Closely following the P1 component (Hamm et al., 2013; Yvert, Crouzeix,

Bertrand, Seither-Preisler, & Pantev, 2001), some authors prefer to consider the

mesogenous P1-N1-P2 complex, a negative polarized response with its latency around

100 ms. It is a cortical response to sound, thought to be useful in evaluating the

integrity of the auditory pathway (Zheng et al., 2011).

These ERP components reflect sensory and perceptual processes. Further, N1

seems to reflect early synchronization between primary and secondary auditory

cortices in the lateral and STP (Liasis et al., 2006; Yvert, Fischer, Bertrand, & Pernier,

2005). Additionally, auditory selective attention and interstimulus interval (ISI) are

suggested to modulate N1 amplitude. The N1 amplitude is larger when the subject is

performing a cognitive task during the recording, and the response is even larger with

a more demanding task. This may be due to an increase in the excitability of some

neuronal populations contributing to N1 (Hillyard, Hink, Schwent, & Picton, 1973;

Näätänen & Picton, 1987). Regarding ISI, N1 amplitude increases for ISIs from 0.5 s

up to about 10 s (Davis & Zerlin, 1966).

For a review of N1 see Paper II. Additional article’s requests can be found from

appendix 2 to 5.

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The P2 wave

P2 arises with a latency of 150-250 ms (for review, see Crowley & Colrain,

2004). It is maximal over the vertex and is generated mainly in the vicinity of the

auditory cortex within the temporal lobe. Unlike the N1 or the other late ERPs, little

work has been done on the P2 to elucidate the generation mechanisms and clinical

significance. However it appears to represent activity from at least two sources, the

planum temporale and the auditory association cortex. P2 is affected similarly to N1

by many factors, for example, when the stimulus intensity decreases the amplitude

decreases and latency increases (Picton, Woods, & Proulx, 1978). However, there is

evidence that N1 and P2 are results of independent processes with different

topography and P2 is one of the few peaks that is enhanced across the adult lifespan

(Crowley & Colrain, 2004).

The N2 wave

The N200 or N2 in response to attended or unattended deviant auditory stimuli

was originally seen by Sutton, Braren, Zubin, and John (1965). However, it was

Squires, Squires, & Hillyard (1975) whom first described the N200 in a paradigm in

which they manipulated stimulus frequency and task relevance independently, and

found that the N200 was larger for rare stimuli.

This is one of the ERP components that require caution in interpreting. Scalp

distribution and functional significance vary according to modality and experimental

manipulations. For instance, different N200s can be observed for the visual modality

(with maximum amplitude at occipital recording sites) and for the auditory modality

(with maximum at the central or at frontal recording sites). It is represented by a

negative-going wave that peaks 200-350 ms post-stimulus, and can be further divided

into three different sub-components: N2a or auditory MMN, N2b, and N2c; the main

neural generators are the anterior cingulated cortex, frontal and superior temporal

cortex (Folstein & van Petten, 2008; Patel & Azzam, 2005). The first two components

are widely accepted to contribute to forming N2, usually labeled MMN (N2a) and N2b

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(Novak, Ritter, Vaughan, &, Wiznitzer, 1990; Novak, Ritter, & Vaughan, 1992). The

first component (MMN) has been related to the automatic detection of stimulus

changes, reflecting the disparity between the deviating stimulus and a sensory-memory

representation of the standard stimulus (Näätänen, 1982; Ritter, Simson, Vaughan, &

Friedman, 1979), while the later component (N2b) is interpreted as a correlate of

controlled detection of stimulus changes and phonological categorization (Amenedo &

Díaz 1998; Näätänen, 1982; Näätänen et al., 2007; Ritter et al., 1979).

Furthermore, after incoming stimulus detection, additional cognitive processes

are required for stimulus classification and categorization. For speech stimuli, N2b

subcomponent is particularly important for the study of phonological activation

processes (Becker & Reinvang, 2012; Patel & Azzam, 2005). N2b component seems

particularly important, if we consider Pulvermüller’s work that proposes cell

assemblies organization in perisylvian cortices for phonological word forms and

memory traces (Pulvermüller, 1996; Pulvermüller et al., 2001; Pulvermüller &

Shumann, 1994).

It is largely consensual that the N2 is an endogenous potential and represents

some cognitive control function. However, some authors state that N2 reflects a

cognitive control function, specifically an inhibitory response control mechanism

(Folstein & van Petten, 2008), and others consider that N2 does not represent

response-inhibition, but rather conflict monitoring (Donkers & van Boxtel, 2004).

For review of N2 see Paper II.

The MMN wave

In the auditory oddball paradigm, when the repetitive stimulation (frequent) is

interrupted by a stimulus audibly different (called deviant), an enhanced negative

potential and strength of magnetic field occurs in the 100-200 ms poststimulus latency

range (May & Tiitinen, 2010). This response was first discovered by Butler (1968) and

suggested by Snyder and Hillyard (1976) as having a mismatch detector function.

Later, Näätänen, Gaillard, and Mäntysalo (1978) subtracted the wave response to the

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standards from the response to the deviant obtaining a resulting difference wave. They

named it mismatch negativity (MMN).

After decades of research, the mismatch negativity (Näätänen, 1995; Näätänen

et al., 2007) is a change-specific component of the ERP considered representing the

brain processes that form the biological substrate of central auditory perception,

memory and attention. The classical MMN is a fronto-centrally (Fpz, Fz and Cz)

negative component of the auditory ERP usually peaking at 100–250 ms from stimulus

onset and positive at mastoids. Its mainly generators are the bilateral supratemporal

cortices with contributions of the frontal lobes, right parietal lobe, thalamus and

hippocampus (Näätänen, 1975, 2001; Näätänen et al., 2007). Currently, MMN

provides an objective measure of auditory perception and discrimination based on the

presence of short-term memory (sensory memory) and echoic memory trace,

representing a repetitive aspect of the ongoing stimulation before a deviant event elicit

it, fading within 5-10 s (Hari et al., 1984; Näätänen, Paavilainen, Alho, Reinikainen, &

Sams, 1987; Näätänen & Alho, 1997; Näätänen, 2001).

Although this memory-based model is widely accepted, there are different

views concerning MMN generation and interpretation, such as the adaptation and the

predictive models (for a short overview see: May & Tiitinen, 2010; Winkler, 2007).

But the main differences are that the memory-based model (Näätänen, 1990) states that

N1 reflects an afferent exogenous process (transient and feature-detector system) and

MMN reflects a separate endogenous process (memory mechanism) whose

representations of the environment are used by a neural comparison process to detect

auditory changes (the same for other type of sensory information). On the other hand,

the adaptation model (Jääskeläinen et al., 2004; May & Tiitinen, 2004, 2010)

considers that the enhanced response is due to the activation of new neuronal units,

also called fresh afferents, not habituated by the preceding frequent stimulus but that

overlap the neuronal population that is mapping the latter. Further, the concepts of

adaptation (refractoriness) and lateral inhibition imply that neurons responding to the

repetitive stimuli become suppressed through stimulus repetition; the deviant then

activates neurons that are less suppressed and therefore elicits a larger ERP/ERF

response. Thus, the MMN is essentially an enhanced N1 response, because it is

generated by the same neural populations. Thus, MMN is sometimes considered a

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bridging component between exogenous and endogenous categories (Kraus & Nicol,

2009). Lastly, the predictive (generative) model (Winkler, 2007) is a very interesting

interpretational framework of MMN. It considers that our brain encodes auditory

streams and temporal patterns of the surrounding sound environment, producing

predictions about what sounds are likely to be encountered in the near future. The

CANS links each incoming sound with the currently active regulatory representations.

When this process fails or there is a violation the MMN is elicited and the predictive

model is updated. This model provides the basis that the memory representations in

MMN-generation show both auditory sensory memory effects and categorical memory

representations, thus a crucial step in the formation of auditory objects or phonological

skills.

Bauer et al. (2009) found that children with auditory processing disorders

(APD) had significantly lower incidences of MMN compared with normal controls,

which implied poorer discriminative ability in children with APD. In patients with

cochlear implants, the MMN can be used as an early indicator for speech perception

(Lonka et al., 2004).

The MMN amplitude increases as the difference (e.g., frequency, latency,

intensity) between the frequent and the deviant stimulus is greater, suggesting that the

amplitude is a function of the magnitude of the physical difference between stimuli

(Amenedo & Escera, 2000; Näätänen, 1982; Tiitinen et al., 1994).

Lastly, analysis of the auditory cortices indicates that the MMN reflects NMDA

channel activity (glutamate N-methyl-aspartate), more precisely NMDA antagonists

block MMN elicitation (Javitt, Steinschneider, Schroeder, & Arezzo, 1996). Other

authors also established a correlation between gray matter volume of left Heschl gyrus

and the MMN amplitude in middle-front location (Kasai et al., 2003).

The P3 wave

Half a century ago, the group of Sutton (1965) first described the P300, an

endogenous component from the event-related potential (ERP), as its occurrence links

not to the physical attributes of a stimulus, but to a person's reaction to it, peaking

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between 250-500 ms after stimulus onset. The research conducted so far suggests that

the P300 may result from the summation of activity from multiple generators, located

in widespread cortical and possibly subcortical areas (Knight, Scabini, Woods, &

Clayworth, 1989), but there is still no conclusive indication of the brain sources

underlying this scalp-recorded activity. However some authors consider as generators

of auditory P300 the auditory cortex, centroparietal cortex, hippocampus, and frontal

cortex (Martin, Tremblay, & Korczak, 2008).

Generally, the P300 has been associated with cognitive information processing

(e.g., memory, attention, executive function, context-updating). It contains two

distinguishable subcomponents: the novelty P3, or P3a, and the classic P300, which

has since been renamed P3b (for review see Polich, 2007; van Dinteren, Arns,

Jongsma, & Kessels, 2014). The P3a is related to the engagement of attention,

especially the orienting, involuntary shifts to changes in the environment, and the

processing of novelty not necessarily related to the generation of responses (Donchin,

1981), displaying maximum amplitude over frontal/central electrode sites. The P3b

amplitudes are typically highest on the scalp over parietal brain areas (Pz), and this

subcomponent is widely studied on information processing, decision making, and even

measure how demanding a task is on cognitive workload (Duncan et al., 2009; Polich,

2007).

Other Late AERPs

Other AERPs peaking after 300 ms exist and are widely studied as endogenous

language-related components. We will not discuss them in detail, since they are mainly

not studied with auditory oddball.

One of these components is the N400, originally recorded in a sentence-reading

task by Kutas and Hillyard (1980). Peaks around 400 ms post-stimulus onset and is

typically maximal over centro-parietal electrode sites. The N400 response is seen to all

meaningful or potentially meaningful stimuli, thus indexing semantic processing. As

such, a wide range of paradigms have been used to study it, involving spoken words,

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pictures embedded at the end of sentences, music, etc. (Daltrozzo & Schön, 2009;

Kutas & Federmeier, 2000).

Regarding linguistic and musical syntax processing, there are three distinct and

promising AERPs: (1) the Early Left Anterior Negativity (ELAN) is a recent described

ERP, elicited by phrase structure violations (Friederici & Weissenborn, 2007), (2) the

Left Anterior Negativity (LAN) associated with syntactic processing, often linked to

grammatical function words (Kluender & Kutas, 1993); (3) the Early Right Anterior

Negativity (ERAN), which reflects fast and automatic neural mechanisms that process

complex musical (music-syntactic) irregularities (Koelsch, Schmidt, & Kansok, 2002).

Lastly, the P600 or syntactic positive shift (SPS) is a late centroparietal

positivity associated with the processing of syntactic anomalies (Hoen & Dominey,

2000; Osterhout, 1997). First reported by Osterhout and Holcomb (1992), the P600 is

elicited by hearing or reading grammatical errors and other syntactic anomalies,

representing sentence processing in the human brain. However, it is still debated on

whether or not it is specific to syntactic processing (Osterhout & Hagoort, 1999).

Magnetoencephalography (MEG) indicates that the generators of the P600 are in the

posterior temporal lobes (behind Wernicke's area), basal ganglia, thalamus and anterior

cingulate cortex (Service, Helenius, Maury, & Salmelin, 2007).

In sum, the EEG is a non-invasive, economic and high temporal resolution

method to evaluate brain neurophysiology. One of the most important advances in

EEG-based research was the development of a technique to isolate the brain activity

related (time-locked) to specific events, from the background EEG (Winterer &

McCarley, 2011).

With the use of averaging techniques, it is possible to isolate brain activity

related to specific events by analyzing small portions (epochs) of the EEG, always

synchronized with stimulus presentation. Thus, ERPs allows researchers to study

human brain activity that reflects specific cognitive and attentional processes, in

temporal and spatial domains. Furthermore, the distribution of the voltage on the scalp

can be used alone or in conjunction with other imaging techniques to better analyse the

neuroanatomical loci of neural processes. Understanding the basic neural processes

that underpinne more complex cognitive systems and operations is a fundamental goal

of cognitive neuroscience.

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Table 1 summarizes the above mentioned auditory evoked responses and its

auditory processing structures. Lastly, the following chronological events summarize

the most important advances and landmarks in electrophysiology (adapted from

Maurer & Dierks, 1991 and Neidermeyer, 1993):

1875: R. Caton – First tracing in animals of fluctuating potentials that constitute the

EEG

1924: H. Berger – First human EEG measurement

1929: H. Berger – First human EEG publication in Archive für Psychiatrie und

Nervenheilkunde

1930: Wever and Bray – Cochlear microphonic potential in cats

1932: J. T. Toennies – First ink-writing biological amplifier

1932: G. Dietch – First application of Fourier analyses on human EEG

1934: F. Gibbs – First systematic application of the EEG to epilepsy

1935: A. L. Loomins – First systematic application of the EEG to sleep

1936: W. G. Walter – Discovery of slow (delta) activity in the presence of tumors

1939: Pauline and Hallowel Davis – Single trial ERPs

Davis – long latency response (N1 and P2)

1942: K. Motokawa – First EEG brain map

1943: I. Bertrand and R. S. Lacape – First book on EEG modeling

1947: American EEG Society is founded

1947: G. D. Dawson – First demonstration of human evoked potential responses

1949: Electroencephalography and Clinical Neurophysiology, the first EEG journal, is

launched

1950: Wilder Penfield and Herbert Jasper – pioneered the electrocorticography

(ECoG), neurosurgeons at the Montreal Neurological Institute

Davis et al., Von Békésy – Summating potential

1952: A. Remond and F. A. Offner – First topographic analyses of occipital EEG

1952: M. A. B. Brazier and J. U. Casby – Introduction of auto- and cross-correlation

function

1955: A. Remond – Application of topographical EEG analyses

1958: H. Jasper – Introduction of 10–20 system for standardized electrode placement

Geisler, Frishkopf, and Rosenblith – Auditory middle latency response

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1960: W. R. Adley – Introduction of Fast Fourier Transformation (start of

computerized spectral analyses)

1961: T. M. Itil – Application of EEG analyses for classification of

psychopharmacological agents

1962: Galambos and Sheatz – First publication of computer-averaged ERPs

1963: N. P. Bechtereva – Localization of focal brain lesions by EEG

1964: Walter, Cooper, Aldridge, McCallum, and Winter – the ERP Contingent

Negative Variation

1965: J. W. Cooley and J. W. Tukey – Introduction of fast Fourier algorithm

Sutton, Braren, Zubin, and John – the ERP P300

1967: Sohmer and Feinmesser – Discovery of ABRs, seven waves by putting the

electrode in the earlobe

1968: D. O. Walter – Introduction of coherence analyses for the human EEG

1970: B. Hjorth – Development of new quantitative methods, including source

derivation

1971: D. Lehmann – First multichannel topography of human alpha EEG fields

1973: M. Matousek and I. Petersen – Development of age-corrected EEG spectral

parameter for detecting pathology (qEEG)

1977: E. R. John – Introduction of “neurometrics” (standardized qEEG analyses with

normative databases)

1978: R. A. Ragot and A. Remond – EEG field mapping

1979: F. H. Duffy – Introduction of brain electrical activity mapping (BEAM)

1980: Merton and Morton – Motor evoked potential (transcranial electric stimulation)

Kutas and Hillyard – the ERP N400

1990s: Cognitive neuroscience and psycholinguistics, integration of ERPs with PET

and fMRI (high density EEG; source location LORETA). Intracranial electrodes

Tucker and the geodesic sensor net Large-scale MEG systems come on line.

Integration of ERPs/ERMFs with PET and fMRI

1992: Lee Osterhout and Phillip Holcomb – the ERP P600

1993: Friederici, Pfeifer, and Hahne – the ERP ELAN.

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Table 1. Auditory processing structures and its evoked response: assessment and dysfunction Structure

Processing Function Evoked Response Behavioral tests Compromised behavior / Disorder

Cochlea Deriving spectral (20-20000 Hz) and temporal information from the acoustic signal. Tonotopic organization.

ECochG (cochlear microphonic CM, summating potential SP, action potential AP). Otoacoustic emissions (physiologic test)

Audiometry (pure-tone and speech)

Sensorineural hearing loss / e.g., presbyacusis, Ménière's disease/endolymphatic hydrops, acoustic trauma

Auditory nerve Frequency (pitch), intensity (loudness), duration, timing. Frequency preserves tonotopic organization from the cochlea

Waves I & II of Auditory Brainstem Response (ABR). Wave II often absent, even in normal population

Audiometry (pure-tone and speech) Sensorineural hearing loss / e.g., auditory neuropathy, acoustic neuroma

Cochlear nucleus frequency, intensity, temporal coding, sound localization Wave III ABR Acoustic startle reflex/

cochleopalpebral reflex Poor hearing in noisy environment / e.g., hearing loss

Superior olivar complex

Frequency, intensity, timing, spatial localization of sounds by comparing the arrival of interaural pitch and intensity of stimuli on a frequency-by-frequency basis, from binaural inputs. Fusion and integration of bilateral inputs.

Wave IV ABR

Auditory Figure-Ground, Speech in- Noise Masking Level Differences (MLD) Interaural Time Differences, Interaural Intensity (IID) Differences (ITD; not used clinically

Difficulties in localization and hearing speech in noise (Cocktail Party Effect). Disturbance in the processing of binaural and dichotic signals / e.g., unilateral hearing loss, autism (MSO), epilepsy (?) and mental retardation (?)

Lateral lemniscus, inferior colliculus, and medial geniculate body (thalamus)

Frequency, tntensity, timing localization function based on sensitivity to Interaural Timing Differences (ITD) and Interaural Intensity Differences (IID). This is the first location with sound duration-sensitive neurons.

Wave V ABR. Waves VI & VII of ABR, (not always present). Auditory Middle Latency Response (AMLR) especially Ventral and MGB

IID, ITD and gap detection

LL (not yet documented in humans) Localization, lateralization and tracking sound; Problems hearing in noise / e.g., central deafness (IC), abnormal morphology seen in some dyslexic brains (MGB), mesencephalon tumors

(continued)

http://www.google.pt/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&sqi=2&ved=0CB8QFjAA&url=http%3A%2F%2Fen.wikipedia.org%2Fwiki%2FM%25C3%25A9ni%25C3%25A8re%27s_disease&ei=cqc7VNrwE8fOaOn4gPgJ&usg=AFQjCNH0yJQuax8zqTR_iuMkywoPgcI9Fg&bvm=bv.77161500,d.d2s

http://www.google.pt/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&sqi=2&ved=0CB8QFjAA&url=http%3A%2F%2Fen.wikipedia.org%2Fwiki%2FM%25C3%25A9ni%25C3%25A8re%27s_disease&ei=cqc7VNrwE8fOaOn4gPgJ&usg=AFQjCNH0yJQuax8zqTR_iuMkywoPgcI9Fg&bvm=bv.77161500,d.d2s

110

Table (continued)

Structure


Insula, amygdala and hyppocampus

Frequency, intensity, timing, localization, phonological processing, Nonverbal auditory processing Visual-auditory integration

AMLR (Po, Na, Pa, Nb, Pb) P50, P300 (insula) Dichotic rhyme

Phonological difficulties, auditory sensory gating / e.g., decreased activation in dyslexic children (fMRI), central deafness with bilateral lesion, schizophrenia

Corpus callosum Interhemispheric transfer of signals; mostly in sulcus area

Some tests of electrical impulse transmission speed; only used in research at this time.

Dichotic tests; Pitch pattern perception in commissurotomy patients; Agenesis of CC patients within normal limits because of bilateral distribution of speech

Commissurotomy patients show disconnection syndrome for language; Agenesis of CC patients usually perform within normal limits; Tourette syndrome, ADHD

Cortical network generators

Supratemporal plane and gyrus, and parietal cortex contribution (mainly right hemisphere)

Perception and predictability of auditory stimuli. Selective attention. Cortical tonotopic organization.

N1 Not known

Pre-attentive auditory processing, speech processing for low-level speech cues, poor Frequency discrimination / e.g., dyslexia, specific language impairment, schizophrenia (paired clicks), headache, tinnitus

Mesencephalitic reticular activating system and vicinity of the temporal lobes (auditory association complex and planum temporale)

Cognitive matching system that compares sensory inputs with stored memory. Auditory learning and repeated stimulus exposure (visual vs. auditory?)

P2 Not known

Attention withdraw, memory and expectancy / e.g., reduced in schizophrenia (?), Alzheimer’s disease (to visual stimuli)

Auditory cortical region, frontal lobe, and possibly hippocampus

Auditory sensory memory. Automatic change detection and central auditory processing (depending on stimuli paradigm)

MMN (N2a) Not known Deficits in auditory memory trace and discrimination / e.g., dyslexia, psychosis, aphasia (etc.)

(continued)

111

Table (continued)

Structure


Anterior cingulated cortex, frontal and superior temporal cortex

Stimulus categorization and classification, phonological activation processes Related to response inhibition, response conflict, and error monitoring

N2b Not known

Deficits in sound categorization (phonological), short term memory, and cognitive control function or conflict monitoring / e.g., reduced in ADHD, dyslexia (?)

Medial thalamus, bilateral supramarginal gyrus, bilateral supratemporal gyrus, dorsolateral prefrontal cortex, insula, hippocampus (?)

Stimulus evaluation or categorization. Decision making. Orienting and re-orienting response. Attentional resources. Cognitive workload.

P300 (P3a and P3b) No specific tests at present

Cognitive impairment and deficits in attention engagement / e.g., schizophrenia, crime and attentional-shift, psychopathy, dyslexia, epilepsy, aphasia, dementia, CAPD (etc.)

Temporal lobes (>left superior temporal gyrus), left inferior frontal gyrus and angular gyrus

Indexes semantic processing (?), amplitude reduced by repetition or orthographic or phonological analysis (?). Elicited by semantic errors but not syntactic or musical

N400 No specific tests at present

Deficits in semantic memory, integration and lexical accessing (accessing a word's meaning in long term memory) / e.g., aphasia, temporal lobe epilepsy, amnesia, dementia, auditory agnosia (?)

Bilateral inferior frontal and superior temporal gyrus

Musical and linguistic syntax processing. Elicited by word category violations. Reflects the phrase-structure-building, “syntax-first model” (ELAN). Unexpected chords in harmonic progression (ERAN)

ELAN (early left anterior negativity), ERAN (early right anterior negativity) and LAN (left anterior negativity)

No specific tests at present

Deficits in detecting morphossyntactic or harmonic violations in an expected ruled structure (ELAN/ERAN) / e.g., left and right frontal cortical lesions, epilepsy (?)

Basal ganglia (?), posterior temporal lobes (behind Wernicke’s area), thalamus (?), anterior cingulate cortex (?)

May reflect second syntactic processes of reanalysis and repair, revise structure. Sentence processing. Linguistic and nonlinguistic rules. "Surprise" upon encountering an unexpected stimulus (?)

P600 (Syntactic Positive Shift - SPS) No specific tests at present

Unclear which behaviors are specific to the auditory aspects of the basal ganglia. Deficits in detecting rule-governed sequences (linguistic and musical), syntactic integration / e.g., Parkinson’s disease

Adapted from Bailey (2010), with permission (appendix 6).

112

At this stage, we should be reviewing the AERPs normative data. In other

words, data that characterize what is usual in a defined population at a specific point or

period of time, seeks to describe rather than explain phenomena, develops standards of

care and establishes illness nosologies. This is highly important for clinicians.

However, such information is lacking in literature. Therefore, it became necessary to

do such work and suggest normative values for AERPs across lifespan. We selected

N1 and N2 waves. N1 is one of the most prominent AERP components studied in last

decades, reflects auditory detection and discrimination. Subsequently, N2 indicates

attention allocation and phonological analysis. The simultaneous analysis of N1 and

N2 elicited by feasible novelty experimental paradigms, such as auditory oddball,

seems an objective method to assess central auditory processing.

Paper II suggests normative values for N1 and N2 components in order to be

considered by clinicians and researchers in assessing central auditory processing, and

includes a narrative analysis on factors, such as changes in brain development and

components topography over age, that should be taken in account in clinical practice.

113

Paper II

The development of the N1 and N2 components in auditory oddball

paradigms: a systematic review with narrative analysis and suggested

normative values

David Toméa,b, Fernando Barbosaa, Kamila Nowakc, João Marques-Teixeiraa


University of Porto, Portugal bDepartment of Audiology, School of Allied Health Sciences, Polytechnic Institute of Porto, Portugal

cLaboratory of Neuropsychology, Nencki Institute of Experimental Biology, Polish Academy of Sciences,

Warsaw, Poland

Tomé, D., Barbosa, F., Nowak, K., & Marques-Teixeira, J. (2014). The development

of the N1 and N2 components in auditory oddball paradigms: a systematic review with

narrative analysis and suggested normative values. Journal of Neural Transmission,

121(7). doi:10.1007/s00702-014-1258-3

Journal of Neural Transmission ISSN: 0300-9564

Impact Factor 2013: 2.871

114

Abstract

Auditory event-related potentials (AERPs) are widely used in diverse fields of today’s

neuroscience, concerning auditory processing, speech perception, language

acquisition, neurodevelopment, attention and cognition in normal aging, gender,

developmental, neurologic and psychiatric disorders. However, its transposition to

clinical practice has remained minimal. Mainly due to scarce literature on normative

data across age, wide spectrum of results, variety of auditory stimuli used and to

different neuropsychological meanings of AERPs components between authors. One

of the most prominent AERP components studied in last decades was N1, which

reflects auditory detection and discrimination. Subsequently, N2 indicates attention

allocation and phonological analysis. The simultaneous analysis of N1 and N2 elicited

by feasible novelty experimental paradigms, such as auditory oddball, seems an

objective method to assess central auditory processing. The aim of this systematic

review was to bring forward normative values for auditory oddball N1 and N2

components across age. EBSCO, PubMed, Web of Knowledge and Google

Scholarwere systematically searched for studies that elicited N1 and/or N2 by auditory

oddball paradigm. A total of 2,764 papers were initially identified in the database, of

which 19 resulted from hand search and additional references, between 1988 and 2013,

last 25 years. A final total of 68 studies met the eligibility criteria with a total of 2,406

participants from control groups for N1 (age range 6.6–85 years; mean 34.42) and

1,507 for N2 (age range 9–85 years; mean 36.13). Polynomial regression analysis

revealed that N1 latency decreases with aging at Fz and Cz, N1 amplitude at Cz

decreases from childhood to adolescence and stabilizes after 30–40 years and at Fz the

decrement finishes by 60 years and highly increases after this age. Regarding N2,

latency did not covary with age but amplitude showed a significant decrement for both

Cz and Fz. Results suggested reliable normative values for Cz and Fz electrode

locations; however, changes in brain development and components topography over

age should be considered in clinical practice.

Keywords: event-related potentials; auditory oddball paradigm; N1 wave; N2 wave;

aging; normative values.

115

Introduction

As a researcher of the third generation of neuroscientists, we are in the course of

explaining the possession of psychological attributes by human beings, probably

obsessively ascribing such attributes not to the mind but to the brain or parts of the

brain. This is a rising issue among neurophilosophers, we still cannot explain how we

perceive or think by reference to the brain or some part of the brain, for it makes no

sense to ascribe such psychological attributes to anything less than a human being as a

whole (Bennett and Hacker 2007).

Thereupon, systematic reviews are required to update, appraise and synthesize all

quality research evidence relevant to a question. Such method is necessary and

essential in today’s neuroscience, cognitive psychology and psychophysiological

research.

Keeping the above in mind, ever since Berger (1929) demonstrated that it is

possible to record the electrical activity of the brain by placing electrodes on the

surface of the scalp and with ¾ of century of knowledge since the first investigation of

sound-evoked changes in the electroencephalogram (EEG) in the waking human brain

(Davis 1939), there has been always considerable interest in the relationship between

these recordings of neurophysiological activity and psychological processes in various

fields and types of studies (e.g., experimental, translational, clinical, case study). We

will review one of the most prominent human auditory event-related potential and field

(ERP and ERF, respectively) – the N1/N1m.

The electrical activity occurring on the scalp consists of changing electrical

voltages that are caused by action potentials summed over large numbers of neurons,

synapses, neuronal pathways and systems. There are two non-invasive measures for

this electrical brain activity, the EEG and ERPs, both in time course. The EEG

measures the spontaneous electrical brain activity and the ERPs are derived by

averaging EEG changes over experimental or cognitive events. The averaging process

attenuates the spontaneous activity in the EEG and results in electrical potential

changes related to specific events (Eysenck and Keane 2003).

ERPs are induced exogenously by environmental events (such as sensory stimuli)

or endogenously by processes such as decision making, eliciting a characteristic series

116

of waves labeled according to their latency and polarity (Davis and Zerlin 1966).

Parallel streams of neuronal activity originate overlapping ERP deflections composed

of several components. Therefore, a component can be defined as a voltage

contribution to the ERP which reflects a functionally discrete stage of neuronal

processing occurring in a restricted cerebral area (Näätänen and Picton 1987), also are

hypothesized to be linked and reflected by psychological and cognitive processes

(Hillyard and Kutas 1983; Fabiani et al. 2007).

In auditory novelty processing experiments, the experimental paradigm that seems

the most feasible is the oddball paradigm. The oddball paradigm, as a signal-detection

paradigm was first described by Ritter and Vaughan (1969). In the auditory modality,

it was first used in 1975 by Squires, Squires and Hillyard at the University of

California, San Diego, USA (Squires et al. 1975). In this paradigm, physically deviant

stimuli (silence included) are randomly presented among repetitive streams of

homogenous sounds (standard stimuli; Näätänen 1975; Näätänen et al. 1978; Donchin

1981; Jääskeläinen 2012).

The electrically recorded N1 or N100 in auditory oddball stimulation is a negative

wave response, which peaks about 100 ms after stimulus onset and lasts for

approximately 100 ms (Näätänen and Picton 1987; Tiitinen et al. 1994; May and

Tiitinen 2010). Multiple sources have been identified to generate N1 wave.

In the classical review of Näätänen and Picton (1987), it was concluded that at

least six different cerebral processes, occurring in different cerebral locations and

subserving different psychophysiological functions, can contribute to a negative wave

recorded from the scalp peaking between 50 and 150 ms: (1) a component generated

bilaterally in the auditory cortex by vertically oriented sources in the supratemporal

plane (STP); (2) a component generated in the association cortex on the lateral aspect

of the superior temporal gyrus (STG) and parietal cortex, also termed by T-complex

(Wolpaw and Penry 1975); (3) a vertex negative component generated in the motor

and premotor cortices, its widespread and nonspecific neuronal networks with

thalamo-reticular system facilitates stimulus detection, analysis and response (Crowley

and Colrain 2004); (4) the mismatch negativity (MMN); (5) a temporal component of

the processing negativity; and a (6) frontal component of the processing negativity.

The first three are considered the true N1 components. Thus, N1 is a fronto-centrally

117

component with a peak latency of 100 ms after stimulus onset generated bilaterally

mainly in the auditory cortices. Its magnetic equivalent (N1 m/N100 m; Elberling et al.

1980; Hari et al. 1980) originates deep within the Sylvian fissure in tonotopically

organized areas (Yamamoto et al. 1988; Cansino et al. 1994), but also comprises

secondary areas such as Heschl’s gyrus, STG and planum temporale providing the

major source (Papanicolaou et al. 1990; Pantev et al. 1995; Jääskeläinen et al. 2004;

Inui et al. 2006).

The auditory ERP N1, does not reflect a single underlying cerebral process, but it

appears to contain both stimulus-specific and stimulus-nonspecific components,

closely following the P1 component (Yvert et al. 2001; Hamm et al. 2013). These ERP

components reflect sensory and perceptual processes. Further, N1 seems to reflect

early synchronization between primary and secondary auditory cortices in the lateral

and STP (Yvert et al. 2005; Liasis et al. 2006).

The generation source location of N1 depends on stimulus frequency. Woods et al.

(1993) have found that N1 is more frontally distributed following 4,000 Hz than 250

Hz tone burst stimuli. Numerous studies have shown that N1 amplitude and latency

have a large variation according to type of deviant auditory stimuli. For example, in

speech oddball paradigms, the first stages of detection, graphemic analysis and stimuli

recognition correspond to the appearance of a N1 with latency between 150 and 200

ms (Bentin and Carmon 1984). Subsequently, the N2 indicates an attentional allocation

and stage of phonological type analysis of the information, related to the sounds of the

language, both in the auditory and visual modalities of presentation (Sams et al. 1985;

Reinvang et al. 2000). Two components contribute to forming N2, usually labeled

MMN (N2a) and N2b (Novak et al. 1990, 1992). The first component (MMN) has

been related to the automatic detection of stimulus changes (Ritter et al. 1979;

Näätänen 1982), the later component (N2b) is interpreted as a correlate of controlled

detection of stimulus changes and phonological categorization (Ritter et al. 1979;

Näätänen 1982; Amenedo & Díaz 1998; Näätänen et al. 2007).

In auditory oddball, N1 amplitude is strongly modulated by attentional context and

interstimulus interval (ISI; Hillyard et al. 1973; Rosburg et al. 2008; May & Tiitinen

2010). During the process of falling asleep, N1 gradually declines in amplitude,

possibly because of the decrease in the level of attention, and during REM sleep it is

118

approximately 25-50% of its waking amplitude (Crowley & Colrain 2004). According

to Hamm et al. (2013) this indexes the earliest cognitively influenced auditory

neuronal event reliably measureable with EEG (Hamm et al. 2013).

