Universitätsspital Zürich

Klinik für Ohren-, Nasen-, Hals- und Gesichtschirurgie

Direktor: Prof. Dr. med. Alexander Huber

Betreuung der Masterarbeit: Dr. med. Colette Hemsley

Leitung der Masterarbeit: Prof. Dr. med. Tobias Kleinjung

Active listening to tinnitus is related to enhanced electroencephalography high frequency activity and alpha connectivity

MASTERARBEIT

zur Erlangung des akademischen Grades

Master of Medicine (M Med) der Medizinischen Fakultät der Universität Zürich

vorgelegt von

Fabian Kraxner

Matrikelnummer: 10-752-640

2016

2

Inhaltsverzeichnis

1 Begleittext zur Masterarbeit ............................................................................. 4

2 Publikation ......................................................................................................... 8

2.0 Abstract .................................................................................................................................. 8

2.1 Introduction ............................................................................................................................ 9

2.2 Methods ...............................................................................................................................10

2.2.1 Participants ...............................................................................................................10

2.2.2 Room ........................................................................................................................11

2.2.3 Design .......................................................................................................................11

2.2.4 Materials ...................................................................................................................11

2.2.4.1 Questionnaires ...........................................................................................11

2.2.4.2 Short Questionnaire....................................................................................11

2.2.4.3 Audiometry .................................................................................................11

2.2.5 EEG Recordings .......................................................................................................11

2.2.6 Procedure .................................................................................................................11

2.2.7 Data Analysis ............................................................................................................12

2.2.7.1 Questionnaires ...........................................................................................12

2.2.7.2 EEG Data ...................................................................................................12

2.2.7.2.1 Preprocessing ...........................................................................12

2.2.7.2.2 Global Average and Topographical Power Analysis.................12

2.2.7.2.3 Source-localized Current Density Analysis ...............................12

2.2.7.2.4 Functional Connectivity .............................................................13

2.3 Results .................................................................................................................................13

2.3.1 Audiometry ................................................................................................................13

2.3.2 Short Questionnaire ..................................................................................................13

2.3.3 EEG Data ..................................................................................................................14

2.3.3.1 Power Analysis ...........................................................................................14

2.3.3.2 Source-localized Current Density Analysis ................................................14

2.3.3.3 Source-localized Connectivity Analysis ......................................................15

2.4 Discussion ............................................................................................................................15

2.4.1 Psychometry .............................................................................................................15

2.4.2 EEG ..........................................................................................................................16

2.4.2.1 Power Analysis ...........................................................................................16

2.4.2.2 Source-localized Connectivity Analysis ......................................................17

2.4.3 Limitations .................................................................................................................17

2.4.4 Conclusion ................................................................................................................18

2.4.5 Future Directions.......................................................................................................18

2.5 References ...........................................................................................................................18

3

2.6 Appendix ..............................................................................................................................25

2.6.1 List of Figures ...........................................................................................................25

2.6.2 List of Tables .............................................................................................................26

2.6.3 Supplemental Tables ................................................................................................27

3 Lebenslauf ....................................................................................................... 28

4 Ethikhinweis .................................................................................................... 29

5 Erklärung ......................................................................................................... 30

4

Begleittext zur Masterarbeit

Active listening to tinnitus is related to enhanced electroencephalography high frequency activity and alpha

connectivity

Zusammenfassung

Tinnitus beschreibt das subjektive Hören eines Geräusches, meist ein Rauschen oder Sausen,

ohne Vorliegen einer objektivierbaren Tonquelle. In unserer klinischen Studie wurden 45

Tinnituspatienten aus der ORL Klinik des Universitätsspitals Zürich (USZ) eingeschlossen. Von

ihnen wurde mittels Elektroenzephalogramm (EEG) die Gehirnaktivität unter 2

Versuchsbedingungen gemessen; zunächst im passiven Ruhezustand (RZ), danach unter

aktiver Konzentration auf ihren Tinnitus (AK). Verschiedene Fragebögen vor, während und nach

den 2 Sequenzen ermöglichten die Erhebung psychometrischer Daten.

Letztere zeigten, dass signifikante Unterschiede zwischen den beiden Bedingungen vorliegen,

hinweisend auf eine erhöhte Präsenz und Leiden unter aktiver Tinnitusperzeption. Ebenso

veränderte sich das EEG zwischen den beiden Bedingungen. Die α-Wellenkonnektivität

zwischen dem anterioren Cingulum und dem primären Hörkortex ist nämlich erhöht. Überdies

treten -, - sowie ϑ-Wellen gehäuft auf, während sich die δ-Wellenstärke erniedrigt darstellt.

Hintergrund/Fragestellung

Tinnitus ist von nicht zu unterschätzender volksgesundheitlicher Relevanz. Beispielsweise liegt

die Lebenszeitprävalenz in der US-Population bei 35%. Ca. 10% haben regelmässigen oder

kontinuierlichen Tinnitus und 1-2% leiden schwer darunter mit allenfalls zusätzlichen

Komorbiditäten.

In dieser empirischen Studie wurden 2 Versuchssituationen innerhalb einer Patientengruppe

verglichen, RZ vs. AK. Dabei wollen wir wissen, welche neurophysiologischen Unterschiede wo

im EEG auftraten und wie diese zu interpretieren sind. Nebst diesen objektiven Daten

erwünschen wir uns mittels den Fragebögen Auskunft über den subjektiven Belastungszustand

des Patienten. Im Besonderen interessieren uns die Veränderungen von diesem zwischen den

beiden Messbedingungen.

Material und Methoden

Die eingeschlossenen 45 Patienten (11 Frauen, 34 Männer; Ethik-Nr.: ZH-2012-0324) befinden

sich alle in Behandlung in der ORL-Klinik am USZ wegen manifestem Tinnitus und nehmen auf

freiwilliger Basis an dieser klinisch-empirischen Querschnittsstudie teil. Es wurde darauf

geachtet, dass Verschiedenheiten in Altersgruppen, Geschlecht, sozioökonomischem Status

und Bildungsniveau bestanden. Überdies durften die Teilnehmer keinen Koffeinkonsum

mindestens in den letzten 4 Stunden vor der Messung getätigt haben. Ebenfalls lagen

audiometrische Voruntersuchungen bei allen Probanden vor. Der gegebenenfalls

tinnitusbedingte Hörverlust war nicht signifikant unterschiedlich zwischen den beiden Ohren

(p<0.878).

Als Messort diente der schallisolierte, fensterlose Audiometrieraum, in welchem ein besonders

geräuscharmes Umfeld vorherrschte. Diese unübliche Stille erlaubte ein ideales Setting für das

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Ruhe-EEG. Gleichwohl ermöglicht es dem Patienten sich optimal und ablenkungslos auf den

Tinnitus zu konzentrieren, sobald dies gewünscht wird.

Die EEG-Messungen wurden mit einem 64 Kanal EEG System (Brainamp DC Brain Products,

2013) durchgeführt, stets zuerst im RZ, dann unter AK. Während der technischen Vorbereitung

des Probanden wurde explizit darauf geachtet, Messartefakte zu minimieren. Die Impedanz für

jede Elektrode lag unter 5 Ω. Der Teilnehmer sollte Kiefer-, Mund-, Schluck-, Kopf- sowie

Augenbewegungen vermeiden. Deshalb fixiert dieser einen auf seiner Augenhöhe platzierten

Punkt während der EEG-Messung. Des Weiteren wurde das Thema Tinnitus erst bei den

Instruktionen zur AK angesprochen. Die Erniedrigung der Raumhelligkeit sowie der

standardisierter Übergang vom RZ zur AK mittels folgender Instruktion „Bitte hören Sie nun auf Ihren Tinnitus“ zielten ebenso auf eine Fehlerquellenreduktion ab.

Die erhobenen EEG-Daten wurden mit entsprechenden Programmen von Artefakten wie z.B.

Augenblinzen, Bewegungen jeglicher Art oder Schlucken gesäubert und in einem zweiten

Schritt ausgewertet. Genaueres hierzu ist der Originalpublikation zu entnehmen.

Resultate

Erwartungsgemäss wiesen die Fragebögen auf einen signifikanten Unterschied (p<0.001)

zwischen RZ und AK hin in allen geprüften Modalitäten. Hierbei wurden ein vermehrtes

Tinnitusleiden mit erhöhter Geräuschlautstärke sowie eine verstärkte Beeinträchtigung bei

verminderter Ignorierbarkeit des Tinnitus festgestellt.

