karen heslop thesis 2012.final - qut eprintseprints.qut.edu.au/59610/1/karen_heslop_thesis.pdfthe...

BINOCULAR RIVALRY AND VISUOSPATIAL ABILITY IN INDIVIDUALS WITH SCHIZOPHRENIA

Karen R. Heslop

Bachelor of Nursing

Graduate Diploma (Social Science – Counselling)

Master of Education (Adult and Workplace)

A Thesis submitted as fulfilment for Degree of Doctor of Philosophy

School of Psychology and Counselling

Institute of Health and Biomedical Innovation

Queensland University of Technology

2012

i

Keywords

A1 allele, backward masking, Benton’s Judgment of Line Orientation, binocular

rivalry, dopamine, schizophrenia, Taq1A

ii

Abstract

Visual abnormalities, both at the sensory input and the higher interpretive

levels, have been associated with many of the symptoms of schizophrenia.

Individuals with schizophrenia typically experience distortions of sensory perception,

resulting in perceptual hallucinations and delusions that are related to the observed

visual deficits. Disorganised speech, thinking and behaviour are commonly

experienced by sufferers of the disorder, and have also been attributed to perceptual

disturbances associated with anomalies in visual processing. Compounding these

issues are marked deficits in cognitive functioning that are observed in

approximately 80% of those with schizophrenia. Cognitive impairments associated

with schizophrenia include: difficulty with concentration and memory (i.e. working,

visual and verbal), an impaired ability to process complex information, response

inhibition and deficits in speed of processing, visual and verbal learning. Deficits in

sustained attention or vigilance, poor executive functioning such as poor reasoning,

problem solving, and social cognition, are all influenced by impaired visual

processing. These symptoms impact on the internal perceptual world of those with

schizophrenia, and hamper their ability to navigate their external environment.

Visual processing abnormalities in schizophrenia are likely to worsen personal,

social and occupational functioning.

Binocular rivalry provides a unique opportunity to investigate the processes

involved in visual awareness and visual perception. Binocular rivalry is the

alternation of perceptual images that occurs when conflicting visual stimuli are

presented to each eye in the same retinal location. The observer perceives the

opposing images in an alternating fashion, despite the sensory input to each eye

remaining constant. Binocular rivalry tasks have been developed to investigate

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specific parts of the visual system. The research presented in this Thesis provides an

explorative investigation into binocular rivalry in schizophrenia, using the method of

Pettigrew and Miller (1998) and comparing individuals with schizophrenia to healthy

controls. This method allows manipulations to the spatial and temporal frequency,

luminance contrast and chromaticity of the visual stimuli. Manipulations to the rival

stimuli affect the rate of binocular rivalry alternations and the time spent perceiving

each image (dominance duration). Binocular rivalry rate and dominance durations

provide useful measures to investigate aspects of visual neural processing that lead to

the perceptual disturbances and cognitive dysfunction attributed to schizophrenia.

However, despite this promise the binocular rivalry phenomenon has not been

extensively explored in schizophrenia to date.

Following a review of the literature, the research in this Thesis examined

individual variation in binocular rivalry. The initial study (Chapter 2) explored the

effect of systematically altering the properties of the stimuli (i.e. spatial and temporal

frequency, luminance contrast and chromaticity) on binocular rivalry rate and

dominance durations in healthy individuals (n=20). The findings showed that altering

the stimuli with respect to temporal frequency and luminance contrast significantly

affected rate. This is significant as processing of temporal frequency and luminance

contrast have consistently been demonstrated to be abnormal in schizophrenia.

The current research then explored binocular rivalry in schizophrenia. The

primary research question was, “Are binocular rivalry rates and dominance durations

recorded in participants with schizophrenia different to those of the controls?” In

this second study binocular rivalry data that were collected using low- and high-

strength binocular rivalry were compared to alternations recorded during a

monocular rivalry task, the Necker Cube task to replicate and advance the work of

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Miller et al., (2003). Participants with schizophrenia (n=20) recorded fewer

alternations (i.e. slower alternation rates) than control participants (n=20) on both

binocular rivalry tasks, however no difference was observed between the groups on

the Necker cube task.

Magnocellular and parvocellular visual pathways, thought to be abnormal in

schizophrenia, were also investigated in binocular rivalry. The binocular rivalry

stimuli used in this third study (Chapter 4) were altered to bias the task for one of

these two pathways. Participants with schizophrenia recorded slower binocular

rivalry rates than controls in both binocular rivalry tasks. Using a ‘within subject

design’, binocular rivalry data were compared to data collected from a backward-

masking task widely accepted to bias both these pathways. Based on these data, a

model of binocular rivalry, based on the magnocellular and parvocellular pathways

that contribute to the dorsal and ventral visual streams, was developed.

Binocular rivalry rates were compared with performance on the Benton’s

Judgment of Line Orientation task, in individuals with schizophrenia compared to

healthy controls (Chapter 5). The Benton’s Judgment of Line Orientation task is

widely accepted to be processed within the right cerebral hemisphere, making it an

appropriate task to investigate the role of the cerebral hemispheres in binocular

rivalry, and to investigate the inter-hemispheric switching hypothesis of binocular

rivalry proposed by Pettigrew and Miller (1998, 2003). The data were suggestive of

intra-hemispheric rather than an inter-hemispheric visual processing in binocular

rivalry.

Neurotransmitter involvement in binocular rivalry, backward masking and

Judgment of Line Orientation in schizophrenia were investigated using a genetic

indicator of dopamine receptor distribution and functioning; the presence of the Taq1

v

allele of the dopamine D2 receptor (DRD2) receptor gene. This final study (Chapter

6) explored whether the presence of the Taq1 allele of the DRD2 receptor gene, and

thus, by inference the distribution of dopamine receptors and dopamine function,

accounted for the large individual variation in binocular rivalry. The presence of the

Taq1 allele was associated with slower binocular rivalry rates or poorer performance

in the backward masking and Judgment of Line Orientation tasks seen in the group

with schizophrenia.

This Thesis has contributed to what is known about binocular rivalry in

schizophrenia. Consistently slower binocular rivalry rates were observed in

participants with schizophrenia, indicating abnormally-slow visual processing in this

group. These data support previous studies reporting visual processing abnormalities

in schizophrenia and suggest that a slow binocular rivalry rate is not a feature

specific to bipolar disorder, but may be a feature of disorders with psychotic features

generally.

The contributions of the magnocellular or dorsal pathways and parvocellular or

ventral pathways to binocular rivalry, and therefore to perceptual awareness, were

investigated. The data presented supported the view that the magnocellular system

initiates perceptual awareness of an image and the parvocellular system maintains the

perception of the image, making it available to higher level processing occurring

within the cortical hemispheres. Abnormal magnocellular and parvocellular

processing may both contribute to perceptual disturbances that ultimately contribute

to the cognitive dysfunction associated with schizophrenia. An alternative model of

binocular rivalry based on these observations was proposed.

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Table of Contents

Keywords ...................................................................................................................... i

Abstract ........................................................................................................................ ii

List of Figures ............................................................................................................ xii

List of Tables ............................................................................................................. xiv

List of Abbreviations ................................................................................................. xvi

Statement of Original Authorship ............................................................................. xix

Acknowledgments ...................................................................................................... xx

CHAPTER 1: Literature Review - Visual Processing In Schizophrenia and Binocular Rivalry ......................................................................................................... 1

1.1 Schizophrenia ...................................................................................................... 1

1.2 Perceptual Disturbances in Schizophrenia .......................................................... 3

1.3 Delusional Experiences ....................................................................................... 4 1.3.1 Disorganised thoughts and behaviour. ...................................................... 5

1.4 Cognitive Deficits in Schizophrenia ................................................................... 6 1.4.1 Visual-evoked potentials in schizophrenia. ............................................... 7 1.4.2 Functional magnetic resonance imaging Studies (fMRI) in

schizophrenia. .......................................................................................... 10 1.4.3 Magnocellular and parvocellular visual pathways in schizophrenia. ...... 12 1.4.4 The cerebral hemispheres and schizophrenia. ......................................... 14 1.4.5 Neurotransmitters in schizophrenia. ........................................................ 14 1.4.6 Dopamine genes in schizophrenia. .......................................................... 16 1.4.7 Perceptual rivalry in schizophrenia. ........................................................ 17 1.4.8 Binocular rivalry in schizophrenia. ......................................................... 19

1.5 Binocular Rivalry .............................................................................................. 22 1.5.1 Stimulus parameters moderate binocular rivalry ..................................... 24

1.5.1.1 Spatial frequency....................................................................... 25 1.5.1.2 Movement. ................................................................................ 26 1.5.1.3 Luminance. ................................................................................ 26 1.5.1.4 Colour. ...................................................................................... 27 1.5.1.5 Orientation. ............................................................................... 27 1.5.1.6 Size. ........................................................................................... 28 1.5.1.7 Context. ..................................................................................... 28

1.6 Theories of Binocular Rivalry .......................................................................... 28 1.6.1 Bottom-up theories of binocular rivalry. ................................................. 29 1.6.2 Visual-evoked potentials (VEPs) in binocular rivalry ............................ 31

1.7 Top- down Theories of Binocular Rivalry ........................................................ 32 1.7.1 Single-cell studies. ................................................................................... 33 1.7.2 Imaging studies. ....................................................................................... 33 1.7.3 Eye-swapping methodologies. ................................................................. 34 1.7.4 Neurotransmitter involvement in binocular rivalry. ................................ 35 1.7.5 Monocular rivalry compared to binocular rivalry. .................................. 36

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1.8 Multi-level or Hierarchical Theories ................................................................ 36 1.8.1 Visual pathway theories of binocular rivalry .......................................... 37

1.8.1.1 Monocular and binocular pathways. ......................................... 37 1.8.1.2 Magnocellular and parvocellular pathways. ............................. 38

1.8.2 Inter-hemispheric theory of binocular rivalry. ........................................ 39

1.9 Summary and introduction to Chapters ............................................................ 41

CHAPTER 2: Altering Binocular Rivalry Rate by Increasing Luminance Contrast and Temporal Frequency: Support for an Oscillation Model of Binocular Rivalry .. 49

2.1 Binocular rivalry ............................................................................................... 49 2.1.1 Binocular rivalry rate. ............................................................................. 49 2.1.2 Dominance durations. ............................................................................. 52

2.2 Study 1 .............................................................................................................. 53 2.2.1 Aims. ....................................................................................................... 53 2.2.2 Hypotheses. ............................................................................................. 53

2.3 Method .............................................................................................................. 54 2.3.1 Participants. ............................................................................................. 54 2.3.2 Apparatus. ............................................................................................... 55

2.3.2.1 Binocular rivalry stimuli. .......................................................... 55

2.4 Design ............................................................................................................... 58

2.5 Procedure .......................................................................................................... 59

2.6 Statistical Analyses ........................................................................................... 60 2.6.1 Two-sided Smirnov test to compare dominance duration

distributions. ............................................................................................ 60

2.7 Results .............................................................................................................. 61 2.7.1 Binocular rivalry rate. ............................................................................. 61 2.7.2 Fast versus slow alternators (binocular rivalry rate). .............................. 64 2.7.3 Binocular rivalry dominance durations in fast and slow alternators. ...... 68

2.8 Discussion ......................................................................................................... 72 2.8.1 Binocular rivalry rates. ............................................................................ 72 2.8.2 Dominance durations. ............................................................................. 76 2.8.3 Age. ......................................................................................................... 78

2.9 Conclusion ........................................................................................................ 78

CHAPTER 3: Slower Binocular Rivalry Rates in Individuals with Schizophrenia Compared to Healthy Controls .................................................................................. 81

3.1 Binocular Rivalry Rate in Major Psychiatric Illness ........................................ 81

3.2 Study 2 .............................................................................................................. 85 3.2.1 Aims. ....................................................................................................... 85 3.2.2 Hypotheses. ............................................................................................. 86

3.3 Method .............................................................................................................. 86 3.3.1 Participants. ............................................................................................. 86

3.3.1.1 Healthy participants. ................................................................. 87 3.3.1.2 Participants with schizophrenia. ............................................... 87 3.3.1.3 Procedure .................................................................................. 89

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3.3.1.3.1 BINOCULAR RIVALRY TESTING. .................................................................... 89

3.3.1.3.2 PERCEPTUAL RIVALRY TESTING; THE NECKER CUBE. ................................... 90

3.4 Statistical Analyses ........................................................................................... 91

3.5 Results ............................................................................................................... 93 3.5.1 Binocular rivalry rate. .............................................................................. 93 3.5.2 Necker Cube alternation rates. ................................................................ 94 3.5.3 Normalised mean dominance durations. ................................................. 96

3.6 Discussion ......................................................................................................... 97 3.6.1 Binocular rivalry rates in schizophrenia. ................................................. 99 3.6.2 Monocular rivalry rates in schizophrenia. ............................................. 100 3.6.3 Distributions, gamma plots. ................................................................... 101 3.6.4 Effect of stimulus strength. ................................................................... 102 3.6.5 Diagnostic value of binocular rivalry rate. ............................................ 103 3.6.6 Physiological mechanisms for the slowing of binocular rivalry rate. ... 104 3.6.7 Effect of schizophrenia medication dose. .............................................. 105

3.7 Conclusion ...................................................................................................... 106

CHAPTER 4: Binocular Rivalry and Backward-Masking Tasks Reveal Pathway-Specific Abnormalities in Schizophrenia ................................................................. 108

4.1 Magnocellular and Parvocellular Pathways in Schizophrenia ........................ 108 4.1.1 Physiological differences in the magnocellular and parvocellular

pathways. ............................................................................................... 110 4.1.2 Magnocellular and parvocellular pathways in binocular rivalry. .......... 112

4.2 Study 3, Experiment 1: Assessing Binocular Rivalry in Schizophrenia Using Stimuli that Bias the Magnocellular and Parvocellular Visual Pathways ................ 114

4.2.1 Method. .................................................................................................. 115 4.2.1.1 Participants with schizophrenia. ............................................. 115 4.2.1.2 Control participants. ................................................................ 115 4.2.1.3 Binocular rivalry stimuli to bias the magnocellular and parvocellular pathways. ...................................................................... 116 4.2.1.4 Recording binocular rivalry. ................................................... 117

4.2.2 Statistical analyses. ................................................................................ 117 4.2.3 Results. .................................................................................................. 118

4.2.3.1 Binocular rivalry rate. ............................................................. 118 4.2.3.2 Dominance intervals. .............................................................. 121

4.2.4 Discussion related to magnocellular and parvocellular tasks. ............... 122 4.2.4.1 Binocular rivalry rates. ............................................................ 122 4.2.4.2 Dominance duration intervals. ................................................ 123 4.2.4.3 Gender differences. ................................................................. 127

4.3 A Backward-Masking Task Utilising Stimuli that Bias the Magnocellular and Parvocellular Visual Pathways ................................................................................. 129

4.3.1 Introduction. .......................................................................................... 129 4.3.1.1 Comparing binocular rivalry with other neurophysical tasks. 129 4.3.1.2 Development of the visual backward masking task. ............... 131 4.3.1.3 The visual backward masking task procedure. ....................... 133 4.3.1.4 Results of preliminary testing. ................................................ 134

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4.4 Experiment 2: Comparing Visual Backward Masking and Binocular Rivalry Tasks to Investigate Magnocellular and Parvocellular Processes. ........................... 136

4.4.1 Methods. ................................................................................................ 136 4.4.1.1 Schizophrenia participants. ..................................................... 136 4.4.1.2 Healthy controls. ..................................................................... 137 4.4.2.2 Binocular rivalry and visual backward masking stimuli. ...... 137

4.4.2 Statistical analyses. ............................................................................... 138 4.4.3 Results. .................................................................................................. 138

4.4.3.1 Binocular rivalry rates. ........................................................... 138 4.4.3.2 Dominance intervals. .............................................................. 140 4.4.3.3 Visual backward masking (VBM). ......................................... 141 4.4.3.4 Comparing binocular rivalry and visual backward masking results. ................................................................................................. 145

4.4.4 Discussion relating to visual backward masking. ................................. 147

4.5 General Discussion ......................................................................................... 150 4.5.1 A model of binocular rivalry based on visual backward masking

theory. .................................................................................................... 154

4.6 Conclusion ...................................................................................................... 159

CHAPTER 5: Benton’s Judgment Of Line Orientation - An Indicator of Visuospatial Ability In Schizophrenia ..................................................................... 161

5.1 The Right Hemisphere and Visuospatial Dysfunction ................................... 161

5.2 The Benton’s Judgment of Line Orientation Task ......................................... 163 5.2.1 Scoring the Benton’s Judgment of Line Orientation task. .................... 164

5.2.1.1 Global score. .......................................................................... 164 5.2.1.2 Error type. .............................................................................. 166 5.2.1.3 Individual line errors.............................................................. 167 5.2.1.4 Hemi-space errors. ................................................................. 167

5.3 Pilot Testing the Computer Version of BJLO and Alternative Scoring Systems168 5.3.1 Method. ................................................................................................. 170

5.3.1.1 Participants. ............................................................................. 170 5.3.1.2 Procedure. ............................................................................... 170

5.3.2 Results of pilot test ................................................................................ 171

5.4 Study 4, Benton’s Judgment of Line Orientation in Participants with Schizophrenia ........................................................................................................... 172

5.4.1 Aims. ..................................................................................................... 172 5.4.2 Method. ................................................................................................. 173

5.4.2.1 Participants with schizophrenia. ............................................. 173 5.4.2.2 Healthy control participants. ................................................... 173 5.4.2.3 Procedures. .............................................................................. 173

5.4.3 Statistical analyses. ............................................................................... 174 5.4.4 Results. .................................................................................................. 175

5.4.5.1 Global score analysis. ............................................................. 175 5.4.5.2 Error type analysis. ................................................................. 176 5.5.5.3 Line error analysis. ................................................................. 176 5.5.5.4 Hemi-space analyses. .............................................................. 177

5.5 Association between Benton’s Judgment of Line Orientation and binocular rivalry ....................................................................................................................... 177

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5.6. Global score ....................................................................................................... 178 5.7.1.1 Error type. ............................................................................... 182 5.7.1.2 Hemi-space.............................................................................. 183

5.7.2 Potential Impact of BJLO Performance ................................................. 184 5.7.2.1 Age and gender. ...................................................................... 184 5.7.2.2. Medication effects. ................................................................. 184 5.7.2.3 Schizophrenia sub-types and symptom ratings. ...................... 184 5.7.2.4 Cognitive ability. ..................................................................... 185

5.7.3 Comparing Benton’s Judgment of Line Orientation with Binocular Rivalry ................................................................................................... 185

5.7.4 Cortical Pathway and Hemispheric Models of Involvement ................. 186 5.7.4.1 Dorsal and Ventral Pathways .................................................. 186 5.7.4.2 The Cortical Hemispheres ....................................................... 187

5.6 Conclusion ...................................................................................................... 188

CHAPTER 6: Taq1 Allele of the DRD2 Dopamine Receptor Gene, Binocular Rivalry, Visual Backward Masking and Benton’s Judgment of Line Orientation ... 190

6.1 Dopamine in Vision ........................................................................................ 190 6.1.1 The A1 allele of the DRD2 receptor gene. ............................................ 191 6.1.2 The A1 allele of the DRD2 receptor in vision. ...................................... 194

6.2 Aims ................................................................................................................ 195

6.3 Method ............................................................................................................ 195 6.3.1 DNA collection and extraction. ............................................................. 195 6.3.2 Participants. ........................................................................................... 196

6.3.2.1 Control participants who participated in the binocular rivalry tasks in Study 1. .................................................................................. 197 6.3.2.2 Participants with schizophrenia and healthy controls who participated in binocular rivalry, Studies 2 and 3 and the Necker Cube task in Study 2 (Chapters 3 and 4). ..................................................... 197 6.3.2.3 Participants with schizophrenia and healthy controls who participated in visual backward masking tasks in Study 3 (Chapter 4).198 6.3.2.4 Participants with schizophrenia and healthy controls who participated in Benton’s Judgment of Line Orientation in Study 4 (Chapter 5). ......................................................................................... 198

6.4 Results ............................................................................................................. 199 6.4.1 Binocular rivalry results. ....................................................................... 199

6.4.1.1 Binocular rivalry in control participants in 16 stimulus Conditions from Study 1. .................................................................... 199 6.4.1.2 Binocular rivalry rates in low- and high-strength, magnocellular and parvocellular biased binocular rivalry tasks and the Necker cube.200

6.4.3 Benton’s Judgment of Line Orientation Task results. ........................... 200

6.5 Discussion ....................................................................................................... 204

CHAPTER 7: Overview, General Discussion and Conclusions ........................... 209

7.1 Overview and General Discussion .................................................................. 209 7.1.1 Exploring binocular rivalry rate. ........................................................... 209 7.1.2 Dominance durations. ............................................................................ 210

7.2 Neurotransmission and Binocular Rivalry: Does Dopamine Have a Role? ... 212

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7.3 Combining Theories to Produce a New Model of Binocular Rivalry ............ 213

7.4 Slower Binocular Rivalry and Visual Processing in Schizophrenia ............... 216

7.5 Limitations ...................................................................................................... 217

7.6 Implications for Future Research ................................................................... 223

7.7 Conclusion ...................................................................................................... 225

REFERENCES ......................................................................................................... 228 APPENDICES……………………………………………………………………..296 Appendix A: Backward Masking Task Instructions for Parvocellular VBM Task………………………………………………………………………………..296

Appendix B: Backward Masking Task Instructions for Magnocellular Visual Backward Masking (VBM) Task ............................................................................. 298

Appendix C: Effect of Schizophrenia Characteristics on Visual Backward Masking (VBM) Tasks ............................................................................................................ 300

Appendix D: Score Sheet - Benton’s Judgment of Line Orientation (BJLO) .......... 302

Appendix E. Benton Judgment of Line Orientation (BJLO) Performance Scores in Participants with Schizophrenia and Healthy Controls by A1 Allele of the DRD2 Receptor Gene. ......................................................................................................... 304

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List of Figures

Figure 2.1: Binocular rivalry rates by 20 participants across all stimulus conditions (n = 16). ...................................................................................... 62

Figure 2.2: Mean binocular rivalry rates (n = 20) across the 16 stimulus

conditions. .................................................................................................... 63

Figure 2.3: The effect of increasing stimulus strength on binocular rivalry rate

in ‘slow’ and ‘fast’ alternators: binocular rivalry rates recorded by 20 healthy volunteers grouped based on the participants mean binocular rivalry alternation rate, A. The effect of increasing stimulus strength by introducing movement to low and high luminance stimuli in fast (n=3) and slow (n=3) alternators. B. ............................................................ 67

Figure 2.4: The effect of stimulus strength on binocular rivalry rate: Binocular

rivalry rate increases as stimulus strength increases. ................................... 68

Figure 2.5:Cumulative frequency distributions of normalized dominance

durations recorded by fast alternators (n = 3) compared with slow alternators (n = 3) in 16 stimulus conditions. ............................................... 72

Figure 3.1: Mean alternation rates recorded in schizophrenia participants (n =

20, grey diamonds) compared healthy controls (n = 20, black squares) in two binocular rivalry tasks. ...................................................................... 95

Figure 3.2: Normalised mean dominance durations (the time intervals between

button pushes (in seconds)/mean) plotted as cumulative distributions. ....... 98

Figure 4.1:Binocular rivalry rates recorded in participants with schizophrenia

(black triangles) compared to healthy controls (black diamonds). ............ 120

Figure 4.2: Difference between the dominance durations of participants with

schizophrenia (black lines) and healthy control participants (grey lines) for (A) the magnocellular binocular rivalry (BR) task and (B) the parvocellular BR task. .......................................................................... 124

Figure 4.3: Binocular rivalry (BR) rates recorded in participants with schizophrenia (black triangles) compared to healthy controls (black diamonds). .................................................................................................. 140

Figure 4.4: The dominance durations between participants with schizophrenia

(black lines) compared to healthy participants (grey lines) for (A) magnocellular binocular rivalry (BR) task and (b) parvocellular BR task. ............................................................................................................ 143