The effects of aging on ERPs vary among studies. With respect to changes of the

N2 component from childhood to adulthood, most studies showed a decrease in the N2

amplitude and latency (Johnstone et al. 1996; Mueller et al. 2008). Regarding N1

latency, only Iragui et al. (1993) reported significant age-related increases at Cz, while

the common finding has been that N1 latency remains unchanged with advancing age

(Barrett et al. 1987). Ladish and Polich (1989) found an increase in N1 amplitude and

a decrease in N1 latency with increasing age from 5 to 19 years, but other studies

reported variations of N1 amplitude from childhood to adolescence (Ladish & Polich

1989; Ponton et al. 2000; Čeponienė et al. 2002, 2003, 2008). As for findings

regarding adult development and aging, N1 amplitude increased significantly with age

and increased N1 latency was only significant in the posterior region (Anderer et al.

1996).

This wide spectrum of results, findings and variety of auditory stimuli used, has

possibly delayed the translation of N1 and N2 to clinical practice. Without linking

auditory N1 and N2 to a restricted neuropsychological meaning, we are undoubtedly

and objectively assessing the first stages of cognitive auditory processing.

Aims and objectives

The clinical significance and application of auditory ERPs such as N1 and N2 also, has

remained marginal in the current practice of audiology, neurophysiology, neurology or

psychiatry. Particularly the N1 wave, as an exogenous and robust auditory ERP may

be used to assess central auditory processing.

This review will address the following aspects of N1 and N2: latency, amplitude,

electrode location (most prominent – Cz and Fz), development and maturation, aging,

data published by year and country, type of stimuli in auditory oddball and research

areas. We purpose that this review may lead to the first human normative values for

N1 and N2 components when elicited by auditory oddball, being beneficial for a

119

standard, controlled and wide accepted application to assess central auditory

processing.

Methods

For this review we searched EBSCO, PubMed, Web of Knowledge and Google

Scholar to identify potential studies, without pre-defined time-window. Further studies

were identified through references and citations. As inclusion criteria we searched the

term “N1” limited by the term “auditory oddball” in title, abstract, keyword or topic.

Papers with no control group and animal research were excluded.

A search between ending November and early December 2013 found 2764 articles.

Duplicates were removed and articles with no full text available were kindly asked by

mail to authors, leaving a selection of papers for assessment of eligibility upon reading

the full text article.

Data extraction, quality and relevance assessments

Data extracted from each full text article for eligibility assessment included: Authors;

Year Publication; Aim; Country; Research areas; Control group (n), age (mean); Type

of stimuli (frequency, intensity, speech/consonant-vowel, pure-tone); Electrodes

recording for target/deviant stimuli (amplitude and latency of N1 and N2); Findings

and Suggestions. The complete systematic process of deduction can be found below in

Fig. 1.

Polynomial regression was applied as a descriptive method to data analysis that

better fits a nonlinear model.

120

Fig.1 PRISMA systematic search flow diagram (Moher et al. 2009)

Results

A total of 2764 papers were initially identified in the database search from which 19

were hand searched and additional references. After, 2680 papers that did not meet

inclusion criteria or duplicated were removed through title and abstract screening,

leaving a total of 84 papers. Sixteen papers could not be accessed, 14 of which were

not archived or we didn’t receive answer from authors and two were foreign language

articles. A final total of 68 full text articles were assessed for eligibility, none of which

required translation. Study’s authors, country, mean age of control groups, number of

participants, results for amplitude and latency across Fz and Cz electrodes for deviant

stimuli and subject’s article (notes) are summarized in Table 1 and Table 2, for N1 and

N2 respectively. Many studies have results for different electrode location. We

considered Fz and Cz since they’re the most common locations and were maximal

amplitude for N1, N2 and MMN is achieved (Näätänen & Picton 1987; Winkler 2007;

Duncan et al. 2009; May & Tiitinen 2010). Studies with mean global field power were

considered as Cz data, representing the standard deviation across electrodes at a given

time point indicating the presence of a specific underlying neuronal component

(Murray et al. 2008; Altieri 2013).

Initial Database search: EBSCO (n = 114) PubMed (n = 100)

Web of Knowledge (n = 111) Google scholar (n = 2420)

TOTAL: 2764

Hand searching, citations, references (n = 19)

Records after initial abstract screening and duplicate

removal (n = 84)

Did not meet inclusion criteria and duplicates

(n = 2680)

Papers not accessible (n = 16)

Full text articles assessed for eligibility and included in

qualitative synthesis (n = 68)

121

0

5

10

15

20

25

Num

ber

of P

ublic

atio

ns

Publications per 5-year

N1

N2

The results revealed papers between 1988 and 2013, last 25 years. The majority of

the studies were published between 1995 and 1999, also it was when most of the

studies elicited and analysed both N1 and N2 (presented in Fig. 2). The five most

published research areas were neurosciences/neurology, psychology, physiology,

psychiatry and engineering. The five countries/territories with more papers published

were USA, Australia, Germany, Japan and Austria.

Fig. 2 Number of publications per 5-year for auditory oddball N1 (N2 included in N1 studies)

Data analysis revealed a total of 3934 participants from control groups (Table 3),

2427 for N1 studies (male = 1247, female = 1180), ranging in age from 6.6-85.0 years

with a mean of 34.4 (SD = 18.6). Regarding N2 studies, a total of 1507 participants

were obtained from all control groups (male = 769, female = 738), ranging in age from

9.0-85.0 years with a mean of 36.1 (SD = 20.7). All participants from control groups

were reported to have normal hearing and vision, no neurological, psychiatric or other

disorder. The majority of studies applied a frequency auditory oddball. The most

standard stimuli used was a pure-tone of 1000 Hz at an intensity level range from 55 to

109 dB above hearing threshold, with at least 200 Hz of difference to the deviant

stimuli, except in Demiralp et al. (1999), Wang et al. (2005) and Čeponienė et al.

(2008) studies. Others used duration auditory oddball (Shelley et al. 1999; Segalowitz

et al. 2001; Bortoletto et al. 2011; Wetzel et al. 2011; Neuhaus et al. 2013) and few

intensity auditory oddball (Anderer et al. 1996, 1998; Wang & Wang 2001; Wang et

al. 2005; Barry et al. 2006). Only two papers elicited N1 and N2 with speech stimuli

122

(Henkin et al. 2002; Toscano et al. 2010), due to the scarce data and type of stimuli

they were not considered in the regression analysis.

Table 1 Studies with auditory oddball N1 elicitation (control groups data from deviant stimuli at Fz and Cz)

Author Country N Age Cz (amp)

Fz (amp)

Cz (lat)

Fz (lat) Stimuli Notes

Hegerl et al. (1988) Germany 27 34.1 12.2 91.4

Std: 1600Hz Dev: 800Hz / 65 dB

schizophrenia prognosis

Verma et al. (1989) USA 11 63.5 103.7

Std: 1000Hz Dev: 2000Hz / 60 dB

Dementia

Iragui et al. (1993) USA 28 29 6.6 94 Std: 1000Hz

Dev: 1500Hz / 70 dB

aging; correlations; reaction time 16 49 8.1 95

27 71 6.6 97 Lembreghts et

al. (1995) Belgium 86 34.1 6.6 6.7 94 95 Std: 800Hz Dev: 1470Hz / 70 dB

Age, gender, intervariability

Tarter et al. (1995) USA 56 13.2 9.5 119.9

Std: 1000Hz Dev: 2000Hz / 64,5 dB

Adolescence; substance abuse

Winter et al. (1995) Netherlands 13 21.4 5.3 6.7 105 103

Std: 1000Hz Dev: 1200 and 2000Hz / 65 dB

sleep stage 2

Siedenberg et al. (1996) USA 10 36.5

103

Std: 1000Hz Dev: 2000Hz / 65 dB

ERP vs ERF

Anderer et al. (1996, 1998) Austria 58 25 8.6

95

Std: 90 dB Dev: 70 dB / 1000Hz

aging; ERPs; LORETA

19 35 8.3

100

13 45 8.7

99

33 55 9.2

95

29 65 9

96

12 75 8.5

93

8 85 8.1

96

Wright et al.

(1996) Australia 28 62.8 13.6 164

Std: 1000Hz Dev: 2000Hz / 60 dB +back noise

Parkinson's disease

Johnstone et al. (1996) Australia 10 9,1 9.6 12.1 132 133

Std: 1000Hz Dev: 1500Hz / 60 dB

Child and adolescent; waves morphology; ERPs

10 11.2

10 12.8 8.3 9.1 127 133

10 15

10 16.8 6.3 8.3 123 124

Hirata et al. (1996) Japan 14 66.8 6.9 82

Std: 2000Hz Dev: 1000Hz / 80 dB

Stroke

Table 1 continued

123


Fz (amp)

Cz (lat)


Akaho (1996) Japan 47 21.9 9.1 100.2

Std: 1000Hz Dev: 2000Hz / 70 dB

cognition; effects of AED

Kazis et al. (1996) Greece 53 45.6 10.3 98.9

Std: 1000Hz Dev: 2000Hz / 70 dB

Myotonic dystrophy

Brigham et al. (1997) USA 29 11.5 5.9 8.1 157.9 168.4

Std: 1000Hz Dev: 2000Hz / 64,5 dB

polysubstance and alcohol

Haig et al. (1997) Australia 25 27.3 8.6 99

Std: 1000Hz Dev: 1500Hz / 60 dB

Gaussian component; schizophrenia

Potts et al. (1998a) USA 24 39 3.8

100

Std: 1000Hz Dev: 1500Hz / 97 dB

Schizophrenia

Potts et al. (1998b) USA 20 21.1 2 6.7 100 110 Std: 440Hz

Dev: 1245Hz various ERPs

Amenedo & Díaz (1998) Spain 20 30.5 5.7 5.2 112 108 Std: 1000Hz

Dev: 2000Hz / 90 dB

Aging; ERPs

20 50 7.5 7 105 104

33 71.5 7.1 6.5 110 108

Gonsalvez et al. (1999) Australia 12 28.3 10,5 8.4 110 105

Std: 1000Hz Dev: 1200Hz / 60 dB

target-to-target hypothesis (P3)

Shelley et al. (1999) USA 17 37.4

8.0

102.4

Std: 1000Hz Dev: 1200Hz / 75dB (ISI:variable)

schizophrenia; cortical dysfunction

Demiralp et al. (1999) Turkey 10 21.5 11.6 10.2 125 125 Std: 2000Hz

Dev: 1950Hz / 60 dB

wavelet transform; cognitive processes

Golgeli et al. (1999) Turkey 38 20.6 9.2 9 107 113 Std: 2000Hz

Dev: 1500Hz gender diferences

Barry et al. (2000) Australia 14 30.5 6

117.6

Std: 1000Hz Dev: 1500Hz / 60 dB

alpha activity

Sumi et al. (2000) Japan 39 68.5

Pz

Std: 2000Hz Dev: 1000Hz / 70 dB

Alzheimer

Reinvang et al. (2000) Norway 27 29.7 6,4 4.9 99 97


head injury

Johnstone et al. (2001) Australia 50 12.5 7.8

Std: 1000Hz Dev: 1500Hz / 60 dB

Two sub types AD/HD

Ford et al. (2001) USA 32 38 9.3 7.3 105 100


epilepsy and schizophrenia

Segalowitz et al. (2001) Canada 12 20.7 8.2 119.3

Std: 800Hz Dev: 1500Hz / 100ms

mild head injury

Ullsperger et al. (2001) Germany 15 23.8 4.5 6.3 133,3 133.3

Std: 1000Hz Dev: 2000Hz / 55 dB

mental workload changes

Wang & Wang (2001) China 39 26.6 11.4 10.2 120,1 118.6


sensation seeking

Table 1 continued

124


Fz (amp)

Cz (lat)


Brown et al. (2002) Australia 40 36.7 11.4 10.2 103.1 108.3 Std: 1000Hz

Dev: 1500Hz / 60 dB

1st episode Schizophrenia

40 19.7 10.6 9.3 104.5 110.4

Cohen et al. (2002) USA 39 24.7 4.9 5.5 117 117.6


Alcohol

Henkin et al. (2002) Israel 20 14.4 8 7.5 103.9

Std: 1400Hz Dev: 1000Hz (?)

AERPs; phonetic and semantic processing

Valkonen-Korhonen et al.

(2003) Finland 19 29 5.0 100


auditory processing; psychotic

Lucchesi et al. (2003) Brazil 12 24.8 10 11.2 100 100


flunitrazepam effect

Barry et al. (2003) Australia 16 28 6.3 90

Std: 1000Hz Dev: 1500Hz / 80 dB

EEG brain states; effects ERPs

Barry et al. (2004) Australia 14 31 8.7 9.6 114 114.5

Std: 1000Hz Dev: 1500Hz / 60 dB

EEG alpha phase

Mulert et al. (2004) Germany 9 24.2 10.2 119.3


fMRI; source localization

Chao et al. (2004) USA 15 44.1 6.5 90.9

Std: 1000Hz Dev: 2000Hz / 55 dB

suppressed HIV patients

Wang et al. (2005) USA 6 32.3 1.1

145

222

260

Std:440Hz 80dB Dev:494Hz 80dB e 440Hz 65dB

TWI; development of auditory processing; MMN

9 10.8 5.3

11 6.6 5.6 Gilmore et al.

(2005) USA 14 43.6 2.1 102

Std: 1000Hz Dev: 2000Hz / 76 dB

Schizophrenia

Chunhau et al. (2005) Japan 16 23.5 7 7.7 101 109

Std: 1000Hz Dev: 2000Hz / 60 dB

40min oddball

Brown et al. (2006) Australia 20 24.8 2.7 3.7 105 105

Std: 1000Hz Dev: 2000Hz / 60 dB

inter-modal attention

Barry et al. (2006) Australia 20 36 2.3 4.2 139 144


narrow band EEG phase effects

van Harten et al. (2006) Netherlands 53 73.6 8.3 12 100.8 100.8

Std: 1000Hz Dev: 2000Hz / 80 dB

Vascular cognitive impairment; peak-to-peak ERPs

Dixit et al. (2006) India 40 21.5 6.1 7.4 110.7 100.4

Std: 1000Hz Dev: 2000Hz / 60 dB

Caffeine users

Čeponienė et al. (2008) USA 19 25.5 2.4 2.4 119


aging; N1-N2-P2

19 71.3 2.1 2.0 118 Kreukels et al.

(2008) Netherlands 23 53.2 8.7 101

Std: 1000Hz Dev: 2000Hz / 75 dB

chemotherapy; N1 independent from P3

Table 1 continued

125


Fz (amp)

Cz (lat)


Zhu et al. (2008) China 15 23 4.9 7.7 110 120 Std: 1000Hz Dev: 2000Hz / 80 dB

music; mandarin lexical tones

Wise et al. (2009) Australia 98 35.6 7.7 7.3 113.8 111.7


panic disorder

Guney et al.

(2009)

Turkey

32

37.1

11.6

12.2

97.7

97.2

Std: 1000Hz Dev: 2000Hz / 80 dB

Tobacco smokers

Dassanayake et al. (2009) Sri Lanka 38 49 99.1

Std: 1000Hz Dev: 2000Hz / 75 dB

Pesticides

Gilmore et al. (2009) USA 12 25 3.2 2.6 101 107.8

Std: 1000Hz Dev: 2000Hz / 76 dB

hemispheric differences

Ogawa et al. (2009) Japan 19 64.5 5.7 85.9

Std: 1000Hz Dev: 2000Hz / 80 dB

amyotrophic lateral sclerosis

Cahn & Polich (2009) USA 16 45.5 3.1 3,3 105 105


meditation; different mental states

Sakamoto et al. (2009) Japan 11 30.9 5.5 6.7

Std: 1000Hz Dev: 2000Hz / 55 dB

Mastication

Whelan et al. (2010) Ireland 21 40.3 1.6 90.6 Std: 500Hz

Dev: 1000Hz multiple sclerosis

Boucher et al. (2010) Canada 99 11.3 4.7 127.1

Std: 1000Hz Dev: 2000Hz / 70 dB

MeHg; PCBs; neurodevelopment

Gandelman-Marton et al.

(2010) Israel 18 35.6 113.2 113.4

Std: 1000Hz Dev: 2000Hz / 70 dB

Immediate and short-term retest

Bortoletto et al. (2011) Italy 20 25 5.1 133

5pair of Hz and 3 different ISI

sleep deprivation

Wetzel et al. (2011) Germany 18 25 4.5 2.2 110 110

Std: 500Hz Dev: 200 and 500 ms

novel; duration; better in children

Tsai et al. (2012) Taiwan 63 9 Pz

Std: 3000Hz Dev: 2000Hz / 60 dB

ADHD; Age-related; correlations; 51 9 13.6 14.4 119.5 126.2

Tanaka et al. (2012) Japan 14 43 4.8 99

Std: 1000Hz Dev: 2000Hz / 80 dB

myotonic dystrophy type 1

Ho et al. (2012) Taiwan 15 23.7 91 88.9 Std: 2000Hz Dev: 1000Hz / 80 dB

normal aging 15 70,1 95 90

Neuhaus et al. (2013) Germany 144 32.4 15.1 11.4 111.1 127.8

Std: 500ms 109 dB Dev: 40ms 83dB

schizophrenia; gatings; AUC e ROC

Schneider et al. (2013) USA 40 13.9 3.4 125

Std: 1000Hz Dev: 2000Hz / 70 dB

fragile X syndrome treatment

Hamm et al. (2013) USA

70 38.4 2.2 2.2 92 92 Std: 1500Hz Dev: 1000Hz / 75 dB

Bipolar disorder

Table 2 Studies with auditory oddball N2 elicitation (control groups data from deviant stimuli at Fz and Cz)

126

Author Country N age Cz (amp)

Fz (amp)

Cz (lat)


Verma et al. (1989) USA 11 63.5 237.8

Std: 1000Hz Dev: 2000Hz / 60 dB

Dementia

Iragui et al. (1993) USA 28 29 2,26 211 Std: 1000Hz

Dev: 1500Hz / 70 dB

aging; correlations; reaction time 16 49 3.9 220

27 71 5.5 231 Lembreghts et

al. (1995) Belgium 41 34,1 4.7 3.6 207 212 Std: 800Hz Dev: 1470Hz / 70 dB

Age, gender, intervariability

Anderer et al. (1996) Austria 58 25 6.7 6.5 210 212 Std: 90 dB

Dev: 70 dB / 1000Hz

Aging; ERPs 19 35 5.6 4 213 218

13 45 7.1 5 224 225

33 55 8.1 3.8 221 220

29 65 4.2 1.5 222 217

12 75 3.1 1.9 212 212

8 85 2 0 254 253 Siedenberg et al.

(1996) USA 10 36.5 216

Std: 1000Hz Dev: 2000Hz / 65 dB

ERP vs ERF

Johnstone et al. (1996) Australia 10 9.1 14.6 253.3

Std: 1000Hz Dev: 1500Hz / 60 dB

ERPs; child and adolescent; morphology

10 11.2

10 12.8

10 15 6.7 12.9 240 253.3

10 16.8 5.8 253.3

Akaho (1996) Japan 47 21.9 3.5 223.2

Std: 1000Hz Dev: 2000Hz / 70 dB

Cognition; effects of AED

Kazis et al. (1996) Greece 53 45.6 8.4

Std: 1000Hz Dev: 2000Hz / 70 dB

Myotonic dystrophy

Brigham et al. (1997) USA 29 11.5 7.3 16.3 221 221.1

Std: 1000Hz Dev: 2000Hz / 64,5 dB

polysubstance and alcohol

Haig et al. (1997) Australia 25 27.3 4 201

Std: 1000Hz Dev: 1500Hz / 60 dB

Gaussian component; schizophrenia

Amenedo & Díaz (1998) Spain 20 30.5 2.5 4.5 237 242 Std: 1000Hz

Dev: 2000Hz / 90 dB

age related ERPs 20 50 3.4 3.1 250 252

33 71.5 3.8 3.7 271 277

Demiralp et al. (1999) Turkey 10 21.5 6.8 3.4 270 270

Std: 2000Hz Dev: 1950Hz / 60 dB

wavelet transform; cognitive processes

Golgeli et al. (1999) Turkey 38 20.6 7.1 8 225 240 Std: 2000Hz

Dev: 1500Hz gender diferences

Table 2 continued

127


Fz (amp)

Cz (lat)


Sumi et al. (2000) Japan 39 68.5 Pz

Std: 2000Hz Dev: 1000Hz / 70 dB

Alzheimer

Reinvang et al. (2000) Norway 27 29.7 2 1.5 207 207


head injury

Johnstone et al. (2001) Australia 50 12.5 8.5 238.5

Std: 1000Hz Dev: 1500Hz / 60 dB

Two sub types AD/HD

Segalowitz et al. (2001) Canada 12 20.7 235.3

Std: 800Hz Dev: 1500Hz / 100ms

mild head injury

Wang & Wang (2001) China 39 26.6 2.9 245.1 236.8


sensation seeking

Brown et al. (2002) Australia 40 36.7 7.5 5.3 207.2 209.8 Std: 1000Hz

Dev: 1500Hz / 60 dB

1st episode Schizophrenia

40 19.7 3.2 9.9 209.3 214.1

Cohen et al. (2002) USA 39 24.7 2.3 5.1 217.6 235.3


Alcohol

Henkin et al. (2002) Israel 20 14.4 4.9 8.8 246.3

Std: 1400Hz Dev: 1000Hz (?)

AERPs; phonetic processing in children

Valkonen-Korhonen et al.

(2003) Finland 19 29 2.4 200


auditory processing; psychotic

Lucchesi et al. (2003) Brazil 12 24.8 5 3 200 200


flunitrazepam effect; N2b

van Harten et al. (2006) Netherlands 53 73.6 5.6 5.6 232.5 232.5

Std: 1000Hz Dev: 2000Hz / 80 dB

Vascular cognitive impairment; peak-to-peak ERPs

Dixit et al. (2006) India 40 21.5 3.9 5.5 209.6 215.3

Std: 1000Hz Dev: 2000Hz / 60 dB

Caffeine

Čeponienė et al. (2008) USA 19 25.5 2.5 2.4 341


aging; N1-N2-P2

19 71.3 1.0 1.1 371

Zhu et al. (2008) China 15 23 3.1 225 Std: 1000Hz Dev: 2000Hz / 80 dB

music; mandarin lexical tones

Wise et al. (2009) Australia 98 35.6 5.5 4.9 231.6 238


panic disorder

Guney et al. (2009) Turkey 32 37.1 8 10.0 216.3 225.8

Std: 1000Hz Dev: 2000Hz / 80 dB

Tobacco smokers

Dassanayake et al. (2009) Sri Lanka 38 49 226.3

Std: 1000Hz Dev: 2000Hz / 75 dB

Pesticides

Ogawa et al. (2009) Japan 19 64.5 4.7 210

Std: 1000Hz Dev: 2000Hz / 80 dB

amyotrophic lateral sclerosis

Table 2 continued

128


Fz (amp)

Cz (lat)


Whelan et al. (2010) Ireland 21 40.3 1.7 211.7

Std: 500Hz Devts: 1000Hz

Multiple sclerosis

Gandelman-Marton et al.

(2010) Israel 18 35.6 7.1 7.1 221.2 223.1

Std: 1000Hz Dev: 2000Hz / 70 dB

Immediate and short-term retest

Tsai et al. (2012) Taiwan 63 9 Pz

Std: 3000Hz Dev: 2000Hz / 60 dB

Age-related; correlations

51 9 14.2 10.8 240.7 239.2 ADHD

Tanaka et al. (2012) Japan 14 43 5,9 215

Std: 1000Hz Dev: 2000Hz / 80 dB

Myotonic dystrophy type 1

Schneider et al. (2013) USA 40 13.9 1.6 285

Std: 1000Hz Dev: 2000Hz / 70 dB

fragile X syndrome treatment

Orthogonal polynomial regression equations were fit to the data, including degrees

4 through 6 in order to significantly increase predictability.

For N1, results revealed at Cz a mean amplitude of 7.3 µV (SD = 3.0) ranging from

2.0-15.1 µV (data from 69 cells) and a mean latency of 107.6 ms (SD = 15.0) ranging

from 82.0-164.0 ms (data from 75 cells). At Fz mean amplitude was 7.0 µV (SD = 3.2)

ranging from 1.1-14.4 (data from 48 cells) and a mean latency of 118.2 ms (SD = 31.5)

ranging from 88.9-260.0 ms (data from 45 cells).

Regarding N2, results revealed at Cz a mean amplitude of 4.9 µV (SD = 2.6)

ranging from 1.0-14.2 µV (data from 40 cells) and a mean latency of 231.4 ms (SD =

33.9) ranging from 200.0-371.0 ms (data from 43 cells). At Fz the mean amplitude was

5.7 µV (SD = 3.9) ranging from 0-16.3 µV (data from 34 cells) and a mean latency of

231.8 ms (SD = 18.9) ranging from 200.0-277.0 ms (data from 32 cells). Table 3

summarizes the results for N1 and N2 by four age ranges, suggested as normative

values.

Polynomial regression curves showed that latency of N1 component slightly

decreases with aging at Cz (r = 0.50; Fig. 3) and Fz (r = 0.78; Fig. 4). As for

amplitude, N1 seems to decrease from birth until 30 years and stabilize after 40 years

old at Cz (r = 0.20), but at Fz a similar decrement only finishes by 60 years and starts

to highly increase after (r = 0.35) . Regarding N2 component (Fig.5 and 6), latency did

not covary with age for both Cz (r = 0.36) and Fz (r = 0.44) locations. In contrast, N2

129

amplitude at Cz (r = 0.68) and Fz (r = 0.81) showed a significant decrement with age,

with a curious slight increment between 20-45 years at Cz.

Fig. 3 Scatter plots of the relationship between N1 amplitude (µV; left), latency (ms; right) and age (years) at Cz

(curved lines are the fifth degree polynomial regression over the age range 0-100 years)

Fig. 4 Scatter plots of the relationship between N1 amplitude (µV; left), latency (ms; right) and age (years) at Fz

(curved lines are the fourth and fifth degree, for amplitude and latency respectively, polynomial regression over the age range 0-100 years)

Fig. 5 Scatter plots of the relationship between N2 amplitude (µV; left), latency (ms; right) and age (years) at Cz (curved lines are the sixth degree polynomial regression over the age range 0-100 years)

y = -4E-08x5 + 1E-05x4 - 0,0014x3 + 0,0686x2 - 1,4889x + 18,196

R² = 0,0401

0 2 4 6 8

10 12 14 16

0 20 40 60 80 100

Am

plitu

de C

z

Age

y = -1E-07x5 + 2E-05x4 - 0,0025x3 + 0,1493x2 - 4,7588x + 165,15

R² = 0,2494

0 20 40 60 80

100 120 140 160 180

0 20 40 60 80 100 L

aten

cy C

z

Age

y = 8E-06x4 - 0,0011x3 + 0,0558x2 - 1,1531x + 15,9

R² = 0,1196

0

5

10

15

20

25

30

35

0 20 40 60 80 100

Am

plitu

de F

z

Age

y = -3E-06x5 + 0,0007x4 - 0,0582x3 + 2,3551x2 - 44,73x + 432,7

R² = 0,6109

0 40 80

120 160 200 240 280

0 20 40 60 80 100

Lat

ency

Fz

Age

y = 2E-09x6 - 8E-07x5 + 0,0001x4 - 0,0082x3 + 0,317x2 - 5,9175x + 45,276

R² = 0,4583

0 2 4 6 8

10 12 14 16

0 20 40 60 80 100

Am

plitu

de C

z

Age

y = -3E-08x6 + 8E-06x5 - 0,0009x4 + 0,0516x3 - 1,5681x2 + 21,495x + 139,14

R² = 0,1318 0

50 100 150 200 250 300 350 400

0 20 40 60 80 100

Lat

ency

Cz

Age

130

Fig. 6 Scatter plots of the relationship between N2 amplitude (µV; left), latency (ms; right) and age (years) at Fz (curved lines are the fifth degree polynomial regression over the age range 0-100 years)

Table 3 Suggested normative values for N1 and N2 by age (control groups data from deviant stimuli at Fz and Cz)

Component Age (years)

N (3934)

Participants age

(mean/SD)

Amplitude (mean/SD) (µV)

Latency (mean/SD) (ms)

Cz Fz Cz Fz

N1

[6-20] 518 12.3 / 3.3 8.0 / 3.0 8.8 / 2.8 124.0 / 15.1 160.0 / 54.0

[21-40] 1326 28.8 / 5.7 7.1 / 3.2 6.9 / 2.9 107.2 / 11.8 111.0 / 13.6

[41-60] 276 47.0 / 4.4 7.4 / 2.3 3.5 / 2.4 99.1 / 4.3 99.9 / 8.1

[61-85] 307 69.9 / 6.0 7.6 / 2.9 6.8 / 5.0 103.5 / 21.4 99.6 / 9.1

N2

[9-20] 343 12.9 / 3.3 6.3 / 4.4 11.0 / 3.5 239.2 / 28.8 239.9 / 15.1

[21-40] 706 28.3 / 5.8 4.7 / 2.1 4.7 / 2.2 224.8 / 30.9 225.6 / 17.5

[41-60] 208 47.1 / 4.6 5.5 / 2.6 4.0 / 1.0 224.0 / 12.5 232.3 / 17.2

[61-85] 250 70.9 / 6.3 3.7 / 1.6 2.3 / 2.0 249.0 / 49.7 238.3 / 26.9

Discussion

Most of the studies assessed have elicited N1 and several N2 as well, in clinical

groups, mainly in Neurology, Psychiatry and Psychology areas. This fact, suggests that

in the last decades N1 and N2 components have been studied as possible

endophenotypes or bio-markers for different disorders and in some cases for recovery

index. Namely in schizophrenia (Hegerl et al. 1988; Haig et al. 1997; Potts et al.

1998a; Shelley et al. 1999; Ford et al. 2001; Brown et al. 2002; Gilmore et al. 2005;

Neuhaus et al. 2013), dementia (Verma et al. 1989), Alzheimer (Sumi et al. 2000),

epilepsy and AED effects (Akaho et al. 1996; Ford et al. 2001; Lucchesi et al. 2003),

alcohol (Brigham et al. 1997; Cohen et al. 2002) and substance abuse (Tarter et al.

1995; Brigham et al. 1997), psychosis (Valkonen-Korhonen et al. 2003), panic

y = -8E-08x5 + 2E-05x4 - 0,0023x3 + 0,12x2 - 2,9989x + 33,328

R² = 0,6546

0 2 4 6 8

10 12 14 16 18

0 20 40 60 80 100

Am

plitu

de F

z

Age

y = 1E-06x5 - 0,0002x4 + 0,018x3 - 0,632x2 + 8,4299x + 205,86

R² = 0,1918

0 50

100 150 200 250 300 350 400

0 20 40 60 80 100

Lat

ency

Fz

Age

131

disorder (Wise et al. 2009), Parkinson’s disease (Wright et al. (1996), ADHD

(Johnstone et al. 2001; Tsai et al. 2012), stroke (Hirata et al. 1996) and vascular

cognitive impairment (van Harten et al. 2006), myotonic dystrophy (Kazis et al. 1996;

Tanaka et al. 2012), head injury (Reinvang et al. 2000; Segalowitz et al. 2001),

suppressed HIV patients (Chao et al. 2004), chemotherapy (Kreukels et al. 2008) and

pesticides exposure (Dassanayake et al. 2009), smoking (Guney et al. 2009),

amyotrophic lateral sclerosis (Ogawa et al. 2009) and multiple sclerosis (Whelan et al.

2010), more recently fragile X syndrome treatment (Schneider et al. 2013), and bipolar

disorder (Hamm et al. 2013).

In several respects, our data replicate the findings of others with regard to the

effects of age on the amplitude and latency of N1 and N2. Regarding N1 latency, only

Iragui et al. (1993) reported significant age-related increases at Cz. The common

finding has been that N1 latency remains unchanged or slightly decreases with

advancing age for target stimuli at this electrode, from where it has usually been

recorded (Goodin et al., 1978; Brown et al., 1983; Picton et al., 1984; Barrett et al.,

1987; Anderer et al. 1996; Amenedo & Díaz 1998; Tsai et al. 2012). Further, Anderer

et al. (1996, 1998a) found a latency increase over age only for standard stimuli. But at

Fz, N1 latency decrement is particularly pronounced during childhood and

adolescence, this result confirms the assumptions that the maturation of the frontal N1

is not yet completed at the age of 9–12 years due to incomplete frontal myelination

(Bruneau et al. 1997). Overall, the decrease in N1 latencies probably result from an

increase in neural transmission speed due to age-related changes in myelination of

underlying neural generators as well as increases in synaptic synchronization and

efficacy (Huttenlocher 1979; Eggermont 1988; Courchesne 1990; Ponton et al. 1999).

A paradoxical but astonishing phenomenon seems to take place from childhood to

adulthood. In 1979, Huttenlocher observed that a decline in synaptic density between

ages 2-16 years was accompanied by a slight decrease in neuronal density. This is

consistent with our results if we consider that synaptic density is related to N1 and N2

amplitudes. Both components have an amplitude decrement at Fz and Cz (Fig. 3, 4, 5

and 6). Human cerebral cortex is one of a number of neuronal systems in which loss of

neurons and synapses appears to occur as a late developmental event. The relationship

of N1/N2 to the adult N1/N2 is unclear. Maturational changes in the central auditory

132

system are complex and extend well into the second decade of life (Sharma et al. 1997;

Gilley et al. 2005). We believe that the effects of age, stimulation rate and education

influences components morphology and amplitude, the latter is usually taken as an

exclusion or inclusion criteria. The scarce literature on possible education effects on

N1 and N2 doesn’t enable us to achieve further conclusions. However a profound and

comprehensive revision on these topics should be made in a future article. In a recent

systematic review and meta-analysis regarding P3, no education effects were found

(van Dinteren et al. 2014). This was possible because P3 is one of the most studied

components with over 12,000 publications in 50 years of intensive research (van

Dinteren et al. 2014). Despite the interesting literature review and discussion made by

van Dinteren et al. (2014), we cannot compare results since they analyzed data only for

the Pz electrode site. Although, it definitely seems that N1/N2 and P3 have different

development across the lifespan, due to different generators and underlying

psychophysiological processes.