Die EEG-Daten, analysiert mit einer Fast Fourier Transformation, zeigten eine global alterierte

Wellenintensität im Rahmen einer verminderten δ- sowie erhöhten ϑ-, - und - Wellenpräsenz

in AK verglichen zum RZ. In den lokalisationsberücksichtigenden Analysen ist hervorzuheben,

dass eine erhöhte α-Wellenkonnektivität zwischen dem subgenualen anterioren Cingulum

(sgACC) links und dem linken primären auditorischen Kortex / Heschl’sche Querwindungen / Gyri temporalis transversi (GTT) eruierbar ist.

Diskussion

Nach bald 20 Jahren neurowissenschaftlicher Forschung bleibt Tinnitus ein schlecht erklärbares

Phänomen ohne kurative Heilmethode.

Die genannten psychometrischen Modalitäten des Tinnitus korrelieren mit einem erhöhten

Niveau an Depressionen sowie Ängsten. Die verstärkte α-Wellenkonnektivität unter AK

zwischen dem sgACC und den GTT kann mittels 2 Theorien erklärt werden.

Eine spezifische, umstrittene Theorie aus der Fachliteratur (Rauschecker et al., 2010) inkludiert

diese zwei kortikalen Strukturen zu einem sogenannten „Geräusch-Annullierungssystem“. Bei einem gewissen Anteil der Patienten funktioniert dieses durch serotinerge Strukturen vermittelte

Konstrukt, primär aus subcallosalen Bereichen hervorgehend. Diese können ihr störendes

Ohrgeräusch somit mehr oder weniger unwillentlich ausblenden. Der andere Teil hingegen hat

damit Schwierigkeiten.

Der Mechanismus erklärt zudem, weswegen erniedrigte hormonelle Serotoninaktivität oft nebst

störender Tinnitusperzeption auch mit depressiver Symptomatik und Schlaflosigkeit als

Komorbidität einhergeht. Spielt doch in der Regulation von letzteren beiden ebenfalls Serotonin

eine zentrale Rolle.

6

Die erste Theorie geht davon aus, dass eben gerade die bewusste Tinnituswahrnehmung in der

AK-Phase dies verursacht. Die zweite Theorie erklärt sich die festgestellte Alteration unter AK

als nun willentlicher Versuch der Tinnitusgeräuschannullierung im beschriebenen System.

Konklusion

Zum ersten Mal konnte gezeigt werden, dass aktive beziehungsweise wissentliche

Tinnituswahrnehmung die elektrische Hirnaktivität im EEG verändert. Subgenuales anteriores

Cingulum und primäre auditive Hörrinde werden dabei vornehmlich linksseitig aktiviert und

bilden ein aktives Netzwerk. Sie stehen dadurch im Verdacht, die heimtückische

Tinnituswahrnehmung zu beeinflussen beziehungsweise gar zu unterhalten.

Mit der Unterscheidung zwischen RZ und AK wird auch das bis anhin häufig gebrauchte

Paradigma der alleinigen EEG-Ruhemessung bei Tinnitus in Frage gestellt. Dieses ist zu

schlecht kontrolliert und liefert folglich verzerrte Daten. Zukünftiges Studiendesign muss diesen

Umstand berücksichtigen, indem man beispielsweise versucht, den Teilnehmer vor und

während der Ruhemessung abzulenken oder geeignet zu instruieren.

Des Weiteren zeigt diese Arbeit auf, wie methodisch wichtig multimodale Integration ist, welche

neuroanatomische, neurophysiologische und neuromodifizierende Ansätze berücksichtigt. Das

effektive, funktionelle Netzwerk hieraus kennzeichnet den Grundpfeiler von zukünftiger

Forschung und neuromodulatorischer Therapie.

Weitere Studien sollten ein longitudinales klinisches Studiendesign anstreben. Denn

insbesondere im Hinblick auf neuroplastische Veränderungen über die Zeit liegen keine

relevanten Forschungsdaten vor. Nichtsdestotrotz ist Tinnitus eine Erkrankung, welche sich

häufig über einen längeren Zeitrahmen hartnäckig manifestiert und im Allgemeinen die

individuellen Verläufe sowie der Leidensdruck sich sehr verschieden ausgestalten können.

Eigenleistung

Meine Hauptaufgabe war es, die artefaktarme Messung der Hirnaktivität mittels der gängigen

Elektroenzepahlographie (EEG) sowie die adäquate Durchführung der Fragebögen zum

momentanen subjektiven Befindenszustand für 45 Patienten eigenständig zu tätigen. Nebst der

sorgfältigen Patienteninstruktion sowie der präzisen Technikbedienung nach standardisiertem

Schema war ebenso meine kritische, objektive und sachkundige Interpretation aller erhobenen

Daten und Parametern während und nach dem Experiment von grosser Bedeutung.

Schlussendlich galt es im Rahmen der Datenprozessierung, die erhobenen Aufzeichnungen

korrekt in das EDV-System einzupflegen.

Die fehlerarme EEG-Messung erforderte genaue Kenntnisse der äusseren Kopfanatomie.

Durch die korrekte Vermessung des Kopfes anhand anatomischer Punkte wie beispielsweise

der Protuberantia occipitalis externa konnte die passende EEG-Messkappe korrekt positioniert

und das Messergebnis verbessert werden. Jede der 64 Elektroden erhielt somit einen

vordefinierten, reproduzierbaren örtlichen Bezugspunkt am Kopfschädel. Die anschliessende

Messung für die bekannten zwei Versuchsbedingungen (RZ, dann AK) durfte standardisiert erst

bei genügend starkem Messsignal, festgelegter tiefer Impedanz (< 5 Ω) über allen Elektroden

sowie glaubhafter Ausräumung aller Verständnisfragen beim Probanden gestartet werden.

Die Patientenakquisition sowie Kontaktierung und Aufbietung gehörten ebenso zu meinem

Aufgabenbereich wie die Terminkoordination sowie die Patientenvor- und Nachbereitung. Die

regelmässige Teilnahme an Meetings bezüglich dem Projektverlauf sowie die initiale

7

thematische Einarbeitung mittels der einschlägigen Fachliteratur stellen eine

Selbstverständlichkeit dar.

Des Weiteren partizipierte ich an der kritischen Gegenlektüre der Publikation sowie an deren

Verbesserung innerhalb des Forschungsteams. Dadurch geschah gleichzeitig ein wertvoller

Wissensaustausch im Rahmen gemeinsamer Diskussionen, wodurch mir die weiteren

Gruppenmitglieder Ihren entsprechenden Arbeitsanteil detailliert erläuterten. Bezüglich der

Publikation trug ich die erstinstanzliche inhaltliche Hauptverantwortung für die Abschnitte 2.2.1

bis inklusive 2.2.6.

10. Februar 2016 – Fabian Kraxner

Active listening to tinnitus is related to enhanced EEG highfrequency activity and alpha connectivity

Patrick Neff1,2,3, Fabian Kraxner4, Colette Hemsley4, SteffiWeidt5, Martin Meyer1,2,6, and Tobias

Kleinjung4

1Neuroplasticity and Learning in the Healthy Aging Brain (HAB LAB), Institute of Psychology,

University of Zurich, Switzerland2University Research Priority Programm ‘Dynamics of Healthy Aging’, University of Zurich,

Switzerland3Institute for Computer Music and Sound Technology (ICST), University of Arts Zurich, Switzerland

4Department of Otorhinolaryngology, University of Zurich, Switzerland5Department of Psychiatry and Psychotherapy and Interdisciplinary Tinnitus Clinic, University Hospital

of Zurich, Switzerland6Cognitive Psychology Unit (CPU), University of Klagenfurt, Austria

Tinnitus is primarily manifest as an audible sound with no external source. Decisive consensus

exists that it is somehow related to central or peripheral hearing loss and related maladaptive

plasticity throughout the brain. A considerable amount of neuroscientific studies was con-

ducted in respect to tinnitus applying anatomic (magnetic resonance imaging (MRI)), func-

tional MRI (fMRI) as well as electroencephalography (EEG), and neurostimulation (mostly

(rhythmic) transcranial magnetic stimulation ((r)TMS) methods. Most of these studies imple-

ment group contrasts paradigms with healthy controls. To that end, resting state recordings are

most commonly performed in EEG studies.

No former study aimed at comparing different (auditory) perceptual modes in engaging to the

tinnitus percept in these ubiquitous EEG resting state paradigms. Therefore, the difference

between "resting state" (RS) and "active listening" to tinnitus (AL) was investigated with both

psychometric and neurophysiological instruments analyzing EEG power and connectivity.

A sample of 45 participants looking for help at the otolaryngology department of the University

Hospital of Zurich (USZ) was recruited. The short questionnaire used after both conditions pro-

duced significant differences in all assessed items (tinnitus distress, loudness, annoyance, ig-

norability, p < 0.05) pointing to an increased presence and distress during AL. Related to that,

insights could be gained into activated intra-cortical functional tinnitus networks during AL,

mainly increased EEG alpha connectivity between (subgenual) anterior cingulate (ACC) and

auditory cortices. Furthermore, EEG beta and gamma power were focally increased in frontal

and medial regions, whereas theta and delta power only showed trends of differences between

the conditions. These EEG power changes during AL reflect the well-established pattern of

altered high-frequency band activity (i.e., beta and gamma) in tinnitus sufferers compared to

healthy controls.