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Figure 4.5: Number of correct responses as a function of inter-stimulus interval in healthy controls and participants with schizophrenia for (A) magnocellular visual backward-masking(VBM) and (B) parvocellular VBM tasks. ................................................................................................ 144

Figure 4.6: The hypothesised time course of activation of transient and

sustained channels after a brief presentation of a stimulus. ....................... 151

Figure 4.7: The time course of the transient and sustained channels when the

target precedes the mask (backward masking). ......................................... 152

Figure 4.8: Transient (magnocellular) neurons inhibit sustained ones via

internuncial neurons at the lateral geniculate nucleus (LGN) and cortex. The impulse response by the internuncial neuron is initiatory at the postsynaptic potential and integrates with the sustained neuron at either the LGN or cortex. ........................................................................... 155

Figure 4.9: A revised model of binocular rivalry with rapid magnocellular

response followed by the parvocellular response to continuous stimuli (vertical and horizontal lines) in the right and left eyes respectively at corresponding retinotopic areas. ................................................................ 158

Figure 5.1: An item from the Benton’s Judgement of Line Orientation (BJLO)

task. ............................................................................................................ 165

Figure 6.1: Benton’s Judgement of Line Orientation (BJLO) line error scores

according to the presence of the A1 allele in subjects with (a) schizophrenia and (b) healthy controls. ..................................................... 206

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List of Tables

Table 2.1: The Kolmogorov-Smirnov goodness of fit analysis statistics for the dominance duration distributions for fast and slow alternators over 16 stimulus conditions (n=20). .......................................................................... 70

Table 2.2: The two-sided Smirnov test statistic for fast and slow alternators (m

and n respectively) compared with the critical values determined by of T1 at the 0.95 quantile (w0.95 ≈1.36√ m+n/ mn) across the 16 test binocular rivalry stimuli conditions (n=20). ................................................ 71

Table 3.1: Age, gender, eye dominance and NART scores of controls and

participants with schizophrenia .................................................................... 88

Table 3.2: Smirnov test statistic for participants with schizophrenia (n=20) and

controls (n=20). ............................................................................................ 97

Table 4.1: Age, gender, eye dominance and NART score of participants with

schizophrenia and controls ......................................................................... 116

Table 4.2: Smirnov test results indicating differences in the distribution of

dominance durations between participants with schizophrenia (n=17) and controls (n=24) for both magnocellular and parvocellular binocular rivalry (BR) tasks. ...................................................................... 121

Table 4.3: Correct target letter identification by location and letter in a

preliminary test of the magnocellular and parvocellular visual backward masking (VBM) task (n = 5). .................................................... 135

Table 4.4: Age, gender, eye dominance and NART score of controls and

participants with schizophrenia. ................................................................. 137

Table 4.5: Differences in the distribution of dominance durations between

participants with schizophrenia and controls in magnocellular and parvocellular binocular rivalry (BR) tasks: Smirnov test outcomes of dominance duration distributions. .............................................................. 141

Table 4.6: Differences in correct identification of a target scores in

magnocellular and parvocellular visual backward- masking (VBM) tasks between participants with schizophrenia and healthy controls at four inter-stimulus intervals (ISI) .............................................................. 142

Table 4.7: Correlations between magnocellular and parvocellular binocular

rivalry (BR) rates (in Hz) with magnocellular and parvocellular visual backward masking (VBM) correct scores (Spearman’s correlation coefficient rho). .......................................................................................... 146

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Table 5.1: Method of analysing Benton’s Line of Judgement Orientation (BJLO) results as per (Ska ......................................................................... 169

Table 5.2: Age, gender, eye dominance and NART score of participants with

schizophrenia and Controls. ....................................................................... 174

Table 5.3: Benton’s Judgement of Line Orientation (BJLO) data for control

participants and participants with schizophrenia: mean global scores (out of 30 and 60), line error scores and hemi-space errors for the BJLO task. .................................................................................................. 179

Table 5.4: Benton’s Judgement of Line Orientation (BJLO) data for healthy

control participants and participants with schizophrenia: error type in the BJLO task ............................................................................................. 180

Table 5.5: Correlations between global Benton’s Judgement of Line

Orientation (BJLO) scores and binocular rivalry (BR) rates for stimuli that bias the BR task for either the magnocellular or parvocellular visual pathways (spearman rank order). .................................................... 181

Table 6.1: Demographic characteristics of participants genotyped for the

presence of the Taq1 A DRD2 alleles receptor for studies 2, 3 and 4. ...... 199

Table 6.2: Binocular rivalry rates recorded by A1+ healthy participants (n = 5)

compared A1- healthy participants (n = 11) over the 16 stimulus conditions. .................................................................................................. 201

Table 6.3: Binocular rivalry rates recorded by A1+ and A1- participants using

binocular rivalry tasks with high and low strength stimuli, magnocellular and parvocellular biased stimuli and the Necker Cube ...... 202

Table 6.4: Correct scores in backward masking tasks that bias magnocellular

and parvocellular visual pathways at 4 inter-stimulus intervals (ISI) recorded by A1+ and A1- participants with schizophrenia. ...................... 206

Table 6.5: Correct scores in backward masking tasks that bias magnocellular

and parvocellular visual pathways at 4 inter-stimulus intervals (ISI) recorded by A1+ and A1- control participants .......................................... 205

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List of Abbreviations

A1+ Positive for the presence of the A1 allele of the DRD2 receptor gene

A1- Negative for the presence of the A1 allele of the DRD2 receptor gene

BJLO Benton’s Judgement of Line Orientation

BOLD Blood-oxygenation level dependent

bp Base pairs

BPD Bipolar Disorder

BPRS Brief Psychiatric Rating Scale

BR Binocular Rivalry

c/d Cycles per degree

COMT Catechol-O-methyl transferase

CNTRICS Cognitive Neuroscience Treatment Research to Improve Cognition in

Schizophrenia

cpd Cycles per degree of visual angle

c/s Cycles per second

CPZE Chlorpromazine equivalents

deg Degrees

dLGN Dorsal Lateral Geniculate Nucleus

DSM-IV Diagnostic and Statistical Manual of Mental Disorders – Edition 4

DRD2 Dopamine D2 receptor

DSA Dichoptic stimulus alternation

EEG Electroencephalography

ERP Event related potential

fMRI Functional Magnetic Resonance Imaging

GABA Gamma-Aminobutyric acid

xvii

H Horizontal

Hz Hertz

ISI Inter-stimulus interval

LGN Lateral Geniculate Nucleus

msec Milliseconds

MEG Magnetoencephalography

MRI Medical resonance imaging

MT Middle Temporal visual area (also referred to as V5)

N Negative

NART National Adult Reading Test

NMDA N-methyl-D-aspartic acid

PANSS Positive and Negative Schizophrenia Syndrome scale

P Positive

PET Positron emission tomography

PTSD Post-traumatic stress disorder

SCID Structured Clinical Interview for DSM-IV

Sec Seconds

t-VEP Transient visual-evoked potential

VBM Visual Backward Masking

VEP Visual Evoked Potential

V1 Visual area 1, the extra striate cortex (also known as the primary

visual pathway)

V2 Visual area 2, the pre-striate cortex

V3 Visual area 3

V4 Visual area 4

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V5 Visual area 5 (also known as the middle temporal visual area)

5-HT Serotonin

xix

Statement of Original Authorship

The work contained in this Thesis has not been previously submitted to meet

requirements for an award at this or any other higher education institution. To the

best of my knowledge and belief, the Thesis contains no material previously

published or written by another person, except where due reference is made.

Name: Karen Ruth Heslop

Signature: …………………..

Dated: …………………..

xx

Acknowledgments

I would like to acknowledge the support, guidance, scholarly advice and

encouragement offered by Professor Ross Young and Associate Professor and

Katrina Schmid. I also wish to thank them both for providing practical support and

the many hours they spent reviewing my written work and providing constructive

feedback that helped with the direction of the project.

I would also like thank Dr Bruce Lawford for his infectious enthusiasm for

genetics, schizophrenia and research, and Dr Simon Burton for his clinical insights,

moral support and his assistance in developing many of the tasks.

Thank you also to the individuals who participated in this research as part of

the clinical group, and to my friends, colleagues and fellow students who acted as

controls and spent many hours in dimly-lit rooms, wearing strange goggles and

pushing buttons on a computer keyboard in response to some lines on a screen.

I wish to also thank Dr Steven Miller, Dr Guang Bin Lui and Professor Jack

Pettigrew whose work initially inspired me to investigate this fascinating

phenomenon, and for making the binocular rivalry task available to me. Thank you

also to Professor Stan Catts and Professor Laurie Geffen for their valued

contributions early in the project, and to Associate Professor Jason O’Connor and Dr

Cameron Hurst for their statistical advice.

Most of all I wish to thank Brett for his continued support and patience.

Literature Review - Visual Processing in Schizophrenia and Binocular Rivalry 1

1.1 Schizophrenia

Schizophrenia is a complex brain disorder characterised by cognitive

dysfunction that causes long-term disability, altered sensory perception,

dysregulation of emotion and disturbed behaviour (Brenner, Krishnan, Vohs, Ahn,

Hetrick & Morzorati, 2009). Despite many years of research into the disorder

spanning the disciplines of the physical, psychological and neurological sciences,

genetic and epidemiological research, there is no one theory that satisfactorily

explains the symptoms or pathophysiology of schizophrenia. While advances in the

field of neurosciences, and brain imaging have provided key insights into this

disorder many fundamental questions remain unanswered.

It is generally agreed that sufferers experience both subjective sensory

anomalies and objective deficits of sensory function (Brenner et al., 2009) that

contribute to many of the symptoms of schizophrenia. Symptoms of schizophrenia

include visual, auditory and olfactory hallucinations associated with distortions of

sensory perception (Andreasen, Arndt, Alliger, Miller & Flaum, 1995; Butler,

Silverstein & Dakin, 2008) and delusions or firmly-held false beliefs that result from

mis-interpretations of these perceptions and personal experiences (Frith, & Dolan,

1997). Sufferers may also experience disorganised speech, thinking and behaviour,

agitation, social dis-inhibition and bizarre behaviours (Andreasen et al., 1995).

Many individuals with schizophrenia experience a reduced intensity range of

emotional expression (affective flattening), poverty of speech (alogia), a reduction or

inability to initiate and maintain goal-directed behaviour (avolition) and a marked

decrease in reaction to the immediate surrounding environment (Cadenhead, Geyer,

Chapter 1: Literature Review - Visual Processing in Schizophrenia and Binocular

Rivalry

2 Literature Review - Visual Processing in Schizophrenia and Binocular Rivalry

Butler, Perry, Sprock & Braff, 1997; Uhlhaas, Phillips & Silverstein, 2005). The

symptoms of schizophrenia impact on the individuals’ internal world and hamper

their ability to navigate their external environments and impair their overall

functioning (Couture, Granholm & Fish, 2010). Therefore, individuals with

schizophrenia experience poorer social and occupational functioning compared to

their unaffected peers (Peuskens, Demily & Thibaut, 2005; Tan, 2009; Tsang, Leung,

Chung, Bell & Cheung, 2010).

Compounding these issues are marked deficits in cognitive functioning.

Cognitive impairment is considered a core feature of schizophrenia, with more than

80% of patients showing significant impairment (Bora, Yucel & Pantelis, 2010).

Cognitive deficits associated with schizophrenia include: difficulty with

concentration and memory (i.e. working, visual and verbal), the limited ability to

process complex information, response inhibition, and deficits in speed of

processing, visual and verbal learning. Those with schizophrenia also experience

difficulty with sustained attention or vigilance, and difficulties in executive function

such as reasoning, problem solving and social cognition (Bora, Yucel, & Pantelis,

2010; Green, 2006; Tomás, Fuentes, Roder & Ruiz, 2010).

Researchers investigating visual abnormalities in schizophrenia, that are known

to contribute to cognitive deficits and perceptual disturbance characteristic of the

disorder, generally subscribe to either “top-down” or “bottom-up” theories (see

Butler, Silverstein & Dakin, 2008; Javitt, 2009; Piskulic, Oliver, Norman & Maruff,

2007, for reviews). Traditionally, the perceptual visual disturbances in schizophrenia

have been viewed as being consequential to “top-down” processing (Frith & Dolan,

1997; Gilbert & Sigman 2007; Grossberg, 2000; Kveraga, Ghuman & Bar, 2007;

Laycock, Crewther & Crewther, 2007) where disturbances in localised cortical


regions diminish cognitive processing, attention, memory and executive functioning

and ultimately affect social functioning and outcomes (Javitt, 2009). However, the

focus in schizophrenia research has shifted toward perceptual disturbances,

abnormalities early in the visual pathway, and their contributions to higher cognitive

deficits (Bulter et al., 2005; Butler, Martinex, Foxe, Kim, Zemon, Silipo, Mahoney,

Shpaner, Jalbrzikowski & Javitt, 2007; Javitt, 2009; Martinez, Hillyard, Dias, Hagler,

Butler, Guilfoyle, Jalbrzikowski, Silipo & Jarvitt, 2008).

1.2 Perceptual Disturbances in Schizophrenia

Individuals with schizophrenia have marked deficits in detecting low-contrast

visual stimuli (Keri, Antal, Szekeres, Benedek & Janka, 2000; Keri & Benedek,

2007), stimuli with low luminance and spatial frequencies, and stimuli presented at

varying temporal speeds (or pulsing stimuli) (Chen, Levy, Matthysse, Holzman &

Nakayama, 2000; Keri, Antal, Benedek & Janka, 2000; Keri, Antal, Szekeres,

Benedek & Janka, 2000; Schwarts, McGinn & Winstead, 1987; Schwartz, Mallot &

Winstead, 1988; Slaghuis, 1998; Slaghuis & Bishop, 2001; Slaghuis & Thompson,

2003; Slaghuis, 2004). Such deficits in perception reduce the individual’s ability to

identify salient visual information in day-to-day situations (Poirel, Brazo, Turbelin,

Lecardeur, Simon, Houde, Pineau & Dollfus, 2010). Damage to sensory processing

areas, that allow prior knowledge of a sensory input to be related to random

incoming sensory information (Frith & Dolan, 1997), may inhibit the correct

identification of visual stimuli, resulting in sensory hallucinations. These perceptual

disturbances involve aberrant cortical activations of networks at differing levels of

complexity in the brain (Jardri, Pouchet, Pins & Thomas, 2010). Dysfunction in the

posterior area of the brain that mediates visual perceptual processing (the primary

visual cortex) has been implicated in object and visual spatial perceptions that are


frequently noted in schizophrenia (Tek, Gold, Blaxton, Wilk, McMahon &

Buchanan, 2002). Prefrontal areas that are involved in maintaining information

during short delay intervals between visual stimuli are also affected in schizophrenia

(Tek et al., 2002).

1.3 Delusional Experiences

Sensory gating abnormalities (i.e. the ability to ignore irrelevant information

while focusing on a salient features) that are related to perceptual and attentional

mechanisms, have been reported by individuals with schizophrenia (Hetrick,

Erickson & Smith, 2010). Poor sensory gating, together with a reduction in the

quality of sensory input, results in a heightened awareness of background stimuli and

poor selective attention. Therefore, individuals with schizophrenia often have

difficulty correctly identifying the source of a perceptual stimulus, filtering out

unimportant information and interpreting sensory perceptions to determine a context

for the incoming stimuli. The individual may thus misinterpret sensory information;

believing external forces are controlling their actions or thoughts, or thinking that

they can control events that are not under their control (Voss, Moore, Hauser,

Gallinat, Heinz & Haggard, 2010). Failure to correctly make this distinction may

account for the strong association between hallucinations and paranoid delusions in

schizophrenia; the person with schizophrenia not only hears voices or misinterprets

visual stimuli, but attributes (usually hostile) intentions to these voices and visual

experiences (Frith & Dolan, 1997). Prior knowledge, or memory of sensory input,

enables us to distinguish our own actions from those of independent agents in the

outside world. Many theorists posit that delusional disturbances are related to a mis-

match between predicted and actual sensory feedback that relies on an intact central

comparator mechanism (Voss et al., 2010).


The visual environment consists of global features (for example, a forest) and

local features (for example a tree). Global visual information provides the context in

which local information is interpreted. For example, a tree in a forest appears to be

in context, while a tree in a kitchen of a house is considered out of context. It has

been suggested that individuals with schizophrenia have difficulty processing global

information and therefore context, and tend to focus more on local features (Poirel et

al., 2010) therefore resulting in a local bias. This local bias leads to an incorrect

interpretation of visual information.

1.3.1 Disorganised thoughts and behaviour.

Individuals with schizophrenia require greater delays between two temporally

presented images in order to detect the two discrete images. When images are

separated by only 90-150 millisecond (msec) intervals they tend to view temporally-

modulated images as continuous presentations (Schwartz, Evans, Pena & Winstead,

1994). Tasks that require observers to identify a blank image (an inter-stimulus

interval) between two sinusoidal gratings (Schwartz & Winstead, 1998; Schwartz, et

al., 1994) or between two flashed stimuli consistently separate those with

schizophrenia from healthy controls (Schwartz, Satter, O’Neill & Winstead, 1990;

Schwartz & Winstead, 1988; Schwartz, et al., 1994). These abnormally-long inter-

stimulus intervals have been correlated with disorganised thoughts and behaviours in

schizophrenia (Norton, Ongur, Stromeyer & Chen, 2008).

Furthermore, the visual motion pathway that includes a local and a global

processing stage, each of which has distinct neural substrates, is disrupted in

schizophrenia. In schizophrenia, global (but not local) processing stage of the visual

motion system is compromised. These motion-sensitive brain areas are abnormal in

schizophrenia. These areas possess large receptive fields for spatial and temporal


integration, such as the middle temporal and medial superior temporal areas (Chen,

Nakayama, Levy, Matthysse & Holzman, 2003). These regions are integral for the

detection of motion and spatial orientation, the shifting of attention and orientating

oneself during self-movement (Duffy and Wurtz, 1997). Such abnormalities may

manifest in schizophrenia as disorganised or slowed thinking, difficulty with

understanding, expressing and integrating thoughts, feelings and behaviours. These

deficits are generally thought to be related to deficits in the neural pathways that

relate to the sequencing of information or timing of neural information flow

(Andreasen et al., 1995; Barrett, Mulholland, Cooper & Rushe, 2009; Couture,

Granholm & Fish, 2010).

1.4 Cognitive Deficits in Schizophrenia

Cognitive deficits are thought to be related to higher-order sensory deficits.

Current neurophysiological models suggest deficits in cognitive processing are due

to impairments in basic perceptual processes that localise to primary sensory brain

regions (Butler, Martinez, Foxe, Kim, Zemon, Silipo, Mahoney, Shpaner,

Jalbrzikowski & Javitt, 2007; Butler, Schechter, Zemon, Schwartz, Greenstein,

Gordon, Schroeder & Javitt, 2001; Javitt, 2009).

The ability to track visual information allows us to efficiently process and

interpret incoming visual information which is essential for effective interaction with

our external environment. In schizophrenia, abnormal eye tracking is hypothesised

to be a fundamental component of the perceptual disturbance and abnormal cognitive

processing associated with the disorder (Javitt, 2009). Eye tracking abnormalities

have been observed in working memory (Levin et al; 1988; Park & Holzman, 1993;

Sereno & Holzman, 1995). These abnormalities have also been evident in cognitive

processing tasks (Campanella & Guerit, 2009; Litman et al., 1991; Solomon,


Holzman, Levin & Gale, 1997), contrast and velocity discrimination (Chen, Levy, et

al., 1999) and motion detection (Chen, Nakayama, Levy Matthysse & Holzman,

2003) in schizophrenia. Importantly, they are independent of medication effects

(Grawe & Levander, 1995; Holzman, O’Brian & Waternaux, 1991; Litman et al.,

1989; Litman, Hommer, Radant, Clem & Pickar, 1994) and severity of illness

(Bartifai, Levander, Nyback, Berggren & Schalling, 1995). These abnormalities may

reflect a failure of cortical and/or cerebellar function in areas coordinating saccadic

and pursuit eye movements during visual tracking (Avila, Weiler, Lahti, Tamminga

& Thaker, 2002; Hong et al., 2005; O’Driscoll et al., 1998) or magnocellular deficits

(Laycock, Crewther & Crewther, 2008; Schwartz, Maron, Evans & Winstead, 1996b)

Cognitive deficits associated with schizophrenia are also likely to be related

to abnormalities in the architecture or structure of the brain, or dysfunction in the

structures or mechanisms associated with information processing. These include the

neural pathways and neurotransmitters involved in visual processing. There have

been many advances in the scientific investigation into visual processing that have

provided new insights into schizophrenia. Investigations of brain function by

measuring visual-evoked potentials, using functional magnetic resonance imaging

(fMRI) to investigate visual pathways and the cortical hemispheres have made a

significant contribution over the recent decades. Investigations into the

neurotransmitters and the genetic determinants of neurotransmission have also

gathered momentum.

1.4.1 Visual-evoked potentials in schizophrenia.

A visual-evoked potential (VEP) is an electrical potential (forming either

positive [P] or negative [N] waves when detected by electroencephalography or

EEG), that is generated within the visual system following the presentation of a


stimulus. Reduced amplitude in positive P100 waves (Doniger, Foxe, Murray,

Higgins & Javitt, 2002; Schechter et al., 2005; Thompson & Drasdo, 1992; Vohs et

al., 2008; Yeap et al, 2008), P300 and C100 waves, negative N100 amplitudes

(Doniger et al., 2002; Schechter et al., 2005; Vohs et al., 2008) and prolonged P300b

latency (Vohs, et al., 2008) have been observed in individuals with schizophrenia and

their siblings (Groom et al., 2008). Although a feature of schizophrenia, abnormal

P300 amplitudes are thought to be more characteristic of functional psychosis in

general, rather than being specific to schizophrenia (Bestelmeyer, Phillips, Crombie,

Benson & St Clair, 2009).

Visual-evoked potentials can also be measured in response to particular stimuli

to further investigate specific visual abnormalities. For example, altered VEP spatial

frequency functions have been observed in schizophrenia (Clementz, Wang & Keil,

2008; Celesia & Toleikis, 1991). Abnormal VEPs in tasks using stimuli that

preferentially stimulate magnocellular or parvocellular pathways have been observed

in schizophrenia (Butler et al., 2001; Butler et al., 2005; Butler et al., 2007; Kim,

Wylie, Pasternak, Butler & Javitt, 2006). These findings confirm the existence of

early-stage visual processing dysfunction in schizophrenia (Butler et al., 2005).

Abnormal steady-state VEPs (evoked potentials measured during continuous

stimulation) have been observed in schizophrenia during visual processing of

complex visual tasks. P300b amplitudes have been observed to be lower in the

parietal regions in identity and happiness tasks (in those with schizophrenia

compared to controls using an oddball paradigm to evaluate face identity recognition

and facial emotional recognition of happiness and fear) (Ramos-Loyo, Gonzalez-

Garrido, Sanchez-Loyo, Medina & Basar-Eroglu, 2009). This implicates higher-

order processing. It has been proposed that abnormal N250 suggests that those with


schizophrenia are less efficient at decoding features of facial affect (Wynn, Lee,

Horan & Green, 2008). Individuals with schizophrenia showed abnormal P100 and

N170 responses to spatial frequency changes in faces, thus demonstrating decreased

ability to process facial features (Obayshi et al., 2009). P100 amplitude reductions

that occur early in visual processing have been implicated in working memory

deficits and have been observed in adolescents with schizophrenia and are a feature

of early onset psychosis (Haenschel et al., 2007). These disruptions of visual steady-

state responses in schizophrenia are consistent with neuropathological and medical

resonance imaging (MRI) evidence of anatomic abnormalities in visual cortices

(Brenner et al., 2009). Visual-evoked potentials (and contrast sensitivity measures)

significantly predict community functioning in schizophrenia (Butler et al., 2005),

suggesting that abnormal visual processing contributes to the fundamental cognitive

decline and perceptual disturbances seen in the disorder.