The range age between 41-60 years is the one with fewer participants, both to N1

and N2 (Table 3). This seems to be related with scarce literature and less investigation

oriented to clinical populations in this range.

Regarding N1 amplitude results are inconsistent among authors, possibly due to

short age range comparison. Our results reveal that N1 amplitude at Cz remains stable

after adolescence as seen in Fig. 3 (Tsai et al. 2012), but at Fz there is a linear decrease

from birth to 60 years old and then an exponential increment (Fig. 4). This result is

consistent with the common finding in the literature, that young, adult and elderly

differ in their ability to inhibit the processing of task irrelevant information resulting in

a higher level of general attention during oddball task (Ford & Pfefferbaum 1991;

Friedman et al. 1993; Anderer et al. 1998a; Ford et al. 2001). Furthermore, if we

analyze the differences between deviant and standard N1 sources of low resolution

electromagnetic tomography (LORETA) studies, younger subjects show a pronounced

difference, while it’s hardly to distinguish deviant N1 from standard N1 source in elder

subjects (Pascual-Marqui et al. 1994; Anderer et al. 1998a, 1998b).

This is called the reduction or decline of frontal inhibitory control, due to an

ineffective top-down modulation of primary auditory responses by prefrontal cortex

(Hasher & Zacks 1988; Čeponienė et al. 2008; for neuro-anatomical evidence see Raz

133

et al. 1997; Chao & Knight, 1997b; Dustman et al. 1996; Kok 1999). In addition, it has

been recently found that aging is related with a decrease in event-related spectral

power activity, a low phase locking in N1 theta (4-7 Hz) band over the parietal/frontal

regions and with a decrease of functional connections in the alpha (7-13 Hz) and beta

(13-30 Hz) bands (Ho et al. 2012) this might indicate a higher neuroplasticity of

younger brains and easy engagement of attentional resources.

Lastly, if we consider and combine results on P3 amplitude decrement and

topography change to two distinct foci of activity over age and neuropsychological

deficits pointed by several studies it may be concluded that aging is associated with a

general difficulty to distinguish relevant stimulation from irrelevant stimuli, in other

words difficulties in selection, categorization and storing in working memory (Picton

et al. 1984; Iragui et al. 1993; Lembreghts et al. 1995; Friedman et al. 1997; Amenedo

& Díaz 1998; Polich 2007; Martin et al. 2008).

These findings are consistent with N2 common results. The N2 component is

responsible for the classification or categorization of deviant stimuli (Mueller et al.

2008), a previous and required process before storing in working memory. Most

studies showed a decrease in the N2 amplitude and latency from childhood to

adulthood (Ladish & Polich 1989; Iragui et al. 1993; Lembreghts et al. 1995;

Johnstone et al. 1996; Bertoli & Probst 2005; Mueller et al. 2008; Čeponienė et al.

2008; Tsai et al. 2012), our results are consistent with literature at Fz and Cz but only a

slight decrement in latency until 40 years old (Fig. 5 and 6). Similarly, Goodin et al.

(1978) have already found a decrease in N2 latency with age in children of 6 to 15

years but an increase in this latency activated or passed as early as during the N1 and

P2 components. Regarding adulthood, Picton et al. (1984) reported a significant

increase in N2 peak latency with age at a rate of 0.65 ms per year in adults of 20 to 79

years, for similar results have been achieved by several authors (Anderer et al. 1996;

Mueller 2008). Our results also revealed a slight increment in latency after 40 years

old for both Fz and Cz (Fig. 5 and 6). The increases in N2 latency seem to be due to

linear increases in one of its components latency (N2b) at Fz, Cz and Pz, indicating

that the aging-related slowing begins at controlled memory comparison between non-

target and target stimuli (Amenedo & Díaz 1998).

134

Keeping the above in mind, N2 amplitude decrement over age and latency

increment after adulthood are the only auditory ERP findings that are in agreement

with age-related decrease in auditory acuity (Baltes & Lindenberger 1997; Chao &

Knight 1997a, 1997b; Tremblay et al. 2003; Čeponienė et al. 2008). However, other

studies have found no changes in N2 amplitude with advancing age (Brown et al.

1983; Picton et al.1984; Barrett et al. 1987) and even increases at central and parietal

scalp sites (Iragui et al. 1993; Enoki et al. 1993) which might explain N1 & N2

amplitude increment at Cz from 20-45 years in our scatter-plot (Fig. 3 and 5). N1 &

N2 amplitude increase in this range (20-45 years) might correlates with growth of

synaptic density, paralleled by improving synaptic efficiency and spatiotemporal

synchronization.

Further, Čeponienė et al. (2008) consider that N2 diminution with age could

represent cyto-architectonic derangement in sensory regions, including diminished

synaptic synchronization causing decreased processing speed (Peters 2002).

Finally, to consider using N1 and N2 components in clinical practice it must be kept

in mind that ERPs change topography over age, due to senescent-related changes and

individual profound cortical reorganization. Regarding N1 and N2, a change from

frontal to central-parietal topography peak with aging is the most common finding

(Anderer et al. 1996, 1998a; Amenedo & Díaz 1998; Mueller et al. 2008) because

frontal areas have also been reported to be more affected by aging than others (Goodin

et al. 1978; West 1996; Amenedo & Díaz 1998; Mueller et al. 2008). Anderer et al.

(1996) reported that N1 latency increases with advancing age were dependent on

electrode position, as they only increased at posterior scalp sites. However, gender is a

variable that one should be taken notice of. Some authors have reported differences

across electrode location and amplitude (Golgeli et al. 1999). Very few studies

reported control groups by gender precluding us to include it in our statistical analyses.

In addition, a comprehensive review regarding possible effects of IQ and years of

education is of particular importance, in a forthcoming article. Also, despite means and

standard deviations for N1 and N2 in Table 3, it is still a challenge to compare results

of a single participant, and doesn’t exempt of establishing normative values in the

local laboratory, department or service.

135

It is important to conduct systematic reviews and normative values regarding P1

and P2 components and P1-N1-P2 complex (Zheng et al. 2011) also with auditory

oddball paradigms and considering putative gender differences. The objective

measurement of central auditory processing and integrity of final auditory pathway

should not depend on just one component but on the presence of several ERPs

(complex), reflecting progressive central sound processing and representation (McGee

et al. 1997; Näätänen et al. 2007; Nikjeh et al. 2009) and also preservation of neuronal

synchrony encoding temporal information (Rance et al. 2002; Tomé et al. 2012).

Summary and conclusion

The clinical use of N1 and N2 remains minimal because recording requires special

equipment and knowledge to process and extract ERPs. But also because normative

data are lacking and responses vary widely between subjects.

Results from this systematic review suggest that Fz and Cz are the electrode

locations to clinically consider the normative values presented in results section.

However, to accept N1 and N2 components as brain markers of pre-attentive and early

cognitive function it should be regarded parallel changes in brain development and

components topography over age, mainly in childhood, adolescence and after 60 years.

But certainly, using auditory oddball paradigms in an attended or unattended

condition, N1 and N2 components seem a promising clinical indexing measure in the

assessment of central auditory processing among several clinical conditions and

populations.

Conflict of interest

The authors have declared that there are no conflicts of interest in relation to the

subject of this study. The contribution of Kamila Nowak was supported by NCBR

grant No.INNOTECH-K1/IN1/30/159041/NCBR/12.

136

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In this section we will explain the importance of early auditory processing

stages based on the neurocognitive auditory sentence processing model, ERPs,

imaging and neuroanatomical correlate. Further, we will analyze the contribution of

dyslexia and its theorical hypothesis, TLE in childhood (Paper III), and aphasia (Paper

IV) as explanatory clinical models of auditory and language processing, but also as

disorders that would benefit from AERPs components as measures to assess central

auditory processing in clinical practice.

Psycholinguistic Models and Language Processing

“Biological evolution and cultural evolution (of which the transmission of

information about the construction of language is a particular type) are both dynamical

systems in that the transmission of information over time results in change of that

information. In fact, they are not the only dynamical systems involved in language -

individual learning is another one, operating at an even shorter timescale to that of

culture and biological evolution” (Kirby, 2007, p.679).

These three dynamical systems interact in non-trivial ways (Figure 5). The

mechanisms for acquiring and learning language are part of our biological inheritance,

and are thus subject to biological evolution. It requires neuroprocessing multiple

modalities such as hearing, vision, and somatosensory/motor (for handwriting). It is

these learning mechanisms that underpin the cultural process of linguistic transmission

through iterated learning. We will focus on the individual’s biological language

neuroprocessing mechanisms. Language is a system mapping between

concepts/intentions and perception/articulation.

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Figure 5. Language emerges from the non-trivial interactions of three dynamical systems operating on three different timescales: individual learning, cultural transmission and biological evolution (Kirby, 2007).

The classical triangle of the lexicon tries to simplify the complexity of the

language. The latter reflects researchers’ current beliefs that information about words

is represented in a network that relates meaning (thought), sound/phonology

(speaking), and spelling/orthography (writing) (Smith & Kosslyn, 2007). Although, the

acquisition process firstly starts with the lexical, phonological processes, and then the

syntactic and morphological aspects, requiring a multimodal communication

environment and action (Clark, 2003; Ingram, 1989; Rvachew & Brosseau-Lapré,

2012). Figure 6 represents and updating of the classical triangle for the basic design of

language. The main updated points were the external interface to phonological

formation and the internal-intentional interface regarding meaning and reasoning

(Berwick, Friederici, Chomsky, & Bolhuis, 2013). These updates consider factors such

as the environment and individual’s active behavior or work to learn and to improve

his/her language comprehension and production as cognitive abilities.

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Figure 6. The basic design of language. There are three components: syntactic rules and representations, which, together with lexical items, constitute the basis of the language system, and two interfaces through which mental expressions are connected to the external world (external sensory-motor interface) and to the internal mental world (internal conceptual-intentional interface). From Berwick et al., 2013; with permission, appendix 7.

The human being starts to listen and learning from speech already in the womb

and after birth the baby listens to the mother’s voice above all other auditory inputs. In

the last decades, many different theories and perspectives of phonology development

and language acquisition have been proposed to scientist and clinicians. One thing is

certain: speech is considered a quintessential human behavior. From this perspective

the dichotomy “nature-nurture” or “inside in/inside out” between innate factors and

environmental influences is a reductionist explanation for the variability of

developmental outcomes that can occur (Spencer et al., 2009).

Today’s modern science supports an integrated perspective to explain

phonological development based on dynamic systems theory. One of its main authors

was Esther Thelen, recognized for the embodiment hypothesis, the notion that

cognition is derived from our perceptions of and actions on the “world” throughout the

life span (Smith & Thelen, 2003; Thelen & Smith, 1994). Keeping the above in mind,

phonological and speech development is viewed on a connectionist and constructivist

emergent product of cross-domain knowledge, environment, endogenous

components/biological aspects (e.g., normal auditory processing and perceptual

processing is essential) and the social and functional needs of the child to meet the

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demands of a new task in a specific context (Munakata & McClelland, 2003; Rvachew

& Brosseau-Lapré, 2012). A clear concept adapted from dynamic systems theory will

re-occur during this process: nonlinearity (Fogel & Thelen, 1987; Thelen & Smith,

1994).

Advances in our understanding of the nature of language processing are being

facilitated by studies and narrative reviews that integrate and combine discoveries by

methodological techniques such as neurophysiological measures, imaging (e.g., fMRI,

MRI, PET), neuropsychological measures, audiometric tests, for example.

In psycholinguistics, most existing theoretical and computational approaches

explain language processes either as the activation and long-term storage of localist

elements (Dell, 1986; Levelt, Roelofs, & Meyer, 1999; McClelland & Elman, 1986;

Page, 2000) or based on fully distributed activity patterns (Gaskell, Hare, & Marslen-

Wilson, 1995; Joanisse & Seidenberg, 1999; McClelland & Rumelhart, 1985). The

latter, gave birth to a plethora of connectionist models of word learning and language

processing (e.g., Christiansen & Chater, 1999; Dell, 1986; Elman, 1991; Garagnani,

Wennekers, & Pulvermüller, 2007; Gaskell, Hare, & Marslen-Wilson, 1995;

McClelland & Elman, 1986; Norris, 1994; Plaut & Gonnerman, 2000; Plaut,

McClelland, Seidenberg, & Patterson, 1996; Plunkett & Marchman, 1993; Shastri &

Ajjanagadde, 1993). From a neurophysiological and neuroanatomical perspective,

these connectionist models are the most coherent explanations to the understanding of

how different parts of the human brain may play an active role in language processing,

at a system level.

In a retrospective analysis, today we have theoretical models for language

acquisition, language learning, speech perception, word recognition (e.g., logogen

model, cohort model), and speech production (mainly based on aphasia model). The

majority of the most recent was impelled by the model of Damásio and the model of

Wernicke-Geschwind of language processing (Plaja, Rabassa, & Serrat, 2006).

Several studies have attempted to link the various brain areas involved in

language processing. However, there is consensus that language processing is

multidimensional and with difficult clinical assessment of its individual components

(Plaja, Rabassa, & Serrat, 2006): phonetics and phonology; morphology; syntax;

semantics; pragmatic; speech content analysis; and metalinguistic. All of these

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components require a complex but synchronized neural network, interacting with and

supported by attention, and the different types of memory. Furthermore, we still do not

know the quantitative contribution of each of these factors, necessary for the

acquisition of language and communication skills.

It would be a challenge to explain language processing from “Sensory input

systems analysis” to “Phonological analysis and integration of different modalities” to

the final stage of “Semantic/orthographic systems output (spoken word/writing)”.

Event-related potentials measures have been used to investigate language

processes and establish potential correlation with AERPs since 1980s (Kutas &

Hillyard, 1980). The neuroimaging techniques provide objective measures of brain

activity associated with language and cognition, with high spatial resolution. However,

their temporal resolution is insufficient to detect and reveal the fast neural activity that

occurs during a language-related task (Kutas & Federmeier, 2000; Pettigrew,

Murdoch, Chenery, & Kei, 2004). Language processing is a cognitive activity that

occurs in the millisecond domain (Levelt, 1989). Therefore, AERPs as a non-invasive

EEG recording with high temporal resolution and time-locked to a controlled event

(Hillyard, 2000), is probably the most adequate technique to investigate normal and

abnormal language function (Friedirici, 1997) and without the need for behavioural

responses from the individual (Hough, Downs, Cranford, & Givens, 2003). One should

keep in mind that with or without behavioural response, in language processing

research the tasks involved still require attention. Since there are no AERPs

components exclusively elicited without attention (Coull, 1998), probably only MMN

(Näätänen, 1990; Näätänen, Paavilainen, Tiitinen, Jiang, & Alho, 1993; Pettigrew et

al., 2004), considering that attention is commonly impaired in language-disorder

individuals, AERPs in language research must be interpreted carefully and wisely

before applying to clinical practice.

Hence, despite the ERPs seem undoubtedly the best tool to study the underlying

neurophysiological mechanisms of language processing, the correlation to

psycholinguistics models is not clearly defined. A linkage would certainly facilitate

our understanding of the nature and neurophysiological processing of language and

enable the accuracy of psycholinguistic models to be improved.

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Human’s brain can process (access, coordinate, manipulate, elaborate)

segmental phonemes, phonological information, as well as syntactic and semantic

information within milliseconds. Thus, functional dissociations within the neural basis

of auditory language processing are difficult to specify due to the mentioned processes.

Regarding exclusively auditory language comprehension, there are two main

classes of psycholinguistic comprehension models (Friederici, 2002): the serial or

syntax-first models and the interactive or constraint-satisfaction models. The serial or

syntax-first models consider that syntax is processed autonomously prior to semantic

information, if both cannot be mapped onto one another, reanalysis takes place

(Frazier & Clifton, 1997). The interactive or constraint-satisfaction models consider

that syntactic and semantic processes interact from an early stage during auditory

language comprehension to achieve understanding (Marslen-Wilson & Tyler, 1980).

Later, some authors started to consider that prosody and syntactic information also

start to interact in early stages, facilitating the resolution of ambiguities (Kjelgaard &

Speer, 1999).

One of the most recent models that consider the above stated linguistic

processes, and is able to distinguish the latter in early and late processes in temporal

dimension using AERPs, is the neurocognitive model of auditory sentence

comprehension (Friederici, 2002). The latter is based on electrophysiological,

magnetic fields and brain-imaging data. The model approaches three processing phases

from 100 to 1000 ms, we adapted the model’s phase 0 and 1, considering the early

components described at the beginning of this chapter (Figure 7; Table 1; courtesy of

Professor Friederici, appendix 8). Nevertheless, we do not include the very early

neuronal auditory processing analysis that occur from cochlea, brainstem and

mesencephalon assessed by other evoked potentials such as ABRs or AMLR, since it

is a neurocognitive model. But that will certainly be approached in a future work.

The neurocognitive model of auditory sentence processing considers that a

bilateral temporo–frontal network subserves auditory sentence comprehension (Figures

7 and 8). The left temporal regions process the primary acoustic analysis (primary

auditory cortex), phoneme/phonological identification (Broadmann’s areas 42 and 44),

lexical/word category, and structural elements/syntax (anterior and posterior superior

temporal gyrus) – phases 0 (0-100 ms) and 1. At this stage, the information is

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complemented with the processing of prosody by the right posterior superior temporal

gyrus. Afterwards, semantic and morphological information is processed (left middle

temporal gyrus; Figure 8) – end of phase 1 (100-300 ms).

Almost at the same time, frontal regions support the formation of relationships.

The left frontal areas will establish and process morpho-syntactic relationships and

thematic structure/sequencing processing of different types of stimuli (Broadmann area

44/inferior frontal gyrus) and semantic relationships (Broadmann’s areas 45 and

47/frontal opercular cortex). The right frontal cortex will complement with the

processing of melody – phase 2 (300-500 ms).

Finally, in the last stage of processing, the different types of information are

integrated and eventually may occur processes of reanalysis and repair – phase 3 (500-

1000 ms).

The presented model also considers the role of the working memory (Figure 7),

demonstrated by fMRI studies that Broca’s area (Broadmann’s area 44) support

aspects of syntactic memory (Fiebach, Schlesewsky, & Friederici, 2001; Friederici,

Meyer, & von Cramon, 2000). The different areas within the network must be

activated and coordinated to achieve auditory sentence comprehension. Syntactic and

semantic processes interact during a later processing phase. Though prosodic processes

influence syntactic processes, the exact timing of this integration it is still not known.

The above described model, in its inherent language auditory processing but

also learning and maintenance, may be supported by the cell assembly model. The

latter, is based on the Hebbian concept on neuronal activity with almost 65 years

(Hebb, 1949).

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Figure 7. Neurocognitive model of auditory sentence processing. The boxes represent the functional processes, the ellipses the underlying neural correlate. The ERP components specified in their temporal structure are assigned to their neural correlate by the function rather than the localization of their generator. Abbreviations: BA, Broadmann’s area; ELAN, early left-anterior negativity; ERP, event-related brain potential; IFG, inferior frontal gyrus; MTG, middle temporal gyrus; MTL, middle temporal lobe; STG, superior temporal gyrus; (Adapted from Friederici, 2002; with permission, appendix 8).

Figure 8. The cortical language circuit (schematic view of the left hemisphere). The major gyri involved in language processing are colorcoded. In the frontal cortex, four language-related regions are labeled: three cytoarchitectonically defined Brodmann areas (BA 47, 45, 44), the premotor cortex (PMC) and the ventrally located frontal operculum (FOP). In the temporal and parietal cortex the following regions are labeled: the primary auditory cortex (PAC), the anterior (a) and posterior (p) portions of the superior temporal gyrus (STG) and sulcus (STS), the middle temporal gyrus (MTG) and the inferior parietal cortex (IPC). The solid black lines schematically indicate the direct pathways between these regions. The broken black line indicates an indirect connection between the pSTG/STS and the PMC mediated by the IPC. The arrows indicate the assumed major direction of the information flow between these regions. During auditory sentence comprehension, information flow starts from PAC and proceeds from there to the anterior STG and via ventral connections to the frontal cortex. Back-projections from BA 45 to anterior STG and MTG via ventral

Phase 0 N100 (100 ms) P200 (200 ms) N200 (150–200 ms) MMN (150–250 ms)

Phase 1 ELAN (200–300 ms) P300 (250–350 ms)

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connections are assumed to support top-down processes in the semantic domain, and the dorsal back-projection from BA 44 to posterior STG/STS to subserve top-down processes relevant for the assignment of grammatical relations. The dorsal pathway from PAC via pSTG/STS to the PMC is assumed to support auditory-to-motor mapping. Furthermore, within the temporal cortex, anterior and posterior regions are connected via the inferior and middle longitudinal fasciculi, branches of which may allow information flow from and to the mid-MTG; (Friederici, 2012; courtesy, appendix 9).

The Hebbian concept of cell assemblies states that cognitive entities such as

gestalts and words represented by neurophysiological activity result from organised

and strongly connected assemblies of cortical neurons (Pulvermüller, 2001). These cell

assemblies are result of frequent simultaneous neural activity that causes neural

connections to strengthen (Hebb, 1949; Pulvermüller, 1996). Thus, the latter are the

neurobiological conception for the phonological word forms memory and phonological

awareness in the perisylvian cortices (Pettigrew et al., 2004; Pulvermüller, 1999).

This has been tested and proven by neurocomputational models (Garagnani,

Wennekers, & Pulvermüller, 2007; 2008). A cell assembly is a highly specialized

functional unit, with an “ignition threshold” (minimum number of active neurons

needed to trigger the neuronal circuit), that “responds” by becoming fully active only

with a specific brain activation pattern brought by a sensory (or internal) stimulation of

auditory or motor modalities. It can also explain the neural mechanisms underlying the

learning of language and synaptic plasticity, through associative Hebbian learning

mechanisms. The slogan is “neurons that fire together wire together…acting briefly as

a closed functional system” (Hebb, 1949, p.62).

The neurocomputational model of Garagnani (2008) is able to explain the

nearness but differently specialized neurofunctional areas and reciprocity, and simulate

cortical inhibition mechanisms that could be indexed by N2. Area-specific inhibitory

loops implement a mechanism of self-regulation preventing the overall network

activity from falling into non-physiological states (total saturation or inactivity). Thus,

this model is well suited for the parcellation of perisylvian cortex into core, belt, and

parabelt or even the terminology of inferior frontal gyrus, superior temporal gyrus and

middle temporal gyrus. Further, it represents the general principles of cortical

connectivity, especially sparseness and patchiness, topography of projections of long-

distance connections and next-neighbour preference of local links, such as cortico-

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cortical connections of the dorsal and ventral pathways (Figure 8). Also consistent

with Catani, Jones and Ffytche work (2005).

The cell assembly model is being applied successfully to ERP studies on

language processing, mainly with MMN (Pulvermüller et al., 2001). However,

connections between non-adjacent cortical areas and between primary and associative

cortices still remain to be clarified, such as the role of the different types of ion

channels, neurotransmitters and synaptic receptors. Finally, is does not differentiate the

role of grey matter from white matter fiber tracts. Considering the recent findings and

discussions, the dorsal pathway projecting from the posterior portion of Broca’s area to

the superior temporal region seems to be of particular importance for higher-order

language functions (Friederici, 2009). This pathway is particularly weak in non-human

compared to human primates and in children compared to adults. It is therefore

considered to be crucial for the evolution of human language, which is characterized

by the ability to process syntactically complex sentences (Fitch & Hauser, 2004;

Rilling et al., 2008).

A clinical model that has been relevant for assembly model affirmation has

been aphasia (see Paper IV). The function of cell assemblies may be altered by brain

lesions (Pulvermüller & Preissl, 1991). In other words, cell groups become linked

within an assembly after learning; after a cut or damage they may return to

functionality if the neurons left unaffected by the lesion are not smaller than the

“ignition threshold” required to ignite after stimulation (Pulvermüller, 1999).

Moreover, if small lesions do not lead to overt language deficits, cell assemblies may

ignite after stimulation but will take longer to do so.

Future research applying the Hebbian concept to ERP studies might focus on

the neuroplasticity of the auditory processing system.

Clinical Models for Understanding and Applying: conceptus et constructus

from Temporal Lobe Epilepsy, Aphasia, and Dyslexia

The circumscribed brain lesions have always provided reasonable inferences on

specialized brain functions areas. In other words, the early conceptualization of mind-

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brain relationships was based on the clinical anatomical method, like the pioneering

work of Paul Broca and Karl Wernicke.

Brain lesions described post-mortem have been tentatively related to cognitive

deficits evaluated in vivo, and vice versa, to establish structure-function relationships.

Such was the case of aphasia. That led to a primary functional model of language,

which emerged in the form of a temporal frontal network (Démonet, Thierry, &

Cardebat, 2005).

If there is an anatomical lesion, it has to be seen. This led to a massive

investigation and tremendous progress on imaging techniques. The purpose is still to

visualize with the highest spatial resolution brain structures affected and in an ultimate

abstraction to image cognition. However, task-activated fMRI can provide evidence of

cortical reorganization of language areas, due to mass lesions or after surgical

resection (Stufflebeam & Rosen, 2007). An anatomic brain damage is not only

structural, but also psychological, physiological, biochemical and neural networking.

Therefore, an appropriate and reliable technique that could comprise the inherent

complexity of the countless brain lesions and disorders is required. Such technique is

the EEG, and its measures the ERPs.

The clinical applications of neuroimaging technologies such as magnetic

resonance imaging (MRI), functional MRI (fMRI), positron emission tomography

(PET), magnetoencephalography and electroencephalography (MEG/EEG), and

diffusion tensor imaging (DTI), are just beginning to be realized (Stufflebeam &

Rosen, 2007). However, neuroscientists and clinicians must bear in mind the essence

and complementarity of each method, for the conceptualisation of cognitive models

and to bring to a conclusion what is really important to evaluate or monitor in clinical

practice.

Aphasia, temporal lobe epilepsy, and dyslexia are adequate clinical models to

study central auditory processing and its correlation with the disorder or dysfunction.

Further, the appropriate method and measures are the AERPs, due to its high temporal

resolution, control of the psychological set (to establish a feasible psychophysiological

relation).

Alterations to AERPs are not pathognomonic (characteristic for a particular

disease) to these disorders. Yet, AERPs provide progressive but underpinned advances

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in the (re)conceptualisation of the above stated disorders integrating behavioral

metrics, diagnosis, prognosis and treatment monitoring.

The Paper III relates to temporal lobe epilepsy in childhood. The Paper IV

relates to AERPs results to pure-tone and speech consonant-vowel oddball paradigms

in a case study of Broca’s aphasia that evolved to an anomic aphasia.

as explanatory clinical models of auditory and language processing, but also as

disorders that would benefit from AERPs components as measures to assess central

auditory processing in clinical practice.

Dyslexia

In the last decades, there have been some more comprehensive theories in an

attempt to explain the causes of dyslexia (Bowers & Wolf, 1993; Palesu et al., 2001;

Snowling, 2004): the cerebellar deficit theory; the magnocellular deficit hypothesis, a

deficit in sensory processing caused by an abnormality of auditory and visual

magnocellular pathways; the phonological deficit hypothesis; the temporal processing

deficit hypothesis; and the recent anchoring-deficit hypothesis.

Twenty years ago, Nicolson, Fawcett and Dean (1995) presented the cerebellar

deficit hypothesis, based on the problems in motor coordination and balance reported

in about 80% of dyslexic children. They also described difficulties of automation,

information processing speed and poor handwriting (Nicolson & Fawcett, 1999). Later

other studies supported the association between the cerebellum and the dyslexia,

stating that the cerebellum may affect reading in different ways due to its functions.

The cerebellum is involved in eye movement control, speech, the visuo-spatial

attention and peripheral vision. In addition, the oculomotor control may be affected,

compromising the saccadic and pursuit systems, both necessary for reading (Moretti,

Bava, Torre, Antonello, & Cazzato, 2002). Imaging and anatomical studies showed

abnormalities in the density of the gray matter of the cerebellum and metabolic deficits

(Berry et al., 1998; Eckert et al., 2003). In addition, dyslexic children show impairment

in postural stability and balance, as well as in other types of motor tasks (Ramus,

Pidgeon, & Frith, 2003). However, this theory leaves some unexplained gaps, in

particular the replication of studies have not shown consistent results, and many of the

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children in the experimental groups had other associated problems. The presence of

this comorbidity is not a consensual aspect among several authors, maintaining the

doubt if it is a result, consequence or independent of dyslexia (Ramus, 2004).

The magnocellular deficit theory arose when Lovegrove, Bowling, Badcock,

and Blackwood (1980), in the 80s, proposed that the dyslexic readers had low level

visual impairments affecting the transient visual system. There are two complementary

systems responsible for the different transmission characteristics of the visual stimulus

from the retina through the superior colliculus (SC) and the lateral geniculate nucleus

(LGN) 17 to the occipital pole area of the cerebral cortex, also known as primary

visual cortex (V1), surrounded by the visual association cortex (V2 to V5) – the

magnocellular system and the parvocellular system (Mackay, 1999; Stein, 2001). The

magnocellular or visual transitional system is characterized by large cells that have fast

transmission features. Predominates in peripheral vision, it mediates low spatial

frequencies of stimuli, low contrast, and fast temporal resolution, for example the

movement and the rapid change of stimuli (Schulte-Körne & Bruder, 2010). The

parvocellular or long-term system, on the other hand, consists of small cells

concentrated within the fovea, and thus having slow transmission. This pathway

projects to the visual cortex via the dorsal lateral geniculate nucleus, and culminates in

the temporal cortex. It is sensitive to spatial details (medium and high spatial

resolution) such as texture, form and colours, predominantly present in central vision

for object discrimination (Hutzler, Kronbichler, Jacobs, & Wimmer, 2006; Schulte-

Körne & Bruder, 2010). Parvocellular system is considered to be largely intact in

dyslexia, though there are some exceptions (Farrag, Khedr, & Abel-Naser, 2002;

Skottun, 2000).

The magnocellular system is essential for the control of guided eye movements

and visual scanning, and is responsible for overseeing the visual movements necessary

for subsequent fixations in a stimulus after a first fixation. Failure to properly control

these eye movements during the search of the next point of fixation, may lead to

corrective saccade, that may result in too many just to read one single word (Stein,

2001). Further, this system also has the saccadic suppression function (removing the

excess or dispensable visual information) and holds the binocular convergence during

reading (Hutzler et al., 2006; Mackay, 1999). The magnocellular deficit theory

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considers that all these functions are impaired in about 75% of individuals with

dyslexia (Plaja, Rabassa, & Serrat, 2006).

It has been very difficult to assesse this magnocellular pathway. The

magnocellular deficit theory has been supported by postmortem dissection data,

revealing disorganized magnocellular pathways in 30% of dyslexic brains, reduced

size of magnocellular cells as well as in the magnocellular blade of LGN – with

projections to visual area V1 (Livingstone, Rosen, Drislane, & Galaburda, 1991).

Studies with fMRI showed activation deficits both in the area V5 as in V1 (Eden et al.,

1996), relating the magnocellular pathway integrity to visual motion perception and

reading ability (Demb, Boynton, & Heeger, 1998).

Frith and Frith (1996) consider the magnocellular deficits as biological markers

of dyslexia, though not being related to cognition (Plaja, Rabassa, & Serrat, 2006).

Thus, according to these authors, this theory does not link dyslexia problems with

reading (the text is a stationary target and the magnocellular system is responsible for

moving targets), nor presents explanation for the remaining dyslexics who do not show

a magnocellular deficit. Apparently, the magnocellular deficit is a feature, not a cause,

since it is not common to all dyslexic cases.

Psychologists initiated the quest for a cognitive explanation for dyslexia in the

60s, giving rise to the phonological deficit hypothesis or, more recently, the model of

central and variable phonological difference (Snowling, 2004). This is a prevalent

cognitive-level hypothesis, which states that dyslexia is due to specific deficits in the

representation and processing of phonemes (basic elements of the linguistic system),

possibly giving rise to difficulties in learning the relationship between the word or

written letter and sound, the so-called grapheme-phoneme associations, and reading

delays or failure (Stanovich, 1994; 1998). It has been repeatedly shown that

phonological processing is one of the most relevant factors for learning to read and

spell and is impaired in dyslexic children, adults and in compensated adults (for

reviews see Rack, 1994; Ramus et al., 2003; Schulte-Körne & Bruder, 2010;

Snowling, 2004).

Phonology is an abstract language scheme that provides a structure to the

process of language, while phonological awareness is the ability of the individual to

consciously represent the phonological properties (sounds) and speech’s basic units

164

(syllables, onsets and rhymes, phonemes). Phonological awareness is therefore a

metalinguistic ability that allows humans to recognize/identify, decompose/separate,

compose/generate, combine and manipulate speech sounds (Loningan, 2006; Plaja,

Rabassa, & Serrat, 2006). Consequently, children with weak phonological awareness

will have difficulties in developing a broad base of words necessary to become fluent

readers, but also impairments in sensory memory, short-term verbal memory, naming,

and writing.

The phonological deficit hypothesis has also anatomical evidence. Some studies

correlate the phonological deficit with a lack of asymmetry between left and right

planum temporale in dyslexic brains (Cohen, Campbell, & Yaghmai, 1989; Habib,

2000; Larsen, Høien, Lundberg, & Ødegaard, 1990). Further, microscopic

examinations have shown numerous ectopias and dysplasias in the cerebral cortex,

raising the hypothesis that abnormally high testosterone activity during fetal period is

related to an altered neurological and immunological development (Galaburda &

Aboitiz, 1986). This is consistent with the presented temporal neocortex

neurofunctional specialization model (Paper III), the lack of anatomical asymmetry

might underpinne a lack of neurophysiological asymmetry, and consequently a

possible deficit in left hemispheric temporal resolution which is highly important for

speech processing.

Critics to the phonological deficit hypothesis relate to the fact that it is too

focused on phonological processing. Although a phonological deficit is often found in

dyslexic individuals (between 30% and 60% depending on the study), its etiology

remains, for the most part poorly understood. Despite having a good theoretical basis,

does not draw causal relationships or effect and needs further experimental evidence to

explain how the development and maturation of phonological processing interferes

with learning to read, which is why it must also include central auditory processing of

language (Ramus, 2004).