In conclusion, it is assumed that the established EEG resting state research paradigm in the tin-

nitus field may be partly confounded by aspects of (involuntary) perceptual modes or attention

to the tinnitus. Future studies should consider or integrate these insights, especially in regards

to individual treatment settings and protocols.

2 PATRICK NEFF,

FABIAN KRAXNER,

COLETTE HEMSLEY,

STEFFI WEIDT,

MARTIN MEYER,

TOBIAS KLEINJUNG

1 Introduction

The phenomenon of a ringing, whistling, sizzling, hum-

ming, hissing, buzzing, whooshing, roaring, fizzing, crack-

ling, cricketing, knocking, or pulsing sound in the ear or else-

where is known and reported since archaic and antique times

(Steiner, 2012). Predominately, tinnitus is defined as "the

perception of sound(s) in the absence of an external sound

source" (Eggermont & Roberts, 2004; Erlandsson & Dau-

man, 2013).

Haunted by this phantom auditory perception are no less

than 35 percent of the general (US) population any time dur-

ing their life (Jastreboff, 1990). 10-15 percent report their

tinnitus percept as frequent or continuous whereas about 1-2

percent suffer heavily from it (Langguth, Kreuzer, Kleinjung,

& De Ridder, 2013).

The percept itself, in most cases, manifests as a (sine)

tone or high-pitched noise around 6-8 kHz (Eggermont &

Roberts, 2004) perceived mostly in bilateral ears or with a

slight preference to one side (Lockwood, Salvi, & Burkard,

2002). Loudness and pitch are therefore the main perceptual

parameters of interest alongside maskability and residual in-

hibition (Henry & Meikle, 2000).

Usually, tinnitus is caused by either objective (Egger-

mont & Roberts, 2004; Mazurek, Olze, Haupt, & Szczepek,

2010; Schaette & Kempter, 2006) or hidden hearing loss

(Adjamian, Sereda, Zobay, Hall, & Palmer, 2012; Schaette

& McAlpine, 2011; Nathan Weisz, Hartmann, Dohrmann,

Schlee, & Norena, 2006; Xiong et al., 2013). It is speculated

that related loss of cochlear hair cells (outer hair cells (OHC)

as well as inner hair cells (IHC)) leads to maladaptive plas-

ticity throughout the auditory pathway and brain (Jastreboff,

1990), which then generates the percept in a putative similar

manner than phantom limb or general phantom (pain) per-

ception following sensory deafferentation (De Ridder, Elgoy-

hen, Romo, & Langguth, 2011). Up to this day, there is no

clearly established pathogenesis and -physiology model nor

an effective, understood cure - yet, it can be clearly stated that

both the inner ear (certainly involved in ’pathogenesis’) and

the brain (as the location of awareness and central nervous

system plasticity) are key contributors to tinnitus. With evi-

dence accumulated in tinnitus-related research up to this day,

a clear involvement of the brain has been clearly established

(Adjamian, Sereda, & Hall, 2009; De Ridder, Elgoyhen, et

al., 2011; De Ridder et al., 2013; Eggermont & Roberts,

2004; Jastreboff, 1990; Vanneste & De Ridder, 2012b).

Unfortunately, there is no simple ’switch’ to turn off the

tantalizing sound as is obvious from previous considerations

and clinical experience (Hesse, 2013). There are though

promising insights derived from the last years of research,

which clearly identify three approaches as the most promis-

ing (Langguth et al., 2013): First, an adaption of classi-

cal psychological (cognitive) therapy (Cima et al., 2012).

Secondly, auditive or musical retraining be it either with

tailor-made notched music training (Okamoto, Stracke, Stoll,

& Pantev, 2010; Pantev, Okamoto, & Teismann, 2012)

or acoustic coordinated reset neuromodulation (Adamchic,

Toth, Hauptmann, & Tass, 2014; Tass, Adamchic, Freund,

Stackelberg, & Hauptmann, 2012). Within the third group of

promising treatment approaches, namely neuromodulation,

is neurofeedback (NFB) usually applying EEG (Dohrmann,

Elbert, Schlee, & Weisz, 2007; Hartmann, Lorenz, Müller,

Langguth, & Weisz, 2014; Schenk, Lamm, Gundel, & Lad-

wig, 2005) or in some cases fMRI (Haller, Birbaumer, &

Veit, 2010, 2013). EEG NFB seems to be especially promis-

ing, as other non-invasive neuromodulatory approaches, like

(repetitive) transcranial magnetic stimulation ((r)TMS), e.g.,

(Burger et al., 2011; Müller, Lorenz, Langguth, Weisz, &

Mouraux, 2013; Plewnia et al., 2012; Vanneste & De Ridder,

2012c), failed to prove efficiency or an actual mechanism of

induced neuroplastic change, e.g. (Nathan Weisz, Lüchinger,

Thut, & Müller, 2014). For reviews the reader is referred to

Langguth et al. (2012) and Vanneste and De Ridder (2012a).

Regarding the aim and scope of the study it is considered

unnecessary to cover all involved pathologic and neurophys-

iological mechanism beyond the scope of the applied meth-

ods. For that reason, any basic research involving animals,

surgery, local and global pharmacological interventions and

mere audiology are skipped or referenced to respective com-

prehensive reviews - at this point ideally to the still valid and

highly influential review by Eggermont and Roberts (2004).

Former MEG/EEG studies comparing tinnitus sufferers

with healthy controls identified decreased global as well as

temporal alpha band power (Moazami-Goudarzi, Michels,

Weisz, & Jeanmonod, 2010; Schlee et al., 2014; N. Weisz,

2005) and increased delta band power (Adjamian et al., 2012;

Moazami-Goudarzi et al., 2010; N. Weisz, 2005). The study

of (Moazami-Goudarzi et al., 2010) furthermore showed an

increase in theta band power. Regarding the gamma band,

several studies showed an increase in gamma power (ana-

lyzed frequencies ranging from 35- 90 Hz) (Ashton et al.,

2007; Lorenz, Müller, Schlee, Hartmann, & Weisz, 2009;

van der Loo, Elsa et al., 2009; Weisz et al., 2007) ’Idle’

alpha desynchronization (Nathan Weisz, Hartmann, Müller,

& Obleser, 2011) seems related to increased spontaneous

synchronization in higher bands like gamma as shown in

a respective negative correlation between these two bands

(Lorenz et al., 2009). Reduced alpha therefore is either pre-

requisite to develop tinnitus or the consequence of the patho-

logical hypersynchronization in lower and higher bands. In-

creased synchronization in lower bands (i.e., delta and party

theta) is theorized to be related to activity of deafferenti-

ated neurons (R. R. Llinás, Ribary, Jeanmonod, Kronberg,

& Mitra, 1999) and thus typical of a lesion-induced deaf-

ferentiation pathology like tinnitus. The role of the gamma

band remains unclear as recent work of (Sedley et al., 2012)

proposes that gamma functions as an active attempt of tin-

ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 3

nitus inhibition mediated by local circuits. Nevertheless,

gamma band is still widely accepted to reflect active percep-

tion and/or memory binding processes in tinnitus sufferers.

As not only the participant’s characteristics differ but of

more severity the recording (MEG vs. EEG, number of mag-

netic detectors and electrodes) and analysis methods (e.g.

different source localization methods) the results of these

studies must be interpreted carefully and a unified method-

ological framework should be established (Adjamian, 2014).

Recent advancements in MEG/EEG analysis methods

as well as increased interest in cortical network analyses

spawned respective connectivity analyses of putative tinni-

tus networks in the brain. Schlee, Hartmann, Langguth, and

Weisz (2009) showed decreased global phase coupling in the

alpha band whereas the phase coupling in the gamma band

was increased. Regarding cortical interregional connectiv-

ity, these alpha phase coupling reductions were generally ob-

served between tentative tinnitus network hubs including bi-

lateral frontal, temporal, parietal as well as anterior and pos-

terior cingulate cortices. Again, within the same network the

gamma connections were reduced which in turn was nega-

tively correlated with the alpha network. Furthermore, the

altered connectivity in these bands aggravated with tinni-

tus duration and the auditory cortex became gradually dis-

patched from the tinnitus network. The latter finding was a

major step towards the understanding of neuroplasticity over

the time course of the tinnitus suffering and finally lead to

the construction of a global brain model of tinnitus (Schlee,

Lorenz, et al., 2011; Schlee, Mueller, et al., 2009) which in

short describes the transition of tinnitus from a focal, lesion-

induced, auditory-temporal phenomenon to a wide-spread

global brain network. For a comprehensive overview of cur-

rent theorized tinnitus networks the reader is referred to re-

spective review papers (De Ridder, Elgoyhen, et al., 2011;

Schlee, Lorenz, et al., 2011; Vanneste, Joos, De Ridder, &

Koenig, 2012).