In schizophrenia, event-related brain potentials have revealed reduced inter-

hemispheric co-operation and slower corpus-callosal transfer times when information

is presented to the right hemisphere. Visual information appears to require more time

to cross from the right to the left hemisphere for analysis, thereby reducing the speed

of visual information processing in these individuals (Endrass, Mohr & Rockstroh,

2002; Mohr, Pulvermuller, Rockstroh & Endrass, 2008; Schwartz, Winstead &

Walker, 1984). Significant correlation between left- and right-hand bisection errors

and loss of callosal integrity (McCourt, Shpaner, Javitt & Foxe, 2008) is suggestive

of abnormal connectivity between frontal and parietal circuits (Frecska, White &

Luna, 2004) in schizophrenia. Slow transfer speed and lack of connectivity may

contribute to thought disorder, poverty of thought and prominent perceptual

hallucinations (McCourt et al., 2008). This abnormal connectivity between cortical


regions renders individuals with schizophrenia less able to predict the relation

between ‘action’ and ‘effect’. This difficulty strongly correlates with severity of

positive psychotic symptoms, specifically delusions and hallucinations (Voss et al.,

2010).

Andreasen, Paradiso and O'Leary (1998) postulated that a cortico-cerebellar-

thalamic-cortical brain circuit is responsible for fluid, temporal coordination of

sequences of behaviour. The cognitive fragmentation, or thought disorder, in

schizophrenia is likely to be due to timing anomalies associated with cortico-

cerebellar-thalamic-cortical brain circuit dysfunction (Bolbecker, Mehta, Edwards,

Steinmetz, O'Donnell & Hetrick, 2009). This has been termed ‘cognitive dysmetria’;

meaning difficulty in prioritising, processing, coordinating, and responding to

information. This ‘poor mental coordination’ is a fundamental cognitive deficit in

schizophrenia, and can account for its broad diversity of symptoms (Andreasen et al.,

1998). A meta-analysis of published functional neuroimaging studies showed that

individuals with schizophrenia have lower activation of most right-hemisphere

regions of the cortico-cerebellar-thalamic circuit; a pattern that further indicates poor

connectivity between brain regions (Ortuno, Guillen-Grima, Lopez-Garcia, Gomez &

Pla, 2010). This timing circuit may be connected with cognitive tasks also known to

be abnormal in schizophrenia (Andreasen & Pierson, 2008).

1.4.2 Functional magnetic resonance imaging Studies (fMRI) in schizophrenia.

Functional magnetic resonance imaging studies (fMRI) reveal that individuals

with schizophrenia, and their biological relatives, generate a greater number of

leading saccades during smooth-pursuit eye movement (Schwartz, O’Brien, Evans,

Sautter & Winstead, 1995; Schwartz et al., 1995). Slowed initial pursuit velocity,

more errors in pursuit tasks (Radant, Claypoole, Wingerson, Cowley & Roy-Byrne,


1997; Radant & Hommer, 1992), and abnormal saccadic eye movements (Mather,

1986; Mather & Putchat, 1984; Schreiber et al., 1995) may reflect a trait for the

disorder (Bender, Weisbrod & Resch, 2007; Holzman, 1987; Keri & Janka, 2004;

Kinney, Levy, Yurgelun-Todd, Kajonchere & Holzman 1999; Levy, Holzman,

Matthysse & Mendell, 1994; Levy, Holzman, Matthysse & Mendell, 1993; Thaker,

2008). This is supported by twin studies (Holzman et al., 1988; Holzman, Levy,

Matthysse & Abel, 1977; Litman et al., 1997) where children with childhood-onset

schizophrenia exhibit a pattern of eye-tracking abnormalities similar to that seen in

adults with schizophrenia (Kimra et al., 2001). These abnormalities have been

associated with the compromised ability of individuals with schizophrenia to process

new and complex information (Schwartz et al, 1995).

Abnormalities in motion detection have been demonstrated using fMRI (Chen,

Levy et al., 1999; Chen, Palafox et al., 1999; Chen, Levy, Sheremata & Holzman,

2004; Chen et al., 2008; Low, Rockstroh, Elbert, Silberman & Bentin, 2006). Global

(direction of random dot patterns) rather than local (detection of moving gratings)

stages of the visual-motion processing system are impaired in those with

schizophrenia. Motion-sensitive brain areas, such as the middle temporal area and

medial superior temporal areas, where processing of large receptive fields for spatial

and temporal integration occurs (Chen, Makayama et al., 2003) are implicated in

schizophrenia. Signal changes detected by blood oxygen level dependence (BOLD)

fMRI in motion-detection tasks, consistent with cortical activation, were significantly

reduced in the middle temporal area (MT) and significantly increased in the inferior

prefrontal cortex (an area normally involved in higher-level cognitive processing).

This shift in cortical response from posterior to prefrontal regions suggests that


motion perception in schizophrenia is associated with both deficient sensory

processing and compensatory cognitive processing (Chen et al., 2008).

Individuals with schizophrenia demonstrate temporal resolution deficits when

processing sequential information, such as moving dots, gratings or letters (Schwartz,

Maron, Evans & Winstead, 1999a) and tasks involving visuospatial working memory

(Bollini, Arnold & Keefe, 2000; Silver & Goodman, 2008). When the attentional

load of a visual monitoring task in schizophrenia was measured during fMRI

selective visual processing was integrated in posterior parietal areas, rather than the

earlier occipital cortex (Schwartz et al., 2004). These factors may be manifested as

the misinterpretation of visual (and other) perceptual stimuli commonly observed in

psychosis. Relative to control subjects, fMRI reveals that patients with

schizophrenia show markedly-reduced activation to low, but not high spatial

frequencies in multiple regions of the occipital, parietal, and temporal lobes

(Martinez et al., 2008). Low spatial frequency processing is suggestive of disrupted

magnocellular processing, necessary in locating and identifying moving visual

stimuli, that contributes to the perceptual and cognitive disturbances associated with

schizophrenia (Chen et al., 2008; Laycock, Crewther & Crewther, 2008).

1.4.3 Magnocellular and parvocellular visual pathways in schizophrenia.

Abnormalities associated with magnocellular (or ‘transient’) visual pathways

have been consistently reported in schizophrenia (Butler et al., 2001; Cadenhead,

Serper & Braff, 1998; Green, Nuechterlein & Mintz, 1994b; Green, Nuechterlein,

Mintz, 1994a; Kim et al., 2006; Schwartz & Winstead, 1998; Schwartz et al., 1994;

Slaghuis & Curran, 1999). Some have suggested that magnocellular pathway deficits

are an endophenotype for schizophrenia (Bedwell & Orem, 2008; Butler, Harkavy-

Friedman, Amador & Gorman, 1996; Green, Nuechterlein & Breitmeyer, 1997;


Buttner et al., 1999; Hayashi, 2000; Holzman, 1987; Keri, Bendek & Janka, 2001;

Keri, Szendi, Kelemen, Benedek & Janka, 2000; Keri, Kelemen, Benedek & Janka,

2004; McClure, 2001).

The magnocellular (or ‘transient’) visual pathway integrates dynamic visual

information regarding the position and spatial relationships of visual stimuli. In

broad terms, this is the attention-capturing pathway (Schwartz et al., 1988). In

schizophrenia, the transient (or magnocellular) pathways are thought to be either

impaired or over-active, interrupting the neural processing of the sustained (or

parvocellular) visual pathway (Butler et al., 2003). Over-active magnocellular

pathways correlate with poor selective attention, poor concentration, heightened

awareness of background noise and distractibility (Butler et al., 2003). Individuals

with schizophrenia have difficulty filtering sensory information related to importance

(Hetrick, Erickson & Smith, 2010). These features are the most-frequently

associated symptoms of the disorder.

To investigate these abnormalities, experimental techniques have been

developed to assess early visual magnocellular or parvocellular pathway processing

that contributes to higher-order cognitive impairments. Many researchers have

observed deficits in magnocellular pathway processing in subjects with

schizophrenia using frequency-doubling tasks, (Keri et al., 2004) steady-state VEPs

(Kim et al., 2006) and backward masking tasks (Green & Nuechterlein, 1999; Green

Nuechterlein, Breitmeyer & Mintz, 1999; McClure, 2001; Nuechterlein, Dawson &

Green, 1994; Rund & Landra, 1990; Skottun & Skoyles, 2009). However, not all

researchers report magnocellular abnormalities in schizophrenia (Skottun & Skoyles,

2007). Delord et al., (2006) found no magnocellular dysfunction in participants with

schizophrenia using a four-alternative forced-choice luminance discrimination task; a


task hypothesised to access visual processes early in the visual pathways. They

concluded that if magnocellular dysfunction is a feature of schizophrenia, the

abnormality is likely to reflect integrative processes at higher cortical levels where

the magnocellular and parvocellular paths interact.

1.4.4 The cerebral hemispheres and schizophrenia.

Schizophrenia is generally thought to involve disturbance of right hemisphere

mechanisms involved in spatial perception and sustained attention (Evans &

Schwartz, 1997; O’Donnell et al., 2002). In right-handed individuals with

schizophrenia, the left hemisphere is superior for temporal sequential analysis

(Schwartz et al., 1984). Subtle right-hemisphere dysfunction has been noted in

individuals diagnosed with schizophrenia, and in individuals at high risk for

schizophrenia (Leib et al., 1996). Others have observed laterality differences that

suggest the left hemisphere may be less efficient than the right (Holzman, 1987).

Spatial working memory deficits are more severe in the left hemisphere in patients

with schizophrenia and in 'psychosis-prone' individuals (Park, 1999). Poorer reaction

times in response to visuospatial information in schizophrenia also implicate left

hemispheric mechanisms (Frecska, White et al., 2004; Gastaldo, Umilta, Bianchin &

Prior, 2002) and frontal function (Levander, Bartfai & Schalling, 1985).

1.4.5 Neurotransmitters in schizophrenia.

In addition to brain region and pathway dysfunction, abnormalities at the

cellular level have been implicated in schizophrenia. Alterations in the structure of

neurons results in a loss of synaptic connectivity and the ability to transmit afferent

information (Benitez-King, Ramirez-Rodriguez, Ortiz & Meza, 2004). Abnormal

neurotransmission is a hallmark of schizophrenia, with a number of neurotransmitters

and neurotransmission pathways involved (Javitt, 2009). These include dopamine,


glutamate, gamma aminobutyric acid (GABA), serotonin and acetylcholine (Benitez-

King, Ramirez-Rodriguez, Ortiz & Meza, 2004). However, the dopamine theory of

schizophrenia has remained the most dominant in the schizophrenia research

literature. The dopamine theory is based on observations that substances that

increase dopamine levels in the brain (for example, amphetamines) induce

schizophrenia-like symptoms (or psychosis) (Kapur & Mamo, 2003). However

substances that block dopamine (for example, antipsychotic medications, such as

Chlorpromazine) or antagonise dopamine receptors (particularly D2 receptors)

improve or reverse these symptoms (Kapur & Mamo, 2003).

Dopaminergic pathways predominantly project to the pre-frontal cortex in

humans, which prompted ‘top-down’ models to explain dysfunction in schizophrenia

(Javitt, 2009). Studies utilising the visuospatial working memory (George et al.,

2002), memory-related visual and cognitive tasks (McGowan, Lawrence, Sales,

Quested & Grasby, 2004; Sheremata & Chen, 2004) and neuroimaging studies

(McGowan et al., 2004; Tost, Alam & Meyer-Lindenberg, 2009) suggest top-down

visual-processing disturbances. However, studies in individuals with schizophrenia

that utilise spatial, temporal, and contrast sensitivities known to be mediated by

dopamine and dopamine receptors, suggest that dopamine-related dysfunction

originating in the primary visual pathway contribute to abnormalities detected at

higher levels of visual processing in schizophrenia (Chen et al., 2003; Harris, Calvert

& Snelgar, 1990; Keri, Antal et al., 2002; Keri, Janka & Benedek, 2002; Masson,

Mestre & Blin, 1993; Schwartz et al., 1988; Schwartz, 1990; Sheremata & Chen,

2004; Slaghuis, 1998; Slaghuis & Curran, 1999).

Both serotoninergic and dopaminergic systems are important in visuospatial

attention tasks that involve attentional performance, selective attention, vigilance and


executive control exerted by the prefrontal cortex and striatum (Boulougouris &

Tsaltas, 2008; Chudasama & Robbins, 2004) and abnormal saccades (Gurvich,

Fitzgerald, Feorgiou-Karistianis & White, 2008). Visuospatial working memory is

partially mediated by prefrontal cortical dopamine, and dysregulation of prefrontal

cortical dopamine systems may contribute to the pathophysiology of schizophrenia

(George, Vessicchio, Termine, Sahady, Head, Pepper, Kosten & Wexler, 2002),

suggesting ‘top-down’ processing. Ketamine, a-N-methyl-d-aspartate (NMDA)

antagonist, disrupts leading saccades during smooth-pursuit eye movements in

schizophrenia (Avila et al., 2002). Dopamine imbalances (striatal excess and cortical

deficiency) in schizophrenia may be secondary to NMDA hypofunction in the

prefrontal cortex and its connections (Kapur & Seeman, 2002; Laruelle, Kegeles &

Abi-Dargham, 2003).

1.4.6 Dopamine genes in schizophrenia.

In recent times, researchers have investigated the genetic determinants of

schizophrenia and how genetic factors may moderate symptoms and treatment

outcomes. Many dopaminergic genes have been investigated in schizophrenia

including: DRD1, DRD2, DRD3, DRD4 and DRD5 receptor genes, catechol-O-

methyltransferase (COMT) and dopamine-transporter genes (DAT). Although

multiple polymorphisms of each of gene have been investigated in schizophrenia,

most are restricted to single studies or provide inconsistent results across studies

(Talkowski, Bamne, Mansour, Vishwajit & Nimgaonkar, 2007). The most

researched dopamine polymorphism in the literature is the Taq1 A allele of the

DRD2 receptor gene. There have been a number of associations and functional

interactions in schizophrenia investigated with this polymorphism, thereby making

the Taq1 A allele of the DRD2 receptor gene the most promising to investigate in the


current study. Investigations into the effect of anti-psychotic medications in

schizophrenia in the presence of the A1 allele indicate that this polymorphism may

modify the efficiency of DRD2 antagonism of such drugs in the central nervous

system (Suzuki, Mihara et al., 2002). Serum prolactin levels, that index dopamine

D2 blockade (Cotes, Crow & Johnstone, 1997; Gruen, 1978, Seeman, 2002), are in

those with schizophrenia who are A1+ (that is, positive for the A1 allele of the

DRD2 receptor gene) receiving anti-psychotic medications compared to those

without (Young et al., 2004). It has been noted that individuals with schizophrenia

who are A1+ (A1/1A1 and A1/1A2 genotypes) tend to experience more favourable

responses to medications (Scharfetter, 2004) than those with A1- status (A2/A2

genotype). A1+ individuals show greater improvement in total Brief Psychiatric

Rating Scale (BPRS) scores and in positive symptoms with treatment (Suzuki,

Mihara et al., 2000), again indicating that the allele may have a moderating effect.

1.4.7 Perceptual rivalry in schizophrenia.

Bistable or ambiguous figures such as the Necker Cube, Rubin’s Vase,

duck/rabbit and Schroder’s Staircase (Meng & Tong, 2004; Miller, Gynther, Heslop,

Liu, Mitchell, Ngo, Pettigrew & Geffen, 2003), present pictorial images to the visual

system that can be perceptually organised in several ways (Meng & Tong, 2004).

These figures require the visual system to interpret information from two equally-

compelling interpretations. This results in spontaneous perceptual alternations

between the two images; a phenomenon known as perceptual rivalry. It is thought

that perception rivalry results from lateral competition between neural mechanisms

or alternative images at some level in the visual pathway (Tong, 2001; Meng &

Tong, 2004). However, there is debate as to exactly where this competition occurs.

Using event-related potentials, it has been demonstrated that perceptual rivalry is


resolved before perceptual awareness is established at 200-300 msec (Kornmeier &

Bach, 2004), suggesting competition at lower levels in the visual system. However,

other studies indicate that competition occurs in higher cortical regions of the visual

system. Single-cell studies have suggested that fronto-parietal areas initiate the

competition during perceptual rivalry by sending top-down signals to guide activity

in the visual cortex toward one representation at a time (Leopold & Logothetis,

1999). These studies are supported by fMRI data that show that activity in frontal

and parietal areas correlate with perceptual alternations reported when viewing

bistable images (Lumer, Friston & Rees, 1998).

Difficulty integrating incoming visual information and attentional selection

has been associated with the perceptual disturbances and delusions observed in

schizophrenia (Stephan, Friston & Frith, 2009; Synofzik, Thier, Leube, Schlotterbeck

& Lindner, 2010). Individuals with schizophrenia have demonstrated abnormal

visual processing associated with early cortical processing (for example, deficits that

occur between 100-300 msec, discussed above in Section 1.3.1) and in deficits in

higher cortical regions (as discussed in Sections 1.3.2). Therefore, it is likely that

those with schizophrenia would also show impaired performance on perceptual

rivalry tasks.

Available perceptual rivalry data in schizophrenia inconclusive. Levander et

al., (1985) suggest slower reversals in subjects with schizophrenia. An earlier study

Hunt and Guilford (1933) demonstrated Necker cube reversals were not significantly

different to healthy controls in subjects with ‘dementia praecox’ (an older term for

schizophrenia), but were four times faster than those with manic depression. Using

the ‘Schroder’s Staircases’, Calvert et al., (1988) demonstrated that subjects with

schizophrenia perceived the staircase from above for significantly less time, and had


a (non-significant) tendency to have more reversals than controls. More recent

studies, such as Hoffman, Quinlan, Mazure and McGlashan (2001) and Keil, Elbert,

Rockstroh and Ray (1998) have demonstrated that subjects with schizophrenia had

faster reversals compared to healthy controls using Rubin’s Vase and the Necker

Cube. It has also been demonstrated that long term anti-psychotic therapy has no

significant effect on reversal rate or dominance duration during perceptual rivalry

(Calvert et al., 1988).

1.4.8 Binocular rivalry in schizophrenia.

Binocular rivalry is a unique type of perceptual rivalry where two opposing

images (that cannot be fused into a single stable image) are presented to each eye

exclusively. Each eye’s image during binocular rivalry is perceived in alternating

fashion. Binocular rivalry is thus considered to be competition between the eyes,

rather than between images or patterns (Tong, 2001). Similar to perceptual rivalry,

the mechanisms involved in binocular rivalry are widely debated. Some suggest

competition in the primary visual pathway (Blake,1989; Tong, 2001; Meng & Tong,

2004), while others suggest that mechanisms higher in cortical regions (Lumer,

Friston & Rees, 1998; Leopold & Logothetis, 1999) or cortical hemispheres

(Pettigrew & Miller, 1998; Miller, Liu, Ngo, Hooper, Riek, Carson & Pettigrew,

2000; Miller, 2001) are responsible for the competition between images presented to

each eye.

Binocular rivalry has the advantage as a research method that each of the rival

stimuli can be altered to access specific aspects of the visual system. For example,

the stimulus presented to one eye may be a complex image (such as a face), and the

other may be a simple grid pattern (see Blake, 2001), to determine how visual

information is integrated and processed. The stimuli may also be presented at


differing temporal or spatial frequencies or luminance to examine the effect of

processing early in the visual pathway (Blake, 2001; Liu, Tyler & Schor, 1992). The

specific effect of altering the stimuli can be measured by alternations over time

(binocular rivalry rate) or how long each image dominates (dominance duration).

Each image dominates for a fluctuating period of time, indicative of non-linear

dynamic processing within the visual system. Non-linear processes are also

associated with other biological phenomena, such as the cortical spreading that

occurs in depression and slow-wave sleep (Tong, 2001). These characterisitics of

binocular rivalry provide an opportunity to investigate the neural components of

conscious visual awareness (Blake & Logethetis, 2002) in clinical populations,

including in those with schizophrenia. By exploiting the visual deficits known to be

a feature of schizophrenia, and investigating factors that contribute to visual

awareness and selective visual attention, binocular rivalry may provide novel insights

into cortical processing in schizophrenia in specific cortical regions and pathways

within the visual system.

To date, there are few studies of classical binocular rivalry in schizophrenia.

(Miller et al., 2003) reported no significant differences binocular rivalry rates in

subjects with schizophrenia compared to those with depression or healthy controls;

however (Foxe, 1965; Frecska et al., 2003; Sappenfield & Ropke, 1961; Wright, et

al., 2003) report slower binocular rivalry rates in schizophrenia. Pettigrew and

Miller and colleagues have proposed that slow binocular rivalry rate is a trait maker

for bipolar disorder (see Pettigrew & Miller, 1998 and Miller et al., 2003), and not

schizophrenia. They suggest that slow binocular rivalry rate may be a helpful tool in

diagnosis. However, this issue remains unresolved, as there are conflicting reports.


There are limited data related to eye swapping during binocular rivalry tasks in

subjects with schizophrenia. As discussed previously, eye swapping eliminates eye-

of-origin information, so explores ‘top–down’ visual processing. Frecska, White et

al., (2003), White et al., (2001) and Wright et al., (2003) have applied conflicting

stimuli to the eyes in rapid reversal in subjects with schizophrenia in a method they

coined ‘dichoptic stimulus alternation’. Binocular rivalry ceased in healthy control

subjects when dichoptic stimulus alternations were above 30 Hz, however

approximately half of subjects with schizophrenia continued to experience rivalry

under these conditions (White et al., 2001). Healthy controls reported a consistent

image (vertical or horizontal stripes) for up to one second, while those with

schizophrenia perceived stable images for up to four seconds (Sec) during dichoptic

stimulus alternation (even when the stimuli were swapped at 30 Hz) (Frecska, White

& Leonard et al., 2003; Wright et al., 2003). Increased dominance durations, and thus

binocular rivalry rate, observed in schizophrenia under dichoptic stimulus alternation

may be related to less-effective visual processing. These may result from slow

gamma oscillations within the visual pathway (Frecska, White et al., 2003). These

factors may account for the perceptual disturbances and visual processing anomalies

associated with the hallucinations, delusions and cognitive deficits observed in

schizophrenia.

Studying binocular rivalry in schizophrenia provides a unique opportunity to

investigate components of visual sensory input that ultimately affect perceptual

awareness. A systematic investigation in binocular rivalry in schizophrenia is

missing from the current literature. Advancing the understanding of the mechanisms

involved in binocular rivalry and brain functioning with regard to visual awareness


may provide insights into cortical processing in schizophrenia. The focus of this

review now turns to binocular rivalry.

1.5 Binocular Rivalry

As noted, binocular rivalry refers to the perceptual alternation of images that

occurs when two dis-similar images are presented simultaneously, one to each eye, in

the same spatial location (Blake, 2001; Logethietis, Leopold & Sheinberg, 1996;

Tong & Engel, 2001). For example, when vertical lines are presented to one eye and

horizontal lines are presented to the other in the same retinal location, the vertical

and horizontal lines are perceived in alternating fashion, rather than forming a grid or

composite pattern. During binocular rivalry the observer perceives the opposing

images in alternating fashion, even though the sensory input to each eye remains

constant. The alternation of perceptual images is therefore dissociated from the

sensory input (Clifford, 2009), allowing a unique opportunity to investigate human

visual perceptual awareness, or the ‘neural correlates of consciousness’ (Crick &

Koch, 1998). Thus, in recent times the focus of binocular rivalry research has been

the investigation of factors affecting the dominance of one image for awareness, and

subsequent suppression of the other. Reciprocal suppression and awareness during

rivalry are linked to conscious perception (Mitchell, Stoner & Reynolds, 2004; Ooi

& He, 1999; Tong, Nakayama, Vaughan & Kanwisher, 1998). It is this feature that

makes binocular rivalry a useful tool to investigate the contribution of perceptual and

cortical processes to the cognitive deficits observed in neurocognitive disorders, such

as psychosis and mood disorders.

Binocular rivalry testing yields two measures. The first is the frequency of

perceptual alternation between images (binocular rivalry rate), generally expressed as

alternations per second (Hz). The second is the portion of time spent perceiving the


image of one eye relative to the other, assessed by predominance or perceptual

dominance durations (Blake, 2005; Breese, 1899; Levelt, 1968) in seconds.