General population quickly and automatically tunes around incoming stimuli,

“anchors to them” and performs faster and more accurately when these stimuli are

subsequently repeated due to a gradually formation of an internal reference. This

“psychological anchoring” effect was discovered about almost 70 years ago, when

Harris (1948) found that protocols which include a repeated reference tone yield better

165

performance than protocols with no consistent reference across trials. Anchoring to

recently presented stimuli provides the perceptual system with better predictions for

subsequent stimuli, which tend to have similar characteristics. Consequently,

perception will be more resilient to distracting noises. Without this anchoring

mechanism, perceptual systems are therefore expected to be more sensitive to external

noise, as is the case with the perception of dyslexics (Ahissar, Lubin, Putter-Katz, &

Banai, 2006; Banai & Ahissar, 2006). Dyslexic individuals fail to benefit from

stimulus-specific repetitions, thus having an impaired anchor mechanism. This deficit

can account for phonological, working memory, attentional, visual and auditory

difficulties, in addition to the greater sensitivity of dyslexics to external noise (for

review see Ahissar, 2007).

Lastly, a “temporal (rate)-processing” theory of dyslexia was formulated based

on observations of aphasic children in the 1970’s, also known as rapid auditory

temporal processing theory (RATP; Tallal & Piercy, 1973). Temporal processing

deficits can explain perceptual deficits that could account for the phonological

processing deficits observed in dyslexia (Habib, 2000; Tallal, 2004). Since then

numerous studies were conducted to explore the basic auditory deficits in dyslexia by

investigating the ability to discriminate non-speech stimuli (Farmer & Klein, 1995;

McArthur & Bishop, 2001). The temporal processing theory was extended to the

perception of non-linguistic visual stimuli. Analogously, altered visual evoked

potentials (VEPs) were reported in dyslexic subjects (Stein, 2001). For both areas,

neurophysiological studies have made major contributions to the understanding of the

neurobiological correlates of dyslexia.

A number of electrophysiological studies have provided evidence for basic

perceptual deficits in dyslexia, mainly because it is a technique with high temporal

resolution. Abnormal event-related potentials (ERPs; amplitude, latency, topography)

for auditory processing of non-speech and speech sounds were found in dyslexic

children and adults (Sebastian & Yasin, 2008). Several studies have been conducted to

study auditory processing deficits with respect to discrimination abilities for pitch

discrimination, stimulus duration, tone pattern manipulation, frequency modulation,

gap detection, and temporal order judgments.

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Moreover, AERPs at birth can successfully discriminate 76.5% of children with

dyslexia, 100% of poor readers and 79% of control children at eight years of age

(Molfese, 2000; Molfese, Molfese, & Modgline, 2001), and can also correlate N1

amplitude and latency between ages one and four, and word reading at age eight

(Espy, Molfese, Molfese, & Modgline, 2004). AERPs correlated with speech

perception can strongly predict reading abilities at a very early age compared to other

factors such as home environment, academic stimulation, socioeconomic status,

parental education, preschool language score and short-term memory (Molfese,

Molfese, & Modgline, 2001).

In line with the latter studies, an anomalous ERP activity or functional

difference (between 540 and 630 ms) in the right hemisphere in at-risk children

(defined as one first grade relative reporting dyslexia) was found correlated with lower

word and non-word reading accuracy in the first grade of school (Lyytinen et al., 2005;

Lyytinen, Eklund, & Lyytinen, 2005) poorer language skills at 2.5 years; poor verbal

memory at five years (Guttorm et al., 2005) and reduced phonological skills, slower

lexical access and less knowledge of letters at 6.5 years (Guttorm et al., 2009),

compared to controls that presented largest differences between standard and deviant

stimuli in the left hemisphere.

The most investigated AERP in dyslexia has been the MMN (Garrido, Kilner,

Stephan, & Friston, 2009). No deficits in stimulus duration processing have been

reported in adults and children with dyslexia (Schulte-Körne & Bruder, 2010).

Investigations of frequency (pitch) discrimination with MMN suggest a deficit in

dyslexia (children and adult) only between stimuli that differ with less than 100 Hz

(Baldeweg et al., 1999; Maurer et al., 2003; Shankarnarayan & Maruthy, 2007).

Studies using large pitch differences (e.g., 200 Hz and greater) between tones did not

report any abnormalities in adults with dyslexia (Kujala, Belitz, Tervaniemi, &

Näätänen, 2003; Schulte-Körne et al., 2001), with the exception of Sebastian and

Yasin (2008), suggesting a deficit for shorter spectral changes only. Frequency

modulation is also described as a perceptual deficit in dyslexia (for review see Schulte-

Körne & Bruder, 2010).

Regarding N1 component, there have been reported deficits in gap detection by

adults with dyslexia to tone and speech. Gap detection is a temporal processing task

167

which measures the minimum ISI required to perceive an interruption (gap) in a

constant train of stimuli. Prolonged N1 and P3 latencies, and increased magnitude of

N1 compared to controls might be related to general allocation of pre-attentional

resources and/or reflect compensatory mechanisms serving to increase arousal and

readiness (Farmer & Klein, 1995; Georgiewa et al., 2002; Helenius, Salmelin,

Richardson, Leinonen, & Lyytinen, 2002). Further, decreased amplitude of N1-P2 (to

tone and speech stimuli) seems to index auditory processing impairments, representing

a causal risk factor for both language and reading disorders (McArthur, Atkinson, &

Ellis, 2009). In a more recent study, aiming to correlate neuronal phonological deficits

with auditory sensory processing, decreased N1c amplitude to rise time in the dyslexic

group aged 8-10 years old has been reported (Stefanics et al., 2011)

Speech perception involves the mapping of basic auditory information onto

phonological units. Therefore, phonemic units alone are abstract, but meaningful

acoustic representations of speech parts. Not surprisingly, an auditory speech-

processing deficit was determined in dyslexia in a number of AERPs studies in

children and adult, mainly an attenuated MMN (Csépe, 2003; Schulte-Körne, Deimel,

Bartling, & Remschmidt, 1998; Schulte-Körne et al., 2001). Bishop (2007) reviewed

several MMN prospective studies of children with familial history of dyslexia.

Differences between children at risk for dyslexia were found compared to control

groups in the lateralization of responses to stimuli. Most researchers found decreased

left hemisphere activation in diagnostic groups compared to control groups. Although

there have also been null results, both for speech and tone (Alonso-Búa, Díaz, &

Ferraces, 2006; Heim et al., 2000; Paul, Bott, Heim, Wienbruch & Elbert, 2006) and

even larger MMNs to tone stimuli (Sebastian & Yasin, 2008).

A similar discrepancy is observed in PET and fMRI studies. Whilst some

studies have shown a clear left-lateralization to speech stimuli (Narain et al., 2003;

Scott, Rosen, Wickham, & Wise, 2004), others suggest similar involvement of both

hemispheres in processing speech stimuli (Mummery, Ashmore, Scott, & Wise, 1999;

Scott & Johnsrude, 2003).

The N250 was also studied in dyslexia. This AERP is thought to index general

aspects of audition and sound reception (Čeponienė et al., 2001). Therefore, abnormal

N250 is suggestive of a more general impairment to sound reception in dyslexia.

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Lastly, most studies on MMN and dyslexia have focused on the early MMN. However,

late MMN component, also referred to as the late discriminatory negativity or LDN

(Čeponienė et al., 2004), at a timeframe from 300–600 ms over fronto-central sites has

also been described (Alonso-Búa, Díaz, & Ferraces, 2006; Čeponienė et al., 2001).

Studies have also reported reduced LDN amplitudes in dyslexic individuals (Neuhoff

et al., 2012; Stoodley, Hill, Stein, & Bishop, 2006). Late MMN/LDN generators seem

to be primarily in centro-parietal areas of the right hemisphere, suggesting the

involvement of other brain processes than those attributed to the early MMN (Hommet

et al., 2009). Because the functional significance of the late MMN is less well

understood, it is not yet clear what factors might underlie late MMN deficits (Neuhoff

et al., 2012).

The several ERPs studies cannot unanimously provide a neurophysiological

biomarker for dyslexia. Furthermore, how can each AERP component relate to

performance on behavioral tasks and clearly differentiate between dyslexia,

compensated dyslexia, SLI, ADHD or low phonological awareness, is still to be

achieved. Standardized protocols and rigorous sample criteria selection will help

clarify this issue. Moreover, if pitch discrimination deficit as measured by MMN is

correlated with degree of phonological impairment (Baldeweg et al., 1999; Sebastian

& Yasin, 2008) reflecting a residual auditory processing deficit that has not been

compensated by top-down strategies, why scarce research and results on N1 and N2

are published/reported? Or even to P1-N1-P2 complex? Mainly considered the most

prominent exogenous components in response to acoustic input (at least in adults) and

is thought to index basic encoding of acoustic information at the moment it enters

primary auditory cortex (Näätänen, 1990; Zheng et al., 2011).

The Phantom of Comorbidity

Dyslexia is a developmental disorder that has a serious impact on a child’s

educational and psychosocial outcome. It is identified if a child has poor literacy skills

despite adequate intelligence and opportunity to learn (Snowling, 2004).

169

Developmental dyslexia is also known as a specific reading disability, and is

frequently misunderstood or simply not distinguished from other developmental

disorders such as specific language impairment (SLI), speech sound disorder (SSD),

developmental coordination disorder, and attention deficit hyperactivity disorder

(ADHD, Catts et al., 2005). The latter, among psychiatric disorders, is the most

frequently associated with dyslexia, in about 25% of the cases (for review see

Banaschewski & Brandeis, 2007; Kronenberger & Dunn, 2003). These disorders are

the most common diagnosed in childhood, have similar prevalence, and most of the

times occur simultaneously in cases of comorbid phenotype.

Attention and learning problems usually are considered inter-related and on a

continuum (Mayes, Calhoun, & Crowell, 2000). Between dyslexia and ADHD there is

a bidirectional relationship since the comorbidity is very high if one examines children

with dyslexia for ADHD or children with ADHD for dyslexia (Germanò, Gagliano, &

Curatolo, 2010). Dyslexia is also comorbid with other disorders, including anxiety

disorder (Caroll & Iles, 2006), antisocial behavior (Maughan, Pickles, Hagell, Rutter,

& Yule, 1996), and depression (Willcutt & Pennington, 2000).

Despite the attractive possibility of merging all present theories in only one,

several studies are still not consistent in approving this or other theory. According to

Shaywitz et al. (1999), we cannot forget the extrinsic factors such as the child's

exposure to stimulating environments and characteristics of the teacher responsible for

the teaching method to read. It is important not to generalize dyslexia to all children

that have low income and/or motivation for reading or writing. Dyslexia is a cultural

phenomenon that has its main effect in literacy and therefore will not be observed in

non-literary cultures. The exposition, through childhood, to the language’s

morphosyntactic structure, as well as the realization of phonological exercises in the

preschool years, may be important factors for success in the written language learning.

On the other hand, if genetic research strengthens a predisposition or biological

markers for the difficulties of reading-writing, then it might be possible to consider a

plan of prevention through specific environmental interventions. Language is

something constantly and continuously present in our lives, contributing to the

development of literacy.

170

AERPs protocols (in contrast to fMRI) are particularly well suited to track very

early language development, and to detect language processing deficits ranging from

simple automatic sensory memory to high-level syntactic functions. Additionally,

AERPs can help to clarify and enlighten the limits of comorbidity. For example,

children with dyslexia exhibit MMN attenuations mainly to subtle speech and

frequency deviance (Baldeweg et al., 1999), while schizophrenic patients, or those at

high risk for schizophrenia due to microdeletion in the 22q11.2 gene, have reduced

MMNs especially to duration deviants (Baker, Baldeweg, Sivagnanasundaram,

Scambler, & Skuse, 2005; Michie et al., 2000), and reduced N2-P3 amplitude in

ADHD (Trujillo-Orrego, 2010). Thus, suggesting different deficits in preattentive and

attentive auditory processing in patients with schizophrenia, and individuals with

dyslexia or ADHD.

171

Paper III

Temporal Lobe Epilepsy in Childhood – a study model of auditory processing

David Tomé1,2, Marques-Teixeira1, Fernando Barbosa1

1 Faculty of Psychology and Educational Sciences, Laboratory of Neuropsychophysiology, University of

Porto, Portugal

2 Department of Audiology, School of Allied Health Sciences, Polytechnic Institute of Porto, Portugal

Tomé, D., Marques-Teixeira, J., & Barbosa, F. (2012). Temporal Lobe Epilepsy in

Childhood – a study model of auditory processing. Journal of Neurology and

Neurophysiology, 3(2). doi:http://dx.doi.org/10.4172/2155-9562.1000123

Journal of Neurology and Neurophysiology

ISSN: 2155-9562

Impact Factor 2013: 1.26 (unofficial)

Index Copernicus 2011: 6.79

172

Abstract

TLE in infancy has been the subject of varied research. Topographical and structural

evidence is coincident with the neuronal systems responsible for auditory processing

of the highest specialization and complexity. Recent studies have been showing the

need of a hemispheric asymmetry for an optimization in central auditory processing

(CAP) and acquisition and learning of a language system. A new functional research

paradigm is required to study mental processes that require methods of cognitive-

sensory information analysis processed in very short periods of time (msec), such as

the ERPs. Thus, in this article, we hypothesize that the TLE in infancy could be a good

model for topographic and functional study of CAP and its development process,

contributing to a better understanding of the learning difficulties that children with this

neurological disorder have.

Keywords: Auditory processing; Temporal lobe epilepsy (TLE); Childhood; Event-

related potential (ERP); Model

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Introduction

Central Auditory Processing (CAP) assumes a set of mechanisms and processes

carried out by pathways and neuronal centres, enabling the human sound localization

and lateralization, auditory discrimination, auditory pattern recognition, temporal

resolution, temporal masking, temporal integration, temporal ordering, auditory

performance in competing acoustic signals (including dichotic listening), and auditory

performance with degraded acoustic signals [1-8]. According to the most heuristic

model of CAP, this type of processing is defined as a series of processes that occur in

time and enable acoustic and metacognitive analyses skills of the sound [2-8].

The first years of life are crucial to the proper development of those processes,

depending on brain maturation and cerebral organization relatively, only developed in

humans, parallel to a ubiquitous neuroplasticity, allowing corrections and

improvements during the brain growth and cognitive development [9-11].

The sound transformed into nervous impulse in the cochlea is transmitted by the VIII

cranial pair to the cochlear nuclei in the brainstem, and from here to the central

auditory nervous system (CANS). The ascending auditory pathway is divided into ipsi

and contralateral, starting in the cochlear nuclei complex located on the back of the

pontomedular junction, where the first sound analysis on the intensity, frequency and

duration occurs [5,6]. Throughout the course of ascending auditory pathway, several

neuronal centres will contribute to the auditory processing and forwarding of the

message: (1) the upper olivar complex (UOC), considered the anatomical basis for the

binaurality; (2) the reticular formation responsible for processing and integrating other

sensory modalities (visual, vestibular and somestesic information); (3) the lateral

lemniscus nuclei and the inferior colliculus (midbrain) that have neurons sensitive to

interaural phase differences and to the spatial location of the sound; (4) the medial

geniculate nucleus complex (posterior caudal thalamus) which processes both the

dynamic characteristics of sound (intensity, frequency and amplitude modulation) and

the analysis of phonetics composition (auditory discrimination specific to speech),

sending the verbal information to the dominant hemisphere and nonverbal one to the

non-dominant hemisphere that is involved both in the selective attention processes and

the integration process, the interhemispheric communication occurring through the

174

corpus callosum [6-8,10-12]. This information, after reaching the cortical level in the

temporal lobes, the hippocampus stands out with an important role in declarative

memory and in learning, the Heschl gyrus of the auditory primary cortex and the

corner of the anterior temporal region being both responsible for impulse inhibition

from a temporal lobe to another. In 1930, von Economo and Horn performed the first

measurements of the Heschl gyrus, showing that the left hemisphere is usually bigger

and particularly containing more white matter [13]. This anatomical differentiation is

compatible with the hypothesis that the superior left temporal lobe has neurons capable

of analyzing highly overlapping sequences of post-synaptic potentials, and of detecting

minimum temporal variations, making this lobe more specialized for hearing

discrimination and language processing. On contrary, the right temporal lobe is more

sensitive to frequency variations, and thus being specific to spectral resolution

processing, as shown in Figure 1 [12-15]. This specialization requires working

memory processes, being highlighted in some studies on interactions with the anterior

regions of the frontal lobes [16-19].

TEMPORAL NEOCORTEX

LH RH

(left auditory cortex) (right auditory cortex)

+ temporal resolution (language specificity, 20-50ms) – temporal resolution (150-250ms)

– spectral discrimination + spectral discrimination (music and audio perception

spatial atentional specificity)

Figure 1: Temporal Neocortex neurofunctional specialization model

(LH: left hemisphere; RH: right hemisphere).

This hemispheric asymmetry suggests the existence of a functional adaptation and

optimization in auditory processing of different acoustic environments. Any

amendment or interference in this complex dynamic neuronal network, depending on

the severity and location, can be reflected in one or several processes inherent to the

175

acquisition and learning of a language system (verbal and nonverbal sequential

memory, declarative memory, selective attention, auditory discrimination and

phonological awareness) [20-22]. Certainly this linearity of CAP, somehow

reductionist, can be tested by various methods even when faced with

neurophysiological changes of neurological disorders, particularly in the course of

brain maturation and the concomitant development of language.

Auditory Neuroplasticity

The Temporal Lobe Epilepsy in infancy (TLE) being a neurological disorder that

affects directly the cortical areas of CANS, could be a good model for topographic and

functional study of CAP and its development process, contributing to a better

understanding of the learning difficulties that children with this disorder have and the

paradoxical processes of neuronal plasticity interfered by epileptogenesis.

The relationship between changes in EEG, linguistic deficits and seizures is not

yet well clarified. Not withstanding, there is a bias resulting from the several possible

aetiologies of ELT, which are inconsistent with the proposal of a single

neurofunctional model not considering the possibility of different topographic

locations for the epileptogenesis. These results, on one hand indicate different

structures and systems with highly specific functions in auditory processing that might

be “epileptically” changed, justifying the existence of different and varied

neuropsychological deficits; on the other hand, is increasingly documented that a

higher frequency and longevity of seizures are associated with worst

neuropsychological deficits. This is undoubtedly a very important fact, especially if we

consider the absence of neurophysiopathology and neuropsychology data which could

contribute to sustain or even strengthen the theoretical basis on which findings are

based on.

Finally, the use of research methodologies is very ambitious but little specific to

study a phenomena of high temporal resolution, resulting in non unanimous

conclusions such as linguistic or cognitive deficits are dependent on the structural

lesions identified in MRI, on the seizures, or are secondary to attention deficits or both.

Thus, the demand of “why” led to the search of a responsible element – whether it is a

176

gene, organ, structure or neurotransmitter – that can always escape. A more profitable

demarche, would be trying to answering to the “how” question, especially if we know

that in TLEs with spontaneous resolution of the seizures in adolescence, occurs a

simultaneous improvement in neuropsychological deficits [20,23-25]. In other words,

what we really need is a new paradigm that allows us to explore the consequences of

different etiologies. The following hypothesis is inscribed in this new research

paradigm. Not downplaying the importance of research lines concerning the functional

activity mapping, it is obvious that we are dealing with mental processes that require

methods of cognitive-sensory information analysis processed in very short periods of

time (msec). This is the case of event-related potentials (ERP).

The Hypothesis

The TLE in childhood may be cryptogenic or have several etiologies, being the

most frequent of the mesial temporal sclerosis, cortical dysplasia, brain injuries,

extrahippocampal lesions and/or hippocampal sclerosis, always with progression and

expansion to the temporal cortex [24,26]. Regardless of the neuronal origin of epileptic

focus, neuropsychological deficits are common among children and adults with TLE,

being more serious incidents as higher the frequency of the seizures and the time that

linger [23,27-29].

This fact sustains that neuropsychological expression can be seen as a final

common pathway of the different types of injury or dysfunction. The purely

neuropsychological approach leaves us far from understanding the genesis of these

phenomena in children. In addition, the methods widely used in brain imaging, namely

the fMRI, have the temporal resolution bias, besides the non-evidence based

assumptions usually made by neuroradiologists. The temporal resolution of the order

of second (sec) is manifestly insufficient to give an account of the nature of the

neuronal processes inherent in the processing of information in those cortical areas,

which is of the order of milliseconds (ms). The assumptions underlying the paradigm

used in neuroimaging studies are based on the reductionist conviction that the

activation of a particular area of the cerebral cortex is linked to a particular cognitive

function, and sometimes even to a behavioural function. This type of assumption,

177

beyond reductionist, not only gives importance to the inhibitory and the related

phenomena (e.g., the activation of a cortical area by an inhibitory step from other

areas, which may, once inhibited, disinhibit other areas and so on), as it leaves aside

the hypothesis according to which a substantial part of the information processing in

the brain occurs via anaerobic processes.

The use of high temporal resolution techniques with the possibility to register

several measures of the electrophysiological response (e.g., frequency resolution

techniques, phase correlation, event related potential studies, signal location, among

others), applied to the right and left auditory cortex in children with TLE, would allow

answering more adequately to the following questions:

1. The auditory cortical organization always presupposes a lateralization for

language development? If so, is this lateralization genetically determined?

2. How will be the cortical auditory organization and the response of their

functional specializations in TLE?

Implications and Further Studies

If future research validates these hypotheses, important implications and an

expansion of knowledge may be derived for a better understanding of the

consequences of epileptic seizures and the correlated neuropsychological deficits, as

well as the type of neurological disorder that affects the thalamic auditory pathways

and cortical areas. The creation of new lines of research, involving techniques such as

fMRI, MEG and dichotic electrophysiological evaluation response seem to be the most

promising.

Acknowledgments

There are not any financial, relationship and organizational conflict of interests

that may bias any of the authors in the establishment of the hypothesis model

discussed in this article.

178

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Paper IV

Mismatch negativity and N2 elicited by pure-tone and speech sounds

in anomic aphasia: a case study

David Tomé 1,2,*, Brígida F. Patrício3, Fernando Barbosa1, João Marques-Teixeira1

1 Faculty of Psychology and Educational Sciences, Laboratory of Neuropsychophysiology, University of

Porto, Portugal

2 Department of Audiology, School of Allied Health Technologies, Polytechnic Institute of Porto, Portugal

3Department of Speech Therapy, School of Allied Health Sciences, Polytechnic Institute of Porto, 4400-330

V.N. Gaia, Portugal

(submitted)

* Corresponding author. Tel.: +351 939591301; fax: +351 222061001.

E-mail address: [email protected] (David Tomé).

182

Background: the auditory processing impairments frequently observed in aphasia are

slowly being clarified by event-related potentials (ERPs), the only method that allows

the observation of high temporal resolution processes in the brain. MMN and N2,

represent brain auditory processing of echoic memory, attention and the activation of

phonological representation.

Aims: evaluate the auditory processing of speech and pure-tone stimuli in an anomic

aphasia subject, six years after stroke. Whether, ERPs are able to detect possible

neurophysiologic sequels after recovery and rehabilitation.

Methods and Procedures: a recovered subject with anomic aphasia, 6 years post-

stroke, was compared with 6 healthy controls. Event-related potentials (MMN, N1,

N2b) were obtained during two auditory oddball paradigms, one of pure-tone and other

of consonant-vowel (CV) stimuli.

Outcomes and Results: the anomic aphasia subject revealed reduced MMN amplitude

across frontocentral electrode sites, particularly to speech stimuli when compared to

healthy subjects. Furthermore, average deviant waveform analysis revealed a poor

morphology of N2b to speech stimuli, which might be related to deficits in the

activation of phonological representation.

Conclusions: in the presented case, we have shown that even 6 years post-stroke the

neurophysiologic brain activity for the processing of phonologic representations is not

fully recovered. MMN and N2 are highly sensitive ERPs to evaluate auditory

processing impairments, can be registered in the absence of attention and with no task

requirements, which makes it particularly suitable for studying and monitor aphasic

subjects.

Keywords: mismatch negativity (MMN); N2b; Anomic Aphasia; Auditory

Processing.

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INTRODUCTION

Aphasia is an acquired communication disorder caused by a focal brain lesion,

typically by vascular damage such as stroke in the language-dominant cerebral

hemisphere (Damasio, 1998; Darley, 1982), characterized by a multimodal language

impairment which may include speaking, understanding, reading and writing

(Goodglass, 1993; Hallowell & Chapey, 2008). In this article we will consider the

Boston Classification System (Goodglass & Kaplan, 1983), the most commonly used

in clinical practice in which disorders are classified according to the patient’s

comprehension, fluency, naming and repetition abilities: Broca’s aphasia, transcortical

motor aphasia, conduction aphasia, anomic aphasia, Wernicke’s aphasia, transcortical

sensory aphasia, transcortical mixed aphasia and global aphasia. In anomic aphasia,

naming or word-finding problems are the major features, the lesion is often in the

temporoparietal area (Goodglass & Kaplan, 1983).

There are several studies regarding recovery in aphasic patients, especially with

neuroimaging methods. Although these techniques reveal a high space resolution in

damage location and on the loci of activated areas, they have a low time resolution.

This might be a limitation, if clinicians want to assess neuronal processes or time-

locked brain activity such as perception, attention or echoic memory trace that requires

a high temporal resolution technique (Ilvonen et al., 2004; Tomé et al., 2012; Zatorre

et al., 1992). Electrophysiological methods, such as event-related potentials (ERPs),

are a non-invasive technique that can be used to address the temporal aspects of

auditory discrimination with verbal and non-verbal stimuli, especially in clinical

populations with abnormal language function (Hough, Downs, Cranford, & Givens,

2003; Pettigrew et al., 2005). Although ERPs measures have been used to investigate

language processes since the 1980s (Friederici, Pfeifer, & Hahne, 1993; Kutas &

Hillyard, 1980; Pettigrew et al., 2004), its clinical application in aphasic patients has

remained minimal.

In the past years, few studies have revealed ERP correlation and evolution over time

in patients with different types of aphasia and different types of lesions, allowing a

better understanding of the underlying processing and the reorganization involved in

recovery, which can be used as a recovery index. However, most of the studies focus

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on language production deficits and scarce literature concerning auditory receptive

processing and phonological loop from language and working memory models

(Baddeley, 2000; Jääskeläinen, 2012). From the point of view of clinical research and

applications, this is of particular significance.

In this paper, we elicited the mismatch negativity (MMN; Näätänen, 1995;

Näätänen et al., 2007) a change-specific component of the ERP considered

representing the brain processes that form the biological substrate of central auditory

perception, memory and attention, in a case study of anomic aphasia post

rehabilitation. The classical MMN is a fronto-centrally (Fpz, Fz and Cz) negative

component of the auditory ERP usually peaking at 100–250 ms from stimulus onset

and positive at mastoids, its mainly generators are the bilateral supratemporal cortices

with contributions of the frontal lobes, right parietal lobe, thalamus and hippocampus

(Näätänen, 1975, 2001; Näätänen et al., 2007). Currently, MMN provides an objective

measure of auditory perception and discrimination based on the presence of short-term

memory (sensory memory) and echoic memory trace, representing a repetitive aspect

of the ongoing stimulation before a deviant event elicit it, fading within 5-10 s (Hari et

al., 1984; Näätänen et al., 1987; Näätänen & Alho, 1997; Näätänen, 2001). Although

this memory-based model is widely accepted, there are different views concerning

MMN generation and interpretation such as the adaptation and the predictive models

(for a short overview see: May & Tiitinen, 2010; Winkler, 2007). After incoming

stimulus detection, additional cognitive processes are required for stimulus

classification and categorization. For speech stimuli, N2b subcomponent is particularly

important for the study of phonological activation processes (Becker & Reinvang,

2012; Patel & Azzam, 2005). N2b component seems particularly important, if we

consider Pulvermüller’s work that proposes cell assemblies organization in perisylvian

cortices for phonological word forms and memory traces (Pulvermüller, 1996;

Pulvermüller et al., 2001; Pulvermüller & Shumann, 1994)

It has been shown with auditory oddball paradigms, that MMN for frequency and

duration changes is attenuated in amplitude in patients with a left-hemispheric stroke

(Aaltonen et al., 1993; Auther et al., 2000; Becker & Reinvang, 2007a; Ilvonen et al.,

2001; Pettigrew et al., 2005). Furthermore, Ilvonen et al. (2003) followed up the

recovery of eight left-hemisphere stroke patients, in the first 10 days the MMNs were

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quite small in amplitude for sound duration and frequency changes, but became

progressively larger, disclosing normal-like amplitudes between three to six months

after stroke with an improvement in speech-comprehension tests during the follow-up

period. There are also some studies that elicited MMN with speech sounds oddball

(synthesized vowels, syllables or consonant-vowels), with a consistent result of a

MMN attenuation or absence (Becker & Reinvang, 2007b; Csépe et al., 2001; Ilvonen

et al., 2004; Pettigrew et al., 2005).

Even tough, the same question still arises, whether is language production or the

perception of the acoustic features of speech sounds that is impaired in aphasia, only

the language-specific processing of speech sounds, or a combination of both. The main

problem in answering to these questions, common among authors, probably remains in

the difficulty of gathering a homogenous experimental group concerning type of

aphasia and language function. Further, what can electrophysiological measures tell us

of successful post-rehabilitation cases, namely MMN and its underlying components?

How are AERPs components in an aphasic subject after recovered brain functions

compared to normal subjects? As mentioned before, we present a case study of an

anomic aphasic subject after a successful post-stroke rehabilitation from the cognitive

and behavioral point of view. Our aim is to evaluate the automatic auditory receptive

processing of speech and non-speech stimuli, eliciting the MMN and N2, in a type of

aphasia with deficits mainly in language production. In addition, we will compare

MMN and N2b waves morphology using Zheng et al. (2011) classification, regarding

a possible recovery index and its clinical meaning to study the progression of neuronal

responses associated with sound change detection.

METHODS

Case study

In this article, we present a case study of a woman (age = 46; length of Portuguese

education = 12 years) who had experienced a left-hemisphere stroke, concerning the

left middle cerebral artery nearly six years ago. Shortly after stroke she had a Broca's

aphasia with stereotype, hemiparesis and hemihypoesthesis. She did speech and

language therapy and evolved for an anomic aphasia. Currently, she presents

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hemihypoesthesis and an anomic aphasia (naming of 11/16; auditory comprehension

8/8; and repetition 27/30; level of fluency 4/5; Damasio, 1973). She made an excellent

functional recovery with only a slight naming difficulty remaining, with an Aphasia

coefficient of 85% based on the Lisbon Aphasia Examination Battery, which means a

mild severity of the aphasia. She has normal vision and hearing and a right handedness

laterality index of 85% corresponding to the 6th right decile (Oldfield, 1971).

Procedure

There are different results in MMN amplitude and latency for the same or similar

auditory oddball paradigm between authors, also very scarce literature on normative

data. In order to feasible compare results, six gender-matched control subjects, all

women, were selected for the study (mean age = 30.6 years ± 5.12; mean length of

Portuguese education = 14 years ± 2). All subjects were Portuguese native speakers,

had normal hearing and normal or corrected-to-normal vision, and a mean right

handedness laterality index of 85.9% corresponding to the 6th right decile (Oldfield,

1971). Also, they all signed informed consent, after ethical clearances, nature and

objective of the experiment explained and justified.

During the electroencephalographic (EEG) recording, the participants were

binaurally presented with two auditory oddball stimulation sequences of one block of

pure-tone and one block of consonant-vowel (CV), each containing a stimulus onset

asynchrony (SOA) of 800 ms, to a proximal sound level of 75 dB SPL. In the pure-

tone blocks, the standard stimulus was a pure-tone of 1000 Hz (100 ms duration,

including rise and fall time 10ms) replaced by a frequency deviant of 1100 Hz (same

duration of 100 ms, including rise and fall time of 10 ms). Speech-stimuli blocks

consisted of digitalized (rate 44100 Hz) CV syllables with 175 ms duration spoken by

a male native Portuguese voice. The standard phoneme was /ba/ and the deviant /pa/.

These phonemes were selected due to same place of articulation but different voicing,

thus differing in the frequency domain (Martin et al., 1997; 1999). In all single blocks,

standard stimuli comprised 80% of all trials, while deviant stimuli comprised 20%.

Stimuli were presented using ASA software v4.0.6.8 (ANT, Neuronic S.A.) via closed

headphones while the participants where comfortably seated in an armchair and

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instructed to keep alert with eyes-open, actively listen to the auditory stimuli and

focused on a small cross in the center of a computer screen during recording.

EEG recording and data analysis

EEG was recorded using a bio-amplifier recording device Refa32 (ANT, Neuronic

S.A.). Recordings were obtained from the following cup-shaped silver chloride (Ag-

AgCl) electrodes: Cz, Fz, Fpz, M1, M2 and Oz (ground). Electrodes were referenced

to averaged ear lobes (A1 and A2). Impedance between the electrodes and skin didn’t

exceed 10 kΩ. The quality of recordings was monitored during data acquisition and

continuous EEG data were stored on the computer hard disk for off-line analysis and

grand averaging. An electrode was attached above right eye to monitor the

electrooculogram (EOG). Sweeps with amplitudes exceeding ±70 μV in any channel

except EOG were excluded. Trials during which blinks, saccades or components that

could be attributed to such artifacts based on their topography and time course were

eliminated from the data for each subject before averaging (Jung et al., 2000). The

sampling rate was 512 Hz for each channel and the recording bandwidth between .05

Hz and 100 Hz. Offline processing included band-pass filtering [0.3–30 Hz], linear

detrending and a baseline correction (200 ms prior to stimulus onset, considering

stimulus duration).

The first 10 sweeps of each epoch file were excluded from the averaging process to

reduce ERP variation associated with the start of the stimulation sequence (Pekkonen,

Rinne, & Näätänen, 1995; Pettigrew et al., 2005). The MMN was determined from the

Fz, Cz and Fpz electrodes, measured by separately computing difference waves that

were obtained by subtracting the average standard-stimulus response from the average

deviant-stimulus response for each electrode and subject (Duncan et al., 2009). The

mean amplitude analysis, that is, the mean voltage over the 50 ms period time window,

was centered at the latency of largest negative peak for Fz, Cz and Fpz and positive for

mastoids, occurring between 100 and 250 ms.