The study at hand is generally aiming at further explo-

ration of tinnitus within actual sufferer’s perceptual and at-

tentional modes. This goal is approached by applying a, in

that form, novel approach to EEG resting state study design

in tinnitus research by contrasting auditory engagement to

tinnitus, ’active listening’ (AL), to a passive standard ’rest-

ing state’ (RS) condition. Andersson et al. (2006) applied

a related design in a positron emission tomography (PET)

study and showed decreased activity of the auditory cortices

during distraction compared to a resting state condition. In

line with this finding we hypothesize that the auditory cor-

tex is less activated in the RS condition compared to AL. In a

further related design Adjamian et al. (2012) found decreased

delta activity in the right auditory cortex while tinnitus was

masked.

Beyond that, the approach can also be seen as a conceptual

transfer of the traditional group comparison approach be-

tween tinnitus sufferers and healthy controls into the ’within

subject’ domain of the tinnitus population. Thus, we hypoth-

esize that respective tinnitus-specific alterations in the delta,

theta, alpha, beta and gamma band become observable be-

tween the conditions.

Generally, it is assumed, that the different perceptual

modes may elucidate global and focal altered EEG power

as well as connectivities within the cortical tinnitus network.

Related to the nature of the task general neurophysiological

correlates of attention and perceptual mode engagement are

expected on a large-scale network level (Doesburg, Green,

McDonald, & Ward, 2012; Mathewson et al., 2014; Varela,

Lachaux, Rodriguez, & Martinerie, 2001) and especially

task-specific decreases in alpha power (Jensen & Mazaheri,

2010; Klimesch, Sauseng, & Hanslmayr, 2007; Mathew-

son et al., 2014; Pfurtscheller & da Silva, 1999). Concern-

ing tinnitus-specific alterations, an involvement of accessi-

ble (i.e., through EEG) brain regions, primarily (primary)

auditory cortices as well as medial limbic structures is ex-

pected throughout all planned subanalyses (e.g., (De Ridder,

Vanneste, Marco Congedo, & Koenig, 2011; Rauschecker,

Leaver, & Mühlau, 2010; Vanneste, Plazier, der Loo, Elsa

van, et al., 2010).

2 Methods

2.1 Participants

The study comprises tinnitus patients of the University

Hospital of Zürich (USZ), which partook in a psychomet-

ric study including an online survey. In the EEG analysis at

hand 45 participants (11/34 female/male) with high fidelity

EEG recordings were chosen resulting in a heterogeneous

and representative sample of tinnitus sufferers.

An overview with all relevant characteristics for this study

can be found in Table 1.

Table 1

Participant Characteristics

4 participants have a right-lateralized tinnitus, 5 a left-

lateralized, 11 a "central", 10 with a preference to the right

side, 9 with a preference to the left side, 5 diffusely inside

the head, and 1 participant in some other place. With most

of participants experiencing tinnitus in both "ears" or with a

preference to one side the sample is again representative of

the tinnitus population (Lockwood et al., 2002).

In respect to tinnitus pitch, only the completely-assessed,

categorical data is reported where 16 participants indicate a

4 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG

"very high frequency", 20 a "high frequency", 8 a "middle

frequency", and 1 a "low frequency".

No secondary exclusions were performed based on medi-

cation (e.g., antidepressants or relaxants (7 cases)), or other

features (e.g., handedness (one left-hander)) as no indica-

tions or concerns related to tinnitus or the actual recording

procedure were identified.

2.2 Room

The room itself is a faraday cage as well as decoupled

from the rest of the building preventing concussions. It is

protected against every outside noise and has, at quiet, an

environmental noise level of about 27dBL or 35dBA. This

unusually quiet surrounding not only delivers an ideal setting

for the resting state EEG recording in not producing any au-

ditory stimuli possibly triggering neuronal activity, it further-

more enables the participant to focus on his tinnitus percept,

especially in the condition where active listening (AL) to the

tinnitus is demanded. An other acoustic feature of the room

is its well-balanced reverberation properties as the walls ab-

sorb most of the produced noises while not giving the im-

pression of a complete anechoic environment, which could

lead to auditory hallucinations or even tinnitus (Del Bo et al.,

2008; Heller & Bergman, 1953; Mason & Brady, 2009).

2.3 Design

In the first condition, patients were undergoing a standard-

ized vigilance-controlled EEG recording (RS) whereas, after

a break including a short questionnaire of tinnitus character-

istics, they were instructed to actively listen to their tinnitus

(AL) in the second condition.

This approach renders the study into a distinct method-

ological chimera mostly eliciting traits of standard resting

state EEG measurements with traits of a task-related design

as participants are asked to engage into a steady perceptual

mode.

2.4 Materials

2.4.1 Questionnaires. The questionnaires analyzed in

the course of the EEG study at hand are the Tinnitus Ques-

tionnaire (TQ) (G. Goebel & W. Hiller, 1994), Tinnitus

Handicap Inventory (THI) (Newman, Jacobson, & Spitzer,

1996), and "Tinnitus Beeinträchtigungsfragebogen" (TBF)

(Greimel, Leibetseder, Unterrainer, Biesinger, & Albegger,

2000) for tinnitus-related suffering, Beck Depression Inven-

tory (BDI) (Beck, Ward, Mendelson, Mock, & Erbaugh,

1961) and Beck Anxiety Inventory (BAI) (Beck, Epstein,

Brown, & Steer, 1988) for possibly comorbid affective dis-

orders, short forms of Symptom Check List (SCL) (Dero-

gatis, 1977) and Health Questionnaire ("Gesundheitsfrage-

bogen") (SF) (Bullinger & Kirchberger, 1998) for general

mental respectively physical health, and finally a short form

of WHO Quality of Life (WHOQOL-BREF) (WHOQoL

Group, 1998) to assess general well-being aspects of life. All

of these questionnaires are advocated as standards in tinnitus-

related studies (Landgrebe et al., 2012, 2010; Zeman, Koller,

Schecklmann, Langguth, & Landgrebe, 2012).

2.4.2 Short Questionnaire. The intention behind the

use of the Short Questionnaire (SQ) was to obtain a psy-

chometric confirmation of an increased tinnitus presence in-

cluding loudness and related distress in the second condi-

tion (AL). For this purpose, a selection of questions out of

the online survey and a previous EEG study (Meyer, Luethi,

Neff, Langer, & Büchi, 2014) was adapted. The first and

main question assessed the general tinnitus distress level on

5-point likert scale. Following that, the loudness, the annoy-

ance and the ignorability was assessed on a 10-point likert

scale each.

2.4.3 Audiometry. Standard audiometry was per-

formed by well-trained otolaryngologists binaurally starting

at 125 Hz pure tone presentation (in 5dB steps) in octaves

up to 8 kHz (i.e., 125, 250, 500, 1000, 2000, 4000, 6000,

and 8000 Hz). The measurement was taken in the course of

the patient’s diagnosis and assessment following standards

issued by the American Medical Association (AMA).

2.5 EEG Recordings

The EEG data was collected using a BrainAmp DC ampli-

fier system in combination with a 64 active channel EasyCap

electrode cap (BrainProducts, 2013), corresponding to the

established 10/5 electrode position system (Jurcak, Tsuzuki,

& Dan, 2007; Oostenveld & Praamstra, 2001), using the Fcz

electrode as the online reference. Impedances were kept be-

low 5 kOhm (mean, SD), sampling frequency was set to 1000

Hz. Recordings were performed in direct current (DC) mode

and hardware low-pass filtered with a cutoff frequency of 125

Hz with a slope of 12dB/Octave.

2.6 Procedure

All clinical, audiometric and demographical data were

gathered precursively during clinical consultations at the oto-

laryngology department of the USZ. The patients volunteer-

ing for the EEG recordings where then instructed to re-

frain from caffeine consumption at least 8 hours prior to the

recording session to prevent a confounding effect on the EEG

signal (Landolt et al., 2004), as neural oscillations in the theta

frequency band are hypothesized to be prominent in tinni-

tus pathophysiology (e.g., (De Ridder, van der Loo, Elsa,

et al., 2011; Moazami-Goudarzi et al., 2010; Nathan Weisz,

Moratti, Meinzer, Dohrmann, & Elbert, 2005)).