Inhibitory processes during rivalry behave in an ‘all or none’ fashion (Blake &

Camisa, 1979), typically causing the suppressed image to return to dominance within

20 msec (Walker & Powell, 1979).

It is argued that the factors that affect the rate, rather than dominance or

suppression durations are the most critical to understanding the underlying process of

binocular rivalry (Chen & He, 2003). Binocular rivalry rates are thought to be driven

by monocular image contrast during the suppressed phase (Mueller & Blake, 1989),

with rates decreasing monotonically with increasing stimulus strength (Levelt, 1968;

Shpiro, Curtu, Rinzel & Rubin, 2006). It is generally accepted that manipulations to

the rival stimuli can modulate binocular rivalry rate (increasing or decreasing

dominance durations), however the fluctuations in perception between the two

images are ‘hard wired’ into the visual system (Blake, 2005). Breese (1899) made

the observation that subjects could exert some control over the length of time they

could perceive the dominant image during binocular rivalry; however they could not

control the fluctuations between images. Therefore, binocular rivalry rate may

provide some measure of underlying cognitive efficiency (Fox, 1965).

The alternation of perceptual images during rivalry has been argued to reflect

cortical responses to active, programmed events initiated by brain areas that integrate

sensory and non-sensory information to coordinate behaviour (Leopold &

Logothetis, 1999). When dominance durations are expressed as a function of their

mean and plotted as histograms, they typically approximate gamma-density functions

(Carter & Pettigrew, 2003; Fox & Herman, 1967; Levelt, 1968; Miller, 2001; Miller

et al., 2003; O’Shea, Parker, La Rooy & Alais, 2009) although this less convincing in


some studies, (Kobayashi, 1992). Leopold (1999) suggests activity throughout the

visual cortex in higher, largely non-sensory brain centres, is consistent with

perceptual reversals during rivalry. This activity is associated with planning and

motor programming, and serves an important role in perceptual organisation and

selective attention. However, Levelt (1968) argued that mechanisms lower in the

visual system are responsible for the alternations in rivalry. He argued that

suppressed images produce, “A series of randomly-distributed excitation spikes”,

that were related to a ‘flick’ in eye-movements, and that these were necessary for the

suppressed image to return to dominance. He noted that plotted time intervals of

each of these ‘flicks’ fitted gamma distributions. The parameters of these

distributions were consistent between subjects (Logothetis et al., 1996).

Although several authors have fitted dominance durations to gamma

distributions, others note that binocular rivalry dominance durations can also be

fitted to Weibul, log-normal (Lehky, 1995; Zhou, Gao, White, Merk & Yao, 2004),

Wiener and Capocelli-Riciardi distributions (De Marco, Penego & Trabucco, 1977).

Voluntary control changes the shape of the distributions (Van Ee, Noest, Brascamp

& van den Berg, 2006). These observations question whether gamma distributions

are truly a mechanism of binocular rivalry, and therefore perception. Thus, the

validity of gamma-distribution-based computer models to describe the neural events

during binocular rivalry have been questioned (Brascamp, van Ee, Pestman & van

den Berg, 2005; Brascamp et al., 2006; Kobayashi, 1992; Murata, Matsui, Miyauchi,

Kakita & Yanagida, 2003; Sugie, 1982).

1.5.1 Stimulus parameters moderate binocular rivalry

Investigations into the binocular rivalry phenomenon have spanned a century

with most attention on the effect of stimulus features on binocular rivalry. ‘Strong’


figures (in terms of figure-ground contrast) are thought to alternate more quickly

than ‘weak’ (figure-ground contrast) when viewed stereoscopically (Alexander,

1951) and rivalry rate is faster the more disparate the competing stimuli (Whittle,

1965). Additionally, changing the temporal frequency, spatial frequency or contrast

of an image at the beginning of suppression alters the course of binocular rivalry

(Walker & Powell, 1979).

The perception of binocular rivalry stimuli depends on temporal and spatial

frequency, contrast and luminance of the rival stimuli (Lui, Tyler & Schor,1992),

along with the size (Blake, O’Shea & Muller, 1992; O’Shea et al., 2009) colour

(Andrews & Purves, 1997; Hong & Shebell, 2008a; O’Shea & Williams 1996; Ooi &

Loop, 1994; Wade, 1975), orientation (O’Shea, 1997; Andrews & Purves, 1997;

Blake & Lema, 1978) and context of each image (Blake, 2001; Carter, Campbell, Lui

& Wallis, 2004; Hong & Shevell, 2008b).

1.5.1.1 Spatial frequency.

The spatial frequencies that produce the crispest binocular rivalry are those

between 2 cycles per degree (cpd) (Carlson & He, 2000) and 10 cpd (Livingstone &

Hubel, 1987). When the spatial frequency of the stimuli presented to each eye is

equal, gratings of high spatial frequency (and especially those of low contrast) tend

to fuse to produce a stable perception of a dichoptic plaid (Burke, Alais &

Wenderoth, 1999). Lower spatial frequency gratings typically alternate. The greater

the difference between the spatial frequencies of the stimulus presented to each eye,

the faster the binocular rivalry rate (O’Shea, 1997; Wade 1994). O’Shea (1997)

noted that when exclusive visibility of one grating relative to the other was plotted,

an inverted U-shaped relationship with spatial frequency emerged. The peak of this

curve shifted to larger spatial frequencies as the field size increased (O’Shea, Sims &


Govam, 1997). These findings suggest that spatial frequency channels in human

vision are employed during binocular rivalry (Fahle, 1982), where each spatial-

frequency-dependent cortical column inhibits only the adjacent column (Aladi,

1976). Each cortical column is a basic unit for sensory processing, containing

neurons with similar spatial-response properties stacked on top of each other in

different layers throughout the depth of the cortex.

1.5.1.2 Movement.

Flickering images, eye blink and moving stimuli all produce transient

stimulation across the retina (Blake & Fox, 1974). A moving image (irrespective of

speed and direction) presented to one eye remains visible for longer than a static

image presented to the other (Blake, Yu, Lokey & Norman 1998; Wade, 1994).

Moving rivalrous stimuli presented at equal strength to each eye, lead to a greater

suppression than static patterns (Norman, Norman & Bilotta, 2000; Cobo-Lewis,

Gilfory & Smallwood, 2000).

1.5.1.3 Luminance.

Dominance or suppression of rival images is determined by the relative image

luminance contrast between the two eyes, with dominance of the higher-contrast

image being favoured (Freeman & Nguyen, 2001; Mueller & Blake, 1989; Whittle,

1965). Blurred patterns are suppressed by sharply-focused ones (Fahle, 1982), and

textured stimuli of high contrast (randomly-orientated patches) are more dominant

than uniform textures (Bonneh & Sagi, 1999). Functional magnetic resonance

imaging studies (fMRI) indicate that when luminance contrast is increased in one

eye, activity in the primary visual cortex (V1) increases, and decreases with a lower

contrast image (Polonsky, Blake, Braun & Heeger, 2000). At very low luminance,


rivalry does not occur, allowing a stable summation between the two images to form

(Lui et al., 1992).

1.5.1.4 Colour.

Presenting images of different colours to each eye increases rivalry (Andrews

& Purves, 1997; Hong & Shevell, 2008a; Oois & Loop, 1994; O’Shea & Williams,

1996; Wade, 1975). Long-, medium- (Rogers et al., 1977) and short-cone pathways

all contribute to binocular rivalry (O’Shea & Williams, 1996). However, it has been

shown that opposing gratings that differ with respect to chromaticity can produce a

unified percept of mixed colour at high-luminance contrast (Hong & Shevell, 2006).

Counter phased gratings of different colours, equal in terms of their luminance and

chrominance, produce a single, fused moving grating (Carney, Shadlen & Switkes,

1987).

1.5.1.5 Orientation.

Greater differences in orientation between the two eyes increases binocular

rivalry rate (Andrews & Purves, 1997; O’Shea, 1997). Threshold levels for the

mechanism responsible for suppression operating non-selectively over a wide range

of orientations (Blake & Lema, 1978). It is argued that binocular rivalry occurs early

in the visual pathway as orientation-selective channels are monocularly driven.

Orientation response is hypothesised to be established before the level at which the

two monocular channels converge (Walker, 1978). Changes during rivalry between

stimuli differing in orientation occur after about 100 msec (P1) (Veser, O’Shea,

Schroger, Trujillo-Barreto & Roeber, 2008). There is some agreement that vertical

gratings predominate over horizontal gratings (vertical gratings are viewed for

approximately 30% longer) (Wade, 1994).


1.5.1.6 Size.

Binocular rivalry is affected by the size of the rival images (O’Shea et al.,

2009). Presenting different-sized stimuli to each eye increases binocular rivalry rate

(Andrews & Purves, 1997), and for a given-sized target exclusive visibility increases

with retinal eccentricity (Blake et al., 1992). The optimal size for targets to gain

exclusive visibility during rivalry is a diameter of 5.3 or 7.3 minutes of visual angle

(Blake et al., 1992), with the target size being inversely proportional to spatial

frequency (O’Shea et al., 1997).

1.5.1.7 Context.

Contradictory contextual information increases dominance duration during

binocular rivalry (Blake, 2001; Carter, Campbell et al., 2004; Hong & Shevell,

2008b). When different objects are presented to each eye at the same location in

visual space, they are likely to rival even if all of the other stimulus features (such as

colour) are identical. Conversely when different, monocular stimuli (with respect to

colour and luminance) represent the same object at the same location in space, fusion

is more likely to result (Andrews & Lotto, 2004).

1.6 Theories of Binocular Rivalry

Two opposing theories have dominated the binocular rivalry phenomenon.

One suggests that binocular rivalry involves inter-ocular competition or “eye rivalry”

(a “bottom-up” theory). While the other suggests binocular rivalry is competition of

the perceptual images higher in the visual cortex or “pattern rivalry” (a “top-down”

theory) - see Blake (1989) and Tong (2001) for reviews. Bottom-up theorists of

binocular rivalry argue the alternation of images during binocular rivalry is due to

events in the early stages of visual perception; that is, in the primary visual pathway

(Tong & Engel, 2001). Detailed investigation of the effect of specific features of the


rival stimuli and manipulation of stimulus features has on the binocular rivalry

phenomena have provided insights into visual information processing at higher levels

of the visual pathway. These insights have informed our understanding of cognition,

memory and executive functioning.

Conversely ‘top-down’ theorists posit that during binocular rivalry the observer

attends to, or selectively concentrates on, one image while ignoring the other. Thus,

higher-level cortical processes influence what the observer perceives. Researchers

investigating binocular rivalry using a ‘top-down’ approach examined the effect that

higher-order cognitive processing (i.e. visual memory, planning and decision

making) has on visual perception (Li, Freeman & Alais, 2005; Logothetis, 1998;

Logothetis et al., 1996).

Theorists have also suggested binocular rivalry involves hierarchical

processing that involve both ‘top-down‘ and ‘bottom-up’ neural processes (Blake &

Logothetis, 2002; Pearson & Clifford, 2005). Others suggest competition between

visual pathways (Carlson & He, 2000; Livingstone & Hubel, 1987; Nguyen,

Freeman & Alais, 2003) or the cortical hemispheres (Carter & Pettigrew, 2003;

Carter et al., 2005; Miller et al., 2000; Miller et al., 2003; Pettigrew & Miller, 1998;

Ngo, Lui, Tilley, Pettigrew & Miller, 2008). Evidence for and against these four

theories (i.e. bottom-up, top-down, pathway and inter-hemispheric processing) will

be critically reviewed.

1.6.1 Bottom-up theories of binocular rivalry.

Evidence drawn from psychophysical studies suggests that binocular rivalry is

fully resolved at the earliest stages of cortical processing in monocular V1 neurons

(Tong & Engel, 2001). Thus, binocular rivalry is hypothesised to be the result of

inter-ocular competition, with suppression and dominance between the two eyes


occurring early in the visual system, where the two neural inputs from the eyes

converge (Levelt, 1965). Central to this model are three basic concepts. Firstly,

signals from each monocular stimulus travel down pathways that connect to

monocular cortical areas to higher areas that subserve perception. Secondly, that at

any one moment during binocular rivalry one of these pathways is suppressed

(neurons along the pathway are suppressed) and, finally, that the depth of

suppression (or the suppression threshold) increases along the suppressed pathway

(Freeman, Nguyen & Alais, 2005).

Tong (2001) presented opposing rival stimuli to each eye and measured the

activity of the area in the primary visual cortex representing the blind-spot using

fMRI. Tong found larger activation in the blind-spot area when gratings presented to

the ipsilateral eye were dominant, as opposed to when they were suppressed. This

suggests that binocular rivalry is resolved within the monocular visual cortex. These

findings indicate V1 may be important for processing conscious visual information.

This is supported by Polonsky et al., (2000) who found that rivalry-related

fluctuations in V1 activity are roughly equal to those observed in other visual areas

(i.e. V2, V3, V3a and V4), indicating that neural mechanisms responsible for

binocular rivalry are localised early in the visual pathway. Therefore, it is possible

that V1 plays a role as a ‘gatekeeper’ of consciousness (Tong & Engel, 2001), and

that neurons in the primary visual cortex have a direct role in visual awareness

(Blake, Tadin, Sobel, Raissian & Chong, 2006). This is further supported by lesion

and inactivation studies (Tong, 2003).

These observations are further supported by single-neuron studies. Single-cell

recordings in the lateral geniculate nucleus (LGN) and area 17 of the cat brain

indicate that switches in perceptual dominance during binocular rivalry depend on


inter-ocular interactions at the level of binocular neurons of the primary visual cortex

(Sengpiel, Blakemore & Harrad, 1995). It is likely that inter-ocular suppression is

directly related to the functional architecture of V1 (interactions between

neighbouring cortical columns) (Sengpiel, Bonhoeffer, Freeman & Blakemore,

2001). This pattern is also observed in human studies (de Labra & Valle-Inclan,

2001). Dominance of one image over the other is thought to result from small

activity differences between channels in the low-level visual cortex (Freeman & Lui,

2009), with the duration of suppression related to the size of the pool of monocular

neurons innervated by the suppressed eye, and to the strength of excitation generated

by the suppressed stimulus (Blake, 1989). When psychophysical studies using fMRI

data are combined, a close association between the dynamics of perception during

rivalry and neural events in human primary visual cortex (V1) are observed,

supporting eye-rivalry theories (Lee, Blake & Heeger, 2005; Nguyen, Freeman &

Wenderoth, 2001). However, it should be noted that neural activity representing the

physical characteristics of a stimulus (sensory neuronal response) does not

necessarily imply that those signals contribute to consciousness (Andrews, 2001) as a

resultant perceptual image.

1.6.2 Visual-evoked potentials (VEPs) in binocular rivalry

Scalp VEPs can be analysed to identify separate responses from monocular and

binocular neurons (Apkarian, Nakayama & Tyler, 1981). Visual-evoked potentials

associated with the perceptual shift in rivalry to perceptual dominance occur with a

corresponding shift in cortical signals (Brown & Norcia, 1997) that correspond to the

time course of activity observed across the retinotopic map in V1 (Valle-Onclan,

Hackley, de Labra & Alvarez, 1999). Dominant patterns produce smaller VEPs early

in the visual pathway (70-240 msec), while suppressed patterns produce activity later


(400-700 msec) (Valle-Inclan et al., 1999). Furthermore, when stimuli differ in

orientation, evoked related potentials occurred after about 100 ms (Veser et al.,

2008). However when the rival stimuli differ in colour, evoked potentials do not

occur until after 200 ms (Veser et al., 2008). This difference suggests that property-

dependent cortical networks influence the timing of visual awareness. It is possible

that neural events in V1 create an endogenous potential (or rivalry-related potential)

that marks the alternation between images (de Labra & Valle-Inclan, 2001). It is

proposed that a p300-like wave response is related to the perceptual shift from the

dominant to the suppressed pattern (or to piecemeal fusion). This event may mark

the breakthrough into awareness of the suppressed eye when attention is captured by

the appearance of a new object into the field of view of that eye (Valle-Inclan et al.,

1999).

1.7 Top- down Theories of Binocular Rivalry

Theorists subscribing to ‘top-down’ models of binocular rivalry argue that each

image during rivalry is available until the late stages of attentional selection. Thus,

binocular rivalry arises from the spontaneous fluctuations in visual attention (Li et

al., 2005; Logothetis, 1998; Logotheties et al., 1996). Binocular rivalry involves

competition between alternative perceptual interpretations at higher levels of analysis

(Logothetis et al., 1996). Neurons that respond to input from both eyes (binocular)

found in higher cortical areas of the visual cortex beyond the primary visual area (Li

et al., 2005), are thought to be responsible for the perceptual alternation of images

that occurs during binocular rivalry (Li et al., 2005; Logothetis, 1998; Logothetis et

al., 1996).


1.7.1 Single-cell studies.

Evidence to support ‘top-down’ processing also includes the results of single-

cell studies. In monkeys trained to respond to perceptions during binocular rivalry

(Logothetis, 1998), correlations between neural activity in many cells of V1, V2 and

especially V4 (which are highly populated with binocular cells) and perceptual

alternation of the rivalling stimuli during rivalry were observed (Leopold &

Logothetis, 1996). Neural firing within the inferior and superior temporal cortices of

monkeys has been interpreted as signalling the change in perception during rivalry,

with the associated response by the monkeys indicating recognition of the stimulus

image (Sewards & Sewards, 2001). This is likely to be due to the computations made

in these same areas (Sewards & Sewards, 2001), where neural activity is thought to

reflect the brain's internal view of objects, rather than the effect of the retinal

stimulus on cells encoding simple visual features (Sheinberg & Logothetis, 1997).

1.7.2 Imaging studies.

Imaging studies using fMRI have revealed an association between the

perceptual alternations during rivalry and frontoparietal cortex activity, thought to

play a central role in conscious perception (Lumer, Friston & Rees, 1998). Other

associations between cortical activity and the perceptual changes during binocular

rivalry have been observed in the visual cortex, medial parietal and left frontal

regions using magnetoencephalography (MEG). Co-activation of occipital and

frontal regions, including anterior cingulate and medial frontal areas, were apparent

when the rival stimulus was dominant (Cosmelli et al., 2004). Tononi and Edelman

(2000) using whole-head MEG measured brain electrical activity by frequency-

tagging the opposing flickering stimuli (temporal frequencies of 7 and 12 Hz) during

binocular rivalry in healthy subjects. They observed widely-distributed activity in the


frontal, parietal, temporal and occipital areas (Tononi, Srinivasanm Russell &

Edelman, 1998).

When house and face stimuli were presented to different eyes, and responses in

the human fusiform face area and parahippocampal place area were measured by

fMRI, responses during binocular rivalry were equal in magnitude to those evoked

by non-rivalrous stimulus (Tong et al., 1998). This suggests that activity in the

fusiform face area and parahippocampal place area reflects the perceived (rather than

the retinal) stimulus, and that neural competition during binocular rivalry has been

resolved prior to these stages of visual processing (Tong et al., 1998). ‘Top-down’

processing may therefore account for slower binocular rivalry rates in subjects with

negative symptoms of schizophrenia observed in response to facial stimuli

(representing four emotional states: happy, sad, angry and neutral) (Yang, Blake &

Park, 2007).

1.7.3 Eye-swapping methodologies.

Investigations incorporating ‘eye swapping’ paradigms into binocular rivalry

have further challenged monocular competition (bottom-up) theories (Ngo, Miller,

Liu & Pettigrew, 2000). Eye-swapping paradigms involve presenting opposing

images of equal strength to each eye, and periodically swapping them between the

two eyes during rivalry (Logothetis et al., 1996). The eye-swapping technique

eliminates perceptual alternations during rivalry because the monocular pathways are

fatigued (Logothetis et al., 1996). Although opposing stimuli are swapped between

the two eyes, images generally stabilise to one eye (Chen & He, 2004), suggesting

that the alternation of images is independent of which eye the information originates

(Person & Clifford, 2005). Perceptual alternations are observed as either slow,

irregular alternations between images (independent of stimulus swapping) or fast,


regular alternations that are time-locked to the stimulus alternations (Silver &

Logothetis, 2006). Some authors suggest that inter-ocular suppression accounts for

the stabilisation effect, rather than the memory of the stimulus (Chen & He, 2004).

Others argue that the brain combines information across multiple visual features to

resolve ambiguities in visual inputs (Silver & Logothetis, 2006).

1.7.4 Neurotransmitter involvement in binocular rivalry.

The observation that pharmacological agents influence binocular rivalry,

including ethanol (Donnelly & Miller, 1995), sodium-amytal and caffeine (George,

1936), has prompted researchers to investigate neurotransmitter involvement. The

traditional hallucinogenic beverage ‘Ayahuasca’ (Carter et al., 2005; Fercska, White,

& Luna, 2003; Frecska, White et al., 2003) affects binocular rivalry via the active

ingredient Psilocybin. This serotoninergic 5HT1A and 5HT2A agonist decreases

binocular rivalry rate in a dose-dependent manner, (Carter et al., 2005; Frecska,

White et al., 2003. Psilocybin has been demonstrated to selectively impair motion

coherence sensitivity for random-dot patterns. This is likely to be mediated by high-

level global motion detectors, but not contrast sensitivity for drifting gratings,

believed to be mediated by low-level detectors (Carter et al., 2004). Binocular

rivalry rate decreases significantly one-to-two hours after oral ingestion (Carter et al.,

2005; Nagamine, Yishino, Miyazaki, Takahashi & Nomura, 2008), and returns to

placebo rates at five to six hours after administration, consistent with the

pharmacokinetics of these compounds (Vollenweider, Vollenweider-

Scherpenhuyzen, Babler, Vogel & Hell, 1998; Vollenweider, Vontobel, Hell &

Leenders, 1999). Similar results have been reported using Tandospurone, a 5HT1A

agonist (Nagamine et al., 2008).


Gamma-aminobutyric acid (GABA) has been suggested to be involved in

binocular rivalry, via suppression of dorsal lateral geniculate nucleus (dLGN) inter-

neurons (Bickford et al., 2008). Selective loss of inter-ocular suppression is

observed in the presence of the GABA antagonist Bicuculline (Sengpiel &

Vorobyov, 2005). Noradrenaline may also have a role in binocular rivalry as

increased pupillary dilation, immediately prior to a switch in perception, reflects

levels of noradrenaline released from the locus coeruleus. The locus coeruleus and

noradrenaline involvement may be via perceptual selection (Einhauser, Stout, Koch

& Carter, 2008).

1.7.5 Monocular rivalry compared to binocular rivalry.

Monocular rivalry differs to binocular rivalry in that one (or both) eyes can

view the two alternative precepts of an image simultaneously. Monocular rivalry

may be observed when viewing a bistable image, such as the Necker Cube, Rubin’s

Vase, or Schroder’s Staircase. Each aspect of the image fluctuates in awareness in a

rhythmical alternation. It is argued that binocular and monocular rivalry is mediated

by a common, high-level mechanism for resolving ambiguity (O’Shea et al., 2009).

However, binocular rivalry is a more automatic, stimulus-driven form of visual

competition than rivalry between bistable images, and is less easily biased by

selective attention (Meng & Tong, 2004) or voluntary control (van Ee, 2005; vand,

Dam & Brouwer, 2005; van Ee et al., 2006).

1.8 Multi-level or Hierarchical Theories

Recent evidence supports a view of rivalry as a series of processes, each

implemented by neural mechanisms at different levels of the visual hierarchy (Blake

& Logothetis, 2002; Pearson & Clifford, 2005) with suppression preceding the

synthesis of subjective contours (Sobel & Blake, 2003). This view suggests multiple


sites of binocular rivalry, each corresponding to analysis of different aspects of the

stimuli (Cobo-Lewis et al., 2000). It is proposed that the brain combines information

across multiple visual features to resolve ambiguities in visual inputs (Solver &

Logothetis, 2006) at different levels of the visual-processing hierarchy (Pearson,

Tadin & Blake, 2007). Therefore, it is possible that rivalry can operate at both the

monocular and binocular levels (Pearson & Clifford, 2004); with both high- and low-

level processes being involved in binocular rivalry perception (Carter, Campbell et

al., 2004). Connections between V1 and higher areas form functional circuits that

are thought to support awareness (Tong, 2003), with synchronisation in cortical

neurons being necessary for the establishment of perceptual states and awareness of

sensory stimuli (Engel, Fries, Konigm Brecht & Singer, 1999). Tong (2003) noted

that damage to V1 disrupts the flow of information to extrastriate areas that are

crucial for awareness.