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RESULTS

The difference waveforms from the pure-tone and speech CV paradigms for the

control and the anomic aphasia subject are shown in Figure 1. Table 1 gives an

overview over the MMN latency and amplitude results. The grand averages for the

deviant waveforms from the CV paradigm are shown in Figure 2.

The largest mean MMN-amplitude for the control group was found over Cz (mean

= -5.19 µV; SD = 1.6) with a median latency of 215 ms (SD = 31.2), to speech stimuli.

For the aphasic subject, the largest MMN amplitude was also for speech stimuli and

over Cz (-2.28 µV) with a latency of 168 ms.

TABLE 1 Mean amplitude and peak latencies of the MMN wave in Fpz, Fz and Cz, for the AA subject and the

comparison group

AA subject Control group (median/SD)

Tone MMN Speech MMN Tone MMN Speech MMN

μV / ms μV / ms μV / ms μV / ms

Fpz -1.62 / 170 --- -1.35(0.7) / 223(46.1) -1.59*(0.5) / 226 (43.6)

Fz -2.05 / 199 -1.85 / 148 -3.68*(1.1)/219(18.4) -5.08*(1.7) / 223 (32.2)

Cz -1.98 / 199 -2.28 / 168 -3.78(1.1) / 188(24.8) -5.19*(1.6) / 215 (31.2)

AA = anomic aphasia; Control group (n = 5); μV: microvolts (amplitude); ms: milliseconds (latency) *Effect size, r > 0.65 (> double absolute value); “---” = absent

In both conditions the control group had larger MMN amplitudes, particularly at Fz,

achieving twice the amplitude value of the aphasia subject. For all subjects, speech

stimuli elicited an enhanced MMN comparably to pure-tone, however the aphasic

subject revealed a slight earlier MMN for speech stimuli at Fz, Cz and absent at Fpz.

The MMN waveform morphology was of a similar pattern across frontocentral

electrode sites for the pure-tone and speech conditions for control subjects. The

aphasic subject revealed poor-moderately defined waveform, according to Zheng et al.

(2011) work. Furthermore, the average deviant waveform for consonant-vowel

paradigm was poorly defined in the aphasic subject, mainly the N2b component.

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500 ms 0

-5 µV

5 µV

100 ms

Pure-tones CV Fpz Fpz

Fz Fz

Cz Cz

Control

Aphasia subject

Figure 1. Grand average MMN difference waveforms (deviant minus standard) for pure-tones and consonant-vowel

(CV) paradigms for the anomic aphasia subject (dashed line) and the control group (solid line).

190

500 ms 0

-10 µV

10 µV

100 ms

Fpz

Fz Cz

Control

Aphasia subject

Figure 2. Grand average deviant waveforms for consonant-vowel (CV) paradigm for the anomic aphasia subject (dashed line) and the control group (solid line).

DISCUSSION

The results of this case study suggest that the aphasic subject has a MMN to pure-tone

and speech stimuli although with poor-moderately defined waveform, according to

morphology classification of Zheng et al. (2011). Thus, with shorter amplitudes in Fz,

Cz and absent in Fpz compared to controls, this supports literature that points MMN as

reflecting automatic processing of acoustic-phonetic input analysis (Aaltonen et al.,

1993; Näätänen, 1995; Pettigrew et al., 2004), related with a low accuracy of

behavioral discrimination of sound change (Ilvonen et al., 2004; Kujala et al., 2001)

and phonological analysis (Dehaene-Lambertz, 1997; Näätänen & Alho, 1997).

Interestingly, our aphasic subject revealed an earlier MMN to CV condition, and

this seems to be related to ERP subcomponents. Keeping in mind that shortly after

stroke she had a Broca’s aphasia, Bird et al. (2003) have indicated that this type of

N2b

N2b N2b

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aphasia may also comprise a deficit in phonological processing. More specifically, the

analysis of the elicited deviant waveform revealed an absence of N2b or perhaps a

fusion with N1 that is also diminished, which resulted in an early MMN compared to

controls. In addition, N1 is suggested to reflect integrative processing of acoustic

features of the incoming stream of speech (Näätänen & Winkler, 1999), but not a

neurological representation of phonemes. Any deviance to this stream will be detected

by automatic attention mechanisms being indexed by N2b (Becker & Reinvang,

2007b; Pritchard et al., 1991), in addition, Gow and Caplan (1996) reported that

phoneme discrimination used to investigate acoustic-phonetic processing always

require close attention. Our results support the findings of Pettigrew et al. (2004, 2005)

in that aphasic subjects may demonstrate deficits in lexical processing at the

attentional level due to a previous impaired phonological analysis. Interestingly, we

observed a reduced N1 in both response to pure-tone and CV similar to Becker &

Reinvang (2012) results, but no similar results concerning N2b reduction even with

both active auditory oddball paradigms. A possible explanation might be the fact that

we are presenting one single case study or N2b reduction to speech stimuli may be

specifically related to anomia because none of the aphasic subjects from Becker &

Reinvang (2012) study presented anomic aphasia type or anomia as a

neuropsychological deficit. If so, N2b could represent the neurobiological substrate for

the activation of phonological representation and categorization of speech elements

with this attentional trigger activation indexed by frontal MMN, but only future studies

with anomic subjects could confirm this hypothesis.

These amplitudes reductions might be related to underlying neuronal damage

sequels, in our case, this damaged probably derived from thalamocortical fibers in the

posterior limb of the internal capsule as revealed from the remaining

hemihypoesthesis.

Hurley et al. (2012) demonstrated a correlation between atrophy in posterior

temporal areas and diminished N400 mismatch potentials as a possible mechanism for

anomia in subjects with primary progressive aphasia. In our case, the lesion was a left-

hemisphere stroke, concerning the left middle cerebral artery known to emerge from

lateral sulcus supplying frontal, temporal and parietal areas. Considering the cell

assembly model theory (for review see: Garagnani et al., 2008; Pettigrew et al., 2004;

192

Pulvermüller, 1996) the perisylvian cortical neurons that process word forms would be

affected or damaged. Therefore, neurons left unaffected by the lesion will reflect an

attenuated MMN response and poor defined ERP components in the average deviant

waveform, mainly N2b. Furthermore, Pulvermüller (1999) has proposed an “ignition

threshold” for the assembly neurons, and the non-activation would be related to lesion

severity. Moreover, the highly reduced N2b in our case might be related with a low

“ignition threshold” resulting in weak internal connections between phonological and

semantic information and subject’s naming difficulties. This seems to be consistent

with new findings on perisylvian language networks (Catani et al., 2005; Wennekers et

al., 2006) and the role of arcuate fasciculus (Catani & Mesulam, 2008) to be discussed

in a future article.

Lastly, we still don’t know what type of neurons or layers generate MMN, although

it seems to follow the vertical functional organization of the neocortex. But we do

know that MMN may reflect damage severity and the recovery of sound

discrimination and the alleviation of aphasia after cortical stroke onset (Ilvonen et al.,

2003). Thus, providing a promising tool for evaluating and following up the recovery

of auditory discrimination in clinical practice (Näätänen, 2003; Näätänen et al., 2007).

Several authors have already pointed MMN as a recovery index, however, this

discussion highlights the importance of using pure-tone and speech stimuli, as well as

the analysis of N1 and N2 components in the average deviant waveform of the

different conditions. Particularly, N2b that seems to indicate the very early initial

differences between speech and non-speech sounds processing and reflects processes

of transient arousal triggered by unattended discrimination processes.

CONCLUSION

In cases of sudden onset brain damage, the cognitive and perceptual deficits are

initially quite severe. In stroke and other brain-injured patients it is important to

determine the damage to neural network involved in sound and speech perception soon

after the damage in order to monitor spontaneous recovery and delineate possible

recommendations for therapy. However, such patients are often unable to cooperate or

to understand instructions. The MMN can be registered in the absence of conscious

193

attention and with no task requirements. From the point of view of clinical research

and applications this is of particular significance, which makes MMN particularly

suitable for studying and monitor aphasic subjects predicting language recovery.

Concerning our present case study and narrative analysis on literature, ERPs

components such as N1, N2b and MMN seem to have highly sensitivity in detecting

acoustic-phonetic processing and phonological analysis deficits in aphasic patients

during acute stage, after spontaneous recovery and even after therapy. Further, these

deficits seemed to be highlighted by speech stimuli paradigm compared to non-speech,

as seen in MMN tone vs. speech results (Table 1).

The evaluation of the effectiveness of training and rehabilitation programs also

highlights the importance to use the MMN as a recovery index, with expected

amplitude increment after therapy sessions. The results of this case study indicate that

even six years post-stroke the neurophysiologic brain activity isn’t fully recovered and

that MMN is a sensitive tool to detect functional brain sequels, mainly to speech

stimuli. Furthermore, it seems that N2b might be related to anomia, thus indexing cell

assemblies disruption and the impaired activation of phonological representation

processes that are the base for this neuropsychological deficit, although further studies

are required. Moreover, researchers and clinicians should consider the use and

comparison of speech and non-speech stimuli always with a previous collected

normative data in their work-set, where the analysis of N1 and N2 components to the

average deviant waveform in the separate conditions, before computing a subtraction

waveform, should not be ignored, thus providing a more reliable and specific

interpretation of results. The analysis of pre-attentive separate components (N1, N2b

and MMN) and a complementary interpretation of results might increase the reliability

and specificity of ERPs measures applied to clinical practice in aphasiology.

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Chapter IV

Methodology

201

Chapter IV describes the aims of this work, the method, and participant’s

recruitment and selection, according to inclusion and exclusion criteria. Moreover, we

will explain the experimental design, that is transversal to case studies and empirical

paper’s within this work. This chapter ends up with Paper V that intends to be a peer-

validation of the experimental procedure for assessing central auditory processing

using AERPs.

Aims of the Work

The aims of the present experimental study were to investigate (describe and

explain) auditory event-related potentials (N1, N2b, and MMN) and their clinical

usefulness (predict) for objective measurement of central auditory processing

(preattentive auditory discrimination, attention allocation and phonological

categorization, and automatic pre-attentive discrimination, perception and echoic

memory, respectively) in neurodevelopmental disorders such as epilepsy and dyslexia.

The specific aims were to:

1. Examine and investigate AERPs as possible endophenotypes or biomarkers

for auditory processing dysfunction due to neuronal systems disorders

(epilepsy, aphasia, and dyslexia);


and MMN) in a group of children with BECTS;

3. Suggest normative values for the development of N1 and N2 components

across the lifespan;


and MMN) in a group of children with developmental dyslexia;

5. Discuss and relate neurophysiopathological mechanisms of language deficits

(developmental dyslexia) explained by anchoring-deficit hypothesis,

phonological defict hypothesis, and RAPT by AERPs results;

6. Discuss an eventual neuropsychophysiological parallel between two school

age neurodevelopmental disorders (BECTS and developmental dyslexia).

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Variables

Independent: BECTS, IGE, developmental dyslexia, aphasia, comorbidity

(ADHD), medication, years of onset, age, and gender.

Dependent: N1, N2b, MMN amplitude and latency, and handedness.

Methodology

Hospital services and recognised clinicians were contacted to collaborate in the

study. That is Serviço de Neuropediatria and Serviço de Neurologia do Hospital de

São João, EPE (for children with BECTS and the IGE participant) and Clínica de

Dislexia Drª. Celeste Silveira (for children with developmental dyslexia). After ethical

approval, previous invitation and information were given to parents by the clinicians

and the principal investigator.

One variable to be taken account was the handedness laterality index from each

participant. Due to scarce literature, we decided to translate, adapt and start the

validation of Edinburgh Handedness Inventory revised to European Portuguese, with

Cohen’s permission (appendix 10). This study was approved by the Ethics Committee

from School of Allied Health Technologies, Polytechnic Institute of Porto (ESTSP-

IPP; appendix 11). The final version can be found in appendix 12. However is still

being validated across Portugal’s regions and islands, gender and age significance

criteria.

Data acquisition took place at Laboratory of Neuropsychophysiology (Faculty

of Psychology and Educational Sciences, University of Porto). For inclusion criteria

regarding hearing loss, when required or suspected, participants were evaluated at

Laboratory of Audiology (School of Allied Health Technologies, Polytechnic Institute

of Porto)

The experimental procedures followed the tenets of the Declaration of Helsinki.

It was approved by the local Ethics Committee from Hospital São João (CES –

Comissão de Ética para a Saúde; appendix 13) and parents gave informed consent

concerning their children’s participation in the study (appendix 14). Adult participants

also gave their informed consent after ethical clearances.

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Participants

Participants were recruited from Serviço de Neuropediatria and Serviço de

Neurologia do Hospital de São João, EPE and from Clínica de Dislexia Drª.Celeste

Silveira (appendix 15; Papers IV and VII). Healthy participants for the control group

were invited by colleagues from the lab. Based on parental report, all participants were

enrolled in mainstream academic programs with successful achievement.

Twenty-four children diagnosed with BECTS, 12 children with developmental

dyslexia and 17 controls were invited (appendix 16), and a total of 26 children who

complied with the inclusion criteria accepted to take part in the study (for details, see

Table 2 in Chapter V, The Results section): eight with BECTS (age, M = 9, SD =

2.10), seven with developmental dyslexia (age, M = 11, SD = 3.31), and 11 controls

(age, M = 12, SD = 3.14).

All participants had the same inclusion criteria: normal hearing and vision,

Portuguese native speakers, no ear malformation, no motor disorders, and no

neurological (except epilepsy, aphasia or dyslexia) or cognitive deficits. In addition, all

participants from control group had no ongoing medication that could affect the central

or peripheral nervous system. Sign informed consent (parents authorization). The

diagnosis of epilepsy (BECTS and IGE) followed the criteria of the Commission on

Classification and Terminology of the International League Against Epilepsy (1989),

by two neuropaediatric clinicians. The diagnosis of developmental dyslexia followed

the criteria (Critchley, 1970): specific problems learning to read and spell, despite

adequate instruction, intelligence, and socio-cultural opportunity. The diagnosis was

made by a multidisciplinary team, composed by a teacher specialized in dyslexia, a

psychologist and a paediatrician. Following Sim-Sim’s (2004) recommendation, the

diagnosis was supported by the evaluation of: phonological awareness, intelligence

quotient (Raven´s Progressive Matrices, portuguese version by Simões, 2000), reading

velocity and reading comprehension (Sucena & Castro, 2010, 2012; Viana & Ribeiro,

2010), writing (dysorthography), and Conners’ parents and teacher rating scales for

assessing ADHD (Rodrigues, 2005, 2006). At the time of the study, all were sufficiently

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compensated for the disorder to enable them to achieve normal academic skills in

mainstream programs, however still with clinical support.

Exclusion criteria: history of traumatic brain injury, otologic surgery in the last

12 months. Inclusion and exclusion criteria were verified with a brief anamnesis,

parents report and individual clinical process consultation during team meeting. None

of the invited participants met exclusion criteria

Experimental Design and Procedures

The main goal in a study design is to test specific hypotheses. Regarding ERPs

design is to manipulate the subject’s experience and behaviour in some way that is

likely to produce a functionally specific neurophysiological response.

We are able to manipulate stimulus type and properties, stimulus timing and

subject instructions. In the event-related design, the oddball paradigm for example,

allows different trials or stimuli to be presented in arbitrary sequences, real world

testing, eliminate predictability of block designs (e.g., expectation), allows to look at

novelty and priming, and look at temporal dynamics of response. This is of particular

importance; with this method we pretend the stability of extended patterns of brain

activation. However, some limitations should be kept in mind: the low statistical

power (small signal change) and more complex design and analysis (e.g., timing and

baseline issues).

Some considerations must be stated regarding ERPs design study. The electrical

activity occurring on the scalp consists of changing electrical voltages that are caused

by action potentials summed over large numbers of neurons, synapses, neuronal

pathways and systems. There are two non-invasive techniques for this electrical brain

activity, the EEG and ERPs, both in time course. The EEG allows measuring the

spontaneous electrical brain activity and the ERPs are derived by averaging EEG

changes over sensory or cognitive events. The averaging process attenuates the

spontaneous activity in the EEG and results in electrical potential changes related to

specific events (Eysenck & Keane 2003).

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In auditory novelty processing experiments, the experimental paradigm that

seems the most feasible is the oddball paradigm. The oddball paradigm, as a signal-

detection paradigm was first described by Ritter and Vaughan (1969). In the auditory

modality, it was first used in 1975 by Squires, Squires and Hillyard at the University of

California, San Diego, USA (Squires, Squires, & Hillyard, 1975). In this paradigm,

physically deviant stimuli (silence included) are randomly presented among repetitive

streams of homogenous sounds (standard stimuli; Donchin, 1981; Jääskeläinen, 2012;

Näätänen, 1975; Näätänen et al., 1978).

With one session, we were able collect data for two experiments. Experiment 1

consisted in the presentation of a block of pure-tone stimuli (std: 1000Hz; dev:

1100Hz; 100ms duration; created in Audacity software v2.0.0) with 300 trials.

Experiment 2 consisted in the presentation of a block of consonant-vowel (CV

digitalized rate of 44100Hz with 175ms duration, spoken by a male Portuguese voice;

std: [ba] 118 Hz (F0); dev: [pa] 127 Hz (F0), recorded with Nuendo software v4.3.0)

with 300 trials.

In both experiments (blocks of 300 trials each) standard stimuli comprised 80%

of all trials (240 trials), while deviant stimuli comprised 20% (60 trials).With a

stimulus onset asynchrony (SOA) of 800 ms to a proximal sound level of 75 dB SPL

confirmed with a sound level meter. A design scheme of the stimuli presentation and

experiments can be seen in Figure 9.

Stimuli were binaurally presented using Presentation® software

(Neurobehavioral Systems, Inc.) via closed headphones with an approximately level of

75 dB SPL, while the participants where comfortably seated in an armchair and

instructed to keep alert with eyes-open, actively listen to the auditory stimuli and

focused on a small cross in the center of a computer screen during recording. Each

individual data collection had an average time of 40 to 50 minutes.

After individual data acquisition, all young participants received a Diploma

(appendix 17) and invited to snack at the faculty bar.

Before each individual data acquisition, the first experiment to start was

randomly selected.

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Experiment 1 Experiment 2

300 trials 300 trials

80% standard pure-tones (1000 Hz) 80% standard consonant-vowel (/ba/)

20% deviant pure-tones (1100 Hz) 20% deviant consonant-vowel (/pa/)

100 ms duration 175 ms duration

Binaurally ~75 dB SPL Binaurally ~75 dB SPL

Figure 9. Design scheme of stimuli presentation for both experiments.

The EEG montage was according to the 10-20 electrode placement

international system (Jasper, 1958). Recordings were obtained from the following cup-

shaped silver chloride (Ag-AgCl) reversible electrodes: Cz, Fz, Fpz, M1, M2 and Oz

(ground), referenced to averaged ear lobes (A1 and A2; Figure 10) in order to reduce

the likelihood of artificially inflating activity in one hemisphere, in other words a non-

lateralized reference (Miller, Lutzenberger, & Elbert, 1991). We decided for a

referential montage as this allows a truer picture of the relative voltage amplitudes at

each electrode (American Electroencephalographic Society, 1986; Sinclair, Gasper, &

Blum, 2007), which seemed more adequate to our goals. The electrodes used were

reversible (nonpolarized), as these are preferred for common neurophysiological

applications because polarization is avoided as the chloride ion is common to both the

electrode and the electrolyte (Sinclair, Gasper, & Blum, 2007).

An electrode was attached above right eye to monitor the electrooculogram

(EOG; Figure 10). The selected position for ground electrode was the most

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100 Hz in frequency and most cognitive neuroscience experiments use a low-pass

cutoff frequency, as we were interested on frequencies below 30 Hz (or below 60 Hz if

gamma activity is investigated; Pizzagalli, 2007) and also on early sensory responses

of high frequency, which require a high sampling rate in order to achieve a good

temporal precision (Luck, 2005a). In addition, according to the Nyquist Theorem, with

this four fold greater sampling rate we prevented the introduction of spurious and

bogus low frequency components and distortion (aliasing) into the signal (Dumermuth

& Molinari, 1987; Luck, 2005a).

Preprocessing included band-pass filtering [0.3-30] Hz, entire sweep linear

detrending and a baseline correction of individual epochs (200 ms). The baseline

window was also used to inspect the overall noise level of recordings and increase the

accuracy for analysing the different waveforms (Luck, 2005b).

The first 10 sweeps of each epoch file were excluded from the averaging

process to reduce ERP variation associated with the start of the stimulation sequence

(Pekkonen, Rinne, & Näätänen, 1995; Pettigrew et al., 2005).

The MMN was determined from the Fpz, Fz, Cz, M1 and M2 electrodes, by

computing difference waves, i.e. by subtracting the average standard-stimulus

response from the average deviant-stimulus response for each electrode and subject

(Duncan et al., 2009). The N1 and N2b were identified as the two largest negative

peaks occurring between 100 and 300 ms.

The analysis and extraction of ERPs quantification followed the procedures

seen in Figure 11. We analysed peak latency in all Papers, base-to-peak (Papers IV and

VI) and peak-to-peak (Papers I and VII). The latter aimed to increase precision in

results interpretation.

209

Figura 21. Schematic representation of an ERP waveform, indicating different procedures for component quantification and measure after stimulus onset: peak latency, peak-to-peak, base-to-peak and area

(Fabiani, Gratton, & Federmeier, 2007).

Statistical analyses were performed using IBM SPSS v.22 for all papers (IBM,

2013). For Paper VII results’ analysis (Chapter V), mean amplitude and latency values

of each component (N1, N2b, MMN) were computed in an two-way repeated

measures ANOVA with electrode (Fpz, Fz, Cz) and stimuli (pure-tone and consonant-

vowel) as within-subject factors, and the group (control, epilepsy, dyslexia) as a

between-subjects factor. Separate tests for group homogeneity were also applied for

gender (Fisher’s exact test), handedness and age (Kruskal-Wallis one-way analysis of

variance).

An alpha level of 0.05 was used. Because we have three levels of a repeated

measure factor, sphericity was evaluated by Mauchly’s test (Shaffer, 1995). Sphericity

was obtained to all measures, thus we can assume that the variances of the differences

between all combinations of the groups are equal. In addition, due to small sample

sizes, Bonferroni correction was performed in order to control and reduce type I errors

when performing multiple hypotheses tests (Maroco, 2007).

For case studies, statistically significant results were obtained with

nonparametric tests (Wilcoxon – 2 independent samples), for α = 0.1 (Paper VI).

Cohen’s effect sizes were obtained with nonparametric Mann-Whitney test Z value

(Papers I and IV).

210

The peer-review validation and detailed procedures for our experimental design

can be seen in Paper V. Some minor aspects have been improved since, but the main

purposed of this experimental design remains the same. Our main goal with this article

was leeting know the scientific and clinical colleagues our method and hypothesis to

assess central auditory processing in childhood. With procedures that can easily be

adapted to hospital practice.

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Paper V

Mismatch Negativity in Temporal Lobe Epilepsy in Childhood: a proposed

paradigm for testing central auditory processing

David Toméa,b, Pedro Moreiraa,c, João Marques-Teixeiraa, Fernando Barbosaa, Satu Jääskeläinend


University of Porto, Portugal bDepartment of Audiology, School of Allied Health Sciences, Polytechnic Institute of Porto,

4400-330 V.N. Gaia, Portugal cSchool of Criminology, Faculty of Law, University of Porto, Portugal

dDepartment of Clinical Neurophysiology, University of Turku, Finland

Tomé D, Moreira P, Marques-Teixeira J, Barbosa F, Jääskeläinen S. Mismatch Negativity

in Temporal Lobe Epilepsy in Childhood: a proposed paradigm for testing central auditory

processing. JHS, 2013; 3(2): 9-15.

Journal of Hearing Science ISSN: 2083-389X


212

Abstract

Background: Temporal Lobe Epilepsy (TLE) is a neurologic disorder that affects

directly cortical areas responsible for auditory processing, resulting in abnormalities

which can be properly assessed by investigating event-related potentials (ERP), due to

the high temporal resolution of this technique. However, little is known concerning

dysfunction in initial sensory memory encoding in TLE and possible correlations

between EEG, linguistic deficits and seizures. Mismatch negativity (MMN) is an ERP

component that reflects pre-attentive sensory memory function, elicited in the absence

of attention or behavioural task, indexing neuronal auditory discrimination and

perception accuracy.

Methodological proposal: In this article, we propose a MMN protocol and paradigm

for clinical application and future research with the hypothesis that children with TLE

may have abnormal MMN for speech and non-speech stimuli, which will emerge in a

passive auditory oddball paradigm, and that those abnormalities might be associated

with epileptic seizures location and frequency.

Expected results: the suggested protocol, could contribute to a better understanding of

neuropsychophysiologic meaning and representation of MMN, extending this notion to

involve the central sound representation of the brain decreased in TLE for speech and

non-speech stimuli.

Discussion: the surplus value of MMN lies on the differences across electrode sites to

speech and non-speech stimuli. TLE in childhood could be a good model for

topographic and functional study of auditory processing and its neurodevelopment,

highlighting MMN as a possible clinical tool for prognosis, evaluation, follow-up and

rehabilitation or recovery index.

Keywords: Temporal Lobe Epilepsy (TLE); Mismatch negativity (MMN); childhood;

auditory processing; model

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EL MMN EN LA EPILEPSIA DEL LÓBULO TEMPORAL EN NIÑOS. EL

PARADIGMA PROPUESTO DEL EXAMEN DEL PROCESAMIENTO

AUDITIVO CENTRAL

Introducción: La epilepsia del lóbulo temporal (TLE) es una enfermedad neurológica,

que afecta directamente a las áreas de la corteza cerebral implicadas en el

procesamiento auditivo. Los cambios en la actividad de la corteza, relacionados con la

epilepsia, pueden ser evaluados a través del método de potenciales evocados (ERP),

que tiene una alta resolución temporal. Poco se sabe, sin embargo, sobre la epilepsia

del lóbulo temporal en cuanto a la disfuncción de la codificación en la memoria a corto

plazo o en cuanto a las posibles correlaciones entre EEG, déficit verbales y

convulsiones. La onda (potencial) de la incompatibilidade (MMN) es un componente

de ERP – que aparece en respuesta a los estímulos raros presentados en el contexto de

estímulos frecuentes e idénticos – que refleja los procesos inconscientes de

diferenciación de sonidos.

Hipótesis: Proponemos la aplicación del protocolo de la onda de incompatibilidad

MMN para futuros ensayos clínicos, basándonos en la tesis de que en niños con la

epilepsia del lóbulo lateral puede aparecer una onda incorrecta de la incompatibilidade

para los estímulos verbales y no verbales MMN puede producirse en el modelo

auditivo pasivo del paradigma oddball, y los cambios en los parámetros MMN pueden

ser relacionados con la localización y frecuencia de convulsiones.

Significado: El protocolo propuesto puede contribuir a una mejor comprensión de las

bases neuropsicofisiológicas de MMN. Sugerimos que en la epilepsia del lóbulo

temporal, la representación de sonidos en la corteza auditiva puede ser reducida para el

habla y para los estímulos no verbales.

Discusión: La onda de la incompatibilidad MMN refleja la diferencia entre los

estímulos verbales y no verbales, que se puede observar en diferentes electrodos. La

epilepsia del lóbulo temporal en niños puede ser un buen modelo para el estudio de la

representación cortical del procesamiento auditivo y de los cambios, a los que está

sujeta en el cerebro en desarrollo, y el registro de la onda de incompatibilidad MMN

puede ser útil en la clínica en el proceso del diagnóstico y tratameinto de la epilepsia

del lóbulo temporal.

214

ПОТЕНЦИАЛ НЕСООТВЕТСТВИЯ В ДЕТСКОЙ ВИСОЧНОЙ

ЭПИЛЕПСИИ: ПРЕДЛАГАЕМАЯ ПАРАДИГМА ИССЛЕДОВАНИЯ

ЦЕНТРАЛЬНОЙ СЛУХОВОЙ ОБРАБОТКИ

Изложение

Введение: Височная эпилепсия (TLE) - это неврологическое заболевание,

которое непосредственно влияет на участки мозговой коры, задействованные в

слуховой обработке. Изменения в активности коры, связанные с эпилепсией,

можно оценить, используя метод вызванных потенциалов (ERP), который имеет

высокое временное разрешение. Однако мало что известно о височной

эпилепсии в области дисфункции кодирования в кратковременной памяти или

возможных взаимосвязей между ЭЭГ, речевыми дефицитами и эпилептическими

приступами. Волна (потенциал) несоответствия (MMN) – это составная часть

ERP – проявляющаяся в виде реакции на редкие импульсы, презентированные на

фоне частых, идентичных импульсов – отражающая предвниматильные

процессы дифференциации звуков.

Гипотеза: Предлагаем использовать протокол волны несоответствия MMN в

будущих клинических исследованиях, базируя на предположении, что у детей с

височной эпилепсией может появиться неправильная волна несоответствия для

вербальных и невербальных импульсов MMN. Она может проявиться в

пассивной модели слуховой парадигмы oddball, а изменения в параметрах MMN

могут быть связаны с размещением и частотой эпилептических приступов.

Значение: Указанный протокол может привести к лучшему пониманию

нейропсихофизиологических оснований MMN. Мы предполагаем, что в

височной эпилепсии репрезентация звуков в слуховой коре может быть

пониженной для речи и невербальных импульсов.

Дискуссия: Волна несоответствия MMN отражает разницу между вербальными

и невербальными импульсами, наблюдающуюся на отдельных электродах.

Височная эпилепсия у детей может быть хорошей моделью ислледования

корковой репрезентации слуховой обработки и изменений, которым она

подвергается в развивающемся мозгу, а регистрация волны несоответствия

MMN может быть полезна в клинике в процессе диагностики и терапии

височной эпилепсии.

215

POTENCJAŁ NIEZGODNOŚCI W DZIECIĘCEJ PADACZCE

SKRONIOWEJ: PROPONOWANY PARADYGMAT BADANIA

CENTRALNEGO PRZETWARZANIA SŁUCHOWEGO

Streszczenie

Wstęp: Padaczka skroniowa (TLE) jest chorobą neurologiczną, która bezpooerednio

wpływa na obszary kory mózgowej zaangażowane w przetwarzanie słuchowe. Zmiany

w aktywności kory związane z padaczką można oceniaæ przy użyciu metody

potencjałów wywołanych (ERP), która ma wysoką rozdzielczość czasową. Niewiele

jednak wiadomo o padaczce skroniowej w zakresie dysfunkcji kodowania w pamięci

krótkotrwałej czy możliwych korelacji pomiędzy EEG, deficytami językowymi i

napadami padaczkowymi. Fala (potencjał) niezgodności (MMN) jest składową ERP –

pojawiającą się w odpowiedzi na bodźce rzadkie prezentowane na tle częstych,

identycznych bodźców – odzwierciedlającą przeduwagowe procesy różnicowania

dźwięków.

Hipoteza: Proponujemy zastosowanie protokołu fali niezgodności MMN do

przyszłych badań klinicznych opierając się na założeniu, że u dzieci z padaczką

skroniową może pojawić się nieprawidłowa fala niezgodności dla bodźców

werbalnych i nie niewerbalnych MMN. Może wystąpić w biernym modelu

słuchowego paradygmatu oddball, a zmiany w parametrach MMN mogą być związane

z lokalizacją i częstotliwością napadów padaczkowych.

Znaczenie: Zasugerowany protokół może przyczynić się do lepszego zrozumienia

neuropsychofizjologicznych podstaw MMN. Sugerujemy, że w padaczce skroniowej

reprezentacja dźwięków w korze słuchowej może być zmniejszona dla mowy i

bodźców niejęzykowych.

Dyskusja: Fala niezgodności MMN odzwierciedla różnicę pomiędzy bodźcami

językowymi i niejęzykowymi obserwowaną na poszczególnych elektrodach. Padaczka

skroniowa u dzieci może być dobrym modelem badania korowej reprezentacji

przetwarzania słuchowego i zmian, jakim ona podlega w rozwijającym się mózgu, a

rejestracja fali niezgodności MMN może być przydatna w klinice w procesie

diagnostyki i terapii padaczki skroniowej.

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Background

Temporal lobe epilepsy (TLE) is the most frequent form of partial epilepsy in

adults, and hippocampal sclerosis is the most common neuropathologic finding in

patients with medically refractory TLE [1,2] resulting in abnormal activity in a group

of neurons that may have significant impact on the normal cognitive processes and

behavior. The TLE in childhood may be cryptogenic or have several etiologies, being

the most frequent the mesial temporal sclerosis, cortical dysplasia, brain injuries,

extrahyppocampal lesions and/or hyppocampal sclerosis, always with progression and

expansion to the temporal cortex [3]. Regardless the neuronal origin of epileptic focus,

neuropsychological deficits are common among children and adults with TLE, being

more serious incidents as higher the frequency of the seizures and the time that

linger[4-6].

It has been repeatedly shown that both short-term and long-term memories are

impaired in TLE [7-8]. However, little is known concerning dysfunction in initial

sensory memory encoding in TLE and possible correlations between EEG, linguistic

deficits and seizures. TLE in childhood is a neurological disorder that affects directly

the cortical areas of central auditory nervous system. Thus, seems to be a good model

for topographic and functional study of auditory processing and its neurodevelopment

processes. The use of event-related potentials (ERPs) techniques, would contribute to a

better understanding of the learning difficulties that children with this disorder have

and the paradoxical processes of neuronal plasticity interfered by epileptogenesis [9].

The mismatch negativity (MMN) and its magnetic equivalent (MMNm) currently

provide an objective measure of auditory perception and discrimination based on the

presence of short-term memory (sensory memory) and echoic memory trace,

representing a repetitive aspect of the ongoing stimulation before a deviant event elicit

it, fading within 5-10 ms [10-13]. It can be registered in the absence of attention and

with no task requirements, which makes it particularly suitable for studying different

clinical populations, newborns and infants [14]. Recently, several studies have pointed

the MNN as a powerful tool to also index cognitive and functional decline, central

auditory abnormalities and deficient N-methyl-D-aspartate (NMDA) receptor function

[13,15-18]. The MMN is a fronto-centrally (Fpz, Fz and Cz) negative component of

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the auditory event-related potential (ERP) and a positive component in mastoids (M1

and M2) usually peaking at 100–250 ms from stimulus onset, although its mainly

generators are the bilateral supratemporal cortices with contributions of the frontal

lobes, right parietal lobe, thalamus and hippocampus [12,13,15].