After being introduced to the aim and scope of the study

as well as signing the informed consent form, the participants

filled in the online survey at a desk in quiet while the record-

ing setting was prepared. Upon completion of the question-

naire they were seated in a comfortable chair in the mid-

ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 5

dle of the room facing a wall with an asterisk as a fixation

point. Participants were informed about different EEG arti-

facts and asked to sit upright, relaxed and avoid unnecessary

movements especially with critical body parts (i.e., eyes, jaw,

head) whenever possible.

For the actual EEG recording lights were dimmed to a

medium level 1. The participants were instructed to simply

follow the vocal instruction played back by Presentation soft-

ware (Neurobehavioral Systems, 2013) and fixate the aster-

isk in the eyes open (EO) condition. A neutral, female voice

requested the participants to open or close their eyes respec-

tively via computer speakers followed by a low-pitched bell

sound. Total recording length was 8 minutes for each con-

dition yielding eight 40 seconds eyes closed (EC) segments

and eight 20 seconds EO segments per condition.

After the recording of the first condition, participants were

asked to fill in the SQ resulting in a little break where the the

room was again lightened to a normal level. For the second

condition, participants were orally instructed to actively lis-

ten to their tinnitus (in german: "Bitte hören Sie nun auf ihren

Tinnitus") and apart from this stick to the instructions of the

first condition (i.e., sit comfortable and upright, avoid unnec-

essary movements etc.). At the end of the second condition

the participants filled in a further exemplar of the SQ.

2.7 Data Analysis

2.7.1 Questionnaires. For statistical analyses of the

questionnaire and audiometry data, SPSS software (version

22) was used.

The 4 items of the SQ were compared using two-tailed

paired t-statistics. Furthermore, to estimate the effect size,

adequacy of sample size, and true significance Cohen’s d

(Cohen, 2013) was calculated using a published formula

suited for paired t-tests (Morris & DeShon, 2002). To con-

trol for multiple comparisons, the bonferroni method was ap-

plied.

2.7.2 EEG Data.

2.7.2.1 Preprocessing. Preprocessing of the EEG data

was performed with BrainVision Analyzer 2 (BrainProducts,

2013). The data was bandpass filtered with Butterworth zero

phase filters between 0.1 Hz and 100 Hz with a slope at the

low cutoff of 24 dB/octave and a slope at the high cutoff of 48

dB/octave. As the alternating current hum had only minimal

influence on the EEG signal, a 2nd order band rejection filter

with a central frequency of 50 Hz and a bandwidth of 1 Hz

was sufficient to eliminate the electrical interference. Bad

channels were excluded following standardized criteria (i.e.,

noise, drift or low activity).

As a next step, an independent component analysis (ICA)

was run with the whole data applying the restricted Infomax

(Gradient) algorithm with classic sphering in 512 iterations.

Resulting components indicative of eye blinks and move-

ments, some indefinite noise sources and very few pulse ar-

tifact components were removed of the data with the subse-

quent inverse ICA procedure. Next, excluded channels were

(re-)interpolated using the spline-type topographical interpo-

lation algorithm, which, simply put, estimates the signal of

a channel based on the activity of neighboring channels. An

average reference (channel) was calculated and applied in-

cluding the implicit reference channel of the actual recording

(i.e, Fcz), which on its part was reused increasing the amount

of analyzable ’active’ channels to 65. After segmenting the

data to the EC (sub-)conditions, always discarding the first

3 seconds due to excessive artifacts caused by the transition

from EO to EC, 8 segments with 37 seconds of EC recordings

each where extracted and further subdivided into 2-second

segments respectively.

The last step in the EEG preprocessing pipeline was the

semi-automatic rejection of remaining artifacts following

standardized criteria. In average, the artifact rejection pro-

cedure yielded 129 segments (SD=14.4) per participant and

conditions in the case of 2-second segments. The amount of

valid segments did not statistically differ between conditions

(t=-0.996, p=0.339 (two-tailed)).

2.7.2.2 Global Average and Topographical Power

Analysis. Eeglab (Delorme & Makeig, 2004) was invoked

to calculate neural activity differences between the condi-

tions on a global and scalp level. First a power spectrum

contrast averaged over all electrodes was calculated. Sec-

ond, topographical maps were produced depicting activation

of frequency bands of interest. The results of the topograph-

ical analysis were corrected for multiple comparisons using

the bonferoni method.

2.7.2.3 Source-localized Current Density Analysis.

SLORETA (Pascual-Marqui, 2007a; R. D. Pascual-Marqui,

2002) was used to source-localize electric potentials to possi-

ble intracortical generators. Technical details to both power-

and connectivity analyses implemented in the sLORETA

software suite can be found in the respective sources (R. D.

Pascual-Marqui, 2002; R. D. Pascual-Marqui et al., 2011).

The volume conductor model (of the brain) behind the

sLORETA algorithm is described in (Fuchs, Kastner, Wag-

ner, Hawes, & Ebersole, 2002) and the integrated proper

electrode position system in (Jurcak et al., 2007). Be-

sides being the most established source-localization algo-

rithm throughout EEG neurophysiology (Greenblatt, Os-

sadtchi, & Pflieger, 2005; Yao & Dewald, 2005), sLORETA

is also widely used in tinnitus-related EEG studies (e.g.,

(Adamchic et al., 2014; Joos, Vanneste, & De Ridder, 2012;

Song, De Ridder, Nathan Weisz, et al., 2013; van der Loo, E.,

Congedo, Vanneste, De Heyning, P. Van, & De Ridder, 2011;

Vanneste, M. Congedo, & De Ridder, 2013; Vanneste, De

Ridder, & Baumert, 2013; Vanneste et al., 2014; Vanneste,

Plazier, der Loo, Elsa van, et al., 2010; Vanneste, Song, &

1The standard room lighting was deemed too glaring for the

study.

6 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG

De Ridder, 2013; Vanneste, Van de Heyning, Paul, & De

Ridder, 2011)).

The two conditions were compared using sLORETA in the

frequency domain (i.e., FFT current density analysis) with

paired tests yielding a differential activity map created by sta-

tistical non-parametric methods (Nichols & Holmes, 2002)

and corrected for multiple comparisons using a permutation

based approach with 5000 iterations.

2.7.2.4 Functional Connectivity. To be able to instan-

tiate connectivity calculations within in the brain, regions of

interest (ROI) had to be defined establishing the nodes of a

putative functional network as derived from previous litera-

ture or actual hypotheses.

A set of ROIs was selected from literature and own reason-

ings about a core tinnitus network as well as a putative noise-

canceling system e.g. (Leaver et al., 2011; Rauschecker et

al., 2010; Schlee, Hartmann, et al., 2009; Song, De Ridder,

Schlee, Van de Heyning, Paul, & Vanneste, 2013; Song, De

Ridder, Nathan Weisz, et al., 2013; Song, Vanneste, Schlee,

Van de Heyning, Paul, & De Ridder, 2013; Vanneste, M.

Congedo, & De Ridder, 2013; Vanneste et al., 2014). No-

tably, the selection of ROIs is not trivial as the locations and

number of selected ROIs influences the obtained results im-

mensely. The choice of ROIs was therefore limited to regions

conjectured in the hypotheses as well as established regions

in previous literature, most prominently frontal, temporal,

anterior and posterior cingulate, and parietal cortical regions

(Schlee, Hartmann, et al., 2009). Furthermore, a parahip-

pocampal ROI was added as of risen interest in recent studies

and models (Vanneste & De Ridder, 2012b). Centroid voxels

in the respective Brodmann areas (BA) were chosen instead

of averaged activity of whole BAs to circumvent ’spillover’

effects between neighboring ROIs.

The respective coordinates and more precise structural

definitions and localizations are referenced in the supplement

(see Supplement: Table 3).

With the ROIs defined, lagged and instantaneous coher-

ence between the nodes can be calculated (Pascual-Marqui,

2007b).

Following network terminology, the brain is a highly in-

terconnected network where brain areas (or underlying sub-

structures like cortical columns or other assemblies of neu-

rons) can be defined as ’nodes’ within a ’network’ and

functional connections between them as ’edges’ within this

network. Classically, these networks were theorized and

probed by means of (scalp) EEG activity phase synchroniza-

tion over multiple frequency bands (Doesburg et al., 2012;

Sauseng & Klimesch, 2008; Varela et al., 2001). In intracor-

tical ROIs, measures of phase synchronization are disturbed

by nonphysiological factors arising from volume conduc-

tion and general low spatial resolution (Bruder et al., 2012).

sLORETA software suite offers a handy toolbox applying a

refined technique (i.e., Hermitian covariance matrices) re-

Figure 1. Mean Audiogram of Participants with Standard

Deviations

moving these confounding factors best-possibly (Pascual-

Marqui, 2007b). The measure of dependence applied in the

sLORETA connectivity toolbox are basically able to calcu-

late all ROIs jointly based on activity in all ROIs estimated

with eLORETA (Pascual-Marqui, 2007a). In also not being

sensitive to propagation lag or energy loss of the signal, the

method is able to cover large-scale synchronous network ac-

tivation within respective frequency bands. Based on these

principles, lagged phase connectivity was calculated using

the connectivity toolbox in sLORETA.