1.8.1 Visual pathway theories of binocular rivalry

1.8.1.1 Monocular and binocular pathways.

The existence of paired monocular and binocular neural pathways that project

to dorsal and lateral streams has been the focus of many binocular rivalry

researchers. It has been suggested that binocular rivalry suppression occurs at a

number of stages along both the monocular and binocular cortical pathways, with

suppression increasing as the visual signal progresses along these pathways (Nguyen

et al., 2003). Wolfe (1986) suggests these two pathways constitute a ‘rivalry only’

pathway and a ‘stereopsis’ pathway, with the mechanisms responsible for binocular

rivalry closely associated with those responsible for stereopsis. Similarly, Barker,

Meese and Summers (2007) conceptualised these two pathways as a ‘within-eye’

(ipsiocular) pathway and a ‘between-eye’ (interocular) pathway, and suggested the


inter-ocular pathway may be a sound candidate for binocular rivalry. It is possible

that rivalry can operate at both monocular and binocular levels (Pearson & Clifford,

2004), and that binocular rivalry and stereopsis can coexist at the same spatial

location (Blake, Yang & Wilson, 1991). Perhaps binocular rivalry always occurs,

even when the two monocular images are identical, but only becomes apparent when

the two monocular images differ (Blake et al., 1988). Hence, the perception of one

image over the other during binocular rivalry is due to inter-ocular suppression

between the two eyes, rather than the memory of the stimulus (Chen & He, 2004).

1.8.1.2 Magnocellular and parvocellular pathways.

Magnocellular and parvocellular neurons originate in the retina and project to

the dLGN, forming distinct visual pathways to V1 and beyond (Livingstone &

Hubel, 1987). Livingstone and Hubel (1987) observed that binocular rivalry

disappears at very high spatial frequencies. They also noted that two half-images

differing in colour but were equal in luminance failed to alternate, and so attributed

binocular rivalry to be a function of the magnocellular system. When investigating

the cortical components of the Westheimer function (an increment-threshold curve

based on a luminance hierarchy, described by Gerald Westheimer, 1965). Yu and

Levi (1997) observed that when a disc presented to one eye and ring to the other

flickered experimentally (i.e. were presented under conditions that engage processing

of the magnocellular pathways) binocular rivalry resulted. However, when the

objects were presented under conditions that engaged processing of the parvocellular

pathway (presented continuously), fusion resulted. Further, indirect support of

magnocellular processing in binocular rivalry is that binocular rivalry alternation

frequency peaks for 3 cpd (Hollins, 1980); the spatial frequency at which the

transient (magnocellular) system is most sensitive (Kulikowski & Tolhurst, 1973).


It is possible that binocular rivalry may be due to interactions higher in the

visual cortex within two independent motion channels; one for low velocities (<20

Hz) the dorsal (mainly magnocellular) pathway, and one for higher velocities (>20

Hz) the ventral (manly parvocellular) pathways, rather than between them (van de

Grind, van Hof, van der Smagt & Verstraten, 2001). This is supported by

modulations of single-neuron activity in MT (Logothetis & Schall, 1989) that

correspond with a state of binocular rivalry (Blake et al., 1998). Another

interpretation is that two pathways forming independent binocular interactions

between form (V1) and motion (MT) (Andrews & Blakemore, 2002) may be

responsible for the alternations of visual stimuli in binocular rivalry.

1.8.2 Inter-hemispheric theory of binocular rivalry.

The inter-hemispheric ‘switching’ hypothesis has been proposed as an

alternative model of binocular rivalry (Carter & Pettigrew 2003; Carter et al., 2005;

Miller et al., 2000; Miller et al., 2003; Ngo, 2008; Pettigrew & Miller, 1998). This

hypothesis posits that the cortical hemispheres compete for perceptual dominance

during rivalry, rather than the competing visual pathways. The inter-hemispheric

switching hypothesis suggests that synchronised activation of homologous areas of

each cerebral hemisphere alternate, by means of a bistable oscillator circuit that

straddles the midline of the ventral tegmentum (Pettigrew, 2001). This oscillator

may be responsible for timing aspects of all forms of perceptual rivalry and may be

linked to circadian rhythms, despite their different periodicities (Pettigrew & Carter,

2005).

Support for this comes from experiments using cold vestibular stimulation and

the application of transmagnetic stimulation to one of the hemispheres during

binocular rivalry. Cold vestibular stimulation during binocular rivalry stimulates


shifts of attention (Miller et al., 2000) and increases the predominance of the face

stimuli (over other types of stimuli), partially supporting brain imaging lateralisation

reports (Miller, 2001). The application of trans-magnetic stimulation to one

hemisphere can trigger a switch in stimulus predominance, suggesting that inter-

hemispheric switching involves alternating uni-hemispheric attentional selection of

neuronal processes for access to visual consciousness (Miller, 2001). This is

supported by fMRI studies, during cold-caloric vestibular stimulation (stimulating

vestibules by applying cold water to the ear cannel) during rivalry, that indicate

perceptual rivalry engages high-level cortical structures that mediate uni-hemispheric

attentional selection (Ngo et al., 2008).

Although supporters of the inter-hemispheric switching hypothesis propose that

binocular rivalry involves competition between higher cortical processes, there are

those that argue that inter-hemispheric involvement may support low-level

processing. It has been demonstrated that visual processes similar to rivalry occur in

the left and right hemispheres of two split-brain observers, consistent with switching

being mediated by low-level processes within each hemisphere (O’Shea & Corballis,

2005a, 2005b). Mechanisms low in the visual system, where the two hemispheres

conduct similar analyses of each half of the visual space (O’Shea & Corballis, 2001),

compete for perceptual dominance. Faster binocular rivalry rate has been observed

when stimuli were presented to the right visual field rather than the left, suggesting

the rivalry may be driven by retinotopically-local processes; visual analysis in the

left hemisphere may be faster in right-handed people (Chen & He, 2003). Trans-

magnetic stimulation during binocular rivalry has also been observed to effect

retinotopic processes, suggesting that binocular rivalry mechanisms are reliant on

neural activity early in the visual pathway (Pearson et al., 2007), and that the


temporal dynamics during rivalry are likely to be local and hemisphere-specific

processes (He, Carlson & Chen, 2005).

1.9 Summary and introduction to Chapters

This chapter has explored the literature surrounding visual abnormalities that

contribute to visual processing deficits and cognitive disturbances in schizophrenia,

the contemporary theories of binocular rivalry, and the effects of altering stimuli with

respect to movement, colour, spatial frequency and luminance binocular rivalry. It is

apparent that although binocular rivalry has been intensively investigated, and much

is known regarding the physical characteristics that modify binocular rivalry, much

has been left unexplained. Binocular rivalry provides a unique opportunity to

explore visual processes and visual perception, and provides a promising tool to

investigate neurological and mental illness. There are only a few studies that

investigate binocular rivalry in schizophrenia. The limited research available is

contradictory, with some claiming slower binocular rivalry rates (Fox, 1965;

Sappenfield & Ripke, 1961) and others showing no differences (Miller et al., 2003).

The research presented in this Thesis seeks to resolve this discrepancy.

There are many methods of collecting binocular rivalry data. For this study the

binocular rivalry method of Pettigrew and Miller (1998) was selected as it had a

number of advantages over other methods. This method had previously been

demonstrated to reliably collect binocular rivalry data in individuals with mental

illness, providing some comparison data. The characteristic alternation of opposing

perceptual images is easily achieved with minimal training and without the need for

individuals to fix their gaze on a central point. This method allows the stimuli to be

manipulated with respect to colour, luminance, movement and spatial frequency to

investigate specific parts of the visual system.


The selection of the method provides a natural starting point for this research.

Pettigrew and Miller (1998) and Miller et al., (2003) investigated binocular rivalry in

groups of participants with mental illness and controls using two stimulus conditions.

Miller et al., (2003) investigated participants with bipolar disorder, depression,

schizophrenia and controls using low-strength stimuli (stationary, 4 cpd horizontal

and vertical monochromatic lines of 90% luminance contrast). These authors

compared their data with data provided in Pettigrew and Miller (1998) from

participants with bipolar disorder and controls using a high-strength stimulus

(monochromatic 8 cpd vertical and horizontal lines of moving at approximately 4

cps). They noted that alterations to the strength of the stimuli effected binocular

rivalry rate. Because these comparisons were between different groups it is not clear

what the effect of increasing the stimuli strength would have on individuals using

this method of binocular rivalry. The investigation in the next chapter (Chapter 2)

explores this issue.

In Chapter 2, the binocular rivalry stimulus is manipulated to produce

horizontal and vertical lines that vary in their presentation with respect to colour,

movement, spatial frequency and luminance. Stimuli are presented in two colour

conditions (red/black), two temporal conditions (moving or stationary), two spatial

frequency conditions (4 cpd and 8 cpd) and two luminance conditions (low and high)

to investigate stimulus effects in binocular rivalry. A total of 16 stimulus conditions

are tested; two being the same as those reported in Pettigrew and Miller (1998) and

Miller et al., (2003). Stimulus effects are investigated in a group of twenty

participants with no mental illness using a 2X2X2X2 repeat within-group design. In

this chapter the ‘inter-hemispheric switch’ hypothesis of binocular rivalry proposed

by these authors is also investigated.


The disadvantage of the Pettigrew and Miller’s method of binocular rivalry is

that the computer software only allows one image to be presented on the computer

screen. There is no way to adjust the stimuli so that a different stimulus can be

presented to each eye. Thus, opposing orientation of lines (vertical and horizontal) is

the only ‘between eye’ difference that can be achieved. Other methods of binocular

rivalry that use stereoscopes or alternative computer methods allow stimuli different

in colour, spatial frequency, temporal frequency or luminance to be presented

independently to the left and right eyes. This allows the researcher to investigate the

effect that the stimulus presented to one eye has on dominance and suppression that

occurs during binocular rivalry. Many researchers in recent times have taken

advantage of this feature to explore the neural events that occur in binocular rivalry

and reported their data in terms of Levelt’s second proposition. Although it is not

possible to test Levelt’s second proposition, Levelt’s fourth proposition that

“increasing the stimulus strength in both eyes will increase the alternation frequency”

can be tested using in a variety of stimulus conditions. This allows confidence in the

validity of the results.

Pettigrew and Miller and colleagues have proposed that slow binocular rivalry

rate is a trait maker for bipolar disorder and may be an important tool for diagnosis

(see Pettigrew and Miller, 1998 and Miller et al., 2003). However, there are little

data to support this claim, and little support is provided by perceptual rivalry studies.

Krug, Brunskill, Scarna, Goodwin & Parker (2008) refute this claim with respect to

bistable figures. There are only three studies that have investigated classical

binocular rivalry in schizophrenia (Fox, 1965, Miller et al., 2003, Sappenfield &

Ripke, 1961). In order to support Pettigrew and Miller’s claim that slow binocular


rivalry is a trait marker for bipolar disorder, there is a need to demonstrate that slow

binocular rivalry is not present in schizophrenia.

Miller et al., (2003) investigated binocular rivalry in schizophrenia using

stationary, 4 cpd horizontal and vertical monochromatic lines of 90% luminance

contrast in participants who had bipolar disorder, depression or schizophrenia and

controls. They reported no difference in binocular rivalry rate in participants with

schizophrenia compared to controls which is contrary to previous reports (Fox, 1965;

Pettigrew & Miller, 1998; Sappenfield & Pike, 1961; White et al., 2001). They then

compared their data with that provided in Pettigrew and Miller (1998) and with other

published data relating to perceptual rivalry. Participants with schizophrenia were

only tested in one stimulus condition using the binocular rivalry method of Pettigrew

and Miller. In order to extend this work and to settle this discrepancy in the

literature, binocular rivalry is investigated in the current study in participants with

schizophrenia and controls using a ‘within group’ design. This design employs low

and high strength stimuli and a perceptual rivalry task; the Necker cube, a task

frequently reported in the schizophrenia literature.

As previously noted, individuals with schizophrenia experience both subjective

sensory anomalies and objective deficits of sensory function (Brenner, Krishnan &

Vohs et al., 2009) that contribute to many of the symptoms of the disease. They have

marked deficits in visual processing that contribute to perceptual abnormalities,

hallucination and the misinterpretation of perceptual information associated with

delusions. Individuals with schizophrenia have delayed or interrupted visual

processing that may account for many of the negative symptoms, such as poverty of

thought and speech, and decreased reaction to the immediate surrounding

environment (Cadenhead, Geyer, Butler, Perry, Sprock & Braff, 1997; Uhlhaas,


Phillips & Silverstein, 2005). Over-active magnocellular pathways correlate with

poor selective attention, poor concentration, heightened awareness of background

noise and distractibility in individuals with schizophrenia (Hetrick, Erickson, &

Smith, 2010). It is suggested that tasks that combine contrast sensitivity to

magnocellular versus parvocellular biased stimuli may be useful in future

schizophrenia research (Green & Butler, 2009). In section 1.8.1.2 it is noted that the

contribution that magnocellular and parvocellular visual pathways have been

investigated in binocular rivalry, with one (Livingstone & Hubel, 1987) or both of

these systems implicated in initiating perceptual alternations (Yu & Levi, 1997).

However the research in this area is scant. Binocular rivalry stimuli that bias the

magnocellular and parvocellular visual pathways can be achieved by modifying the

stimuli presented to each with respect to luminance contrast, movement, colour and

spatial frequency. This provides a unique opportunity to explore magnocellular and

parvocellular processing in participants with schizophrenia and controls using two

binocular rivalry tasks, one to bias the magnocellular and the other the parvocellular

visual pathways in Chapter 4.

An inter-hemispheric model of binocular rivalry has been proposed that

suggests binocular rivalry is the result of competition between the two cortical

hemispheres that occurs by virtue of an ‘inter-hemispheric switching’ mechanism

(Pettigrew & Miller, 1998). Individuals with schizophrenia deficits in spatial

perception and attention related to right hemisphere functioning (O'Donnell, Potts et

al., 2002) and deficits associated with the transfer verbal information from the right

to the left hemisphere via the corpus callosum (Endrass, Mohr et al., 2002). To

investigate whether abnormal right hemisphere functioning has an effect on

binocular rivalry, binocular rivalry rates recorded by participants with schizophrenia


are compared to the Benton’s Judgment of Line Orientation (BJLO) task (Benton,

Varney & Hamsher, 1978); the BJLO task is widely accepted to be processed within

the right cortical hemisphere in Chapter 5.

One of the limitations to researching schizophrenia is most individuals are

taking at least one antipsychotic medication. For clinical diagnosis of schizophrenia

according to Diagnostic and Statistical Manual of Mental Disorders – Edition 4

(DSM-IV) criteria to be determined, a six-month trial period of an antipsychotic

medication with improvement in symptoms is needed. This makes an investigation

into the role of dopamine in binocular rivalry difficult as antipsychotic medications

block dopamine receptors; in particular the dopamine D2 receptor (Javitt, 2009).

Additionally, many hospital human research ethics committees are reluctant to allow

medications to be withheld from individuals with schizophrenia as they are likely to

experience return of symptoms and a reduction in long term cognitive functioning.

This restricts to investigations in medicated individuals or in un-medicated

individuals in the prodromal phase of schizophrenia; that is, the period before a

definite diagnosis is established. These challenges require novel approaches to the

investigation of neurotransmitter involvement in neural visual processing in

medicated participants.

Given that D2 receptors within the visual system play an important role in

visual functioning, and that schizophrenia has been associated with abnormal D2

receptor density and functioning, it is plausible to examine visual processing

according to genetic variations in D2 receptors. The TaqI A of dopamine D2

receptor (DRD2) gene is a commonly-investigated genetic locus in schizophrenia

(Behravan, Hemayatkar, Toufani & Abdollahian, 2008). Carriers of the A1 allele of

the Taq1 of dopamine D2 receptor (DRD2) gene polymorphisms (A1+ individuals


with A1/A1 or A1/A2 genotypes) typically have a lowered DRD2 density and

diminished function of DRD2 in the striatum, (Kondo, Mihara, Suzuki, Yasui-

Furukori & Kaneko, 2003; Mihara, Kondo et al., 2000; Noble, 2000). The presence

of the A1 allele of the DRD2 receptor gene, and thus the distribution of dopamine

receptors and dopamine function, offers a non-invasive and novel approach to

investigating dopamine involvement in binocular rivalry, explored in the final study

(Chapter 6).

Chapter 2: Altering Binocular Rivalry Rate by Increasing Luminance Contrast and Temporal Frequency: Support for an Oscillation Model of Binocular Rivalry 49

Chapter 2: Altering Binocular Rivalry Rate by Increasing Luminance Contrast and

Temporal Frequency: Support for an Oscillation Model of Binocular Rivalry

2.1 Binocular rivalry

2.1.1 Binocular rivalry rate.

Binocular rivalry rates are stable within individuals over time. High

correlations (above r = 0.8) are evident in binocular rivalry rates recorded weeks, or

years, after the initial test using the same stimulus (Miller et al., 2003, Pettigrew &

Miller, 1998; Pettigrew & Carter, 2005). Large between-individuals differences in

binocular rivalry rates have been reported by a number of authors (Carter et al.,

2005; Leat & Woodhouse, 1987, Miller et al., 2003; Pettigrew, 2001; Ukai, Ando &

Kuze, 2003), indicating that binocular rivalry rate may be determined by an

endogenously-driven individual characteristic.

It has been suggested that the less-frequently investigated binocular rivalry

rate, a measure of the rhythmical alternation between rivalling stimuli, reflects an

inextricable component of all forms of visual perception (Pettigrew & Carter, 2005).

Therefore, rate can be considered a key feature of the binocular rivalry phenomenon.

Pettigrew and Miller (1998) suggest that individuals have an endogenous ‘switch

rate’ or an internal rhythm of perceptual oscillations that remains fairly constant for

an individual, however may be modifiable by alterations made to the strength of the

stimulus. Pettigrew and Miller propose that a switching mechanism, located outside

the visual system, regulates binocular rivalry rate and rhythm. This model predicts

that individuals who have a faster endogenous ‘switch rate’ (‘fast switchers’) will

demonstrate more rapid perceptual alternations than ‘slow switchers’. Furthermore,

as the strength of the stimulus increases, perceptual alternations for ‘fast switchers’

50 Chapter 2: Altering Binocular Rivalry Rate by Increasing Luminance Contrast and Temporal Frequency: Support for an Oscillation Model of Binocular Rivalry

will increase at a more rapid rate than that seen in ‘slow switchers’. Pettigrew (2001)

provides a representation of this model as a figure, but provides no empirical data.

As noted in Chapter 1, binocular rivalry is significantly influenced by the

stimuli used. Subtle changes in the characteristics of the binocular rivalry stimulus

can produce large variations in binocular rivalry rates. Increasing stimulus strength,

achieved by increasing the luminance contrast, spatial frequency, colour and

temporal frequency of the competing stimuli (Breese, 1899; Levelt, 1968)

subsequently increases binocular rivalry rate (Fahle, 1982; O’Shea & Williams,

1996; O’Shea et al., 1997; Rogers, Rogers & Tootle, 1977).

Alternation of images is more rapid, and thus dominance durations are reduced,

when the stimuli presented to each eye vary greatly in terms of luminance contrast

(Mueller & Blake, 1989; Whittle, 1965), velocity (Blake, Aimba & Williams, 1985),

colour (Hong & Shevell, 2006; Rogers & Hollins, 1982; Wade, 1976), and spatial

frequency (Fahle, 1982; Wade, 1976). Presenting conflicting rival stimuli of different

strengths is appropriate when examining the effect of stimulus characteristics on

suppression (or dominance) of one eye’s perceptual image over the other. However,

this may not be the case when the rate or frequency of perceptual alternations is of

primary importance. Experimental evidence of binocular rivalry rate is generally

reliant on the examination of dominance duration, or exclusive visibility of the

competing stimuli, rather than a measure of alternation frequency (Hollins, 1980;

Mueller & Blake, 1989; O’Shea et al., 1997, Whittle, 1965).

To investigate the possibility that binocular rivalry rate is regulated by an

intrinsic rhythm or endogenous ‘switching mechanism’ located outside the visual

system, care must be taken in selecting the binocular rivalry stimuli. Experimental

methods allow binocular rivalry data to be collected in conditions where the stimuli


presented to each eye are equal, to ensure the visual system is not biased to observe

one image over the other. Levelt (1968) suggests that when conflicting stimuli are

presented to each eye equally (in terms of stimulus strength, the rate of alternations

recorded using a two-choice paradigm, and assuming all other things being equal) the

time spent viewing the right-eye (Tr) image will be equal to that spent viewing the

left-eye image (Tl), (so Tr = Tl) with the only effect on Tr or Tl being eye

dominance. In his fourth proposition, Levelt concluded that an, “increase of the

stimulus strength in both eyes will increase the alternation frequency” (Levelt, 1968:

page 76). Levelt defined ‘stimulus strength’ as the, “Amount of contour per area,

and for a constant amount of contour per area, the strength of those contours.”

Examining binocular rivalry rate using Levelt’s fourth proposition is therefore

appropriate to test the hypothesis of Pettigrew’s model, as this hypothesis assumes

that the oscillations occur between two stimuli of equal strength, with no inherent

bias. Collecting binocular rivalry data using the method by Pettigrew and Miller

(1998) presents stimuli of equal strength to each eye, with the orientation of the lines

being the only difference.

There are only a small number of studies in the binocular rivalry literature that

investigate the effect of increasing the strength of the stimuli presented to each eye

equally, and therefore Levelt’s fourth proposition. Alexander demonstrated that

‘stronger’ images will alternate more rapidly than ‘weaker’ images using two

conditions of stimulus strength, broken versus continuous contour, and greater or

lesser contrast between figure and ground (Alexander, 1951). However, luminance

levels and spatial frequency were not quantified. In a later experiment, Hollins

(1980) demonstrated that exclusive visibility increases as contrast increases equally

in both eyes; however this significant difference was only seen for one participant.


In an earlier classic study Breese, using red gratings presented to one eye and green

gratings to the other, demonstrated that binocular rivalry rate increased when

luminance levels were increased from low-intensity light to the brightest intensity

(without dazzle) by the same amount in both eyes (Breese, 1899). Once more,

luminance levels were not quantified, and green gratings were present to one eye

while red gratings were presented to the other adding a colour confound. None of

these studies are recent and provide minimal data to support Levelt’s fourth

proposition, and provide insufficient quantifiable data to assess Pettigrew’s

hypothesis.

2.1.2 Dominance durations.

The distribution of perceptual dominance durations produced during binocular

rivalry tend to be right-skewed. More predictable distributions allow researchers a

greater opportunity to examine the relationship between perceptual awareness and

neural function. It has been widely reported that frequency histograms of perceptual

dominance durations during binocular rivalry approximate a gamma-density function

(Borsellino, De Marco, Allazetta, Rinesi & Bartolini, 1972; Carter & Pettigrew;

2003; De Marco et al., 1977, Levelt, 1968; Logothetis et al., 1996, Miller et al.,

2003; Pettigrew & Miller, 1998; Van Ee et al., 2006). Histograms of perceptual

dominance durations are proposed to fit a gamma distribution more adequately when

there are greater than 150 alternations/time periods recorded (Brascamp et al., 2006).

Thus, better fit would theoretically be achieved with high-strength stimuli, rather

than low-strength stimuli. However, there are a number of authors who have failed to

fit empirical data to the gamma distribution (Brascamp et al., 2005; Cogna, 1973;

Zhou et al., 2004), making this assertion controversial. Testing this proposition and

that of Pettigrew and colleagues, with empirical data may allow us the opportunity to


investigate the interaction between stimulus characteristics and individual variability

in binocular rivalry. Mapping dominance durations, as a behavioural measure of

neural activity in participants with schizophrenia and controls, may provide a greater

understanding of the neural processes involved in the perceptual disturbances

attributed to this disorder.