Several authors have studied the MMN in epilepsy. In benign childhood epilepsy

the MMN were longer or absent for speech sounds compared to controls, but for pure-

tone stimuli no differences between groups were found [19]. More recently, Miyajima

et al. [20] found in adult TLE patients an enhanced frontal MMN, and reduced at

mastoids, to pure-tone frequency change, suggesting a frontal lobe hyperexcitability to

compensate temporal lobe dysfunction. In addition, Honbolygó et al. [21] obtained a

MMN for deviant phonemes but not for deviant prosody in Landau-Kleffner

syndrome. This suggests that MMN results (topography, amplitude and latency) are

not equal to all types of epilepsy, possibly related to seizures type, location and

dysfunction of different MMN generators. For example, frontal lobe epilepsy with

focal seizures may not affect MMN at mastoids. Thus the TLE, due to its focal

seizures, is the type of epilepsy that can enable us to better understand the mechanisms

underlying MMN elicitation and achieve a first reliable electrophysiological index in

these patients for central auditory processing of speech and non-speech. On the top of

that, a possible objective measure of short auditory memory, auditory discrimination

and auditory involuntary attention switch, related to seizure location, prognosis and

rehabilitation monitoring. The existing literature provides discrepant accounts of how

MMN is affected in children with TLE. Further, different results to speech and non-

speech stimuli are being obtained. This might suggest a different mechanism for the

auditory processing of speech and non-speech.

Keeping the above mentioned in mind, we propose a protocol for an ERP study

design in which we hypothesize that the pattern of MMN response to individual word

and pure-tone deviants, regarding its memory trace activated in the brain, may offer an

opportunity to investigate neuronal processing of language in non-attention demanding

and task-free fashion, particularly suitable for neurological paediatric population, such

as children with TLE. However, further work is required to optimise the paradigm

before it can be of clinical value, so we invite all researchers and clinicians in this field

to test it in other types of epilepsy and clinical populations and share results.

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Methodological proposal: a suggestion of method and procedures

Two groups must be formed, the epilepsy/experimental group (EG) and the control

(CG), matching characteristics such as age, gender, education, maternal language and

handwriting (if applicable). EG diagnosis based on a combination of clinical

symptoms, EEG, and structural/functional imaging data [22]. Other relevant

information might be considered, such as: duration of epilepsy (months/years), age of

onset, side of epileptic focus (if possible), seizure status, number and dosage of

antiepileptic drugs (AED).

Exclusion criteria for both groups should include hearing loss, age above 10 years

old, comorbid psychiatric disease, and hearing or vision problems at the time of the

experiment. Additional exclusion criteria for the CG should include a history of

developmental disorders, history of traumatic brain injury with any known cognitive

consequences or loss of consciousness, history of convulsions other than simple febrile

seizures, and psychiatric disease or epileptic disorder in first-degree relatives.

Parents should sign consent forms, after being informed of the nature and

objective of the experiment. The selected children will be fitted with a channel cap

containing tin electrodes according to the International 10-20 system; EEG is recorded

using a bio-amplifier recording device allowing a sampling rate above 256 Hz for each

channel and a recording bandwidth between 0.05 Hz and 100 Hz. Electrodes

referenced to averaged ear lobes. Two electrodes should be placed above the left eye

and below the right eye to monitor the electrooculogram (EOG), sweeps with

amplitudes exceeding ±70 μV due to blinks or eye/face movements must be rejected

before averaging. Impedance between the electrodes and skin should not exceed 5 kΩ.

Post hoc analysis may include band-pass filtering (0.3–30 Hz), entire sweep linear

detrending and a baseline correction (200 ms).

Behavioral pure-tone audiograms (250 to 8000 Hz), speech reception threshold

(SRT) and monosyllabic discrimination should be obtained to detect hearing loss,

using a clinical audiometer (we use an Amplaid A177). All listeners must have hearing

thresholds bilaterally of 20 dB HL or better [23]. Additionally, otoscopy and acoustic

immittance testing might be performed prior to each session in order to rule out

219

changing or abnormal middle-ear status in pediatric populations. All listeners must

have a normal tympanogram (admittance curve at 226 Hz with a single peak between -

100 and +50 daPa) and a present ipsilateral acoustic reflex (500, 1000, 2000 and 4000

Hz, 90 dB HL) in the test ear.

The most widely applied stimuli presentation, also with the most replicable results

is a binaurally auditory oddball stimulation. Subjects should be presented with

sequences of three blocks of tones and three blocks of speech-stimuli, each containing

a stimulus onset asynchrony (SOA) between 500 and 1000 ms. In the tone blocks, the

standard stimulus (1000 Hz, 100ms, rise and fall time 10ms) is replaced by a

frequency deviant (1100 Hz, 100ms). Speech-stimuli blocks consist of digitalized (rate

44100 Hz) consonant-vowel syllables with 175ms duration spoken by a male or female

voice; the standard phoneme is /ba/ and the deviant /pa/. These phonemes were

selected for this protocol because they differ in place of articulation and thus differ in

the frequency domain, but were performed by a national citizen, the use of a pure-tone

frequency deviant is far the most used and validated stimuli [24-27]. In all single

blocks, standard stimuli comprise 80% of all trials, while deviant stimuli comprise

20%. During the recording, subjects should be comfortably seated in an armchair

watching a silent DVD or instructed to keep alert with eyes-open and focused on a

small cross in the center of a computer screen. Additionally, you should ask to stay

calm, avoid any eye/face movement and to ignore the auditory stimuli in order to keep

an alert state and reduce attention to experimental stimuli.

Discussion

A large number of converging MMN studies support the feasibility of using the

MMN as a tool in the study of deficient auditory perception in children. Particularly in

clinical pediatric groups such as children with dyslexia, specific language impairment,

epilepsy, cochlear implant candidates [13-15,28-32], dysphasia and specific language

impairment [33-35], but also in any uncooperative patients to behavioral measures [36-

40]. Several authors have studied MMN elicitation in adults with TLE. Among the

different abnormalities found, they all agree on the mechanism dysfunction underlying

the MMN, suggesting electrophysiological evidence to concentration and short

220

memory difficulties observed in TLE patients [19-21,41-43]. However, it is well

known that AEDs and benzodiazepines, for example, can have an effect on motor

reaction times, on latencies and a dampening effect on amplitudes in ERP studies

[15,20,44]. Thus, we believe in achievement of more reliable results in pediatric

population, due to a less pharmacological affect. In further studies, researchers and

clinicians might consider the medication and individual doses of the patients tested.

The ERP may be a powerful tool to reveal and detect clear cortical abnormalities

in TLE patients that have not been well characterized previously by conventional EEG,

RMN or PET, the MMN component seems particularly interesting to this purpose.

The expected results with this protocol might reveal abnormal MMN for speech and

non-speech stimuli at temporal and at frontocentral sites in TLE children relative to

controls. These results could lead us to new findings and discussions on the specific

neuronal mechanisms underlying MMN generation, providing evidence and

knowledge to the enlightenment of the theories that currently explain MMN, such as

memory-based model, predictive model and adaptation model but also for a better

understanding of epileptogenesis neuronal process [45-49]. Language and handedness

are related to hemispheric dominance in most cases, if a developmental consequence

could be established between seizure side and language deficits, clinicians would be

able to prescript a better treatment and rehabilitation sessions of neurophysiologic

deficits.

According to Miyajima et al. (2011) TLE in adults revealed an enhanced frontal

MMN and decreased in mastoids, suggesting that the MMN might indicate cortical

regions of hyperexcitability that compensate epileptic neurons dysfunction in temporal

lobes [13,20]. Since speech and non-speech have different underlying mechanisms,

differences between MMN elicitation with speech and non-speech stimuli within the

same patient might indicate which mechanism or MMN generators are affected and

make possible to choose the best rehabilitation program (speech vs. non-speech

processing, memory and discrimination). For example, if we compare Miyajima et al.

(2011) and Hara et al. (2012) results, the temporal lobe MMN generators appear to be

more involved when MMN is elicited by vowel changes than when it is elicited by

pure-tone frequency changes. TLE patients showed significantly reduced amplitudes at

mastoid sites to speech sounds but no significant changes to pure-tone sounds. On the

221

other hand, TLE patients showed an enhanced MMN at frontocentral sites to pure-tone

sounds but no significant changes to speech sounds [20,50].

These results support the view that the MMN is generated by separable sources in

the frontal and temporal lobes, and that these sources are differentially affected by

TLE, also suggesting that speech production requires a stable sensory memory

reference in temporal cortices [51,52]. Furthermore, if differences within the TLE

group are obtained, there may be related to seizure frequency, duration of epilepsy,

side of epileptic focus, age of onset and seizure status. Regarding temporal lobe

generators and seizure frequency, lower and later the MMN to speech sounds worst the

prognosis. On the other hand, the MMN can be useful to monitoring the seizures

remission and language rehabilitation sessions similar to the amazing results in aphasic

patients, few follow-up studies have revealed a correlation between MMN amplitude

and progressive improvement in speech-comprehension tests from 10 days to 6 months

after stroke [13,37-39,53-55].

The Hypothesis

The existing literature provides discrepant accounts of how MMN is affected in

children with TLE. Regarding published results of MMN applied to dyslexia and

specific language impairment, although similar language and memory deficits may be

present in TLE, different results in MMN elicitation to speech and non-speech stimuli

are being obtained. This might suggest a different mechanism for the auditory

processing of speech and non-speech but also the underlying neurophysiologic

differences between disorders.

We hypothesize that children with TLE may have abnormal MMN amplitude,

morphology and latency for speech and non-speech stimuli across electrode locations

and those abnormalities may be associate with epileptic seizures location and

frequency. A secondary objective is to understand how compromise hemispheric

specialization for speech and non-speech stimuli in TLE in childhood is.

According to model of central auditory processing proposed by Näätänen in 1990,

illustrating attention and automaticity in auditory processing, the expected results

222

could contribute to a better understanding of neuropsychophysiologic meaning and

representation of MMN, extending this notion to involve central sound processing,

thus linking the sound perception and sensory memory tightly together

[11,12,15,45,56]. It also bears noting that as a possible clinical non-invasive tool,

better for pediatric population, with specific paradigms, MMN could be of great asset

and an electrophysiological indicator of neuropsychological aspects of auditory and

language processing, namely attention and sensory memory. Further, a lot of work is

still to be done, but maybe in a near future we will be able to apply the same MMN

index to different clinical populations and thus becoming a reliable clinical tool.

Acknowledgements

We appreciate the advice and expertise of Dr. Victor Osey-Lah (Portsmouth

Hospital/NHS).


There are not any financial, relationship and organizational conflict of interests that

may bias any of the authors in the establishment of the hypotheses discussed in this

article.

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Chapter V

Results

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This chapter describes the results of the main empirical study (Paper VII).

Detailed statistical inference is presented, has a background for Discussion section in

Chapter VI. Participant’s clinical characteristics, medication and outcome are

summarized in Table 2. Amplitude and latency values of each component were

computed in a two-way repeated measures ANOVA design with electrode (Fpz, Fz,

Cz) and stimuli (pure-tone and consonant-vowel) as within-subject factors, and the

group (control, epilepsy, and dyslexia) as a between-subjects factor.

Grand average deviant waveforms and topographic voltage maps across time

for both pure-tone and CV stimuli are presented in order to illustrate the most relevant

findings.

The Results

The main empirical study included a final sample of twenty-six participants: 8

with BECTS (age, M = 9, SD = 2.10), 7 with developmental dyslexia (age, M = 11, SD

= 3.31), and 11 controls (age, M = 12, SD = 3.14). All Portuguese native speakers,

with normal hearing and vision, no ear malformation, and no neurological or mental

deficits. Children from BECTS were seizure free for the last three months and no

history of language regression with the onset of seizures. Based on parental and

medical report, all participants were enrolled in mainstream academic programs. The

detailed characterization of participant groups is presented in Table 2.

232

Table 2. Clinical characteristics, medications and outcome of each participant group.

Control (n=11) BECTS (n=8) Dyslexia (n=7)

Age (mean/SD) 12.1 (3.14) 9.88 (2.10) 10.6 (3.31)

Handedness % índex (mean/SD)

76.7 (74.3) 3 left handed

80.0 (56.9) 1 left handed 70.0 (59.8)

Gender M (7) / F (4) M (7) / F (1) M (6) / F (1)

Medication None CBZ (18 mg/kg/day) (1) VPA (20 mg/kg/day) (3) MPH HCL (18mg/day) (1)

MPH HCL: 45 mg/day (1) 27 mg/day (2) 18 mg/day (1)

Academic skills Excellent (3) Good (5) Regular (3)

Excellent (2) Good (5) Slight learning difficulties (1)

Good (1) Regular (2) Learning difficulties (4)

Systemic disease No CPT II deficiency (1) No

M, male; F, female; VPA, valproic acid; CBZ, carbamazepine; CPT, carnitine palmitoyltransferase; MPH HCL, methylphenidate hydrochloride; BECTS: benign epilepsy with centro-temporal spikes.

Statistical analysis revealed homogeneity between groups for gender (Fisher’s

exact test bilaterally = 0.505, 50 > 20%, 3 < 5 cells), age (H = 0.287, p > .05) and

handedness (H = 0.768, p > .05).

The mean peak-to-peak amplitude and peak latencies of the N1, N2 and MMN

wave from Fpz, Fz and Cz, for the BECTS, dyslexia and the comparison/control group

to pure-tone and speech (consonant-vowel) paradigms are presented in Table 3.

233

Table 3. Mean peak-to-peak amplitude and peak latencies of the N1, N2 and MMN wave in Fpz, Fz and Cz, for the BECTS, dyslexia and the comparison/control group to pure-tone and speech (consonant-vowel) paradigms.

Control

Mean (SD)

BECTS

Mean (SD)

Dyslexia

Mean (SD)

Pure-tone


N1

Fpz -4.20 (2.02) / 126 (20.5) -3.40 (2.53) / 123 (17.7) -2.37 (0.84) / 127 (15.5)

Fz -7.85 (3.69) / 122 (9.2) -6.63 (4.59) / 135 (10.2) -5.40 (3.58) / 136 (33.2)

Cz -5.94 (3.65) / 116 (18.6) -5.21 (1.98) / 135 (17.7) -3.40 (1.41) / 121 (27.7)

Fpz -4.14 (2.31) / 243 (30.7) -5.70 (4.19) / 266 (17.7) -5.33 (2.99) / 270 (37.8)

N2 Fz -8.62 (4.15) / 239 (25.8) -10.0 (5.33) / 274 (35.6) -11.3 (8.38)/ 264 (44.0)

Cz -8.57 (5.13) / 253 (34.0) -9.97 (6.94) / 289 (28.2) -8.09 (6.24) / 261 (55.1)

Fpz -2.83 (1.23) / 196 (48.9) -3.07 (2.21) / 229 (39.3) -2.63 (1.06) / 239 (39.6)

MMN Fz -4.47 (1.44) / 193 (53.2) -3.10 (1.13) / 217 (39.1) -6.45 (3.49) / 217 (41.7)

Cz -4.86 (2.27) / 192 (41.3) -3.11 (1.30) / 214 (42.7) -6.24 (3.99) / 220 (47.1)

Speech (CV)


Fpz -3.36 (2.75) / 134 (17.9) -3.27 (1.15) / 146 (35.1) -1.32 (1.04) / 135 (33.9)

N1 Fz -5.82 (2.45) / 138 (22.6) -5.88 (2.71) / 140 (29.7) -2.57 (2.16) / 128 (29.1)

Cz -4.98 (2.39) / 134 (21.1) -5.33 (1.96) / 141 (18.5) -2.75 (2.44) / 129 (14.9)

Fpz -3.91 (1.60) / 266 (24.3) -3.80 (1.81) / 249 (33.9) -6.65 (3.02) / 288 (25.1)

N2 Fz -8.87 (3.21) / 253 (16.9) -10.6 (5.19) / 269 (28.7) -12.8 (5.87) / 280(29.3)

Cz -8.62 (4.11) / 252 (25.7) -10.9 (6.53) / 288 (42.9) -10.1 (5.99)/ 271 (27.4)

Fpz -2.62 (0.92) / 221 (56.2) -2.09 (0.63) / 219 (38.6) -2.76 (1.09) / 237 (47.6)

MMN Fz -5.28 (2.02) / 220 (64.2) -4.34 (2.04) / 224 (46.6) -4.32 (1.26) / 232 (43.7)

Cz -5.36 (2.15) / 205 (47.9) -4.85 (1.44) / 221 (55.6) -5.68 (2.28) / 233 (46.9)

Control group (n = 11); BECTS group (n = 8); Developmental dyslexia group (n = 7); μV: microvolts (amplitude); ms: milliseconds (latency); SD: standard deviation. The results in bold, have statistical relevance as described in text.

In addition, the grand average waveforms of each above mentioned components

are presented in Figure 12. As well as, for each group and paradigm (pure-tone and

consonant-vowel). After Mauchly’s test procedure, sphericity was assumed to all

measures.

234

a) Pure-tone

Fpz

Fz

Cz

N2b

N1

N2b

N1

MMN

MMN

MMN N2b

N1

P2

P2

235

b) Speech (consonant-vowel)

Fpz

Fz

Cz

MMN

MMN

N2b

N1

N2b

N1

N2b

P2

236

0

10.5 µV

100 ms 500 ms

-10.5 µV

Control

BECTS

Dyslexia

Figure 12. Grand average deviant waveforms for pure-tones (a) and consonant-vowel (CV; b) paradigm for the BECTS group (red solid line), the control group (blue solid line), and the dyslexia group (black solid line). Grand average MMN difference waveforms are represented in the right column.

Amplitude

For N1 amplitude, two-way ANOVA revealed a significant main effect of

stimuli F(1,23) = 7.48, p = .012 and almost significant for group, F(2,23) = 3.34, p =

.053. A significant main effect of electrode was also found for N1, F(2,46) = 20.4, p =

.001 (Figure 13). Post-hoc comparisons using Bonferroni correction revealed that N1

amplitude of the dyslexia group was significantly lower compared to control, to both

stimuli (Table 3). Additionally, we found that N1 amplitude to CV is lower than to

pure-tone stimuli in dyslexia group in all electrodes (Figure 13).

237

Figure 13. N1 mean amplitude across electrodes for CV (right) and pure-tones (left) (error bars represent a

95% confidence interval).

Regarding N2, no significant differences were found between groups, F (2,23)

= 0.91, p = .415, but a significant main effect of electrode was present, (F (2,46) =

39.7, p = .000). No significant effect of stimuli and interactions were found.

As to MMN waves, we found a main effect for electrode, F (2,46) = 26.3, p =

.000). No interaction effect, neither group nor stimuli were observed.

Post-hoc analyses revealed that Fpz is the electrode with the lower amplitudes

for all components. This is consistent with components topography and neural

generators described previously.

Latency

Regarding this measure. N1 latency, results revealed a significant main effect of

stimuli F (1,23) = 4.47, p = .046, for all groups but not between groups. In other

words, the processing of speech (CV) stimuli requires more time than pure-tone. This

is consistent with the hypothesis discussed for MMN (appendix 18), the latter may

occur in a later stage due to overlapping processes since more neural resources are

required to speech processing. The results revealed similar phenomena to N1.

For N2 latency, results revealed almost a significant difference between groups

F(2,23) = 3.26, p = .057 and a significant interaction effect of group*electrode

238

(F(4,46) = 5.70, p = .001) due to the fact that the BECTS has a decrease of N2b

latency from posterior (Cz) to anterior sites (Fpz) and in dyslexia group occurs the

opposite, there is an increase of N2b latency from posterior to anterior (Figures 14 and

15).

Figure 14. N2b mean latency for electrode and participant group (control, BECTS/Epilepsy and

dyslexic).

Figure 15. N2b mean latency across electrodes for CV (right) and pure-tones (left) (error bars represent a


239

This is complemented with voltages map (Figures 27 and 28), notice in dyslexia

group, that after an unclear or even absence frontal N1 negativity the N2b initiates

earlier than the other groups, and absolute peak-to-peak amplitude values are bigger

compared to control, possibly to compensate the poorly exogenous (N1) early sensory

auditory processing. Further, this seems worse for speech stimuli (Figure 28).

Lastly, to MMN latency no significant differences were found between groups

(F(2,23) = 1.44, p = .257). Though, there is a tendency for an increase of latency

across electrodes and between groups for both stimuli (Figure 16).

Figure 16. MMN mean latency across electrodes for CV (right) and pure-tones (left) (error bars represent a


Finally, mind notice the presented topographic MMN voltage maps. It can be

seen that control group only requires four periods of time to onset and fade way, in

other words to complete the total curve travel, between 180-227 ms for pure-tone

stimuli (Figure 29) and 148-195 ms for CV stimuli (Figure 30) with a clear pre-frontal

trigger. However, for BECTS the voltage map is diffuse and positive for pure-tone

stimuli (Figure 29) and highly negative in all presented periods (102- 242 ms) for CV

stimuli. Despiste MMN peak-to-peak amplitude means are decreased compared to

control group, the N2 amplitudes are increased and might have contributed to MMN

voltage distribution.

The same happens with dyslexia group for both stimuli (Figures 29 and 30).

This N2 amplitude enhancement might be related with a potential failure of inhibitory

240

mechanisms, mainly at Fz (Table 3). The brain cannot orient a response by inhibiting

irrelevant information, thus attention allocation processes are highly activated to

compensate this. This is plausible and understandable to happen in developmental

dyslexia group for both stimuli, however in BECTS this is more prominent to speech

stimuli but delayed to both stimuli (Table 3). Another explanation is that the

enlargement of N2 to speech/CV stimuli seen in BECTS group, share the same cortical

generator as the spontaneous rolandic spikes (see Paper VI), because none of the

children with rolandic epilepsy presented learning or language impairments.

In addition, the absence of a clear frontal negativity of N1 component for both

stimuli in dyslexia group suggests a deficit in auditory novelty detection and orienting

response. Requiring lenghty consideration that in developmental dyslexia the

neurophysiological processing deficits occur in the very first primary acoustic analysis,

thus in the primary auditory cortices. Resulting in later stages, in a neural network

deficit processing problem, or in an erroneous “metamorphosic” wave succession.

241

Figure 27. Topographic voltage map of grand average deviant waveforms to pure-tones (a: control b: BECTS c: dyslexia), in a 141 ms time window [113-254 ms].

Figure 28. Topographic voltage map of grand average deviant waveforms to consonant-vowel (a: control b: BECTS c: dyslexia), in a 141 ms time window [117-258 ms].

a

b

a

b

c

c

242

Figure 19. Topographic voltage map of MMN to pure-tones (a: control b: BECTS c: dyslexia), in a 140 ms time window [102-242 ms].

Figure 20. Topographic voltage map of MMN to consonant-vowel stimuli (a: control b: BECTS c: dyslexia), in a 140 ms time window [102-242 ms].

a

b

c

a

b

c

243

Paper VI

Auditory event-related potentials in children with benign epilepsy with centro-

temporal spikes

David Tomé1,2, Mafalda Sampaio3, José Mendes-Ribeiro4, Fernando Barbosa2, João Marques-Teixeira2

1Laboratory of Neuropsychophysiology, Faculty of Psychology and Educational Sciences,

University of Porto, Portugal 2Department of Audiology, School of Allied Health Sciences, Polytechnic Institute of Porto, Portugal

3Serviço de Neuropediatria, Hospital de São João, Portugal 4Serviço de Neurologia, Hospital de São João, Portugal

Tomé, D., Sampaio, M., Mendes-Ribeiro, J., Barbosa, F., & Marques-Teixeira, J.

(2014). Auditory Event-Related Potentials in children with benign epilepsy with

centro-temporal spikes. Epilepsy Research, 108, 1945-1949.

doi:http://dx.doi.org/10.1016/j.eplepsyres.2014.09.021

Epilepsy Research ISSN: 0920-1211


244

Summary

Benign focal epilepsy in childhood with centro-temporal spikes (BECTS) is one of the

most common forms of idiopathic epilepsy, with onset from age 3 to 14 years.

Although the prognosis for children with BECTS is excellent, some studies have

revealed neuropsychological deficits in many domains, including language. Auditory

event-related potentials (AERPs) reflect activation of different neuronal populations

and are suggested to contribute to the evaluation of auditory discrimination (N1),

attention allocation and phonological categorization (N2), and echoic memory

(mismatch negativity – MMN). The scarce existing literature about this theme

motivated the present study, which aims to investigate and document the existing

AERP changes in a group of children with BECTS. AERPs were recorded, during the

day, to pure and vocal tones and in a conventional auditory oddball paradigm in five

children with BECTS (aged 8—12; mean = 10 years; male = 5) and in six gender and

age-matched controls. Results revealed high amplitude of AERPs for the group of

children with BECTS with a slight latency delay more pronounced in fronto-central

electrodes.

Children with BECTS may have abnormal central auditory processing, reflected by

electrophysiological measures such as AERPs. In advance, AERPs seem a good tool to

detect and reliably reveal cortical excitability in children with typical BECTS.

Keywords: benign rolandic epilepsy, N1, N2b, MMN, auditory processing

245

Introduction

Benign epilepsy with rolandic or centro-temporal spikes (BECTS) is the most common

form of idiopathic epilepsy in children, with age of seizure onset between 3-14 years,

representing 8-23% of epilepsies under the age of 16 and is more common in boys than

girls (Bernardina et al., 2005). It is defined as a truly benign partial idiopathic epilepsy,

mainly because spontaneous recovery usually occurs before adolescence in absence of

neurological and cognitive impairment, whether antiepileptic medication is started or

not (Nicolai et al., 2007). However, several studies have questioned the benign nature

of BECTS reporting neuropsychological deficits in many domains (Liasis et al., 2006;

Myatchin et al., 2009). This seems to be related with the atypical form of BECTS,

characterized by the presence of neurological deficits, continuous spike wave during

sleep, atypical absences, speech delay, and intellectual deficits (Wong et al., 1985).

BECTS patients show scalp topography of synchronous discharges of the EEG with

largest amplitudes over the temporal areas of both hemispheres and over frontocentral

regions (Braga et al., 2000; Pan and Lüders, 2000). In addition, high amplitude of

somatosensory evoked potentials has been reported reflecting enhancement of cortical

excitability even during sleep (Ferri et al., 2000). This is consistent with other research

on motor evoked potentials elicited by transcranial magnetic stimulation, that causes

an increase in amplitude substantially above normal values in children with BECTS

(Manganotti and Zanette, 2000; Skrandies and Dralle, 2004). However, literature is

scarce concerning auditory processing reflected on electrophysiological measures such

as auditory event-related potentials (AERPs). In this line of research, Liasis et al.

(2006) reported that asymmetry of P85-120 and absence of mismatch negativity

(MMN) during wake recordings may indicate abnormal processing of auditory

information at a sensory level. The presence of structural abnormality indicated by

imaging is not a predictor of ERPs abnormalities to visual and auditory modalities

(Turkdogan et al., 2003). In a comprehensive study, Boatman et al. (2008) using

behavioral and electrophysiological methods demonstrated speech recognition

impairments in a group of children with BECTS reflecting dysfunction of nonprimary

auditory cortex, with the presence of N100 and MMN to tones but the absence of

MMN to speech stimuli.

246

The ability to detect, discriminate and analyze auditory stimuli is essential for

normal learning and development. AERPs provide objective measures of central

auditory processing. These scalp recorded potentials reflect activation of different

neuronal populations that are suggested to contribute to auditory discrimination (N1),

attention allocation and phonological categorization (N2), automatic pre-attentive

discrimination and perception, and echoic memory (MMN) (Näätänen, 1995; Liasis et

al., 1999, 2001; Henkin et al., 2002).

The aim of the present study was to investigate and document putative changes in

AERPs components (N1, N2b, and MMN) in a group of children with BECTS.

Methods

Five children (all male; M = 10.0 years; SD = 1.87; range 8-12) with clinical and

electroencephalographic criteria for BECTS were included in the study and compared

with a matched control group of six healthy children (all male; M = 11.3 years; SD =

2.65; range 7-14). More accurately, 3 children met clinical and

electroencephalographic criteria, and patient’s number 2 and 5 had only

electroencephalographic characteristics for BECTS diagnosis (Table 1).

All participants had normal hearing and vision, no ear malformation, and no

neurological or mental deficits. Children from BECTS were seizure free for the last

three months and no history of language regression with the onset of seizures.

Medication and other clinical characteristics are shown in Table 1.

247

Table 1

Individual characteristics of the clinical sample.

Patients Age (years) Age at seizure onset(years)

Handedness índex (%)

Laterality of Epileptic focus

Lesion AEDs

(mg/Kg/day)

Academic skills

Systemic disease

1 8 3 -76.7 RCP None CBZ (18) Excellent No

2 12 No seizures 93.3 BCT MRI not performed No Good No

3 12 7 80.0 BCT MRI not performed VPA (20)

Slight learning difficulties

(IQ 74)

No

4 9 5 66.7 LCT MRI not performed VPA (20) Good No

5 9 No seizures 45.0 BCT None No Good CPT II deficiency

M, male; AEDs, antiepileptic drugs; VPA, valproic acid; CBZ, carbamazepine; CPT II, carnitine palmitoyltransferase.

BCT, bilateral centro-temporal; LCT, left centro-temporal; RCP, right centro-parietal.

Based on parental report, all participants were enrolled in mainstream academic

programs (BECTS group: M = 4 years of education, SD = 1.87; Control group: M =

5.17 years of education, SD = 2.48). Both groups had one child left handed and the rest

right handed.

The experimental procedures followed the tenets of the Declaration of Helsinki. It

was approved by the local Ethics Committee from Hospital São João (CES – Comissão

de Ética para a Saúde) and parents gave informed consent concerning their children’s

participation in the study.

During EEG recording (512 Hz sampling and bandwidth 0.05 Hz–100 Hz; 32

channel bio-amplifier Refa32, ANT Neuro, Netherlands) participants were presented

with two active auditory oddball paradigms: a block of pure-tone stimuli (std: 1000Hz;

dev: 1100Hz; created in Audacity software v2.0.0) and other of consonant-vowel (CV

digitalized rate of 44100Hz with 175ms duration, spoken by a male Portuguese voice;

std: [ba] 118 Hz; dev: [pa] 127 Hz, recorded with Nuendo software v4.3.0) with a

stimulus onset asynchrony (SOA) of 800 ms, to a proximal sound level of 75 dB SPL.

In both blocks (300 trials), standard stimuli comprised 80% of all trials, while deviant

248

stimuli comprised 20%. Recordings were obtained from: Cz, Fz, Fpz, M1, M2 and Oz

(ground), referenced to averaged ear lobes (A1 and A2). An electrode was attached

above right eye to monitor the electrooculogram (EOG). Impedance between the

electrodes and skin were kept below 10 kΩ at all sites. Stimuli were presented using

Presentation® software (Neurobehavioral Systems, Inc.) via closed headphones while

the participants where comfortably seated in an armchair and instructed to keep alert

with eyes-open, passively listening to auditory stimuli and focused on a small cross in

the center of a computer screen during recording. Preprocessing included band-pass

filtering [0.3-30] Hz, entire sweep linear detrending and a baseline correction of

individual epochs (60 ms).

The MMN was determined from the Fpz, Fz, Cz, M1 and M2 electrodes, by

computing difference waves, i.e. by subtracting the average standard-stimulus

response from the average deviant-stimulus response for each electrode and subject.

The N1 and N2b were identified as the two largest negative peaks occurring between

100 and 300 ms. Statistically significant results were obtained with nonparametric tests

(Wilcoxon – two independent samples), for α = 0.1.

Results

The N1 and N2b auditory ERP components were present in all participants for both

pure-tones and CV conditions.

Pure-tones

Mild reduced amplitudes of N1 were found to pure-tone stimuli in BECTS group from

Fpz (Md=1.73, SD=1.33), Fz (Md=0.48, SD=3.41) and Cz (Md=2.43, SD=2.90)

compare to control group (Fpz: Md=3.26, SD=5.77; Fz: Md=3.98, SD=3.84; Cz:

Md=4.65, SD=3.61), but with no statistical significance. Regarding latencies of N1 and

N2b, only a slight delay was found for the BECTS group more pronounced in fronto-

central electrodes positions (N1, Fpz: Md=133.0, SD=28.63; Fz: Md=133.0, SD=12.26;

Cz: Md=127.0, SD=16.01; N2b, Fpz: Md=258.0, SD=16.70; Fz: Md=255.0, SD=20.70;

Cz: Md=270.0, SD=28.71) compare to control group (N1, Fpz: Md=135.0, SD=7.94;

Fz: Md=123.0, SD=5.89; Cz: Md=129.0, SD=19.49; (N2b, Fpz: Md=240.0, SD=40.00;

Fz: Md=238.0, SD=34.59; Cz: Md=244.0, SD=35.45; Fig.1), but with no statistical

249

significance. For pure-tone stimuli MMN in BECTS group was almost absent for all

electrodes (Fig.2).

Consonant-vowel

BECTS group revealed high amplitude of N2b to deviant CV stimuli at Cz (Md=8.48,

SD=4.83; p=0.075, 1-tailed) compared to control group (Md=4.13, SD=3.49; Figs. 1

and 2). Regarding latency, a slight but significant delay of N1 was found for the

BECTS group from Fz (Md=150.0, SD=20.89; p=0.036, 2-tailed; Control Group:

Md=125.0, SD=27.42; Fig.1). No relevant differences were found between groups

regarding MMN waves for CV stimuli (Fig.2).

Figure 1 Distribution of components amplitude and latency mean values by electrode position of BECTS group (red) and control group (blue), for consonant-vowel and pure-tone paradigms. Note the enlargement of N2 amplitude in consonant-vowel paradigm from Fz and Cz in BECTS group.

Control

BECTS

250

0

12 µV

100 ms 450 ms

-12 µV

Pure-tone

CV

Fpz Fz Cz

Control

BECTS

Figure 2 Grand average deviant waveforms for consonant-vowel (CV) and pure-tone paradigm for the BECTS group (red solid line) and the control group (blue solid line). Grand average MMN difference waveforms are represented by the dashed lines.