3 Results

3.1 Audiometry

Mean hearing loss was 19.63 dB (SD=15.1) for the right

ear and 19.86 dB (SD=13.73) for the left ear respectively

(n=41). 11 out of the 41 participants with audiometry sur-

passed the clinical threshold for hearing loss of 20 dB re-

duced hearing capacity in at least one frequency and ear,

resulting in 11 participants with mild hearing loss. With

hearing loss levels within the range of 40 and 70 dB, an-

other 4 participants displayed moderate and one participant

severe hearing loss (80+ dB in most frequencies). Hearing

levels did not significantly differ between the ears (t=-0.154,

p<0.878). Figure 1 illustrates the hearing levels for both ears

in a standard audiogram.

3.2 Short Questionnaire

The conditions significantly differed in ratings of tinnitus

distress, loudness, annoyance, and ignorability (p<0.001, ex-

cept loudness: p<0.01, corrected for multiple comparisons

with bonferoni method) displaying higher scores in the AL

condition. Furthermore, Cohen’s d above 0.5 indicate mid-

size effect sizes and confirm the adequacy of the sample size

ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 7

Table 2

Paired Differences T-Test and Cohen’s D of Short Question-

naires Scores

(again with the exception of loudness: d=0.442) (Cohen,

2013) (Table 2). The mean difference in loudness is less

pronounced in contrast to the mean differences of the other

assessed tinnitus aspects.

3.3 EEG Data

3.3.1 Power Analysis. The global average power

analysis for both conditions (i.e., averaged over all recording

electrodes) is plotted in Figure 2. Interestingly, there is no

significant difference between the conditions (p(min)=1.043,

bonferoni corrected, at 4 Hz), also not in the alpha band (peak

around 10 Hz).

Figure 2. Spectral Power Plot Averaged over All Electrodes

for Both Conditions

The topographical analysis of the frequency spectrum pro-

duced two single significant maxima of activation in two

frequency bands (p<0.05 with bonferoni correction, Figure

3). At 22 Hz (Panel A) the observed increase in activity

in AL is most prominent over slight left-lateralized fronto-

medial electrodes (pink dot indicating maximum, t=-4,183,

p=0.009). Further increased activity in this band (statistical

trends) was observed over left temporal and parietal scalp

positions. Panel B shows increased activity in the 41 Hz

frequency band over slight left-lateralized posterior central

regions (t=-4,009, p=0.015).

Figure 3. Topographical Maps of Significant Differences be-

tween Conditions

3.3.2 Source-localized Current Density Analysis.

First, the results of the power analysis (i.e., current density in

mA/mm3) comparison between the two study conditions are

reported. All reported results (i.e., t-values) in this section

and the next section (i.e., connectivity analysis) are corrected

for multiple comparisons applying Statistical non Parametric

Mapping (SnPM) producing "bullet-proof" results (Nichols

& Holmes, 2002; R. D. Pascual-Marqui, 2002).

In contrast to RS, the AL condition exhibits lower alpha 1

activity in left BA3 with the peak voxel in postcentral gyrus

(-55 -15 50) (Figure 4). The finding is significant (t=-1.40,

p<0.05) and the cluster extents to middle frontal gyrus (e.g.,

-45 0 55).

3.3.3 Source-localized Connectivity Analysis. First,

Increased alpha 2 (10-12 Hz) connectivity was found be-

tween left sgACC and left auditory cortices in AL (Figure

5). The projection (not implying any directionality) from the

sgACC to the transverse temporal gyrus (TTG, core primary

auditory cortex, -45 -30 10) was more pronounced (t=3.26,

p<0.1, p-extreme (pe)=0.065) compared to the connection to

the STG (-55 -25 5, t=3.11, p<0.1).

Figure 5. Increased Alpha 2 Connectivity between Left

sgACC and Left Auditory Core Cortices during AL

8 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY,, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG

Figure 4. Decreased Alpha 2 Activity in Left Paracentral Figure 6. Increased Alpha 1 Connectivity between Bilateral

Regions during AL

sgACC and Right PCC during AL

Second, bilateral subgenual regions show increased con-

nectivity in the alpha 1 band with PCC (5 -45 25) dur-

ing AL (Figure 6). The ipsilateral connection is more

pronounced (t=5.11, p<0.01, pe=0.002), as also reflected

in a darker magenta tone, than the contralateral projection

(t=4.20, p<0.05).

4 Discussion

After 20 years of respective neuroscientific research, tin-

nitus remains a poorly understood phenomenon affecting 5-

10 percent of the population in Western civilization, 1-2 per-

cent gravely with intricate comorbidities, related distress,

and no cure in sight (Langguth et al., 2013). Yet, with grow-

ing evidence derived from various studies, separable cortical,

thalamo-cortical, and cortico-limbic (sub-)networks at inter-

play contributing to the heterogeneous symptom and related

suffering arise (De Ridder et al., 2013; Vanneste & De Rid-

der, 2012b).

In this study, the focus was set on the constant tinnitus per-

cept in comparing different perceptual modes in resting state

EEG, namely actively listen (AL), and ’normal’ resting state

(RS) being the ’inattentive’ mode. EEG power and connec-

tivity analyses were performed to discover possible under-

pinnings of functional networks contributing to the tinnitus

sensation.

Differential neurophysiological signatures, in combina-

tion with supporting psychometric differences, came as no

surprise in both perceptual modes and implications for the

widely adapted EEG resting state paradigm in tinnitus re-

search can be derived from the data at hand.

4.1 Psychometry

Alongside the considerations of the last section, re-

sults from various tinnitus-related as well as general health

and well-being questionnaires were also comparable to for-

mer studies, as most importantly TQ scores (Mean=38,

SD=13.14) are in the same range as in various other studies

ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 9

with tinnitus patients ((40.93)(Joos et al., 2012), (40.2)(van

der Loo, E. et al., 2011), and (42)(Schecklmann et al., 2013))

contributing to a solid markedness of the tinnitus symp-

tom in the sample. This is particularly evident, as partici-

pants scored, relatively to the TQ and its subscales, equally

high in the SQ questions, assessing core distress (Mean=2.4,

SD=0.86, range=1-5), annoyance (Mean=4.51, SD=2.52,

range=1-10), ignorability (Mean=5.8, SD=3.27, range=1-

10), and finally tinnitus loudness (Mean=5.96, SD=2.38,

range=1-10) after the RS condition. Herewith the basis for a

successful psychometric backdrop is set enhancing the plau-

sibility of measured differences in EEG ’resting state’ be-

tween conditions (Table 2), as all 4 tinnitus-related dimen-

sions of the SQ elicited higher scores after AL (Al>RS:

distress (t=4.582, p<0.001), loudness (t=2.937, p<0.05),

annoyance (t=4.474, p<0.001), and ignorability (t=5.199,

p<0.0001)).

On the other hand, it was not possible to further ana-

lyze different profiles of differences in SQ with the obtained

results contributing to a marked dichotomy between tinni-

tus distress (measured by distress and annoyance) and tin-

nitus presence (measured by loudness and partly by ignora-

biltity) (Meyer et al., 2014). Respective analyses of variance

(ANOVA) contrasting extreme groups of differences in SQ

did not yield any significant results in both sensor-based and

source-localized activity and connectivity (data not shown).

4.2 EEG

4.2.1 Power Analyses. As hypothesized before, the

two conditions used in the EEG paradigm could possibly be

regarded as a between-subjects design (i.e., patients vs. con-

trols) adapted to a within-subject design (i.e., the two condi-

tions corresponding to normal resting ("controls") and active

engaging in listening to tinnitus ("patients")). Therefore, a

comparison to (older) studies applying a between-subject de-

sign (Adjamian et al., 2012; Ashton et al., 2007; Moazami-

Goudarzi et al., 2010; Weisz et al., 2007) is of particular in-

terest.

The delta band activities are in all mentioned studies in-

creased in tinnitus patients. This finding is not replicated

following the introduced logic as in AL there was a decrease

(statistical trend) in delta both in average whole-scalp power

(Figure 2) as well as in focal left temporal 4 Hz band on the

scalp topography (data not shown). A further explanation

could be a ’tinnitus independent’ alteration in lower band

powers possibly accounting for the attentional shift in per-

ceptual engaging (Jensen & Mazaheri, 2010; Klimesch et al.,

2007; Mathewson et al., 2014), as alterations in the puta-

tively involved alpha band could influence concurrent lower

frequency activities.