2.2 Study 1

2.2.1 Aims.

The first aim of this study was to determine if increasing the strength of

rivalling stimuli (vertical and horizontal gratings of equal strength) in terms of

luminance, spatial frequency, colour or movement increased the rate of binocular

rivalry alternation in a group of 20 healthy participants. The second aim was to

determine whether binocular rivalry alternations increase to a greater extent in ‘fast

alternators’ than in ‘slow alternators’ using the binocular rivalry method used by

Pettigrew and Miller (1998) and Miller et al., (2003). A third aim was to determine

whether the perceptual dominance durations of fast alternators would more readily fit

a gamma distribution than those produced by slower alternators, when the gamma

distribution is defined as f(x) = λr / Г(r) xr-1exp (-λx), where Г(r) = (r-1)!

2.2.2 Hypotheses.

The hypotheses tested were:

Increasing the stimulus strength of binocular rivalry stimuli

subsequently increases binocular rivalry rates. Furthermore, these

increases are greater in ‘fast binocular rivalry alternators’ compared to

‘slow binocular rivalry alternators’;

Histograms of perceptual dominance durations derived from faster

alternators would approximate a gamma distribution.


2.3 Method

Before commencing the study, a power analysis was performed to determine

the minimum number of participants required to reject the null hypothesis that,

“Increasing stimulus strength (by increasing spatial frequency, luminance, movement

and colour) does not increase binocular rivalry rate.” The published binocular rivalry

rates reported in healthy participants by Miller et al., (2003) were entered into the

G*power3 program (Faul & Erdfelder, 1992). It was estimated that a sample size of

20 individuals was required for a two-sided 5% significance level and power of 80 to

produce an overall effect.

2.3.1 Participants.

Twenty healthy volunteers, who were screened to exclude neuropsychiatric

disease with the Structured Clinical Interview for the DSM-IV (SCID), were

recruited. Four participants were male, and 16 were female. The age range was 22-

64 years (M = 39.8, SD = 12.97). All participants were right-handed, as assessed

using the Annett Handed Questionnaire (Annett, 1970). All participants had normal

vision (that is, were free from strabismus, astigmatism or eye disease) and 6/6 visual

acuity (corrected or uncorrected) in each eye as assessed by Snellen visual acuity

testing. All participants had normal vision and at least 6/9 visual acuity (corrected or

uncorrected) in each eye assessed by the Snellen visual acuity testing. To reduce any

eye dominance effect related to inter-ocular differences in visual acuity, participants

were excluded from the study if visual acuity in each eye was not equal (to within

two letters). In addition, each participant undertook a keyhole task to determine

sighting eye dominance as described in (Osburn & Klingsporn, 1998).

Written informed consent was provided by each participant prior to the

commencement of testing. Ethical clearance was obtained from the Royal Brisbane


and Women’s Hospital Human Research Ethics Committee, and the Queensland

University of Technology Human Research Ethics Committee. Binocular rivalry

testing took place at an outpatient facility of the Royal Brisbane and Women’s

Hospital and in the Optometry Clinic at the Queensland University of Technology.

2.3.2 Apparatus.

2.3.2.1 Binocular rivalry stimuli.

The binocular rivalry stimuli were presented as a stationary, circular-grid

target, subtending 1.5 of visual angle, generated on a personal computer monitor

using BRtestTM software (BiReme Pty Ltd. Brisbane, Australia). The grid was

achieved by rapidly alternating the two rivalling stimuli (vertical and horizontal

square wave gratings) at 120 Hz (this methodology reduces any Troxler effect; see

(Blake, 2005; Levelt, 1968). The grid was viewed from a distance of three metres

through liquid crystal shutter goggles (NuVisionTM60GX, MacNaughton, Canada).

This system of collecting binocular rivalry data presents horizontal and vertical line

stimuli (square wave gratings) of equal strength to each eye with respect to contour,

luminance, movement and colour, in the same retinal location with minimal

crosstalk; the only difference being the orientation of the lines. The use of liquid

crystal glasses eliminated the need for fixation, and thus required minimal instruction

allowing completely näive participants to experience binocular rivalry and accurately

record their precepts. Additionally, the researcher could manipulate the presentation

of vertical and horizontal lines to either the left or right eye without the participant

being aware, allowing orientation of the lines to be counter-balanced across

participants and stimulus conditions. This eliminates any potential effects of eye

dominance or vertical/horizontal preference.


Luminance and chromaticity levels were measured at a distance of three metres

through the shutter goggles (NuVisionTM60GX , MacNaughton, Canada) by a

luminance colourimeter (model BM-7, Topcon, Japan). The maximum luminance

condition was determined by the maximum luminance capability of the computer

monitor, with luminance levels measured through the goggles being 60% less than

without the goggles. This limited the maximum actual test luminance, and the range

over which luminance could be varied. Average luminance of each stimulus was

calculated as Lmax+Lmin/2. Lmax and Lmin were measured through the shutter

goggles using a 0.2 field to ensure that the black and red/white bars were measured

independently. However, because the 0.2 field covered the entire diameter of the

target bar in the 8 cpd conditions but not in the 4 cpd conditions, slight variations in

the measurements occurred, however these were small (< 0.4 cd/m2) and therefore

the average was taken. Luminance levels for the high-luminance condition were

(Lmax) 9.6 – 10.0cd/m2 and (Lmin) 1.6–1.7 cd/m2. Luminance levels for the low-

luminance condition were (Lmax) 1.9 – 2.2 cd/m2 and (Lmin) 1.4– 1.6 cd/m2.

Average luminance for low-luminance stimuli was 1.6cd/m2, and in the high

luminance stimuli 5.8 cd/m2. Luminance contrast was calculated using Michelson’s

formula, (Lmax-Lmin)/(Lmax +Lmin); 15% for the low- and 68% for high-contrast

conditions in both the red/black and white/black conditions. For consistency,

reported luminance levels were measured from the centre of the field for the vertical

grating. Cross-talk between the goggle lenses was minimal. Lmax was <0.01 cd/m2

when the vertical lines were measured through the horizontal shutter lens (and vice

versa).

To measure the effect of ‘colour’ and achieve equal-strength coloured stimuli

presented to each eye, vertical and horizontal monochromatic lines were presented


on the same background (consistent with (Carter & Pettigrew, 2003; Miller et al.,

2003; Pettigrew & Miller, 1998). White/black versus red/black gratings were chosen

(white stimulating all cones, and therefore theoretically ‘stronger’ than red gratings

that stimulate only medium- and long-wavelength cones). The chromaticity

recordings were consistent for the red and white bars in all stimulus conditions; white

achromatic gratings (x= 0.3102, y= 0.3307) and red chromatic gratings (x= 0.6181,

y= 0.3251). Chromaticity measures reported here were without the goggles, as

recordings through the lenses could not be achieved.

Moving 4 cycles per second (c/s) versus not moving (stationary, 0 c/s) stimuli

were selected to insure comparison of two discrete groups of stimuli; stationary or

not moving with moving stimuli. Ideally, the rivalling stimuli should be presented at

two different temporal speeds (for example, 2 c/s versus 4 c/s). However, because

stimuli are also presented at two different spatial frequencies (4 cpd and 8 cpd),

movement/spatial frequency confound is introduced. Stimuli of 4 cpd and 8 cpd

appear to move at different speeds when temporally modulated at 2 c/s, as do 4 cpd

and 8 cpd stimuli modulated at 4 c/s. It could not be determined with any certainty

that stimuli moving at 4 c/s were moving faster, and therefore produced increased

stimulus strength, than at 2 c/s when using stimuli of two different spatial

frequencies. The moving stimuli were presented at 4 c/s. This was calculated by

counting the number of cycles (one light and dark bar comprising one cycle) that

crossed the side of the stimulus aperture in 10 seconds. One cycle measured 0.25

cpd for the 4 cpd stimuli and 0.125 cpd for the 8 cpd stimuli.

This study provides a number of methodological improvements over previous

classical studies of binocular rivalry. The binocular rivalry method allowed the

manipulation of luminance contrast, spatial frequency, temporal frequency and


colour of the binocular rivalry stimuli, while ensuring that the strength of stimuli

presented to each eye remained equal, with the orientation of the lines being the only

difference. This ensured that Levelt’s fourth proposition was able to be tested, and

Pettigrew’s model explored.

2.4 Design

Binocular rivalry data were collected using a 2X2X2X2 (luminance, spatial

frequency, chromicity, movement) repeat design. Two luminance conditions

(lower= 1.6 cd/m2, and higher= 5.8 cd/m2), spatial frequencies (4 cpd and 8 cpd),

chromatic conditions (white bars [x= 0.3102, y= 0.3307] on black background and

red bars [x=0.6181, y=0.3251] on a black background) and movement conditions

(stationary and temporally modulated moving stimuli, 4 c/s) were included. To

ensure that all participants experienced optimal binocular rivalry and avoided

binocular fusion, stimuli conditions were chosen well within the binocular rivalry

threshold (being where greater than 50% of participants perceived binocular rivalry

for greater than 50% of the time). Binocular fusion can occur at spatial frequencies

below 2 cpd (Liu et al., 1992) and above 10 cpd (Livingstone & Hubel, 1987), and at

low luminance contrast (Hong & Shevell, 2006; Liu et al., 1992). Each participant

completed sixteen two-minute blocks of binocular rivalry measurements. To ensure

test order did not influence binocular rivalry, the order of binocular rivalry tasks

were counterbalanced with respect to spatial frequency, luminance, colour and

movement.

To compare ‘fast’ with ‘slow’ alternators, individuals were grouped according

to their mean binocular rivalry rates, and considered either ‘fast’ or ‘slow alternators’

when more than 50% of their mean binocular rivalry rates fell within the either the

top or bottom quartile over the 16 stimulus conditions.


2.5 Procedure

Testing took place in dimly lit room (40 lux). Participants were adapted to the

luminance conditions of the binocular rivalry tasks for five minutes, and completed

the low-luminance tasks before completing the high-luminance binocular rivalry

tasks. Participants were seated three metres from the computer screen with the

goggles in place.

They were asked to record binocular rivalry alternations, by pushing a key on a

response keypad, when each image was exclusively dominant (when the image

comprised only vertical or horizontal lines). This method produces a forced two-

choice paradigm consistent with Levelt’s alternation model (1968), where time spent

viewing the right-eye (Tr) image will be equal to time spent viewing the left-eye

image (Tl), (so Tr = Tl), with the only effect on Tr or Tl being eye dominance.

Although in a two-choice forced paradigm the inclusion of mixed images inflates the

period that either the vertical or horizontal image is perceived, this has no effect on

binocular rivalry alternation rate (Blake, 2005; Kovacs & Eisenberg, 2005).

A small experiment was conducted in a subgroup of participants (n = 10) prior

to the main study to compare the accuracy of recording binocular rivalry using a two-

and three-choice paradigm using moving and stationary stimuli. A binocular rivalry

simulation task was developed and presented to ten participants (two males and eight

females) on a personal computer. The two-button task generally produced more

accurate responses than the three-button task (96.5% and 91% correct, respectively)

and seven out of the ten participants reported the two-button task as less confusing.

The frequency of alternations (referred from here on as binocular rivalry rate)

was calculated by dividing the number of button pushes by the total time of rivalry,


and was reported in Hertz (Hz). The period between button pushes (from here on

referred as to as ‘dominance durations’) was measured and recorded in milliseconds.

2.6 Statistical Analyses

2.6.1 Two-sided Smirnov test to compare dominance duration distributions.

To determine the difference between dominance duration distributions

produced by slow and fast alternators, and therefore the likelihood of individual

variations that may contribute to binocular rivalry rate, a two-sided Smirnov test was

conducted for each condition. The data consisted of two independent random

samples, one of size n, X1, X2 …. Xn (slow alternators) and the other of size m, Y1,

Y2, …. Ym (fast alternators). If F(x) and G(x) represent the unknown, distribution

functions of slow and fast alternators respectively, the hypotheses for a two-sided test

would be;

H0 :F(x) = G(x) for all x from - ∞ to + ∞.

H1 : F(x) ≠ G(x) for at least one value of x.

To calculate the test statistic S1 (x) is the empirical distribution function based

on the random sample X1, X2 …. Xn, and S2 (x) is the empirical distribution function

based on the other random sample Y1, Y2, …. Ym. The test statistic, T1, is the greatest

vertical distance between the two empirical distribution functions.

T1 = sup /S1 (x) – S2 (x)/ x.

The decision rule, to reject H0 at the level significance α is if T1 exceeds its 1

– α quantile. For large samples (where n and m > 20) the 0.95 quantile of T1 is given

by w0.95 ≈1.36√ m+n/ mn (Conover, 1971).


2.7 Results


Binocular rivalry rates were normally distributed so parametric analyses were

used. Test conditions included two levels of luminance (lower and higher),

stationary and moving, two spatial frequencies (4 cpd and 8 cpd), and achromatic

(white) and chromatic (red) bars. Individual differences in mean binocular rivalry

rates recorded across the 16 stimulus conditions ranged from 0.26 Hz to 0.89 Hz.

The slowest individual binocular rivalry rate (0.11 Hz) was recorded using the

stationary 8 cpd coloured stimuli of low luminance, while the fastest individual

binocular rivalry rate (1.32 Hz) was recorded using the achromatic, stationary, and

high-luminance 8 cpd stimulus.

Figure 2.1 shows binocular rivalry rates for each participant across the 16

stimulus conditions. Examination of Figure 2.1 shows that altering the binocular

rivalry stimuli characteristic affects binocular rivalry rate more in some participants

than seen in others. For example, participant six (M = 0.321 Hz, SD = 0.042 Hz,

min 0.27 Hz, max 0.42 Hz, range 0.15 Hz) contrasts with participant 13 (M = 0.901

Hz, SD = 0.247 Hz, min 0.43 Hz, max 1.32 Hz, range 0.89 Hz).


Individual Differences in Binocular Rivalry Rates

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Participants

Bin

oc

ula

r ri

va

lry

ra

te in

He

rtz

L4AS L4AM L4CS L4CM L8AS L8AM L8CS L8CM

H4AS H4AM H4CS H4CM H8AS H8AM H8CS H8CM

Figure 2.1: Binocular rivalry rates by 20 participants across all stimulus conditions (n = 16). Dashed line represents the mean binocular rate (M = 0.463Hz) for all stimulus conditions across all subjects. Legend shows stimulus condition (L= low luminance, H= high luminance, 4= 4 cpd, 8= 8cpd, A= achromatic [white], C= chromatic [red], M= moving and S= stationary).

In general, all stimuli presented at higher luminance (5.8 cd/m2) produced

faster mean binocular rivalry rates (M= 0.548 Hz, SD = 0.357 Hz), ranging from 0.49

Hz to 0.61 Hz, than those of lower luminance (1.6 cd/m2), (M= 0.376 Hz, SD = 0.057

Hz), with a range of 0.3 Hz to 0.46 Hz. Changing the binocular rivalry stimulus

condition affected the binocular rivalry rate to varying degrees in each participant.

Participant three recorded the lowest mean binocular rivalry rate of 0.235 Hz,

participant 10 the highest (0.995 Hz) while participant six demonstrated the smallest

range of binocular rivalry rates (range 0.15 Hz) and participant 13 the greatest (0.89

Hz). Moving stimuli (4 c/s) tended to produce faster mean binocular rivalry rates (M

=0.498 Hz, SD = 0.084 Hz) than stationary stimuli (M = 0.426 Hz, SD = 0.106 Hz) in

both high- and low-luminance conditions, with high-luminance moving stimuli

producing faster binocular rivalry rates (0.55 Hz to 0.61 Hz) compared with


stationary stimuli (0.49 Hz to 0.55 Hz). Mean binocular rivalry rates across the 16

stimulus conditions are shown in Figure 2.2.

To ensure that the low- and high-stimulus strength conditions produced a

difference in binocular rivalry rates and were appropriate to test the hypotheses,

repeated measures ANOVA was performed. Repeated measures ANOVA revealed

that luminance and movement had a significant main effect on binocular rivalry rate,

(F[16,19] = 60.571, p < .001 and F[16,19] = 18.692, p < .001, respectively) and that

spatial frequency and colour had no effect on binocular rivalry rate (F[16,19] =

1.015, p = .326 and F[16,19]=0.82, p = .377 respectively). As declines in the visual

system may occur with age, age was added as a covariate, the significant main effect

for movement remained (F(1,18) = 18.677, p < .001), but was reduced to a trend for

luminance contrast (F(1,18) = 4.188, p = .056). Gender, eye dominance and

handedness showed no effect (p > .05).

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

4cpd/White 4cpd/Red 8cpd/White 8cpd/Red 4cpd/White 4cpd/Red 8cpd/White 8cpd/Red

Stationary Moving

BR

Rat

e in

Hz

Low Luminance High Luminance

Figure 2.2: Mean binocular rivalry rates (n = 20) across the 16 stimulus conditions. Note: Error bars show standard error.


Normalised dominance durations (time periods between button pushes,

measured in milliseconds expressed as fractions of their means), approximated a

gamma-density function (Carter & Pettigrew, 2003; Logothetis et al., 1996, Miller et

al., 2003). When histograms of the normalised dominance durations of the 16

stimulus conditions were drawn, typical right-skewed distributions resulted. To

determine whether these empirical binocular rivalry data approximated a gamma-

density function, a one-sample Kolmogorov-Smirnov goodness-of-fit test was

performed against the normalised dominance durations for each of the 16 stimulus

conditions, using the Statistical Analysis System (SAS®) computer software. Only

one of the 16 stimulus conditions (the stationary, low-luminance, achromatic of 4 c/d

condition) demonstrated an acceptable fit to the gamma density function

(Kolmogorov-Smirnov D = 0.0288, p = .140). The other conditions demonstrated an

unacceptable fit (p < .05) to the gamma-density function (a p value of greater than

.05, demonstrating a good fit).

2.7.2 Fast versus slow alternators (binocular rivalry rate).

Because colour and spatial frequency did not have a significant main effect on

binocular rivalry rate, mean binocular rivalry rates calculated from the original

analyses were averaged across the conditions of colour and spatial frequency, leaving

luminance and movement. A second analysis was then performed to determine

whether participants who had slower binocular rivalry alternations (‘slow

alternators’) were less affected by changes to stimulus conditions compared to those

with faster binocular rivalry alternations (‘fast alternators’), as proposed by Pettigrew

(2001). The mean binocular rivalry rate of the 320 trials (20 participants x 16

conditions) was 0.41 Hz. ‘Fast alternators’ (n = 3) were those who recorded

binocular rivalry rates within the fastest 25% quartile (with mean binocular rivalry


rates > 0.58 Hz) in more than 50% of the 16 stimulus conditions. ‘Slow alternators’

(n = 3) recorded mean rates within the slowest 25% quartile (with mean binocular

rivalry rates <0.28 Hz) in more than 50% of the 16 stimulus conditions. The

resultant ‘fast’ and ‘slow’ groups were similar with respect to age (mean ages of 37

years and 42 years, respectively). The fast group comprised of three females and the

slow group of one male and two females. The resulting analysis was a 2 X 2 X 2

design (luminance, movement and group).

Repeated measures ANOVA revealed there was a between-participant effect in

binocular rivalry rates (F[1] = 8.201, p = .006) when stimulus strength was increased

by increasing luminance and movement. However, within-participant analyses

revealed an overall difference in binocular rivalry rates between the fast and slow

groups when luminance was increased (F[1] = 8.092, p = .047) but not when

movement was increased (F[1] = 0.774, p = .429). Paired samples t-tests revealed

significant differences between binocular rivalry rates for slow alternators (n = 3)

using stationary stimuli and when stimulus strength was increased from low to high

luminance (t[2] = -10.961, p = .008), and high luminance stimuli with stimulus

strength increasing from stationary to moving (t[2] = -13.0, p = .006). Significant

differences between binocular rivalry rates were observed in stationary stimuli when

stimulus strength was increased from low to high luminance (t (2) = 5.615, p =.03) in

fast alternators (n = 3).

To investigate whether fast binocular rivalry alternators showed a steeper

increase in binocular rivalry rate as stimulus strength increased, the difference in

binocular rivalry rate recorded at low and high stimulus strength was calculated and

compared in each of the four stimulus conditions; stationary, moving, low and high

luminance stimuli conditions and presented graphically in Figure 2.3.


From Figure 2.3 it can be seen that in all conditions slow alternators (dashed

lines) produced slower binocular rivalry than did fast alternators (solid lines). Their

rates increased when the strength of the stimulus increased from low to high.

Comparing the difference in mean binocular rivalry rates produced by low- and high-

strength stimuli in each group, the steepest increases in binocular rivalry rates

occurred in faster alternators (in a manner consistent with Pettigrew, 2001) in three

of the four conditions. With stationary stimuli, increasing stimulus strength by

increasing the luminance increased the mean binocular rivalry rate by a difference of

0.09 Hz in slow alternators. This increase was 0.34 Hz in fast alternators. In moving

(4 c/s) stimuli, increasing stimulus strength by increasing the luminance from low to

high increased the mean binocular rivalry rate by a difference of 0.09 Hz in slow

alternators compared to a difference of 0.3 Hz in fast alternators. This difference

was also observed with low-luminance stimuli where stimulus strength was increased

from 0 c/s to 4 c/s, resulting in a 0.18 Hz increase in binocular rivalry rates in fast

alternators compared with a 0.05 Hz difference in slow alternators. In high-

luminance stimuli, increasing stimuli strength from 0 Hz to 4 Hz resulted in a 0.05

Hz difference in both fast and slow alternators, suggesting that at high luminance

increasing the stimulus strength by movement had a similar effect in both groups.

When these results were presented graphically (Figure 2.3) and compared with

the theoretical graph of Pettigrew (2001) (Figure 2.4), it is evident that slow- and

fast-switchers (measured by binocular rivalry alternation rates) produced consistently

slow and fast binocular rivalry rates that increased when the strength of the stimulus

increased from low- to high-luminance, in a manner consistent with Pettigrew’s

model (2001). The effect was seen least in individuals with a slower switch rate (for

example Figure 2.4 a), who have a relatively shallow slope. Faster switchers (for


example Figure 2.4 d) show the steepest increase in binocular rivalry rate as a

function of stimulus strength. Generally, binocular rivalry rates increased until

rivalry gave way to a mixed precept; this transition varied between individuals. The

highlighted rectangular area relates to the approximate variation in stimulus strength

of the binocular rivalry stimuli used and depicted in Figures 2.3 and approximate

rivalry rates measured.

A

B

Figure 2.3: The effect of increasing stimulus strength on binocular rivalry rate in ‘slow’ and ‘fast’ alternators: mean binocular rivalry rates recorded by 20 healthy volunteers grouped based on the participants mean binocular rivalry alternation rate, A. The effect of increasing stimulus strength by introducing movement to low and high luminance stimuli in fast (n=3) and slow (n=3) alternators. B. Error bars show standard error.

Data in Figure 2.3 A are rearranged to highlight that binocular rivalry rates increased for both stationary and moving stimuli when stimulus strength was increased by increasing luminance contrast. Note: Error bars show standard error.

Low Luminance

0.24

0.80

0.19

0.62

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0c/s 4c/s

BR

Rat

e in

Hz

High Lumiance

0.33

1.01

0.28

0.96

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0c/s 4c/sB

R R

ate

in H

z

Moving

0.33

1.01

0.24

0.80

0.0

0.2

0.4

0.6

0.8

1.0

1.2


BR

Rat

e in

Hz

LegendFast Slow

Stationary

0.280

0.960

0.19

0.62

0.0

0.2

0.4

0.6

0.8

1.0

1.2


BR

Rat

e in

Hz

*

*

*

Statistically significant *


Figure 2.4: The effect of stimulus strength on binocular rivalry rate: Binocular rivalry rate increases as stimulus strength increases.

Note: Figure adapted from the model proposed by Pettigrew JD, Brain and Mind 2; 2001, p97.