Discussion

The findings in this study are consistent with literature, concerning increased

excitability of cortical structures (Manganotti and Zanette, 2000; Skrandies and Dralle,

2004; Turkdogan et al., 2003; Liasis et al., 2006) and larger amplitudes in all

frequency bands of the spontaneous EEG (Braga et al., 2000; Pan and Lüders, 2000) in

BECTS. Although some subjects are on medication, only P300 seems to be affected by

CBZ (Enoki et al., 1996). Our results illustrate that AERPs may detect and reveal

N2b N2b

N1 N1 N1

N2b N2b

251

increased cortical excitability in children with BECTS as reflected by N2b component

in CV paradigm. However, the same amplitude enlargement is not seen with pure-tone

stimuli, but slight reduced amplitude of N1 at Fpz, Fz, and Cz electrode positions, this

is consistent with Boatman et al. (2008) study indicating integrity of the primary

auditory cortex. Regarding MMN, results to speech stimuli seem consistent with the

scarce literature. The amplitude reduction or absence of MMN may indicate disruption

of the evolution and maintenance of echoic memory traces (Liasis et al., 2006)

possibly leading to impairments in speech recognition and consequent risk for

academic difficulties (Boatman et al., 2008).

In agreement with other studies (Liasis et al., 2006; Rosburg et al., 2008), our

results suggest a deficit in auditory novelty detection and orienting response, with a

potential failure of inhibitory mechanisms, as reflected by decreased N1 and an

enhancement of N2b component to speech stimuli. It seems that if the brain cannot

orient a response by inhibiting irrelevant information, attention allocation processes

are highly activated to compensate this. Furthermore, this is in keeping with recent

findings showing the loss of inhibitory properties of pyramidal neurons is related to

epileptogenesis (Yu et al., 2006; Dravet, 2012). Another explanation is that the

enlargement of N2b to speech stimuli seen in BECTS group, share the same cortical

generator as the spontaneous rolandic spikes.

These results provide new insights into altered brain processes underlying the

discrimination and perception of speech and non-speech in the presence of rolandic

epilepsy. Supporting our view that AERPs can provide a useful tool to detect and

reliably reveal cortical excitability in children with typical BECTS that might be at risk

for language deficits and school difficulties. However, the connection or possible

interrelation between cortical excitability, medication and neuropsychological

assessment still needs to be investigated and clarified in further studies with more

participants.


None of the authors has any conflict of interest to disclose.

252

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Chapter VI

Discussion

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This chapter provides the overall discussion, main conclusions, study

limitations, implications and further research. Its main content, form Paper’s VII (in

preparation) base discussion. We will focus on the results of two groups of children,

same age, gender ratio, academic mainstream, but with different neurodevelopmental

disorders. Results are interpreted and discussed enlightened by the neurocognitive

auditory sentence-processing model and related to dyslexia’s phonological deficit

hypothesis, anchoring-defict hypothesis and RAPT deficit. Regarding BECTS, results

are discussed regarding the recent findings on epileptogenesis and pyramidal neurons.

We can advance that though AERPs are not pathognomonic, they can identify auditory

perceptual deficits and reveal neocortical excitability processes.

Discussion of Findings



paradigm, and their clinical usefulness (predict) in neurodevelopmental disorders such

as benign epilepsy with centro-temporal spikes and developmental dyslexia.

The dyslexia group revealed significant reduced N1 amplitude to pure-tone and

speech CV stimuli, compared to control group. Further, an interaction effect of

stimuli*group was also observed, N1 amplitude to speech CV is lower than to pure-

tone stimuli in dyslexia group to all electrodes. This is consistent with several studies

(Espy et al., 2004; Sebastian & Yasin, 2008), suggesting that the N1 is the most

prominent mesogenous component in response to acoustic input and therefore can

reliably correlate and detect neuronal phonological deficits with auditory sensory

processing (Abad & García, 2000; McArthur, Atkinson, & Ellis, 2009; Stefanics et al.,

2011) in developmental dyslexia. Mind notice that our participants group were having

specialized educational support, despite not fully considered compensated for their

language deficits. This decreased N1 amplitude for speech CV may reflect a residual

auditory processing deficit that has not yet been addressed by top-down compensatory

strategies. Other explanation might be the weakened capture of auditory attention in

dyslexia, allowing for a possible impairment in the dynamics that link attention with

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short memory (Papageorgiou et al., 2009). Thus, representing (N1) a deficit in auditory

novelty detection and orienting response.

These results support Ahissar’s opinion that the impaired-anchoring hypothesis

could be viewed as a specific type of impaired-attention hypothesis. It proposes that

although top-down attentional mechanisms of dyslexics are behaviourally unimpaired,

their bottom-up driven attentional mechanisms are less effective because they cannot use

the gradual build-up of predictions around repeated stimuli, which typically reduce

attentional load (Ahissar, 2007; Banai & Ahissar, 2004). Auditory oddball paradigms

are particularly suitable to test this. Furthermore, this is consistent with Bonte and

Blomert (2004) findings in ERPs, the early priming-related responses of dyslexics

(N1–N2, delays of 100 and 200 ms) were abnormal whereas their late priming-related

response components (N400) were adequate. They interpreted this finding as

indicating a deficit at the earlier, perceptual stage, rather than at the later phonological

lexical stage.

The BECTS presented no differences regarding N1 measures, compared to

control group. Besides, BECTS children did not reveal any reading or learning

impairments.

One must bear in mind that more than half of the dyslexic participants had

attention deficit and were under methylphenidate medication. Are the above stated N1

results due to a possible ADHD comorbidity? We suggest this is not the case. Children

with ADHD exhibit increased early automatic attentional orienting (N1), with shorter

latencies (Oades, 1998), firstly fail to inhibit irrelevant stimuli before falling to

allocate sufficient attentional resources in further processing stages – decreased N2

and P3 (Banaschewski & Brandeis, 2007; Brandeis et al., 2002; Trujillo-Orrego,

2010).

Results of N2b component revealed higher peak-to-peak amplitude for both

stimuli to dyslexia and BECTS group compared to control across electrodes, but with

no statistical significance. For BECTS group, as discussed in Paper VI, increased

amplitudes of N2b might be related to potential failure of inhibitory mechanisms, as

reflected by decreased N1, thus attention allocation processes are highly activated to

compensate (increased N2b; Liasis et al., 2006; Rosburg et al., 2008). This is

consistent with recent findings showing the loss of inhibitory properties of pyramidal

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neurons is related to epileptogenesis (Dravet, 2012; Yu et al., 2006), which, in turn, is

consistent with the neurocomputational model of language processing presented in

Chapter III. Based on the Hebbian concept, BECTS might have a failure in the neural

self-regulatory inhibitory feedback mechanism necessary to maintain the total activity

of the network within certain limits (Garagnani, 2008). In addition, an unstable

positive-feedback loop develops, whereby stronger and stronger responses would

follow each new presentation of a given stimulus, leading to the “overgrowth” of one

of the cell assemblies, which would rapidly extend and cover most of the network,

causing widespread unphysiological states of saturated activation. To confirm this

hypothesis we still have to wait until further computational models consider in the

algorithm the complex dynamics of ionic channels and neurotransmitters that

underpinne epileptogenesis.

Another hypothesis is that the enlargement of N2b to speech stimuli seen in

BECTS group, share the same cortical generator as the spontaneous rolandic spikes,

thus indexing epileptic cortical excitability. More parietally pronounced (Cz), as

revealed by significant interaction effect of group*electrode, voltage maps, and a

statistical significant prolonged N2b to both stimuli type. As an endogenous

component, increased N2b could be due to AED effect, but literature confirms that

only P300 seems to be affected by CBZ (Enoki, Sanada, Oka, & Ohtahara, 1996).

On the other hand, increased N2b amplitude in dyslexia group as to be

interpreted the other way round. The most probable explanation is that

methylphenidate normalizes ERP indices (Ozdag, Yorbik, Ulas, Hamamcioglu, &

Vural, 2004; Sunohara et al., 1999), with the plausible contribution of specialized

educational support. Methylphenidate has no effect on N1 and P2 (Verbaten et al.,

1994). This is complemented with voltages map presented in Chapter V, notice in

dyslexia group, that after an unclear or even absence frontal N1 negativity the N2b

initiates earlier than the other groups, and absolute peak-to-peak amplitude values are

bigger compared to control, possibly to compensate the poorly mesogenous (N1) early

sensory auditory processing. Further, this seems worse for speech stimuli. However,

this requires further research to confirm if it is also a MPH effect or the initial stages of

a top-down compensatory mechanism from the right hemisphere (Guttorm et al., 2009;

Habib, 2000).

259

Regarding AERPs latency in dyslexia, we did not find any significant

differences between groups as other authors state to N1 and P3 (Moisescu-Yiflach &

Pratt, 2005) and N2 (Abad & García, 2000), possibly due to sample size. However, the

majority of the present studies do not report any significant differences between

dyslexia and control groups for N1, N2b, and MMN latencies.

Lastly, we used auditory spectral paradigms with a maximum of 100 Hz

difference between standard and deviant stimulus, both speech and pure-tone.

Investigations of frequency (pitch) discrimination with MMN suggest a deficit in

dyslexia (children and adult) only between stimuli that differ with less than 100 Hz

(Baldeweg et al., 1999; Maurer et al., 2003; Shankarnarayan & Maruthy, 2007).

Studies using large pitch differences (e.g., 200 Hz and greater) between tones did not

report any abnormalities in adults with dyslexia (Kujala et al., 2003; Schulte-Körne et

al., 2001), with the exception of Sebastian and Yasin (2008), suggesting a deficit for

shorter spectral changes only. This deficit might reflect a widened representational

width (RW) in sound perception. RW is a concept proposed by Näätänen and Alho

(1997) to describe an individual’s discrimination accuracy, which is dependent on their

particular ability to perceive differences in sound. The narrower the width is, the better

the discrimination ability (Schulte-Körne & Bruder, 2010).

Our results did not reveal any significant difference for MMN between groups,

neither stimuli effect. This is not new, as several studies report no differences for

MMN in dyslexia (Alonso-Búa, Díaz, & Ferraces, 2006; Heim et al., 2000; Paul et al.,

2006). In fact, our results are similar to Sebastian & Yasin’s (2008) study. Although

not statistical significant, the dyslexia participants were the only group to show

diminished MMNs to speech CV stimuli across electrodes compared to pure-tone (Fz

and Cz). This might suggest specific speech discrimination and auditory sensory

memory deficits assessed by MMN (in accordance with diminished N1 amplitude to

speech) or neurophysiological inability to process phonemic contrasts as well as

difficulties in overlapping neuroprocessing that speech requires (this is consistent with

a widened RW in sound perception in dyslexia, and with appendix 18, which may

support the phonological deficit hypothesis). Thus, resulting in non fluent reading

(especially non-words), impairments to short-term verbal memory, naming, and

260

writing (Castles & Coltheart, 1993; Fernandes, Vale, Martins, Morais, & Kolinsky,

2014).

According to the presented neurocognitive model of language processing in

Chapter III, neurophysiological deficits in developmental dyslexia occur during phase

0 and phase 1 (N1, MMN and possibly P2), corresponding to an impaired

identification of phonemes, word forms, phonological segmentation and sequencing.

Furthermore, if we apply the cell assembly model’s notion and Garagnani’s

computational model (2008) of language processing, cell assemblies size decrease as a

linear function of the minimal-activation threshold. Therefore, dyslexia’s decreased N1

amplitude might correlate with a non-achieved “ignition threshold” or a not well

defined cell assemblies in temporal lobe N1 generators (possibly BAs 42 and 44). This

is consistent with the genetic basis for dyslexia and reading disorders, because genes

do not encode hallucinations, delusions or thought disorganization per se. Yet, they

determine the structure of simple molecules in cells, usually proteins, and these

proteins affect low cells process and respond to stimuli. Thus, a variation in the

sequence of a gene could lead to changes in cell’s interactions, in the connections and

cell assemblies that develop (Weinberger, 2002). In addition, this hypothesis also

explains the poor results to pseudo or non-words in ERP studies and behavior testing

in dyslexia, due to a total lack of recognition, even the phonemes. Reading and

learning disorders might be a consequence of “fuzzy” cell assemblies’ formation.

One might consider, if the N2b has normal amplitude, why the deficits? The

“normal” N2b amplitude in dyslexia group (compared to control group), probably is a

medication effect. Methyphenidate normalizes N2 amplitudes. But that does not mean

the cell assemblies are correctly processing the initial erroneous or insufficient

processing of auditory information, as indexed by N1. Thus, a complementary

hypothesis is to conceive dyslexia as neurofunctional integration and connectivity

neural network problem. Functional integration refers to the interaction of functional

specialized systems. The connectivity pattern, in turn, is a function of epigenetic

activity and plasticity dependent on experience. Dyslexic brains might have a white

matter deficit in the dorsal pathway connecting the posterior part of Broca’s area (BA

44) and the posterior STG/STS (BA 42; Figure 8). The latter is crucial for the human

language capacity which is characterized by the ability to process complex sentence

261

structures (Friederici, 2002). This is corroborated by Brauer (2008), according to

whom in children at an age at which they are still deficient in processing syntactically

complex sentences, the dorsal pathway connecting the language areas is not yet fully

myelinized. Thus, it seems that the evolution of language is tightly related to the

maturation of the dorsal pathway connecting those areas which in the adult human

brain are involved in the processing of syntactically complex sentences (Friederici,

2009). This could be the plausible explanation for the lack of hemispheric asymmetry,

and the tenuous frontiers between dyslexia, CAPD and comorbidity. Being in

accordance with the presented CAPD etiology (Jerger et al., 2002; Kraus et al., 1996):

possible flaws in the transduction of the stimulus; slowing or failure in synaptic

transmission; synaptic desynchronization; CANS injury pathways and/or the cortical

areas responsible for auditory information processing; deficits in interhemispheric

transfer and hemispheric asymmetries, result of neurobiological dysfunctions.

Depending on the specific difficulties encountered in reading or writing or the

type of dyslexia, therapist may find it useful in initial sessions to slow down the speech

to make it easier for the children/person to decipher sounds. By giving the brain more

time to process those sounds, it can learn to understand more and with greater ease.

Then, by speeding up the speech step by step, it is possible to train the brain to process

faster and faster, until normal speech no longer represents a barrier to understanding.

In sum, attenuated N1 to speech CV and pure-tone may be good index of

underlying auditory neuroprocessing deficits in dyslexia, though longitudinal AERPs

and genetic studies are still required to consider it a feasible biomarker. Diminished

MMN to an auditory oddball paradigm may not be the most consistent physiological

marker, but the amplitude decrease from pure-tone to speech might be a stable

measure to always consider in future research and clinical application.

Implications and Further Research

The very question that participants characterization rises, it is the gender ratio

for BECTS and dyslexia group. More than half of our dyslexic participants presented

attention deficit. Reading difficulties/disorders (RD) such as dyslexia appears to be

262

strongly related with the predominantly inattentive type of ADHD rather than

hyperactivity or impulsivity (Willcutt & Pennington, 2000).

General population believe that dyslexia and reading disorders affect more the

boys compared to girls. This is not true. The hyperactive and impulsive behaviors

exhibited by boys with reading disorders may be more disruptive than the inattentive

behaviors exhibited by girls, and may therefore be a more frequent cause for clinical

referrals – approximately four boys to one girl (Germanò, Gagliano, & Curatolo,

2010). Moreover, ADHD females may be less vulnerable to the executive deficits

displayed by boys (Seidman et al., 1997) and often their dyslexia is not discovered

until high school or even college. Mind notice, that children with comorbid problems

have more secondary problems, such as low self-esteem, behavioral problems, and

dropping out of school, and a worse outcome compared with children diagnosed with

only ADHD or RD (Willcutt et al., 2001). Therefore, early identification and

intervention are important to improve the outcome of affected subjects.

We are tempted to propose complementarity or even a fusion between the

phonological deficit hypothesis, anchoring-deficit hypothesis and the RATP theory,

underpinned by the lack of anatomical and neurophysiological asymmetry between

hemispheres of individuals with dyslexia. Only a few studies have not found speech

discrimination deficits to temporal content, only to spectral (right hemisphere; Kraus et

al., 1996).

However, the concept of duration and temporal processing might be a

misunderstanding. No deficits in stimulus duration processing have been reported in

adults and children with dyslexia (Schulte-Körne & Bruder, 2010), but temporal

processing instead. The temporal processing deficits that underlie phonological ones

are more pronounced in stimuli that require combining units processing that underlie a

pre-established rules, even for auditory perception, that is speech stimuli. For example,

the CV [da] is [d] + [a], not [a] + [d]. Although, it may not be an exclusively left

hemisphere problem according to TLE model article (Paper III), but a wider neural

network deficit processing when the number of processing units and linguistic rules

becomes progressively complex, such as a word, nonword or a phrase/rhyme.

Moreover, we still do not know if the anchoring-defict hypothesis can be

applied to all types and subtypes of dyslexia and if it is specific to dyslexia or if can

263

also characterize individuals with a range of other learning disabilities (e.g., attention

disorder). In other words, test if the anchoring-deficit is inherited.

Keeping the above in mind, further research on auditory P200, N400

(Noordenbos, Segers, Wagensveld, & Verhoeven, 2013), P600, and visual N170

(Parviainen, Helenius, Poskiparta, Niemi, & Salmelin, 2006) is required and may

clarify how the development and maturation of phonological processing interferes with

learning to read. One must bear in mind that peaks and components are not the same

thing, results must be interpreted wisely. Further, correlating AERPs results with

behavior measures might demand a clear separation of what is phonological speech

representations from the metacognitive task demands such as short-term memory or

conscious awareness that might be involved in accessing linguistic representations

(Duncan et al., 2013). Future work is needed to analyse the association between

phonological awareness and speech rhythm more closely. At present, sensitivity to

speech rhythm is increasingly being linked to reading progress (Goswami et al., 2002;

Holliman, Wood, & Sheehy, 2010).

Further, considering the presented neurocognitive model of auditory sentence

processing and the mapping hypothesis (Harm, McCandliss, & Seidenberg, 2003),

research on auditory and visual modalities integration (Oana, Inagaki, Suzuki,

Horimoto, & Kaga, 2006) may clarify dyslexia’s aetiology, and how orthographic

representations map onto phonological ones and explain letter-processing deficit in

phonological dyslexia, as a phonological recoding deficit (Fernandes et al., 2014). This

may also led to a profound discussion on neuroplasticity, evolving the concept of

central auditory processing and its relations and integrations of different sensory

modalities, hemispheric dominance and handedness.

Neuroplasticity results from the experience and stimulation, leading to cortical

reorganization (remapping), efficiency and synaptic synchronization improvement, and

density and neuronal functioning increase (Elbert, Pantev, Wienbruch, Rockstroh, &

Taub, 1995; Musiek & Chermak 2007). As the stimulation induces modifications, also

deficient stimulation or deprivation can lead to cortical reorganization. The SNAC, the

deficient activation of specialized neural networks that process auditory information

and additional sensory modalities, may impair an individual’s attention, memory and

language. In addition, this impaired multi-stage, multi-sensory and inter-hemispheric

264

processing can result in comorbid conditions, evidenced by learning disabilities,

attention deficit, working memory deficit, impaired language processing and motor

planning (Musiek & Chermak, 2007; Salvi et al., 2002).

It is clear that AERPs more sensitively detect persistent deficits associated to

specific language impairment, related disorders and for identifying children at risk

(Banaschewski & Brandeis, 2007). Furthermore, longitudinal prospective studies are

required to confirm that infants’ AERPs to speech sounds also predict (in a statistical

sense) their subsequent language development, such as verbal memory at age 5

(Guttorm et al., 2005) or reading skills at age 8 (Molfese, 2000). One must avoid small

and heterogeneous groups, in order to achieve stronger effect sizes (Bishop &

McArthur, 2005; Neuhoff et al., 2012).

Lastly, today’s neuroscientists seem to never have enough knowledge to

investigate their primary hypothesis with the constantly renewed techniques, protocols

and theoretical models.

Very interesting results could be discovered with the AERPs and MEG to test

the lack of anatomical and neurophysiological hemispheric asymmetry. The EEG only

measures synchronized pyramidal neurons activity but MEG is produced by the same

electrical currents and has a better spatial resolution, thus providing complementary

information to EEG (Cohen, 1987).

Future studies must consider that pre-attention and attention is involved in

language processing. The neurophysiological correlate and exact contribution of

attention to language processing (e.g., specific attention role is lacking in the presented

neurocognitive model in chapter III) is not clear yet. Though no single unifying

definition of attention currently exists in the literature: “Everyone knows what

attention is. It is the taking possession of the mind, in clear and vivid form, of one out

of what seem several simultaneously possible objects or trains of thought” (James,

1890, pp. 403-404).

Authors should consider, at least in auditory paradigms using words, non words

or sentence, to distinguish between “active” and “passive” modes of attention, due to

lexicality effect (for review see Pettigrew et al., 2004). The active mode, when

attention processes are controlled in a top-down way by the individual’s current goals,

265

thoughts, behaviour, and the passive mode when attention is controlled in a bottom-up

way by external stimuli (Corbetta & Shulman, 2002).

Recent imaging techniques and methods could also give an important

contribution to the above stated hypothesis in Discussion. For example, Diffusion

Tensor Imaging (DTI) enables the quantification of long range connectivity between

different areas in the brain in vivo. It is based on the fact that measured diffusivity

depends on the orientation of the principle axes of fiber tracts, thus detecting subtle

white matter tract microstructural variations across the brain and individuals, yielding

information about the local orientation of the white matter fibers (Basser & Jones,

2002; Weeden, Hagmann, Tseng, Reese, & Weisskoff, 2005). Complementary, the

Diffusion Spectrum Imaging (DSI) has the ability to resolve crossing fibers at the scale

of a single MRI (magnetic resonance imaging) voxel. The resolution of these images is

amazingly fine grained (Schmahmann, et al., 2007). These methods, allied with a

controlled experiment, objectively prepared for studying structural connectivity or

functional connectivity (resting state and effective connectivity; Stufflebeam & Rosen,

2007) might clarify the neurofunctional disconnectivity in dyslexia, but also how do

structural and effective connectivity between language areas correlate, what is the

function-structure relationship of the fiber tracts connecting the language areas during

language development?

This proposed line of research presuppose the consideration of monoaminergic

and serotonin systems, and neurotransmitter acetylcholine facilitate either induction or

maintenance of long-term synaptic changes. Thus, these neurochemical systems may

have regulatory control over the translation of short-term changes to the long-term at a

synaptic level, which are associated with the phenomena of learning and memory.

This work compares AERPs and discusses neurophysiological correlates

between developmental dyslexia and BECTS. We consider that future comparative

research of disorders that affect similar brain areas are of most importance to clarify

etiological mechanisms. In a close future, we pretend to replicate this work with

children having ADHD, temporal lobe epilepsy, and autism.

“People with schizophrenia think people are communicating with them when they

aren’t; people with autism think people aren’t communicating when they are ... we

266

hope that by studying [both conditions] we will learn more, not just about how the

brain works in schizophrenia and autism, but how it works in general.”

(Uta Frith, Oct 10th, 2014)

Conclusion



paradigm to pure-tone and CV stimuli, and their clinical usefulness (predict) in

neurodevelopmental disorders, such as BECTS and developmental dyslexia, and

hypothesize as neurophysiological endophenotypes or biomarkers of auditory

processing dysfunction.

The above objectives were adressed here by combining

neuropsychophysiological methods, such as AERPs, and theoretical models of

neuroprocessing and neurolinguistic deficits (neurocognitive model of auditory

sentence processing; cell assembly model; phonological deficit hypothesis; RATP

hypothesis; and anchoring-deficit hypothesis).

The original contributions of this work are:

1. Increased amplitude of N1 and N2b from Cz and Fz for pure-tone and

speech stimuli paradigms, respectively, are strong candidates to

endophenotypes of IGE. Moreover, increased N1 and N2b might be traits of

neocortical excitability circuits in affected subjects and a predisposition in

unaffected family members. These findings validate future empirical

research, in order to establish the relationship between neurobiological

processes, pathological mechanisms and the clinical expression found;

2. Temporal lobe epilepsy (TLE) in childhood as a theorical model for

topographic and functional study of central auditory processing and its

development. Topographical and structural evidence is coincident with the

neuronal systems responsible for auditory processing of the highest

specialization and complexity;

267

3. Children with BECTS revealed an amplitude reduction of MMN, that may

indicate disruption of the evolution and maintenance of echoic memory

traces. In addition, a decreased N1 may indicate a deficit in auditory novelty

detection and orienting response, with a potential failure of inhibitory

mechanisms, as reflected by an enhancement of N2b component to speech

stimuli. Or, the latter share the same cortical generator as the spontaneous

rolandic spikes. In sum, children with BECTS may have abnormal central

auditory processing, leading to impairments in speech recognition and

consequent risk for academic difficulties as stated by other studies. In

advance, AERPs seem a good tool to detect and reliably reveal cortical

excitability in children with typical BECTS;

4. A narrative analysis on the development of N1 and N2 components across

lifespan with suggested normative values. Specifically, this work revealed

that N1 latency decreases with aging at Fz and Cz, N1 amplitude at Cz

decreases from childhood to adolescence and stabilizes after 30–40 years

and at Fz the decrement finishes by 60 years and highly increases after this

age. Regarding N2, latency did not covary with age but amplitude showed a

significant decrement for both Cz and Fz. However, changes in brain

development and components topography over age should be considered in

clinical practice. Suggested normative values of both N1 and N2 at Cz and

Fz electrode locations are given in Paper II;

5. The presented anomic aphasia case study, 6 post-stroke, revealed reduced

MMN amplitude across frontocentral electrode sites, particularly to speech

stimuli when compared to healthy subjects. Furthermore, average deviant

waveform analysis revealed a poor morphology of N2b to speech stimuli,

which might be related to deficits in the activation of phonological

representation. The MMN and N2 are highly sensitive AERPs in assessing

auditory processing, can be registered in the absence of attention and with

no task requirements, which makes it particularly suitable for studying and

monitor aphasic subjects;

6. Dyslexic children revealed decresead N1 amplitude for speech CV. This

finding may reflect a residual auditory processing deficit in auditory novelty

268

detection and orienting response that has not yet been adressed by top-down

compensatory strategies. Thus supporting the anchoring-deficit hypothesis.

Although not statistical significant, the dyslexia participants were the only

group to show diminished MMNs to speech CV compared to pure-tone (Fz

and Cz). This might suggest specific speech discrimination and auditory

sensory memory deficits assessed by MMN or neurophysiological inability

to process phonemic contrasts as well as difficulties in overlapping

neuroprocessing that speech requires, which may support the phonological

deficit hypothesis.

To conclude, auditory event-related potentials provide sensitive

neurophysiological measures to the investigation of auditory processing (e.g., novelty

detection, auditory sensory memory, and phonemic categorization) in

neurodevelopmental disorders such as developmental dyslexia and BECTS.

Furthermore, this work suggest AERPs as heuristic measures to endorse future

translational empirical studies on endophenotypes and biomarkers in neurofuntional

disorders such as epilepsy. In addition, although many issues still remain to be

addressed, this work represents a first step towards a better understanding of the

surplus value of how AERPs components can be reliably used in clinical practice. It

would improve better diagnosis, prognosis, follow-up and treatment strategies. But

also, the other way round, the clinical research rational would provide different

information and knowledge to the classical basic research.

269

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Addendum

Appendix 1 Poster: Tavares, D., Tomé, D., & Barbosa, F. (2011). Limitações da

Qualidade de Vida na Epilepsia: mito ou realidade? V Congresso

Saúde e Qualidade de Vida (Livro de Actas), 10 e 11 Fevereiro de 2011

– Escola Superior de Enfermagem do Porto

Appendix 2 Article’s request to Professor Ulrich Hegerl

Appendix 3 Article’s request to Professor Warren Brown

Appendix 4 Article’s request to Professor Dietrich Lehmann

Appendix 5 Article’s request to Professor Albert Haig

Appendix 6 Dr.Teresa Bailey’s permission to adapt Table 1 (Afferent Auditory

Pathways)

Appendix 7 Elsevier’s license agreement to reuse and adapt figures / tables /

ilustrations published in: Berwick, R. C., Friederici, A. D., Chomsky,

N., & Bolhuis, J. J. (2013). Evolution, brain, and the nature of

language. Trends in Cognitive Sciences, 17(2), 89–98.

Appendix 8 Professor’s Angela Friederici permission to adapt figure 1 published

in: Friederici, A. D. (2002). Towards a neural basis of auditory

sentence processing. Trends in Cognitive Sciences, 6(2), 78-84.

Appendix 9 Elsevier’s license agreement to reuse and adapt figures / tables /

ilustrations published in: Friederici, A. D. (2012). The cortical

language circuit: from auditory perception to sentence comprehension.

Trends in Cognitive Sciences, 16(5), 262–268.

Appendix 10 Professor Mark Cohen’s permission to use and translate the

Handedness Edinburgh Inventory adaptation

Appendix 11 ESTSP Ethic’s Comission approval for the work Escala de

Lateralidade manual de Edimburgo: tradução e validação para Português



Appendix 12 Portuguese translation and adaptation of the Handedness Edinburgh

Inventory

Appendix 13 Comissão de Ética para a Saúde (CES) approval for Paper’s VII

study

Appendix 14 Informed Consent

Appendix 15 Invitation letter to parents from Clínica de Dislexia Drª. Celeste

Vieira (to study/Paper VII)

Appendix 16 Logistic procedures document to parents and participants

Appendix 17 Participation certificate

Appendix 18 Poster: Tomé, D., Barbosa, F., & Marques-Teixeira, J. (2013).

Differences in Mismatch Negativity (MMN) response to Pure-tone

and Speech sounds in normal subjects: an additional explanation.

Acta Neurobiologiae Experimentalis, 73(suppl.1), 43.

Appendix 1

Poster

Limitações da Qualidade de Vida na Epilepsia: mito ou realidade?

Diana Tavares1, David Tomé2,3, Fernando Barbosa2

1 Área Técnico-Científica de Neurofisiologia, Escola Superior de Tecnologia da Saúde do Porto – Instituto

Politécnico do Porto (ESTSP-IPP) 2 Laboratory of Neuropsychophysiology, Faculty of Psychology and Educational Sciences,

University of Porto, Portugal 3 Department of Audiology, School of Allied Health Sciences, Polytechnic Institute of Porto, Portugal

Tavares, D., Tomé, D., & Barbosa, F. (2011). Limitações da Qualidade de Vida na

Epilepsia: mito ou realidade? V Congresso Saúde e Qualidade de Vida (Livro de

Actas), 10 e 11 Fevereiro de 2011 – Escola Superior de Enfermagem do Porto.

RESUMO

Introdução: a actividade anómala num número restrito de neurónios pode criar

repercussões físicas e orgânicas, condicionando de modo marcante a vida dos

indivíduos, sendo exemplo disso a Epilepsia. Os estudos actuais inserem-se numa

ideologia de investigação, que visa o desenvolvimento de práticas e políticas, para

melhor compreensão da patologia, aliada a uma melhoria das condições inerentes,

objectivando-se a quantificação do seu impacto no indivíduo e sociedade, de forma a

possibilitar uma melhoria da Qualidade de Vida. Contudo, esta caracteriza-se pelo seu

carácter impreciso e vertente comparativa. Cada ser humano é único, sendo a

variabilidade interpessoal condição identificativa da sociedade actual e dos seus

agentes.

Objectivos: pretende-se analisar se a Epilepsia conduz a alterações individuais

significativas e determinar até que ponto a doença interfere no desenvolvimento

pessoal, com abrangência das esferas familiar, social e escolar e possíveis repercussões

na Qualidade de Vida.

Material e métodos: pesquisa exaustiva nas bases de dados Pubmed e Biblioteca

Nacional (incluindo teses de mestrado/doutoramento), para os termos ‘quality of life’

e/ou ‘epilepsy’ e/ou ‘repercussion’, nos idiomas português, inglês e espanhol, até ao

ano de 2009. Em critérios de exclusão quanto a faixa etária, género ou tipo de

Epilepsia.

Resultados: de um modo global, os principais factores condicionadores destes doentes

e da sua vida diária prendem-se com o tipo e frequência das crises, possíveis efeitos

secundários decorrentes da medicação anti-epiléptica, défices cognitivos/intelectuais,

dinâmica relacional e estigma/exclusão social.

Conclusão: existem diversas situações que incutem uma classificação de “diferente”

nas pessoas. A doença é uma dessas fontes de cunho, modificando os caminhos de

vida e condicionando os objectivos major vivenciais – ser como os demais, como

desejo ser e como os demais gostavam que eu fosse. Ainda hoje são visivelmente

notórios os traços de estigmatização/exclusão social, que de certa forma a delimitam e

restringem, negativa e pesarosamente.

Palavras-chave: Epilepsia; Qualidade de Vida; Estigma; Exclusão Social

ABSTRACT

Introduction: a small number of neurons presenting an abnormal activity is enough

to create organic and physical repercussions affecting remarkably the lives of

individuals, as for example Epilepsy. Current studies are part of an ideology of

research which aims to develop policies and practices to better understand the

pathology, combined with an improvement of the inherent conditions that aim to

quantify their impact on individuals and society in order to enable a better quality of

life. However, this is characterized by its imprecise and comparative aspects. Every

human being is unique, and the interpersonal variability is the identifiable condition of

contemporary society and its agents.

Objectives: we aim to examine whether the epilepsy leads to significant individual

changes and determine how the disease affects the personal development, with

coverage of the familiar, social and school and possible repercussions on quality of

life.

Material and methods: exhaustive research in the search engines PubMed and

National Library, including Master's/PhD theses, for the words 'quality of life' and/or

'epilepsy' and/or 'repercussion' in Portuguese, English and Spanish, by the year 2009.

No exclusion criteria regarding age, gender or type of epilepsy.

Results: in a general way, the main factors conditioning these patients and their daily

lives relate to the type and frequency of seizures, possible side effects arising from the

anti-seizure medication, cognitive/intellectual impairment, and relational dynamics of

stigma and social exclusion.