Surprisingly there was no significant alteration in al-

pha band activity observed on the sensor level but source-

localized decreased alpha 1 activity (8-10 Hz, peak MNI: -

55 -15 50) could be observed in left lateral paracentral re-

gions including part of the middle frontal gyrus. This could

possibly reflect findings in previous group comparison stud-

ies of temporal decreases in alpha power of tinnitus patients

(Moazami-Goudarzi et al., 2010; Schlee et al., 2014; Weisz

et al., 2007) or intracortical reduction of alpha power induced

by residual inhibition at similar sites (W. Sedley et al., 2015).

Neither convincingly congruent with tinnitus literature as

well as with basics of (event-related) alpha (de-) synchro-

nization (Jensen & Mazaheri, 2010; Klimesch et al., 2007;

Mathewson et al., 2014; Pfurtscheller & da Silva, 1999) these

results are puzzling. Nevertheless it can be clearly stated that

the absence of any significant difference in alpha power on

the sensor level between the conditions (Figure 2 and 3) fur-

ther reinforces the widely observed global and temporal al-

pha reduction in tinnitus patients compared to healthy con-

trols as there is no observable difference in alpha activity be-

tween AL and RS.

A further overlap with previous work is conceivable as

the beta band most prominently represented by the 22 Hz

frequency (Panel A Figure 3) shows a similar spatial dis-

tribution as in Moazami-Goudarzi et al. (2010) where in-

creases in beta band power (18-25 Hz) agglomerate over

mid-frontal regions with a peak in (slightly left-lateralized)

central frontal regions. Again, it is difficult to disentangle

auditory-perceptual aspects of tinnitus presence from tinni-

tus distress related activity changes. Yet, looking at our pre-

vious study (Meyer et al., 2014) it could be assumed that

this enhanced beta activity is related to the higher distress

in the AL conditions (previous study beta range: 20-25 Hz).

Location-wise it could be speculated that the increased beta

activity is possibly originating from ventromedial/cingulate

(e.g., (Vanneste et al., 2014)) or insular/auditory regions

(e.g., (Moazami-Goudarzi et al., 2010)). Unfortunately,

the source-localization using sLORETA at the 22 Hz fre-

quency did not yield significant results. A clear increase

in gamma activity in AL around 41 Hz was also observed

in previous studies but rather in overall gamma frequency

band power (approximately between 40 and 80 Hz) (Ashton

et al., 2007; Moazami-Goudarzi et al., 2010; Weisz et al.,

2007). Location-wise the congruence is not that clear as lat-

eral patches (see Panel B, Figure 3) in the data at hand are

only weakly pronounced and the hot spot is located (slightly

left-lateralized) over parieto-occipital electrodes. Again, re-

spective source-localization of the 41 Hz gamma increase on

the sensor level was not possible. Nevertheless, it is assumed,

that the local maximum over posterior electrodes is possibly

indicative of enhanced gamma band activity in posterior cin-

gulate and parietal (including precuneus) regions.

In conclusion, we tentatively attribute the enhanced high

frequency band activity to the larger presence and distress

indicated by the SQ: Increased frontal beta activity is pos-

sibly related to increased distress whereas increased poste-

10 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG

rior gamma activity is possibly related to increased pres-

ence as especially posterior cingulate regions are theorized in

tinnitus-specific memory-related (probably memory updat-

ing and forming) processes (Vanneste & De Ridder, 2012b).

Generally, the increased high frequency activity here could

partly explain the heterogeneous findings in former studies.

4.2.2 Source-localized Connectivity Analysis. First,

a major finding is the increased connectivity of the upper al-

pha band (alpha 2) between left sgACC and left (primary) au-

ditory cortices, which speaks heavily in favor of a proposed

"noise-cancellation" system (De Ridder et al., 2013; Leaver

et al., 2011, 2012; Rauschecker et al., 2010) linking the pu-

tative "noise-gate" in and around sgACC with the prime site

of auditory perception or activity (i.e., primary auditory cor-

tices). If this finding in this study holds true, it can be rea-

soned that the increased alpha connectivity may be indica-

tive of an ongoing attempt of noise-, or ’tinnitus’-canceling.

As alpha activity is also widely brought into connection with

inhibitory processes in auditory perception (e.g., (Jensen &

Mazaheri, 2010; Klimesch et al., 2007)), this general ob-

servations may further corroborate the "noise-cancellation"

hypothesis. On the other hand, contrasting the above in-

hibitory function of this connectivity, the increase could also

just merely reflect a heightened percept of tinnitus increasing

its auditory ’presence’. Beyond that, a pronounced prefer-

ence of the left hemisphere is observable in this putative core

tinnitus network, which is a distinct pattern emerging of the

data at hand and previous work both in tinnitus as well as in

general auditory phenomena (e.g., (Geven, Kleine, Willem-

sen, & van Dijk, 2014)).

Secondly, a similar pattern is discernible in the increased

connectivity between bilateral sub- and pregenual areas with

posterior (cingulate cortical) regions. The latter regions are

brought into connection with tinnitus distress and memory

in alpha 2 band (Vanneste, Plazier, der Loo, Elsa van, et

al., 2010), possibly related to the results at hand, but more

prominently with "tonal" features of the percept in higher

frequency bands (i.e., beta and gamma bands) (Vanneste,

Plazier, van der Loo, Elsa, Van de Heyning, Paul, & De Rid-

der, 2010). The results of this subanalysis are therefore inter-

preted in a similar way as in the last section, linking increased

connectivity to "noise-gate" and "perceptual" (here: "tonal")

networks.

Finally, though tendentiously spun in contrast to other

connectivity subanalyses and in the case of the alpha 2 band

possibly elusive (see limitations section and Schlee et al.

(2014)), the general increased connectivities between frontal

and posterior regions in the case of the alpha 2 band still are

in range of any proposed tinnitus network frameworks espe-

cially the seminal data of Schlee, Hartmann, et al. (2009).

4.3 Limitations

Sample size is always an issue as the amount of partici-

pants in the study at hand is certainly above general averages

in basic research psychological studies but tendentially be-

low the average of EEG resting state studies in the context of

tinnitus (e.g., (Vanneste, M. Congedo, & De Ridder, 2013)).

For future studies or the continuation of the project - espe-

cially aiming at more distinct tinnitus subgrouping - larger

case numbers and/or more specific sampling strategies are

deemed extremely useful. Nevertheless, sample size is obvi-

ously superior to the previous study (Meyer et al., 2014) as

the results are more robust, clear-cut and imbued with more

statistical power (i.e., correctable for multiple comparisons

in whole-brain/-head voxel-/electrode-wise analyses).

Methods like cluster analysis in (Schecklmann et al.,

2012) or (group) blind source separation analysis (BSS)

(Marco Congedo, John, De Ridder, Prichep, & Isen-

hart, 2010; De Ridder, Vanneste, Marco Congedo, &

Koenig, 2011) are of special interest as they possibly reveal

new insights into cortical mechanisms of tinnitus applying

assumption- and hypothesis-free data-driven algorithms.

As worked out in previous work by Weisz et al. (2007) at-

tributing it specifically to a ’pathological’ tinnitus activation

pattern, slow waves and related periods of high frequency ac-

tivities were observed during preprocessing of EEG data but

interpreted as ’normal’ activation below the threshold of pos-

sible drowsiness effects. In future re-analysis of the data or

new studies, special attention should be directed to this phe-

nomenon as it may be highly indicative of thalamo-cortical

networks (De Ridder, van der Loo, Elsa, et al., 2011; R. R.

Llinás et al., 1999; R. Llinás, Urbano, Leznik, Ramírez, &

van Marle, Hein J.F., 2005).

Temporal integrity of tinnitus-related or general resting

state EEG signals is a considerable issue as averaged excerpts

(i.e. segments) over the whole time course of the recording

are usually the basis for respective statistical analysis. Future

analyses of the data should take this limitation into consid-

eration. It may though not be that confounding within tin-

nitus sufferers as, for example, alpha activity seems to elicit

less variability than in controls (Schlee et al., 2014). Never-

theless, another finding in the same study identifies tinnitus

duration as a possible cause of this decrease in variation.

Network-related interregional coupling is only looked at

in single, identical frequency bands (e.g., in alpha 2 connec-

tivity) whereas previous literature in other research fields is

highly indicative of cross-frequency coupling in large-scale

assemblies (Doesburg et al., 2012; Varela et al., 2001), also

in tinnitus (e.g., (De Ridder, van der Loo, Elsa, et al., 2011)).

In the actual version of the sLORETA software suite, this

feature is still missing.