2.7.3 Binocular rivalry dominance durations in fast and slow alternators.

Differences in the steepness of increase of binocular rivalry rates between slow

and fast alternators were observed as stimulus strength increased. More frequent

dominance durations (approx 150 reversals per percept) have been reported to

produce a better fit to a gamma function (Brascamp et al., 2005; Brascamp et al.,

2006). It was expected that the distributions of normalised dominance durations of

fast alternators would show a more-acceptable fit to the gamma-density function over

the 16 stimulus conditions than slow alternators. Kolmogorov-Smirnov goodness-of-

fit analyses (Conover, 1971) on the fast and slow groups revealed that the null

hypothesis was unable to be rejected for any of the 16 stimuli normalised dominance

duration distributions produced by the fast group, (i.e. all distributions showed an

unacceptable fit to the gamma distribution). The slow group produced dominance

duration distributions that demonstrated acceptable fit in six of the 16 stimulus

conditions (being the low luminance of 4 c/d spatial frequency, moving and


stationary, chromatic and achromatic conditions; the low luminance, chromatic, 8c /d

moving stimulus and the high luminance chromatic, 8 c/d stationary stimulus).

When these results were presented graphically (Figure 2.5), differences in the

shape of the cumulative frequency distributions of binocular rivalry recordings of

slow switchers compared with fast switchers in nine stimulus conditions can be seen.

Level of significance α is if T1 exceeds its 1 – α quantile. The test statistic, T1, is the

greatest vertical distance between the two empirical distribution functions.

Normalised perceptual dominance durations in fast and slow alternators were

significantly different in nine of the 16 stimulus conditions.


Table 2.1: The Kolmogorov-Smirnov goodness of fit analysis statistics for the dominance duration distributions for fast and slow alternators over 16 stimulus conditions (n=20).

Slow Alternators Fast Alternators

Stimuli KS_T p KS_T p

L4AS 0.0629 *.5 0.1041 .001

L4AM 0.0575 * .5 0.0864 .001

L4CS 0.0928 * .162 0.0821 .002

L4CM 0.0746 * .25 0.0948 .001

L8AS 0.134 .029 0.0948 .001

L8AM 0.1234 .007 0.0848 .001

L8CS 0.1502 .025 0.0918 .001

L8CM 0.0728 * .25 0.0939 .001

H4AS 0.1109 .008 0.1107 .001

H4AM 0.1314 .001 0.098 .001

H4CS 0.1442 .001 0.1095 .001

H4CM 0.1418 .001 0.0974 .001

H8AS 0.1295 .001 0.1244 .001

H8AM 0.1478 .001 0.1025 .001

H8CS 0.0575 * .5 0.1003 .001

H8CM 0.1259 .001 0.06969 .001

Note: Values indicate* p >.05 acceptable fit to Gamma Distribution. Stimuli Legend: L= low luminance, H= high luminance, 4= spatial frequency of 4 c/d, 8= spatial frequency of 8 c/d, A= achromatic white/black gratings, C= coloured red/black gratings, S= stationary 0c/s and M= moving at 4 c/s.


Table 2.2: The two-sided Smirnov test statistic for fast and slow alternators (m and n respectively) compared with the critical values determined by of T1 at the 0.95 quantile (w0.95 ≈1.36√ m+n/ mn) across the 16 test binocular rivalry stimuli conditions (n=20).

Stimulus

Slow

(n)

Fast

(m)

CV_T for S at

95%

Smirnov

T

Reject

H0?

L4AS 88 199 0.174105 0.071208 No

L4AM 106 300 0.153669 0.079308 No

L4CS 68 211 0.189647 0.116323 No

L4CM 88 306 0.164507 0.265134 Yes

L8AS 51 251 0.208891 0.296852 Yes

L8AM 77 275 0.175347 0.167273 No

L8CS 41 239 0.229893 1.8808 No

L8CM 73 271 0.179337 0.238134 Yes

H4AS 93 318 0.160326 0.216372 Yes

H4AM 127 340 0.141434 0.159472 Yes

H4CS 129 362 0.139453 0.284059 Yes

H4CM 164 369 0.127634 0.103659 No

H8AS 125 358 0.141291 0.130034 No

H8AM 128 376 0.139172 0.210771 Yes

H8CS 112 348 0.147747 0.735324 Yes

H8CM 124 369 0.141168 0.215032 Yes

Note: *Decision to reject the null hypothesis (H0) i.e. there is no difference in the normalised dominance distribution produced by slow compared with fast alternators.


Figure 2.5: Cumulative frequency distributions of normalized dominance durations recorded by fast alternators (n = 3) compared with slow alternators (n = 3) in 16 stimulus conditions.

Legend: L= low luminance, H= high luminance, 4= spatial frequency of 4cpd, 8= spatial frequency of 8cpd, A= achromatic white/black gratings, C= coloured red/black gratings, S= stationary 0c/s and M= moving at 4 c/s.

2.8 Discussion

2.8.1 Binocular rivalry rates.

In this study, the effects of increasing the stimulus strength of rival stimuli

from low to high luminance, movement, colour and spatial frequency on rivalry rates

rate were examined extending the work of Pettigrew and Miller (1998) and Miller et

L4AM

0.0

0.2

0.4

0.6

0.8

1.0

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5

Percept Durations (sec)

Cum

ulat

ive

Prob

abilit

y

L4CM

0.0

0.2

0.4

0.6

0.8

1.0

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5


Cum

ulat

ive

Prob

abili

ty

L8AM

0.0

0.2

0.4

0.6

0.8

1.0

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5


Cum

ulat

ive

Prob

abilit

y

L8CM

0.0

0.2

0.4

0.6

0.8

1.0

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5


Cum

ulat

ive

Prob

abili

ty

L4CS

0.0

0.2

0.4

0.6

0.8

1.0

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5


Cum

ula

tive

Prob

abili

ty

L8AS

0.0

0.2

0.4

0.6

0.8

1.0

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5


Cum

ula

tive

Pro

babi

lity

L8CS

0.0

0.2

0.4

0.6

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al., (2003). Increasing stimulus strength of rival targets, from low to high, equally in

each eye by increasing luminance and movement of the rival targets significantly

increased rivalry rates in healthy volunteers. Significantly faster binocular rivalry

rates were produced for stimuli of higher luminance contrast compared to those of

lower luminance contrast. This is consistent with previous reports where luminance

contrast was increased equally in both eyes (Alexander, 1951; Breese, 1899; Hollins,

1980; Liu et al., 1992; Mueller & Blake, 1989; Whittle, 1965) and when moving (4

c/s) were compared with stationary gratings (Blake et al., 1985). Although Blake,

Sobel and Gilroy (2003) reported longer dominance duration and slower alternation

rates with moving compared to stationary rival stimuli when the stimulus was altered

in only one eye. In the current study spatial frequency and colour had no effect on

binocular rivalry rate. This was unexpected as long- and medium-cone pathways

(Rogers et al., 1977), as well as short-cone pathways (O’Shea & Williams, 1996), are

thought to be able to generate binocular rivalry. No significant differences in

binocular rivalry rates were found for high spatial frequencies (8 cpd) compared with

lower spatial frequencies (4 cpd), consistent with (Blake & Fox, 1974). These results

differed to Fahle (1982), Hollins (1980) Miller et al., (2003) and O’Shea et al.,

(1997), and Levelt’s alternation model (1968) with respect to spatial frequency. It

should be noted that these authors did not hold luminance contrast constant, so this

difference in binocular rivalry rates may reflect spatial frequency/luminance contrast

interactions. The failure to find an increase in binocular rivalry rate as spatial

frequency increased from 4 cpd to 8 cpd cannot be interpreted as evidence that

spatial frequency does not affect binocular rivalry rate, as the range of spatial

frequencies tested was limited (4 cpd versus 8 cpd was used in the current study, as

these spatial frequencies were well within the binocular rivalry frequency threshold).


Stimuli of 1 cpd versus 10 cpd may have produced greater differences than those

noted in the current study.

Regardless of whether individuals were classified as slow or fast switchers,

binocular rivalry rates increased as stimulus strength increased from low to high in

terms of luminance and movement. These findings were consistent with Pettigrew’s

proposed oscillation model in both groups. Moreover, alternation rates in ‘faster

switchers’ increased to a greater extent than in ‘slower switchers’ as stimulus

strength increased from low to high - this is demonstrated by the steeper gradient of

‘faster switchers’ binocular rivalry rates in Figure 2. Although the data presented

here support Pettigrew’s model in terms of the intrinsic nature of binocular rivalry

rate, this study did not examine whether the perceptual alternation between

conflicting images during rivalry is an inter-hemispheric phenomenon resulting from

an oscillatory mechanisms that originates in brainstem (Carter et al, 2005). Other

authors have suggested that reciprocal inhibition oscillators may be responsible for

the binocular rivalry phenomena (Mueller & Blake, 1989). Other oscillation models

of binocular rivalry have been proposed, based on neural oscillation activity

occurring both in the early and late stages of the visual pathway (Laing & Chow,

2002; Lumer, Edelman & Tononi, 1997; Stollemwerk & Bode, 2003; Sohmiya,

Sohmiya & Sohmiya, 1998; Wilson, 2005).

It has been hypothesised that synchronous oscillations, involving all levels of

the visual system, play a major role in the generation of rhythmic activity in

binocular rivalry (Lumer et al., 1997). Oscillatory activity early in the primary visual

cortex has been implicated in binocular rivalry (Lee et al., 2005; Lumer, 1998;

Polonsky et al., 2000), further along the visual pathway in the thalamus and

corticothalamocortical loop (Lumer et al., 1997) and in cortical neurons (Carter et al.,


2005; Cosmelli et al., 2004; Srinivasan, Russell, Edelman & Tononi, 1999).

Cortical-form vision associated with binocular rivalry has been suggested to

comprise multiple, hierarchically-arranged areas with feed-forward and feed-back

interconnections, with neural competition a general characteristic throughout the

form-vision hierarchy (Wilson, 2003). Synchronised oscillations are thought to be

generated in the visual system when concentric circles and parallel lines are

presented half of each form, to opposite eyes, provoking binocular rivalry (Diaz-

Caneja, 1928; O’Shea, 1999). It is thought that these oscillations enable the

dichoptically viewed halves of the one form to be perceived as a whole (Alais,

O’Shea, Mesana-Alais & Wilson, 2000).

Critics of models of binocular rivalry suggest binocular rivalry originates in

early stages of visual processing (V1) and have argued that early stages of visual

processing produce oscillations that are too fast (in the 30 Hz range) to contribute to

the rhythmic alternations of images seen in binocular rivalry. However there is

ample physiological evidence indicating that slower oscillations, at speeds of 1-5 Hz

(reflecting the approximate speed of alternations in binocular rivalry) occur early in

visual processing (Castelo-Branco, Neuenschwander & Singer, 1998; Cosmelli et al.,

2004; Neuenschwander, Castelo-Branco & Singer, 1999; Newman & Grace, 1999;

Rudrauf et al., 2006; Sohmiya et al., 1998; Srinivasan et al., 1999; Srinivasan et al.,

1999; Tononi et al., 1998). If this is the case, then subtle differences in the features

of the rivalling stimuli are likely to increase neural firing, for example changes in

target movement and luminance will result in large individual variations in binocular

rivalry rate (as demonstrated here). Although these data do not enable speculation on

whether the perceptual alternation of competing stimuli that occurs in binocular

rivalry is related to a single switching mechanism in the visual pathway, or is the


result of synchronisation of oscillatory mechanisms along, or in, pathways of the

visual system, the data presented here support a general oscillation model of

binocular rivalry. That is, individuals have an intrinsic binocular rivalry rhythm that

can be modulated with alterations to the stimulus strength.

The main findings of the current study are consistent with physiological studies

that demonstrate an increase in contrast and target movement produces increased

neural activity in the cortex (Freeman, 2003; Livingstone & Hubel, 1988; Logothetis

& Schall, 1989; Sengpiel, Baddeley, Freeman, Harrad & Blakemore, 1998; Sengpiel

et al., 1995). An increase in binocular rivalry rate as luminance increases is thought

to correlate with an increase in the ‘stimulus energy’, therefore increasing the mean

firing rate of early cortical neurons (Hess, Dakin & Field, 1998). It is suggested that

V1 maps reflect the layout of neurons selective for stimulus energy, not for isolated

stimulus features such as orientation, direction, and speed (Mante & Carandini,

2005). No significant increase in binocular rivalry rate was found with increasing

stimulus strength in terms of spatial frequency and colour, which arguably may not

contribute to ‘stimulus energy’. It is therefore possible that increased binocular

rivalry rates associated with an increase in stimulus strength tracks the activity of

these V1 neurons, thus presenting a behavioural measure of neural activity within the

visual system.


The second aim of this study was to determine whether the perceptual

dominance durations of faster alternators would more readily fit a gamma

distribution than those produced by slower alternators (as in Brascamp et al., 2005).

The data presented here suggest the opposite. Slower alternators, those who produce

fewer dominance durations, produced normalised dominance-duration distributions


that more frequently predicted a gamma distribution (six of a possible 16 conditions

in slow alternators) compared to none in the fast alternators. Significant differences

were found in the shape of the normalised perceptual dominance durations of fast

and slow alternators in nine of the 16 stimulus conditions (Figure 2.5), which is

cautiously interpreted as suggesting individual physiological differences that effect

binocular rivalry processing.

It is unlikely that the failure to fit dominance durations to a theoretical gamma

distribution function was because the binocular rivalry data from 20 individuals were

pooled. Other authors demonstrated a good fit to theoretical gamma distribution

functions using the method adopted here (Carter & Pettigrew, 2003; Logothetis et al.,

1996; Miller et al, 2003; Pettigrew, 1998). The unacceptable fit of the current data to

the gamma distribution may have resulted from the inclusion of mixed precepts due

to the two-choice method of recording the binocular rivalry perceptions. The

inclusion of mixed perceptions increases the length of the dominance duration, so we

would expect that in slow alternators binocular rivalry data would be less likely to

approximate a gamma distribution than in fast alternators; the results presented here

suggest the opposite. Furthermore, it was noted during pilot testing that recording

data where mixed images were included was more difficult when using moving

stimuli, producing less accurate results, than that seen with stationary stimuli.

When the distribution of normalised dominance durations were compared,

using a two-sided Smirnov test, greater differences were found between slow and

faster alternators at higher luminance contrast (six of the eight stimulus conditions at

high luminance compared to only three in at lower luminance). The fast alternators

recorded significantly shorter dominance durations (with the interval between button

pushes/alternations being less than 1 second) in each condition. This suggests faster


visual processing at high luminance contrast in fast alternators. Thus, fast alternators

are more likely to ‘see’ images of short duration and respond to them (by recording

a response), so will demonstrate faster temporal resolution than slow alternators (see

Di Lollo, Hogben & Dixon, 1994; Dixon & Di Lollo, 1994; Johnson, Nozawa &

Bourassa, 1998; Kawabata, 1994; Schwartz & Winstead, 1988; Schwartz et al.,

1995).

2.8.3 Age.

Age affected the rate of binocular rivalry at low and high luminance in the

study sample. This may be due to age-related visual and luminance contrast deficits

that are consequential of age-induced changes in the optics of the eye and

degeneration of the visual neural pathway (Jackson & Owsley, 2003; Masson et al.,

1993). Other researchers have reported similar effects (Tarita-Nistor, Gonzalez,

Markowitz & Steinbach, 2006; Ukai et al., 2003). The effects of age strengthen the

view that individual physiological characteristics play a role in binocular rivalry.

Although specific conclusions cannot be drawn from the data presented here, it can

be speculated that physiological factors that influence visual processing of luminance

and movement, such as age related changes in dopamine and GABA activity

(Djamgoz, 1997) may play a significant role in binocular rivalry. Further

investigation into these stimuli attributes, in groups with physiological variation such

and in the aged or in clinical groups, may be fruitful for unlocking the mechanisms

contributing to binocular rivalry and visual awareness.

2.9 Conclusion

Increasing the stimulus strength by comparing low- and high-strength stimuli

in terms of luminance and movement equally in both eyes, produced significantly-

increased binocular rivalry rates in 20 healthy volunteers, consistent with Levelt’s


fourth proposition. Individuals were grouped into slow- and fast-switchers, according

to their mean binocular rivalry rate. As stimulus strength was increased from low to

high, individuals with fast-switch rates showed a steeper increase in binocular rivalry

rates than those with slower-alternation rates. Individuals who had slower binocular

rivalry rates produced normalised perceptual dominance distributions that could be

approximated to the gamma distribution more readily than those with faster

alternation rates. These data support models of binocular rivalry that recognise that

individual factors may influence binocular rivalry, and provide empirical data

relating to Levelt’s fourth proposition.

In this study participants were classified as ‘fast switchers’ or ‘slow switchers’

according to their mean binocular rivalry rate across the sixteen stimulus conditions.

Two small comparison groups (n=3) were identified. It may have been beneficial to

classify participants according to their performance on a task that provided an

alternative measured visual processing speed, for example a reaction time task.

Levelt’s model suggests that participants with faster binocular rivalry rates would

perform better on tasks that require faster visual processing than those with slower

binocular rivalry rates. Correlations between binocular rivalry rate and comparision

task may provide insights into how binocular rivalry is processed within the visual

system. These investigations may inform researchers how to incorporate binocular

rivalry tasks into a battery of tasks to investigate visual processing in schizophrenia

and other mental illnesses in future studies.

The group of ‘fast switchers’ comprised three females with a mean age of 37

years where the group of ‘slow switchers’ comprised one male and two females with

a mean age of 42 years. This introduced a potential age and gender bias. Replication


in a larger age and gender-matched groups is therefore necessary to confirm the

results presented here.

In the next chapter, group differences in binocular rivalry are explored.

Binocular rivalry rate and dominance durations elicited from high-strength stimuli

(as reported in Pettigrew & Miller, 1998) will be compared with low-strength

binocular rivalry stimuli (as reported in Miler et al., 2003) in participants with

schizophrenia compared to controls, using the methods of collecting binocular

rivalry.

Chapter 3: Slower Binocular Rivalry Rates in Individuals with Schizophrenia Compared to Healthy Controls 81

3.1 Binocular Rivalry Rate in Major Psychiatric Illness

Abnormal binocular rivalry has been reported in individuals with a clinical

diagnosis of bipolar disorder (BPD), schizophrenia, schizoaffective disorder or

depression and their relatives (Fox, 1965; Miller et al., 2003; Pettigrew & Miller,

1998; Sappenfield & Ripke, 1961; White et al., 2001; Yang et al., 2007). Slow

binocular rivalry rate has been suggested as a trait marker for BPD (Pettigrew &

Miller, 1998). Miller and colleagues (2003) reliably separated participants with BPD

from healthy participants using a low-strength binocular rivalry stimulus, but failed

to separate healthy participants from those with either schizophrenia or depression.

However, other researchers have identified participants with schizophrenia based on

their slower binocular rivalry rates (or increased mean dominance durations) (Fox,

1965; Frecska, White & Leonard et al., 2003; Sappenfield & Ripke, 1961; White et

al., 2001; Wright et al., 2003), suggesting that binocular rivalry rate may not be able

differentiate the type of mental illness present.

In seven out of the nine studies examining the rate of binocular rivalry and

duration of dominance in rivalry in subjects with schizophrenia, the primary aim of

the study was not to investigate classical binocular rivalry characteristics. Two

neuroimaging studies incorporated binocular rivalry tasks in subjects with

schizophrenia; one utilising functional MRI (Valle-Inclan & Gallego, 2006) and the

other whole-head MEG (Tononi et al., 1998). Although these studies provide

hypotheses related to defective interactions between brain regions, such as the

frontoparietal network and prefrontal area and aberrations in consciousness, they

provide no information about the form and frequency of binocular rivalry

Chapter 3: Slower Binocular Rivalry Rates in Individuals with Schizophrenia Compared

to Healthy Controls

82 Chapter 3: Slower Binocular Rivalry Rates in Individuals with Schizophrenia Compared to Healthy Controls

alternations in participants with schizophrenia. Most of the available data relating to

binocular rivalry rate and dominance durations in schizophrenia have been produced

as comparison data to address other research questions. For example, secondary

hypotheses investigated binocular rivalry switch rate in BPD in the Miller et al.,

(2003) study, Yang et al., (2007) examined binocular rivalry in first-line relatives of

subjects with schizophrenia and the effect of applying conflicting stimuli in rapid

reversal (dichoptic stimulus alternation, DSA) were examined in two studies White

et al., (2001) and Frecska, White et al., (2003). Yang et al., (2007) investigated the

effect of mood states on dominance period during rivalry in subjects with

schizophrenia and schizoaffective disorder. They found that increased dominance

periods were related to negative mood states in those with schizophrenia, but not in

healthy controls. Two early studies measured binocular rivalry in schizophrenia as

their primary aim. Both found binocular rivalry rate was slower in subjects with

schizophrenia compared to healthy controls (Fox, 1965; Sappenfield & Ripke, 1961).

Sappenfield and Ripke (1961) indicated that retinal rivalry in two thirty-second

periods discriminated between subjects with schizophrenia and healthy participants.

Similarly, Fox (1965) noted that participants with schizophrenia recorded slower

binocular rivalry rates compared to healthy participants. Their results were consistent

with the view that binocular rivalry rates are inversely correlated with

psychopathology; however this effect only manifested in the second two minutes of

their binocular rivalry testing paradigm. No contemporary studies have primarily

focussed on binocular rivalry in schizophrenia. Furthermore, the findings of

Pettigrew & Miller (1998) and Miller et al., (2003) are not well supported.

Drawing on perceptual rivalry data, and the assumption that binocular and

perceptual rivalry share common mechanisms (Brascamp et al., 2006; Kanai,


Moradi, Shimojo & Verstraten, 2005; Miller et al., 2000, Miller et al., 2003). Miller

et al., (2003) argued that the perceptual rivalry findings of previous studies Eysenck

(1952), Hunt & Guilford (1933) and Philip (1953) supported their claim that slow

binocular rivalry rate is a trait maker of BPD. Perceptual rivalry, or monocular

rivalry, differs to binocular rivalry in that the two alternative precepts of an image are

viewed by one or both eyes simultaneously, and can be seen even when one eye is

closed (examples include the Necker Cube, Rubin’s Vase, and Schroder’s Staircase).

Some suggest that binocular and perceptual rivalry share several common

characteristics (Kornmeier & Bach, 2004; O’Shea et al., 2009). For example, the

distribution of the duration of dominance also seems to emulate a gamma distribution

(Borsellino et al., 1972; Lehky, 1995; O’Shea et al., 2009). There is high inter-

participant variability in reversal rates (Borsellino et al., 1972; Kornmeier & Bach,

2004). Reversal rates can be influenced by physical properties of the stimulus (Meng

& Tong, 2004) and through voluntary control by the participants (Gomez,

Argandona, Solier, Angulo & Vazquez, 1995; Horlitz & O’Leary, 1993; Lack, 1970).

However, there are also potential mechanistic differences. For example, depth of

suppression is less pronounced in perceptual rivalry (Breese, 1899; O’Shea et al.,

2009) and increases in contrast affect perceptual and binocular rivalry in opposite

ways (O’Shea & Wishart, 2007). Increased contrast results in an increased

alternation rate in binocular rivalry, and a decreased alternation rate in perceptual

rivalry (O’Shea et al., 2009). Attention may influence Necker Cube reversals more

than binocular rivalry alternations (Meng & Tong, 2004; Tong, 2001; Van Ee et al.,

2006).

As previously noted, in terms of schizophrenia, the available perceptual rivalry

data are not conclusive. The data of Levander et al., (1985) suggest slower reversals


in participants with schizophrenia, whereas a much earlier study (Hunt & Guilford,

1933) reported that participants with ‘dementia praecox’ (an older term for

schizophrenia) had normal Necker reversal rates. Participants with schizophrenia

perceived the Schroder’s Staircases from above for significantly less time then the

perception of the stimulus from below, and had a tendency to have more reversals

than controls; however this was not significant (Calvert, et al., 1988). Similarly,

Hoffman et al., (2011) and Keil et al., (1998) reported that participants with

schizophrenia had faster reversals than healthy controls for the Rubin’s Vase. Thus,

it is difficult to argue that perceptual rivalry data support binocular rivalry data in

schizophrenia.