Conclusion: there are several situations to instill a sort of "different" in people. The

disease is a hallmark of these sources, changing the ways of life and existential

conditioning the major existential objectives - to be like others, want to be like and

how others would like me to be. Traces of stigma and social exclusion are still visible

today, which in some way, limit and restrict negatively and sorrowfully.

Key-words: Epilepsy; Quality of Life; Stigma; Social Exclusion

Introdução

A Epilepsia tem sofrido várias interpretações no decorrer das diversas épocas, desde a

idealização de um fenómeno sobrenatural ou místico, passando pela bruxaria e

possessão demoníaca ou associada a uma condição de nível inferior, charlatanismo, até

ao ponto de já ter sido classificada como uma perturbação/doença psiquiátrica. As

crises epilépticas correspondem a um grupo de manifestações clínicas (sinais e

sintomas), que derivam de uma atividade excessiva, síncrona e anómala dos neurónios,

que se localizam predominantemente no córtice cerebral. Esta atividade anómala e

paroxística é habitualmente intermitente e autolimitada (Engel, 2001).

A patologia em questão apresenta-se como uma das doenças neurológicas crónicas

mais frequentes. O levantamento epidemiológico e estatístico relativo a esta doença

revela, principalmente no nosso país, dados díspares e escassos. O estudo

epidemiológico, realizado pelo investigador Lopes Lima, relativamente às Epilepsias e

síndromes epilépticos no Norte de Portugal, restrito ao ano de 1998, constatou uma

frequência mais elevada nos primeiros anos e décadas de vida, não se manifestando

uma diferença significativa em termos de género. Este estudo divulga uma incidência

bruta de 26.0/100 000 habitantes e uma prevalência bruta de 4.4/1000 habitantes

(sendo o valor do género masculino de 5.1/1000 e do género feminino de 3.8/1000

habitantes).

Na última década, constatou-se uma preocupação e vulgarização crescente do

termo “Qualidade de Vida”, nomeadamente em pacientes com Epilepsia.

Vários autores consideram a existência de dois tipos de Qualidade de Vida, a

privada (que diz respeito ao indivíduo em si) e a pública (conceito mais extenso), que

se reporta às áreas ambiental e cultural, ou seja, à sociedade (Megone, 1990). Na

verdade, a expressão Qualidade de Vida caracteriza-se não só pelo seu carácter

impreciso, mas também pela sua vertente comparativa, comparação não só da nossa

vida com a dos demais indivíduos, mas igualmente comparação entre os nossos

desejos, ambições com aquilo que efetivamente possuímos.

É irrefutável que a saúde constitui uma das áreas de maior relevância e impacto,

em termos de qualidade de vida e bem-estar. Importa referir que o conceito de saúde se

remete para uma dimensão futura, que pode, em certa medida, condicionar a maneira

de estar no presente. Este facto é particularmente visível nos doentes epilépticos, que

muitas vezes demonstram uma grande ansiedade relativamente à possibilidade de

virem a desenvolver novas crises. Deste modo, denota-se que cada indivíduo tem o seu

próprio conceito de saúde, inferindo-se que a Qualidade de Vida associada à saúde

será tão subjectiva e mutável como nas demais áreas.

A autora Ann Bowling (1995), define a Qualidade de Vida relacionada com a

saúde, como o nível ideal das funções mentais, físicas, sociais e dos papéis, incluindo

os relacionamentos e as percepções de saúde, de adaptação, de satisfação de vida e de

bem-estar. Esta deve ainda considerar algumas componentes, que se prendem com o

nível de satisfação do doente com o tratamento, com os resultados e o estado de saúde,

bem como as perspectivas futuras. Considera que este conceito incorpora tantos

aspectos positivos como negativos, que é pessoal, dinâmico e multidimensional.

Os primeiros instrumentos de medição na área da Qualidade de Vida relacionada

com a saúde foram desenvolvidos nos Estados Unidos da América e no Reino Unido e

pretendiam sobretudo determinar o impacto da doença e as funções físicas nesta

dimensão, bem como a satisfação com a vida. A característica comum destas medições

prende-se com a intenção de reflectir o impacto das doenças e das intervenções ao

nível da saúde, sobre a vida quotidiana dos doentes, tendo em conta a perspectiva e os

interesses dos mesmos.

Isto suscita-nos questões como – de que nível de qualidade de vida podem os

doentes epilépticos efectivamente usufruir? O rótulo social de “pessoa doente”, ou

melhor, “pessoa epiléptica” condiciona o seu bem-estar?

Com o presente estudo pretende-se analisar se a Epilepsia conduz a alterações

individuais significativas e determinar até que ponto a doença interfere no

desenvolvimento pessoal, com abrangência das esferas familiar, social e escolar e

possíveis repercussões na Qualidade de Vida.

Material e métodos

Pesquisa exaustiva nas bases de dados Pubmed e Biblioteca Nacional (incluindo teses

de mestrado/doutoramento), para as palavras ‘quality of life’ e/ou ‘epilepsy’ e/ou

‘repercussion’, nos idiomas português, inglês e espanhol, até ao ano de 2009.

Ausência de critérios de exclusão quanto a faixa etária, género ou tipo de

Epilepsia/Síndrome Epiléptico.

Análise dos resultados

As pessoas com Epilepsia, tal como os demais indivíduos, também possuem as suas

próprias aspirações, desejos, expectativas e concepções de uma vida boa e de um pleno

bem-estar. Contudo, a sua Qualidade de Vida pode efectivamente ser condicionada

pela patologia que apresentam, dado que em alguns casos esta poderá originar

determinadas limitações funcionais que, por seu turno, poderão ou não conduzir a

incapacidades.

Os três domínios majores que parecem contribuir efectivamente para a Qualidade

de Vida dos doentes epilépticos são: o físico (ocorrência de crises, medicação e

episódios de hospitalização), o social (estigmatização, dinâmica familiar, dificuldades

laborais, restrições legais) e psicológico (défices cognitivos, declínio intelectual e

manifestações psiquiátricas), (Kendrick, 1994). Na prática, a maioria dos instrumentos

de medição não abrange todas as dimensões enumeradas. Além de que é muito

importante ter presente, que nos reportamos a uma doença com possíveis implicações

em termos de Qualidade de Vida caracteristicamente distintas. Quando se analisa a

Qualidade de Vida dos doentes epilépticos e apesar de não existir nenhum instrumento

diretamente aplicável e validado para Portugal, mas somente itens constitutivos de

outras escalas, não se deve minorar em situação alguma, as áreas da auto-estima, do

auto-conceito, do estigma e da satisfação pessoal (Bowling, 1995).

Um dos fatores que se destaca é a presença/ausência e frequência de crises

epilépticas, visto que a ansiedade e o medo de surgimento de uma nova crise podem

ser constantes. Verifica-se a existência de um receio associado à possibilidade das

crises afectarem, de modo adverso, as capacidades da pessoa a nível da educação, do

trabalho, da família, dos relacionamentos sociais ou mesmo do simples acto de

condução de veículos (Fisher, 2000)1. No mesmo estudo, Fisher constatou que as

pessoas invocaram o medo e a incerteza, como os piores aspectos inerentes à vivência

1 12% dos doentes da amostra referiram o facto de já terem tido um acidente de automóvel, devido à ocorrência de uma crise enquanto conduziam.

desta patologia. Por seu turno, Baker e colegas tentaram estabelecer uma relação entre

a frequência das crises, o tipo de crises e a Qualidade de Vida, em três países europeus,

tendo recorrido ao Functional Status Questionnaire (FSQ) 2 , os resultados obtidos

demonstraram que as pessoas sem crises apresentam uma Qualidade de Vida superior

e que quanto maior for a gravidade das crises menor será essa Qualidade de Vida, os

efeitos das mesmas repercutem-se no bem-estar físico, social e psicológico,

conduzindo muitas vezes a uma vida mais restritiva (Baker et al., 1998).

Existe um particular destaque para as crises de acontecimento diurno, em que

existe uma maior exposição à observação e apreciação de terceiros. Estes eventos

podem, de facto, imprimir graves efeitos a nível da esfera laboral (como acontece em

alguns trabalhos com manipulação de maquinaria perigosa), social (em actividades

lúdico-desportivas como a natação) e na condução de veículos (com provável

ocorrência de acidentes de viação).

Como o controlo das crises se apresenta como condição sine qua non, torna-se

muitas vezes indispensável a administração de drogas anti-epilépticas visando tal fim.

Quando estas são aplicadas de forma adequada e o esquema terapêutico é devidamente

cumprido, a probabilidade de sucesso é elevada 3 . No entanto, estes fármacos

apresentam com alguma frequência efeitos adversos ou secundários. Por exemplo, no

estudo de Mills (1997), 56% dos doentes referiram a sedação e a afectação das

capacidades cognitivas como efeitos adversos da medicação, bem como reacções

alérgicas e aumento de peso. Sendo factores capazes de afectar diferentes funções e

papéis individuais, assim como relações interpessoais e o próprio auto-conceito.

Em Portugal os estudos efectuados nesta área são mínimos, mas nem por isso

deixam de fornecer dados interessantes sobre o impacto da Epilepsia na Qualidade de

Vida dos doentes. Uma investigação levada a cabo ente os anos de 1992 e 1994, na

região norte do país, em 92 doentes com idades entre os 15 e os 65 anos, teve como

objectivos primordiais o desenvolvimento de uma medição de Qualidade de Vida para

a população portuguesa, a descrição dessa Qualidade de Vida e a sua análise em

2 A amostra era formada por trezentos doentes da França, Alemanha e Reino Unido, com idades compreendidas entre os 18 e os 65 anos e com diagnóstico de crises parciais simples ou complexas, com ou sem generalização secundária. O questionário aplicado cobriu as áreas física, psicológica, social e do desempenho de papéis. 3 Excluem-se aqueles casos de Epilepsia mais graves, geralmente associados a outras alterações motoras e cerebrais e fármaco-resistentes.

termos de afectação pela Epilepsia, bem como por outras variáveis do doente em si. Os

resultados obtidos revelaram que a Qualidade de Vida era menor nas pessoas com

crises parciais, sendo as pontuações mais elevadas alcançadas pelos doentes sem crises

(Ribeiro et al., 1998).

Na amostra de doentes analisada por Fisher, mais de metade referiu o medo, a

raiva ou a depressão, como principais reacções aquando do diagnóstico da patologia.

Tais comportamentos associam-se com frequência, à concepção das dificuldades

suscitadas pela sociedade aos indivíduos portadores de doença crónica e, mais

especificamente, a este grupo de doentes. Aliás, o estigma, a discriminação e a

exclusão social, são ainda hoje sentidos com frequência pelas pessoas cunhadas de

“epilépticas”. De tal forma, que 23.8% dos inquiridos mencionaram, espontaneamente,

a ocorrência de estigma social, vergonha, solidão e medo das reacções das pessoas,

actualmente defendido por Argyriou (2004). Também na investigação de Mills, os

indivíduos afirmaram como um factor contributivo para a sua “não felicidade”, o

sentimento de serem tratados como se fossem pessoas inferiores.

Os resultados obtidos apoiam, também, a ideia pré-existente de que esta doença tal

como as demais patologias crónicas, se associa a percepções negativas e a uma

ansiedade no contexto laboral. Daí que as atitudes dos colegas e dos empregadores

sejam determinantes para o seu estatuto e bem-estar dentro da empresa.

As restrições em termos de condução de veículos, actualmente existentes,

interferem em termos de independência e autonomia do indivíduo e, muitas vezes, ao

nível do seu estatuto social, dado que actualmente se tornou prática comum a

condução desses veículos, como modo de afirmação de uma vida com boa qualidade.

Como Fisher concluiu, apesar dos avanços inegáveis, as pessoas com Epilepsia

continuam a debater-se com o estigma social, com baixas taxas de casamento, altas

taxas de desemprego, baixo rendimento familiar, considerável esforço com a educação

e uma pobre auto-imagem.

Discussão

A Qualidade de Vida nos doentes epilépticos, tal como nas demais áreas, é

multifactorial, sofrendo influências de diversas vertentes. De um modo global, os

principais factores condicionadores destes doentes e da sua vida diária, prendem-se

com o tipo e a frequência das crises, os possíveis efeitos decorrentes da medicação

anti-epiléptica, os défices cognitivos e/ou intelectuais, a dinâmica relacional e o

estigma ou exclusão social. Dos diferentes estudos efectuados em vários países,

verifica-se uma alusão frequente a uma diminuição ou limitação, da Qualidade de Vida

nestes doentes. Aliás, no estudo realizado por Fisher (2000), mais de um quarto dos

indivíduos estudados referiram algum tipo de limitação na vida diária, havendo igual

alusão no estudo de Miller (2003) – menor Qualidade de Vida no grupo de análise

comparativamente com o grupo controlo.

Uma das principais características que se associam a um nível inferior de

Qualidade de Vida parece ser a ocorrência, o tipo e a frequência de crises epilépticas.

Na literatura há inclusive referência, a tal constituir uma das principais preocupações

dos doentes epilépticos, sendo ocasionalmente tida como factor de infelicidade. No

mesmo estudo de Fisher, o medo e a incerteza de possíveis crises foi considerado um

dos aspectos mais negativos ligados a esta patologia. E que se complementam com as

investigações de Baker (1998) e de Alanis-Guevara (2005), em que um aumento na

gravidade das crises e o seu mau controlo, respectivamente, apresentaram-se como

indicativos de uma Qualidade de Vida inferior.

Conclusões

No processo moroso e particularizado de análise desta temática, constatou-se a

existência de algumas divergências, não só no que concerne ao grau imputado de

Qualidade de Vida atribuído, mas também aos seus factores, ou possíveis factores,

influenciadores. O medo de exposição social acarreta receios e incertezas,

condicionado sobretudo pela exibição como ser vulnerável ou “inferior”, pois sabe-se

que o rótulo “doente” imputa muito para além das consequências fisiopatológicas da

doença em si.

A Epilepsia ainda é tida como sendo uma doença grave, há que ter em

consideração que a ocorrência de crises pode conduzir a um comportamento de

absentismo, que acarreta consequências. Daí a necessidade de existência de um

elevado grau de compreensão e entreajuda por parte de terceiros, visto que, dentro de

determinados limites, estas situações escapam ao controlo de quem as vivência, não

devendo assim ser penalizadas por tal.

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France, 1999.

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no Norte de Portugal. Dissertação de candidatura ao grau de Doutor, apresentado no

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Conteúdo Escrito do Poster

Limitações da Qualidade de Vida na Epilepsia: mito ou realidade?

Diana Tavares1, David Tomé2,3, Fernando Barbosa2

1 Área Técnico-Científica de Neurofisiologia, Escola Superior de Tecnologia da Saúde

do Porto – Instituto Politécnico do Porto (ESTSP-IPP) 2 Laboratory of Neuropsychophysiology, Faculty of Psychology and Educational

Sciences, University of Porto, Portugal 3 Department of Audiology, School of Allied Health Sciences, Polytechnic Institute of

Porto, Portugal

Introdução: a actividade anómala num número restrito de neurónios pode criar

repercussões físicas e orgânicas, condicionando de modo marcante a vida dos

indivíduos, sendo exemplo disso a Epilepsia. Os estudos actuais inserem-se numa

ideologia de investigação, que visa o desenvolvimento de práticas e políticas, para

melhor compreensão da patologia, aliada a uma melhoria das condições inerentes,

objectivando-se a quantificação do seu impacto no indivíduo e sociedade, de forma a

possibilitar uma melhoria da Qualidade de Vida. Contudo, esta caracteriza-se pelo seu

carácter impreciso e vertente comparativa. Cada ser humano é único, sendo a

variabilidade interpessoal condição identificativa da sociedade actual e dos seus

agentes.

Objectivos: pretende-se analisar se a Epilepsia conduz a alterações individuais

significativas e determinar até que ponto a doença interfere no desenvolvimento

pessoal, com abrangência das esferas familiar, social e escolar e possíveis repercussões

na Qualidade de Vida.

Material e métodos: pesquisa exaustiva nas bases de dados Pubmed e Biblioteca

Nacional (incluindo teses de mestrado/doutoramento), para os termos ‘quality of life’

e/ou ‘epilepsy’ e/ou ‘repercussion’, nos idiomas português, inglês e espanhol, até ao

ano de 2009. Em critérios de exclusão quanto a faixa etária, género ou tipo de

Epilepsia.

Resultados:

Conclusão: existem diversas situações que incutem uma classificação de “diferente”

nas pessoas. A doença é uma dessas fontes de cunho, modificando os caminhos de

vida e condicionando os objetivos major vivenciais – ser como os demais, como desejo

ser e como os demais gostavam que eu fosse. Ainda hoje são visivelmente notórios os

traços de estigmatização/exclusão social, que de certa forma a delimitam e restringem,

negativa e pesarosamente.

Appendix 2

Request to Professor Ulrich Hegerl of the article:

Hegerl, U., Gaebel, W., Gutzman, H., Ulrich, G. (1988). Auditory evoked potentials

as possible predictors of outcome in schizophrenic outpatients. International

Journal of Psychophysiology 6: 207-214

Appendix 3

Request to Professor Warren Brown of the article:

Brown, W.S., Marsh, J.T., La Rue, A. (1983). Exponential electrophysiological

aging: P300 latency. Electroencephalography & Clinical Neurophysiology, 55:

277–285

Appendix 4

Request to Professor Dietrich Lehmann of the article:

Hirata, K., Lehmann, D. (1990). N1 and P2 of frequent and rare event-related

potentials show effects and after-effects of the attended target in the oddball-

paradigm. International Journal of Psychophysiology, 9(3): 293-301

http://www.ncbi.nlm.nih.gov/pubmed?term=Hirata%20K%5BAuthor%5D&cauthor=true&cauthor_uid=2276947

http://www.ncbi.nlm.nih.gov/pubmed?term=Lehmann%20D%5BAuthor%5D&cauthor=true&cauthor_uid=2276947


Appendix 5

Request to Professor Albert Haig of the article:

Haig, A.R., Rennie, C., Gordon, E. (1997). The use of Gaussian component

modelling to elucidate average ERP component overlap in schizophrenia. Journal

of Psychophysiology, 11: 173-187

Appendix 6

Dr.Teresa Bailey’s permission to adapt Table 1 (Afferent Auditory Pathways)

published in: Teresa, B. (2010). Auditory Pathways and Processes: Implications for

Neuropsychological Assessment and Diagnosis of Children and Adolescents. Child

Neuropsychology, 16(6): 521-548

Appendix 7

Elsevier’s license agreement to reuse and adapt figures/tables/ilustrations published in:

Berwick, R. C., Friederici, A. D., Chomsky, N., & Bolhuis, J. J. (2013). Evolution,

brain, and the nature of language. Trends in Cognitive Sciences, 17(2), 89–98.



Appendix 8

Professor’s Angela Friederici permission to adapt figure 1 published in: Friederici, A.

D. (2002). Towards a neural basis of auditory sentence processing. Trends in Cognitive

Sciences, 6(2), 78-84.

Appendix 9

Elsevier’s license agreement to reuse and adapt figures/tables/ilustrations published in:

Friederici, A. D. (2012). The cortical language circuit: from auditory perception to

sentence comprehension. Trends in Cognitive Sciences, 16(5), 262–268.

Appendix 10

Professor Mark Cohen’s permission to use and translate the Handedness Edinburgh

Inventory adaptation

Appendix 11

ESTSP Ethic’s Comission approval for the work Escala de Lateralidade manual de

Edimburgo: tradução e validação para Português

Appendix 12

Portuguese translation and adaptation of the Handedness Edinburgh Inventory

Escala de Lateralidade Manual de Edimburgo

David Tomé, José A. Ribeiro

Traduzido e adaptado (em validação) – Edinburgh Handedness Inventory (revised) (Oldfield, 1971; Cohen, 2008; Williams, 2010)

Género: _______ / Idade: _______

Instruções: assinale na seguinte tabela a mão que usa para cada atividade.

AÇÃO Sempre

ESQUERDA Habitualmente

Esquerda Sem

Preferência Habitualmente

Direita Sempre DIREITA

Escrever

Desenhar

Lançar

Usar uma tesoura

Usar escova de dentes

Usar uma faca

Usar uma colher

Varrer

Acender um fósforo

Abrir um frasco

Rato de computador

Usar chave abrir porta

Usar um martelo

Pentear

Beber de um copo/caneca

Appendix 10

Comissão de Ética para a Saúde (CES) approval for Paper’s VII study

Appendix 14

Informed Consent

CONSENTIMENTO INFORMADO

Projeto: Processamento Auditivo na Dislexia Desenvolvimental e Epilepsia na

infância: contributo para a compreensão dos défices neurolinguísitcos

Investigador responsável: David Tomé / 93 959 13 01 / [email protected]

Exmo(a). Sr.(a) Encarregado(a) de Educação / Representante Legal,

Estamos a desenvolver uma investigação no âmbito do doutoramento em

Psicologia pela Universidade do Porto, com o objectivo de analisar possíveis

alterações da atividade cerebral associadas à Epilepsia do Lobo Temporal na

infância.

O estudo envolve, simplesmente, a resposta a um questionário, um exame

auditivo e a realização de um electroencefalograma (EEG) enquanto se escutam

alguns estímulos sonoros. A duração total do estudo não deverá ultrapassar os

45 minutos.

Todos os procedimentos são totalmente seguros, completamente indolores e não

são invasivos. De qualquer modo, a participação é voluntária e está garantida a

possibilidade de desistência do estudo em qualquer momento, sem qualquer

contrapartida.

Os resultados são confidenciais e serão analisados de forma anónima,

reservando-se a sua utilização para fins estritamente científicos. Por isso, só

serão divulgados os resultados de grupo que vierem, eventualmente, a ser

publicados. No entanto, poderão ser facultados os resultados do exame auditivo

mediante solicitação.

A colaboração do(a) seu(sua) educando(a) é muito importante para compreender

qual o efeito da Epilepsia na forma como o cérebro processa sons e poderá

mailto:[email protected]

ajudar ao desenvolvimento de testes clínicos para o prognóstico e tratamento

desta perturbação neurológica. Por essa razão, vimos solicitar a sua autorização

para que o seu educando participe na investigação acima descrita.

Caso pretenda esclarecer alguma dúvida ou receber informação complementar,

poderá contactar o investigador David Tomé, através do email [email protected] /

93 9591301.

Desde já agradecemos a sua colaboração e a do seu(sua) educando(a) neste

estudo, que são fundamentais para a sua realização e para o avanço do

conhecimento nesta área.

Declaro que tomei conhecimento dos objetivos e procedimentos da investigação

acima descrita e que me foi dada a oportunidade de esclarecer as dúvidas

eventualmente restantes, pelo que autorizo voluntariamente a participação de

quem represento na investigação em causa.

Representante legal / Encarregado de educação do participante:

Assinatura: ____________________________________________ Data: / /

Investigador: ___________________________________________ Data: / /

-------------------------------------------------------------------------------------------------------------

Representante legal / Encarregado de educação do participante:

Assinatura: ____________________________________________ Data: / /

Investigador: ___________________________________________ Data: / /


Appendix 15

Invitation letter to parents from Clínica de Dislexia Drª. Celeste Vieira

(to study/Paper VII)

Exmo. Sr.(a) Encarregado de Educação,

Foi solicitada à nossa Clínica a colaboração num estudo de investigação para conclusão de

Doutoramento em Psicologia, intitulado “Processamento Auditivo na Dislexia

Desenvolvimental e Epilepsia na infância: contributo para a compreensão dos défices

neurolinguísticos”.

Pela importância de que se reveste a investigação na melhoria da qualidade de vida de

todos os cidadãos, o pedido foi aceite.

Em anexo segue o convite do investigador David Tomé, o procedimento para a

colaboração e outras informações sobre o estudo em curso.

Atenciosamente,

A Técnica Superior,

__________________________

Matosinhos, _____ Agosto de 2013

http://www.clinicadislexiacelestevieira.com/

Appendix 16

Logistic procedures document to parents and participants

Procedimentos Logísticos

Projeto: Processamento Auditivo na Dislexia Desenvolvimental e Epilepsia na

infância: contributo para a compreensão dos défices neurolinguísitcos

Investigador responsável: David Tomé / 93 959 13 01 / [email protected]

Orientador Institucional (Hosp. São João): Dr. José Augusto M. Ribeiro

O presente estudo é de cariz observacional analítico, sendo mantido o anonimato de todos

os participantes, cujo recrutamento, será feito via convite por parte do(a) Médico(a),

Psicólogo(a) ou Professor(a) que acompanha a criança. De forma, a reduzir ao máximo o

tempo despendido por parte dos participantes e seus acompanhantes, sugere-se que o

Encarregado de Educação entre em contacto com o investigador responsável (David

Tomé: [email protected] / 93 959 1301) para agendar data da avaliação/recolha. A

avaliação electroencefalográfica (EEG), será realizada no Laboratório de

Neuropsicofisiologia da Faculdade de Psicologia e Ciências da Educação da Universidade

do Porto (FPCEUP - Rua Alfredo Allen, 4200-135 Porto), que se localiza a poucos metros

do Hospital de São João (estação de metro “Pólo Universitário”). Se existir suspeita de

perda auditiva ou por vontade do Encarregado de Educação, convidamo-lo a visitar o

Laboratório de Audiologia para a avaliação auditiva (otoscopia + timpanometria +

audiometria tonal e vocal), na Escola Superior de Tecnologia da Saúde do Porto (ESTSP –

Rua Valente Perfeito, nº322, 4400-330 Vila Nova de Gaia), com um tempo previsto de 50

minutos.



http://www.clinicadislexiacelestevieira.com/

Nenhum exame é invasivo, sendo considerados e respeitados os limiares de conforto do

participante e participação autorizada previamente via Consentimento Informado. A

participação do seu educando(a) é muito importante para os avanços no diagnóstico e

reabilitação destas perturbações do neurodesenvolvimento, será atribuído um diploma de

participação como reconhecimento e agradecimento pelo tempo despendido ao “pequeno e

corajoso participante”.

Appendix 17

Participation certificate

Diploma

O nosso muito obrigado! Porto, ______ de dezembro de 2013

O Investigador Responsável:

_____________________________________

Appendix 18

Poster 11th International Congress of the Polish Neuroscience Society

Differences in Mismatch Negativity (MMN) response to Pure-tone and Speech

sounds in normal subjects: an additional explanation

Tomé D1,2, Barbosa F2, Marques-Teixeira J2

1: Department of Audiology, School of Allied Health Technologies, Polytechnic Institute of Porto, Portugal

2: Laboratory of Neuropsychophysiology, Faculty of Psychology and Educational Sciences,

University of Porto, Portugal

Tomé, D., Barbosa, F., & Marques-Teixeira, J. (2013). Differences in Mismatch

Negativity (MMN) response to Pure-tone and Speech sounds in normal subjects: an

additional explanation. Acta Neurobiologiae Experimentalis, 73(suppl.1), 43.

Acta Neurobiologiae Experimentalis ISSN: 0065-1400



Abstract

The relation of automatic auditory discrimination, measured with MMN, with the type

of stimuli has not been well established in the literature, despite its importance as an

electrophysiological measure of central sound representation. In this study, MMN

response was elicited by pure-tone and speech binaurally passive auditory oddball

paradigm in a group of 8 normal young adult subjects at the same intensity level (75

dB SPL). The frequency difference in pure-tone oddball was 100 Hz (standard = 1000

Hz; deviant = 1100 Hz; same duration = 100 ms), in speech oddball (standard /ba/;

deviant /pa/; same duration = 175 ms) the Portuguese phonemes are both plosive bi-

labial in order to maintain a narrow frequency band. Differences were found across

electrode location between speech and pure-tone stimuli. Larger MMN amplitude,

duration and higher latency to speech were verified compared to pure-tone in Cz and

Fz as well as significance differences in latency and amplitude between mastoids.

Results suggest that speech may be processed differently than non-speech; also it may

occur in a later stage due to overlapping processes since more neural resources are

required to speech processing.

Keywords: MMN, auditory processing, speech, pure-tone, adaptation model.

Background

The relation of automatic auditory discrimination, measured with MMN, with the

type of stimuli has not been well established in the literature, despite its importance as

an electrophysiological measure of central sound representation. Several authors

suggested specialized auditory areas in processing different aspects of sound

information, such as speech and tones (Näätänen et al., 2007; Zatorre et al., 2002). The

adaptation model of MMN suggests that human auditory cortex represents the auditory

environment in amplitopically organized fields, containing neurons that are tuned, for

example, to spectrotemporal structure of complex stimuli such as speech sounds (May

& Tiitinen, 2010; Pantev et al. 1989).

Aims

The aim of this study was to investigate MMN responses to speech (CV) and pure-

tone stimuli. Furthermore, differences might suggest specialized areas with

overlapping processes, supporting the adaptation model.

Methods and procedures

Twelve Portuguese native speakers were selected for the study (aged 20-41; M=28

years; male = 4; mean length of Portuguese education = 14 years ± 2). All participants

had normal hearing and vision and a mean right handedness laterality index of 84.3%

corresponding to the 6th right decile (Oldfield, 1971). Signed informed consents were

obtained after ethical clearances. During EEG recording (32 channel bio-amplifier

Refa32, ANT Neuro, Netherlands) participants were presented with two passive

auditory oddball paradigms, a block of pure-tone stimuli (std:1000Hz; dev:1100Hz)

and other of consonant-vowel (CV digitalized rate of 44100Hz with 175ms duration,

spoken by a male Portuguese voice; std: /ba/; dev: /pa/) with a stimulus onset

asynchrony (SOA) of 1000ms, to a proximal sound level of 75 dB SPL. In all single

blocks (300 trials), standard stimuli comprised 80% of all trials, while deviant stimuli

comprised 20%. Recordings were obtained from the following montage of cup-shaped

silver chloride (Ag-AgCl) electrodes: Cz, Fz, Fpz, M1, M2 and Oz (ground),

referenced to averaged ear lobes (A1 and A2). An electrode was attached above right

eye to monitor the electrooculogram (EOG). Impedance between the electrodes and

skin did not exceed 10 kΩ. Stimuli were presented using ASA software v4.0.6.8 (ANT

Neuro, Netherlands) via closed headphones while the participants where comfortably

seated in an armchair and instructed to keep alert with eyes-open and focused on a

small cross in the center of a computer screen during recording. The sampling rate was

512 Hz for each channel and the recording bandwidth between 0.05 Hz and 100 Hz.

Post hoc analysis included band-pass filtering (0.3-30 Hz), entire sweep linear

detrending and a baseline correction (200 ms).

The MMN was determined from the Fz, Cz, M1 and M2 electrodes, measured by

separately computing difference waves obtained by subtracting the average standard-

stimulus response from the average deviant-stimulus response for each electrode and

subject.

Results

A paired-samples t-test was conducted to determine differences across electrode

location between speech and pure-tone stimuli (Table 1). Results revealed an enhanced

MMN to speech at Fz (t(10) = 4.749; p = 0.001, two-tailed) and Cz (t(10) = 5.137; p =

0.000, two-tailed) and a significance difference in latency at Cz (t(10) = 2.001; p =

0.0365, one-tailed) compared to pure-tone (Figure 1,2). No statistical differences were

found between mastoids, probably due to small group size (Figure 3, 4).

Table 1: Mean peak MMN amplitude and latency (n=12)

Pure-tone Speech (CV)

μV (s.d.) ms (s.d.) μV (s.d.) ms (s.d.)

Fz -2.96** (0.83) 199.25 (40.28) -4.77** (1.71) 221.36 (28.71)

Cz -2.74** (1.14) 187.08*(40.78) -5.19** (1.52) 219* (32.19)

RM 0.99 (0.51) 197.91 (36.13) 0.80 (0.30) 188.64 (45.81)

LM 1.23 (0.53) 162 (32.67) 1.09 (0.64) 176.91 (43.33)

CV: consonant-vowel; µV=amplitude; ms = latency; s.d.= standard deviation; RM: right mastoid; LM: left mastoid. **p < 0.01 (two-tailed), *p < 0.05 (one-tailed).

Figure 1: Grand average MMN difference waveforms (deviant minus standard) for pure-tones (dotted line) and consonant-vowel (CV; solid line) paradigms at Fz.

3 µV

200 ms

Figure 2: Grand average MMN difference waveforms (deviant minus standard) for pure-tones (dotted line) and consonant-vowel (CV; solid line) paradigms at Cz.

Figure 3: Grand average MMN difference waveforms (deviant minus standard) for pure-tones (dotted line) and consonant-vowel (CV; solid line) paradigms at LM.

Figure 4: Grand average MMN difference waveforms (deviant minus standard) for pure-tones (dotted line) and consonant-vowel (CV; solid line) paradigms at RM.

3 µV

200 ms

3 µV

200 ms

3 µV

200 ms

Discussion and conclusions

According to the adaptation model, these differences can be explained by the

overlapping activity of neural populations. Non-adapted cells (“fresh afferents”) will

be progressively activated as many sound features are required to process. Moreover,

in addition to a spectrotemporal analysis a MMN response to speech underlies stimuli

categorization and phonological-lexical activation. Furthermore, the spatial

distribution of cortical activity reflects a neuronal map of functional columns in a

synchronized response and connected by association and commissural fibers

(Shamma, 2001; Webster, 1999). Results suggest that speech is processed differently

than non-speech, also it may occur in a later stage due to overlapping processes since

more neural resources are required to speech processing. Neurophysiologic evidence,

once more, points the highly specialization of human brain to speech and language

processing.

References

May, P. & Tiitinen, H. (2010). Mismatch negativity (MMN), the deviance-elicited

auditory deflection, explained. Psychophysiology, 47, 66-122.




Pantev, C., Hoke, M., Lehnertz, K., & Lütkenhoner, B. (1989). Neuromagnetic

evidence of an amplitopic organization of the human auditory cortex.

Electroencephalography and Clinical Neurophysiology, 72, 225–231.

Shamma, S. (2001). On the role of space and time in auditory processing. Trends in

Cognitive Sciences, 5, 340–348.

Webster, D.B. (1999). Neuroscience of Communication (2nd edition). San Diego:

Singular Publishing Group, Thomson Learning.

Zatorre, R., Belin, P., & Penhune V.B. (2002). Structure and function of auditory

cortex: music and speech. Trends in Cognitive Sciences, 6, 37- 46.