Related to that, extending insights of long-known EEG

coherence connectivity measures, is the graph-theory driven

network analysis, which has not been conducted in the con-

ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 11

text of tinnitus using (source-localized) EEG nodes. It is ex-

pected, that this would further validate and possibly extend

the insights derived from previous (i.e., coherence-based)

connectivity results (Langer, von Bastian, Claudia C., Wirz,

Oberauer, & Jäncke, 2013; Stam, 2004) or possibly in com-

bination with fMRI (Mantini, Perrucci, M. G., Del Gratta,

Romani, G. L., & Corbetta, 2007).

The distribution of tinnitus characteristics in the sample

at hand are typical for the respective population and com-

parable to other studies. Nevertheless, in the spirit of further

subgrouping tinnitus types as propagated by the European re-

search initiative TINNET (http://tinnet.tinnitusresearch.net/)

distinct contrasts of these characteristics should also be

probed within the paradigm at hand. Most critically, tinnitus

lateralization may limit the extent of the interpretation as the

task in this study is auditive in nature. Yet, tinnitus-related

as wells as general auditory phenomena with their respective

activity tend to be left-lateralized (Geven et al., 2014), which

is in line with our data.

A last point is aimed towards a ’realistic’ transfer of basic

research insights to therapeutic settings of neuromodulatory

applications as individual EEG profiles of tinnitus make it

difficult to derive concrete neuromodulatory treatment proto-

cols. This concern can be further extended to more general

incongruencies within band-power EEG research related to

the tinnitus percept or suffering. Applying this reasoning,

a putative re-interpretation of the gamma frequency from a

perceptive correlate of tinnitus to a possible inhibitory mech-

anism should be taken seriously (Sedley & Cunningham,

2013; Sedley et al., 2012).

4.4 Conclusion

The study at hand produces novel insights into tinnitus

perception mechanisms as it could be clearly shown that en-

gaging in listening to tinnitus activates a functional network

between subgenual and auditory areas (including auditory

memory) possibly indicative of the malicious tinnitus per-

cept or an active attempt of its inhibition. Additionally, fo-

cal maxima of increased high frequency activity (beta and

gamma) could be observed on the sensor level as well as a

left-lateralized decrease of alpha power in source space. In-

sights gained from these results could be of use in reinter-

preting previous studies applying the established EEG/MEG

resting state approach as differential alterations of activity

and connectivity in well-known tinnitus could be confounded

by the perceptual mode/attentional state towards tinnitus in

the recording settings. Furthermore, these insights could sen-

sitize future EEG resting state studies in tinnitus. Ideally, the

paradigm at hand should be used or at least controlled for

(e.g., by distractors (Andersson et al., 2006)) in these studies.

4.5 Future Directions

Further classifications of distinct tinnitus patients sub-

groups are mandatory to understand and treat the tangled web

of different tinnitus manifestations or comorbidities. Consid-

erable effort has already been taken to that effect (De Rid-

der, Vanneste, Marco Congedo, & Koenig, 2011; Wolfgang

Hiller & Gerhard Goebel, 2007; Landgrebe et al., 2010;

Schecklmann et al., 2012; Schlee, Kleinjung, et al., 2011;

Vanneste et al., 2012).

Method-wise, multimodal integration combining differ-

ent available neuroanatomic and -physiological as well as

neuromodulatory approaches seems very promising (e.g.,

(Bruder et al., 2012; Halchenko, Hanson, & Pearlmutter,

2005)). Networks, either broadly conceived or narrowly

studied through graph theory, establish themselves as the new

research method paradigm (shift).

Longitudinal data is completely missing but would, in-

terleaved with the above methodological advances, certainly

shatter decisive light on neuroplastic changes related to tinni-

tus after its onset or more generally over the whole life span.

More classical, in contrast, are calls for larger sam-

ples and standardized operation procedures of psycho-

metric, clinical, and especially neurophysiological assess-

ments. Applying these recommendations in constructing

large international databases with afore-mentioned assessed

data, this strategy is already deployed in initiatives like

TRI (Landgrebe et al., 2010) and its spring-off TINNET

(http://tinnet.tinnitusresearch.net/).

As a switch or wonderous cure for tinnitus is still missing,

the propositions in this section and the data of the study at

hand, may contribute to better treatment or symptom alle-

viation in the spirit of translational science. The approach

of EEG resting state diagnostic assessment in combination

with psychometric and clinical efforts, could ease the devel-

opment of individual NFB protocols applying neuro-guided

multi-frequency and -localization (network) trainings.

Interpreting the overall impression of the data in this study

as well as a general trend in the (neuro-)scientific community,

functional networks mark a promising future, not only in re-

search, but most certainly also in neuromodulatory therapy.

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5 Appendix

List of Figures

1 Mean Audiogram of Participants with Stan-

dard Deviations . . . . . . . . . . . . . . . . 6

2 Spectral Power Plot Averaged over All Elec-

trodes for Both Conditions . . . . . . . . . . 7

3 Topographical Maps of Significant Differ-

ences between Conditions . . . . . . . . . . . 7

4 Decreased Alpha 2 Activity in Left Paracen-

tral Regions during AL . . . . . . . . . . . . 8

5 Increased Alpha 2 Connectivity between

Left sgACC and Left Auditory Core Cortices

during AL . . . . . . . . . . . . . . . . . . . 8

6 Increased Alpha 1 Connectivity between Bi-

lateral sgACC and Right PCC during AL . . . 8

ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 19

List of Tables

1 Participant Characteristics . . . . . . . . . . 3

2 Paired Differences T-Test and Cohen’s D of

Short Questionnaires Scores . . . . . . . . . 7

3 13 Bilateral ROIs of sLORETA Connectivity

Analysis . . . . . . . . . . . . . . . . . . . . 20

20 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG

5.1 Supplemental Tables

Table 3

13 Bilateral ROIs of sLORETA Connectivity Analysis

28

3. Lebenslauf

Name Kraxner

Vorname Fabian Herbert

Geschlecht männlich

Geburtsdatum 10.02.1992

Bürgerort Lengnau AG

Staatsangehörigkeit Schweiz und Österreich

Ausbildung 08/1998 – 07/2004 Primarschule Basadingen

08/2004 – 07/2006 Sekundarschule Diessenhofen

08/2006 – 07/2010 Kantonsschule Schaffhausen

07/2010 – heute Universität Zürich, Humanmedizin

29

4. Ethikhinweis

Hiermit bestätige ich, dass die obige klinische Studie der kantonalen Ethikkommission des Kantons Zürich zur Bewilligung vorgelegt wurde und die Überprüfung positiv ausfiel. Die entsprechende Ethik-Nummer lautet ZH-2012-0324.

Fabian Kraxner

30

5. Erklärung

Masterarbeit

Ich erkläre ausdrücklich, dass es sich bei der von mir im Rahmen des Studiengangs Master Humanmedizin UZH eingereichten schriftlichen Arbeit mit dem Titel „Active listening to tinnitus is related to enhanced electroencephalography high frequency activity and alpha connectivity“ um eine von mir selbst und ohne unerlaubte Beihilfe sowie in eigenen Worten verfasste Masterarbeit* handelt.

Ich bestätige überdies, dass die Arbeit als Ganzes oder in Teilen weder bereits einmal zur Abgeltung anderer Studienleistungen an der Universität Zürich oder an einer anderen Universität oder Ausbildungseinrichtung eingereicht worden ist.

Verwendung von Quellen

Ich erkläre ausdrücklich, dass ich sämtliche in der oben genannten Arbeit enthaltenen Bezüge auf fremde Quellen (einschliesslich Tabellen, Grafiken u. Ä.) als solche kenntlich gemacht habe. Insbesondere bestätige ich, dass ich ausnahmslos und nach bestem Wissen sowohl bei wörtlich übernommenen Aussagen (Zitaten) als auch bei in eigenen Worten wiedergegebenen Aussagen anderer Autorinnen oder Autoren (Paraphrasen) die Urheberschaft angegeben habe.

Sanktionen

Ich nehme zur Kenntnis, dass Arbeiten, welche die Grundsätze der Selbstständigkeitserklärung verletzen – insbesondere solche, die Zitate oder Paraphrasen ohne Herkunftsangaben enthalten –, als Plagiat betrachtet werden und die entsprechenden rechtlichen und disziplinarischen Konsequenzen nach sich ziehen können (gemäss §§ 7ff der Disziplinarordnung der Universität Zürich sowie §§ 51ff der Rahmenverordnung für das Studium in den Bachelor- und Master-Studiengängen an der Medizinischen Fakultät der Universität Zürich)

Ich bestätige mit meiner Unterschrift die Richtigkeit dieser Angaben.

Datum: 10. Februar 2016

Name: Kraxner Vorname: Fabian

Unterschrift:………………………………………..

* Falls die Masterarbeit eine Publikation enthält, bei der ich Erst- oder Koautor/-in bin, wird meine eigene Arbeitsleistung im Begleittext detailliert und strukturiert beschrieben.