There is also discussion in the literature as to whether binocular rivalry and

perceptual rivalry reflect distinct (or similar) neural mechanisms based on whether or

not the percept durations have similarly-shaped distributions (Van Ee et al., 2006).

Dominance durations vary, are stochastic (random) (Blake, Fox & McIntyre, 1971),

statistically independent of each other (Fox & Herrmann, 1967; Walker, 1975) and

typically form gamma distributions when plotted as histograms (Brascamp et al.,

2005; Brascamp et al., 2006; Fox & Herrmann, 1967; Levelt, 1967; Logothetis et al.,

1996). However, there is debate as to whether gamma-shaped distributions of

dominance durations are a true characteristic of binocular rivalry. Dominance

durations reported in the current study fitted gamma distributions on six of 16

occasions. Other researchers have also failed to fit normalised dominance durations

derived from healthy participants to gamma distributions (Brascamp et al., 2005;

Brascamp 2006; Murata et al., 2003). Zhou et al., (2004) found that during

monocular rivalry, perceptual dominance distributions in participants with


schizophrenia fitted log-normal, Weibull and gamma distributions. This suggests that

multiple or different neural pathways may be involved.

In terms of dominance durations, Miller et al., (2003) found that normalised

dominance durations of binocular rivalry in healthy participants or those with

depression, BPD or schizophrenia were able to be ‘fitted’ to gamma distributions.

However, these authors provided no information regarding perceptual rivalry. The

data from Miller et al., (2003) and the existing available literature paint an unclear

picture with respect to whether participants with schizophrenia have binocular rivalry

rates and dominance distributions that differ from those of healthy participants. In

order to support Pettigrew and Miller’s assertion that slow binocular rivalry rate is a

trait marker for BPD, it is important to examine binocular rivalry rate in other mental

disorders, such as schizophrenia, to examine the generalisability of this

characteristic.

3.2 Study 2

3.2.1 Aims.

Two classic studies, Fox (1965) and Sappenfield & Ripke (1961) report slower

binocular rivalry rates in schizophrenia, that contrast with the study of Miller et al.,

(2003) which found no difference. In order to address this conflict, the aim of the

current study was to advance the work of Miller et al (2003), to ascertain whether

there are differences in binocular rivalry rate and dominance durations in individuals

with schizophrenia compared to healthy controls using their methods. It was

predicted there would be no difference in binocular rivalry rates recorded by

participants with schizophrenia compared to healthy controls using low-strength

binocular rivalry stimuli (as in Miller et al., 2003), but would be faster or the same

when using high-strength binocular rivalry stimuli (as in Pettigrew & Miller, 1998


with BPD). Faster or similar binocular rivalry rates in participants with

schizophrenia would support the claim that slower binocular rivalry rates are a trait

marker for BPD. Conversely, slower binocular rivalry rates in participants with

schizophrenia would question whether slow binocular rivalry is a trait marker for

BPD, and the utility of this task as a potential diagnostic tool. Alternation rates and

dominance durations in binocular rivalry and in a perceptual rivalry task (Necker

Cube) were also compared in subjects with schizophrenia using a within-participant

design.

3.2.2 Hypotheses.

The main hypothesis of the current study was that binocular rivalry rates

recorded by participants with schizophrenia and a perceptual rivalry task (the Necker

Cube) would be slower than those recorded by controls. It was also hypothesised that

normalised dominance durations would approximate a gamma distribution.

3.3 Method

Binocular rivalry rate and dominance durations were recorded for two

binocular rivalry tasks (one low-strength stimulus and one high-strength stimulus)

and one perceptual rivalry task in participants with schizophrenia (n = 20) and

healthy controls (n = 20). The same binocular rivalry methods and stimulus

conditions as described in Chapter 2, Section 2.2.2.1, were used.

3.3.1 Participants.

Written and informed consent were obtained from each participant before

commencement of binocular rivalry testing. Ethical clearance for this study was

obtained from the Royal Brisbane and Women’s Hospital Human Research Ethics

Committee and the Queensland University of Technology Human Research Ethics

Committee. Binocular rivalry testing took place at an outpatient facility of the Royal


Brisbane and Women’s Hospital and in the Optometry Clinic at the Queensland

University of Technology.

All participants were right-handed, as assessed using the Annett Handed

Questionnaire (Annett, 1970). All participants had normal vision and at least 6/9

visual acuity (corrected if necessary) in each eye assessed by the Snellen visual

acuity testing. To reduce any eye dominance effect related to inter-ocular differences

in visual acuity, participants were excluded from the study if visual acuity in each

eye was not equal (to within two letters). In addition, each participant undertook a

keyhole task to determine sighting eye dominance as described in (Osburn &

Klingsporn, 1998). The dominant sighting eye identified by the hole-in-card test

reliably coincides with the dominant eye as determined by binocular rivalry, which is

a useful quantitative indicator of eye dominance in clinical applications (Handa, et

al., 2004). As an indication of predicted IQ all participants completed the National

Adult Reading Test (NART) (O’Carroll et al., 1992; Crawford et al., 1992; Morrsion,

Sharkey, Allardyce Kelly & McCreadie, 2000). All participants were instructed to

abstain from caffeinated drinks for four hours and nicotine for one hour prior to

binocular rivalry testing, as caffeine and nicotine may increase binocular rivalry rate

(George, 1936).

3.3.1.1 Healthy participants.

Twenty control participants, with no previous history of neurological disease

or mental illness (confirmed using the Structured Clinical Interview for the

Structured Clinical Interview for the DSM-IV [SCID]), were recruited to the study.

3.3.1.2 Participants with schizophrenia.

Twenty participants with a clinical diagnosis of schizophrenia were recruited.

Clinical diagnosis of schizophrenia was confirmed using the DSM-IV (SCID). The


researcher (a Registered Mental Health Nurse) had previously undertaken training in

the use of the DSM-IV (SCID). Competence confirmed by inter-rater reliability

testing with two consultant psychiatrists. Nine participants met the schizophrenia

sub-type classification of paranoid schizophrenia with the remaining 11 categorised

to the undifferentiated schizophrenia sub-type. One participant was unable to

complete the NART due to inadequate literacy skills. The participant characteristics

of both groups are described in Table 3.1.

Table 3.1: Age, gender, eye dominance and NART scores of controls and participants with schizophrenia

Controls (n=20)

Schizophrenia(n=20)

χ2 df p

Age Mean (yrs) 37.8 37.9 Range 21-64 264 25.667 25 0.426 Gender Male 4 15 Female 16 5 12.13 1 0.001 Eye Dominance R)eye 11 12 L)eye 9 8 0.417 1 0.519 NART Score Mean 116 109 Range 102-122 105-125 22.687 18 0.196

All participants with schizophrenia were taking an anti-psychotic medication at

the time of testing; drugs and doses were converted to chlorpromazine equivalents

CPZE (Centorrino et al., 2002; Hargreaves, Zachary, LeGoullon, Binder & Reus,

1987; Humberstone, Wheeler & Lambert, 2004; Owen et al., 2002; Woods, 2003)

and ranged from 200-900 mg/day with the mean dose being 482.5 mg/day, and a

median dose of 425 mg/day. Symptoms of schizophrenia were rated according to the

Positive and Negative Syndrome Scale (PANSS) (Kay, Opler & Lindenmayer,

1988). Participants were grouped into having either positive or negative symptoms,


based on a composite scale derived from subtracting negative symptom rating scores

from positive scores on the PANSS (see Kay et al., 1988). Participants were

classified as experiencing a predominance of positive symptoms if their resulting

score was >0 (n = 9), or a predominance of negative symptoms if their score was <0

(n = 9). Two participants had a score of 0, indicative of equal positive and negative

symptoms. The two groups were well matched for age but not gender.

3.3.1.3 Procedure

3.3.1.3.1 Binocular rivalry testing.

To ensure that reliable data were collected, all participants received training in

the binocular rivalry task before testing. Binocular rivalry stimuli were presented on

a personal computer placed three metres from the participant. The participant viewed

the stimulus through liquid crystal shutter goggles that presented vertical or

horizontal gratings exclusively to each eye. Participants recorded their percepts on a

computer key pad attached to a second personal computer that collected binocular

rivalry data. The apparatus and method of collecting binocular rivalry used here

were identical to those employed in the study by Miller et al., (2003).

Each participant was tested using two binocular rivalry stimulus conditions; a

low- and high-strength stimulus. The low-strength stimulus consisted of a circular

field (1.5 degrees diameter) filled with monochromatic, stationary, 4 cpd, square

wave gratings of 90% luminance contrast. The high-strength stimulus consisted of

the same circular field filled with monochromatic, 8 cpd, square wave gratings of

100% luminance contrast, moving at approximately 4 cps. The velocity of the

moving lines was determined by separately counting the number of vertical and

horizontal lines that moved beyond the edge of the circular grid in a one minute time

period; this was then converted to cycles per second. The stimulus characteristics of


these two targets were chosen to match the low- and high-strength stimuli used in

Pettigrew and Miller, (1998) and Miller et al., (2003).

Luminance levels were measured at a distance of three metres through the

shutter goggles (NuVisionTM60GX , MacNaughton, Canada) using a luminance

colourimeter (model BM-7, Topcon, Japan). The maximum luminance condition was

determined by the maximum luminance capability of the computer monitor, with

luminance levels measured through the goggles averaging 60% less than those

without the goggles. The luminance contrast of each stimulus was calculated using

Michelson’s formula, (Lmax - Lmin) / (Lmax + Lmin) (Slaghuis, 1998). Luminance

contrast was calculated as 1.0 in the high-strength stimulus condition and 0.9 in the

low-strength condition.

Initially participants were asked to record when they perceived horizontal lines,

vertical lines and mixed images (as reported in Miller et al., 2003). However, during

pilot experiments it became obvious that the percept changing from vertical to

horizontal was difficult to determine for the high-strength task; there was high

measurement variability when data were collected in this manner. To improve the

accuracy of the data collected, participants were required to report only two

conditions, that is when vertical lines were exclusively seen and when horizontal

lines were exclusively seen. Participants were told to ignore mixed or combined

images. Participants only commenced the formal binocular rivalry testing when the

researcher was satisfied they understood the instructions by verbally reporting their

perceptions and accurately recording the alternation between vertical and horizontal

perceptions on a computer key pad (i.e. their verbal reports matched keyboard

responses).

3.3.1.3.2 Perceptual rivalry testing; the Necker cube.


For the perceptual rivalry task, a black line drawing of the Necker Cube

measuring 7.5cm, extending 1.5 degrees of visual angle, was presented on a personal

computer at a distance of three metres. Each participant was instructed to view the

Necker Cube passively and to verbally indicate when they perceived the cube

viewed, as seen from above, and when it changed and appeared to be seen from

below. When participants could confidently verbally signal the alternation between

views they were asked to indicate when the cube appeared to be viewed from the

front using the left response key, and when viewed from the back using the right

response key of the computer key pad (Kornmeier & Bach, 2004).

3.4 Statistical Analyses

A power analysis was performed to determine the minimum number of

participants that were required to demonstrate a difference in binocular rivalry rates

in low-strength stimuli (as used in Miller et al., 2003) and high-strength stimuli (as

used in Pettigrew and Miller (1998). The data provided by Miller et al., (2003) were

entered into the G*power3 program (Faul, Erdfelder, Lang & Buchner, 2007). It was

estimated that a sample size of 20 in each group was required for a two-sided 5%

significance level and power of 80 to demonstrate a difference in binocular rivalry

rate in the low- and high-strength binocular rivalry tasks in the participants with

schizophrenia compared to the healthy controls.

As the resulting binocular rivalry rates did not form normal distributions, non-

parametric statistics were used. Kruksal-Wallis one-way non-parametric ANOVAs

were performed to determine the effects that group, gender, age, education and

NART score had on binocular rivalry rate. To examine influences on binocular

rivalry rate in participants with schizophrenia, the analyses focussed on three factors

unique to the participants with schizophrenia: diagnostic sub-group (by DSM-IV


classification), type of schizophrenia symptoms (positive versus negative, as

determined by PANSS), and the dose of anti-psychotic medication quantified as

chlorpromazine equivalents (CPZE) were made (Mann-Whitney U tests). Data are

mean ± SD, unless otherwise stated.

The time intervals between responses that signal the onset of perceptual

alternations (measured in seconds) were normalised by dividing each interval by the

mean. Dominance duration intervals were normalised and cumulative gamma

distributions plotted. Classically, normalised dominance durations have been plotted

as histograms and fitted to a gamma distribution using a Kolmogorov-Smirnov

goodness-of-fit test (Borsellino et al., 1972; Carter & Pettigrew, 2003; De Marco et

al., 1997; Levelt, 1968; Logothetis et al., 1996; Miller et al., 2003; Pettigrew &

Miller, 1998; Van Ee et al., 2006). However, normalised binocular rivalry

dominance durations do not always form gamma distributions in healthy participants

(Brascamp et al., 2005; Brascamp et al., 2006; Cogan, 1973, De Marco et al., 1977;

Zhou et al., 2004), or those with schizophrenia (Miller et al., 2003). Thus,

differences in the resulting distributions of normalised dominance intervals were

compared, rather than attempting to fit dominance intervals to gamma distributions.

To determine whether there were any differences in the distributions of dominance

intervals produced by participants with schizophrenia compared to healthy controls, a

two-sided Smirnov test was conducted for each condition, as described in Section

2.5.3.1. In each binocular rivalry condition the data consisted of two independent

random samples, one of size n, X1, X2 …. Xn (dominance durations recorded by

participants with schizophrenia) and the other of size m, Y1, Y2, …. Ym (dominance

durations recorded by healthy controls). The decision rule, to reject H0 at the level

significance α is if T1 exceeds its 1 – α quantile; where n (the number of dominance


durations for the smallest sample- schizophrenia participants) and m (the number of

dominance durations for the largest sample- healthy controls) is greater than 20, the

0.95 quantile of T1 is given by w0.95 ≈1.36√ m+n/ mn (Conover, 1971).

In essence, the Smirnov test is a statistical test that determines the degree of

difference in the normalised distributions of data, regardless of the shape of the

distribution. The Smirnov test compares the differences of the values along the

distribution at specific points (bins). If there is more than a 0.05 difference in values

at any point along the two distributions (as indicated by the vertical distance between

two values) the criteria for a statistical difference in the dominance durations is met

(Conover, 1971).

3.5 Results


Binocular rivalry rate was significantly slower in participants with

schizophrenia compared the control group for both the high- and low-strength

stimulus conditions (Figure 3.1). Participant group had a significant main effect on

binocular rivalry rate for both stimulus conditions; low-strength condition χ2 =

12.952, df =1, p < .001 and high-strength condition χ2 = 12.662, df =1, p < .001. In

the low-strength stimulus condition binocular rivalry rates in the participants with

schizophrenia averaged M= 0.28 Hz, SD = 0.108 Hz, which was nearly half the speed

of that for controls participants where binocular rivalry rates averaged M= 0.545, SD

= 0.256Hz. Binocular rivalry rates in the group comprising of participants with

schizophrenia were significantly slower (Z = -3.612, p < .001). Binocular rivalry

rates in the high-strength stimulus condition were also significantly slower (Z = -

3.545, p < .001) in this group (M = 0.298, SD = 0.126 Hz) compared to controls (M

= 0.548, SD = 0.256Hz).


Age (χ2 [21, 40] =.124, p = .725), gender (χ2 [1, 40] = .165, p = .685), eye

dominance (χ2 [5, 40]= 1.000, p = .317) and NART score (χ2 [14, 40] = 1.091, p =

.296) (Kruksal-Wallis) had no effect on binocular rivalry rate for either stimulus

condition i.e. none of the tested within-participant variables appeared to affect

binocular rivalry rate and none acted as measurement confounders.

3.5.2 Necker Cube alternation rates.

In contrast, the rate of perceptual alternations did not differ (Z = -0.406, p =

6.698) in the group with schizophrenia (M = 0.327, SD = 0.236 Hz) compared to

controls (M = 0.343, SD = 0.185 Hz) for the Necker Cube task (Figure 1). Age,

gender, education and NART score had no effect on the rate of perceptual

alternations in either group (Kruksal-Wallis χ2, p > 0.05). Alternation rates for the

Necker Cube in control participants were slower than for the binocular rivalry tasks.

Binocular rivalry rates compared with Necker Cube perceptual alternations in

healthy controls in the low-strength condition Z = -3.509, p < .001, and in the high-

strength condition Z = -3.733, p < .001 (Wilcoxon sign ranks test). Participants with

schizophrenia recorded similar Necker Cube perceptual alternation rates as binocular

rivalry rates; in the low-strength condition Z = -0.485, p =.627, and in the high-

strength condition Z = -0.423, p < .673 (Wilcoxon sign ranks test). These data are

presented in Figure 3.1.


0.283 0.298

0.545 0.548

0.3260.343

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

BR Low Srength Condition

BR High StrengthCondition

Necker Cube

Alte

rnat

ion

Rat

e in

Hz

(But

ton

push

es p

er

seco

nd)

Schizophrenia Control

Figure 3.1: Mean alternation rates recorded in schizophrenia participants (n = 20, grey diamonds) compared to healthy controls (n = 20, black squares) in two binocular rivalry tasks.

Note; Error bars indicate standard error.

Based on the SCID DSM-IV results, participants with schizophrenia formed

two distinct diagnostic sub-groups groups; those with paranoid schizophrenia (n = 9)

and undifferentiated schizophrenia (n = 11). Statistical testing revealed that

diagnostic sub-group did not affect binocular rivalry rate for either stimulus

condition (low Z = -0.228, p =.82 and high Z = 0.209, p = .23). Similarly, whether

participants with schizophrenia reported positive or negative symptoms scores had

no effect on binocular rivalry for either stimulus condition (low-strength Z = -.44, p

=.965 and high-strength Z = -0.973, p = .331). All participants tested were taking

anti-psychotic medication for the treatment of their symptoms (four were taking

Olanzapine, four Risperidone, six Clozapine, one Quetiapine, one Aripiprazole, one

Amisulphride, and three were taking typical antipsychotic medications, one

Fluphenazine, one Haloperidol and one Zuclopenthixol). As previously noted,

chlorpromazine equivalents (CPZE) were calculated for each medication, so that the


effects of medication could be compared across participants, see Woods, (2003) and

Centorrino et al., (2002). Medication dose was compared using a median split;

CPZEs of lower than 425 mg were considered a lower dose, and higher doses were

considered as those greater than 425 mg. Statistical testing revealed no effect of

medication on binocular rivalry rates measured using the low-strength stimulus (Z =

0.63, p = .103), however for the high-strength stimulus condition a medication effect

was found (Z = -2.271, p = .023). Participants taking lower doses (lower than the

median) of anti-psychotic medications recorded faster binocular rivalry rates (mean

0.311 Hz compared 0.278 Hz).

3.5.3 Normalised mean dominance durations.

For all three rivalry tasks (both binocular rivalry tasks and the Necker Cube

task), the normalised mean dominance durations recorded by both groups failed to

form gamma distributions (Kolmogorov-Smirnov p >.05). Whether participants with

schizophrenia and healthy controls produced different distributions of dominance

durations were examined (see Section 3.5). No differences in the normalised

dominance distribution were produced by participants with schizophrenia compared

to healthy controls. Table 3.2 shows the Smirnov test statistic for participants with

schizophrenia and healthy control participants (m and n, respectively) compared with

the critical values determined by w0.95 ≈1.36√ m+n/ mn (CV-T for S) compared to

the Smirnov T (the greatest distance in values along the distribution) across the three

test conditions.


Table 3.2: Smirnov test statistic for participants with schizophrenia (n=20) and controls (n=20).

Test stimulus Schizophrenia (n)

Healthy (m)

CV_T for S at 95%

Smirnov T

Reject H0?

Low Strength 4992 10488 0.06614 0.062034 No

High Strength 5024 9920 0.06661 0.056328 No

Necker Cube 6672 6904 0.06603 0.019091 No

Viewing the plotted cumulative normalised dominance durations in Figure 3.2,

that compare the two distributions, there were no discernible differences. On

examination of the cumulative probability functions, there were no significant

differences in the vertical distances between the two plots at any point in Figure 3.2,

indicating that the mean dominance durations recorded by participants with

schizophrenia were not significantly different to that of the healthy controls. These

results indicated that it was only rate of binocular rivalry alternations that differed

between participants with schizophrenia and healthy controls, and not the duration or

proportion of time spent viewing (or suppressing) each image before being

interrupted by the alternative image.

3.6 Discussion

Binocular rivalry rates in participants with schizophrenia were slower than

healthy controls in both the low-strength and high-strength binocular rivalry tasks.

However, no differences in the perceptual alternation rates of the Necker Cube

(monocular rivalry) task were found between the two groups. Perceptual alternation

rates for the Necker Cube task in schizophrenia were similar to the alternation rates

recorded in the two binocular rivalry tasks, however Necker Cube alternation rates

were slower in healthy controls compared to binocular rivalry rates. There were no


group differences in the distribution of normalised dominance durations in the two

binocular rivalry tasks and the monocular rivalry task. See Figure 3.2.

Low Strength Condition

0.0

0.2

0.4

0.6

0.8

1.0

0 1 2 3 4 5 6 7 8 9 10 11 12

Dominance Durations in Seconds

Cu

mu

lati

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bab

ility

Control Schizophrenia

High Strength Condition

0.0

0.2

0.4

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0 1 2 3 4 5 6 7 8 9 10 11 12


Cu

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Necker Cube

0.0

0.2

0.4

0.6

0.8

1.0

0 1 2 3 4 5 6 7 8 9 10 11 12


Cu

mu

lati

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bab

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Figure 3.2: Normalised mean dominance durations (the time intervals between button pushes (in seconds)/mean) plotted as cumulative distributions.

It is possible that the difference in rates between the two samples was due to

medication. In the current study all participants were taking a single dose of anti-

psychotic medication (dose range 200-900mg in CPZE). Anti-psychotic dose was

not stated in Miller et al., (2003), so no dose comparisons could be made. In the


Miller et al., (2003) study the four participants were taking two different types of

medication. Three subjects were taking both a typical and an atypical anti-psychotic,

and one was taking lithium. Lithium is typically prescribed for mood disturbances.

It is not clear from Miller et al., (2003) whether co-morbidity was an exclusion

criterion as it was in the current study. Another possible reason for the difference in

results is that only 12 of the 18 participants with schizophrenia in the Miller et al.,

(2003) study had normal vision. All participants in the current study had normal

vision (or normal corrected vision).

It is unlikely that these findings are due to group differences between the

studies. Participants with schizophrenia in the current study were similar in age to

those in Miller et al., (2003); mean age 37.9 years (range 23 -64 years) and 37.7

years (range 21-69 years) respectively. Although in Miller et al., (2003) the group

with schizophrenia comprised nine males and nine females compared to 15 males

and five females, in the current study, this difference was not significant (χ2 = 2.544,

p = .11). Age and gender had no effect on binocular rivalry rate for either stimulus

condition or acted as measurement confounders for either group in the current study.

3.6.1 Binocular rivalry rates in schizophrenia.

Binocular rivalry rates in participants with schizophrenia were consistently

slower than those in healthy participants for both low- and high-strength stimulus

conditions. The data presented here are consistent with the work of Fox (1965) and

Sappenfield and Ripke (1961) who found binocular rivalry rate to be slower in

participants with schizophrenia compared to healthy controls. Furthermore, they

contrast with the findings of Miller et al., (2003) where no differences were found.

Miller and colleagues dismissed the work of Sappenfield and Ripke (1961) and Fox

(1965) on the basis that these studies were limited by the short observation period

100Chapter 3: Slower Binocular Rivalry Rates in Individuals with Schizophrenia Compared to Healthy Controls

where binocular rivalry data were collected for less than two minutes for each

participant. The data presented here replicate slow binocular rivalry rate in a group

of 20 participants with schizophrenia over eight minutes of binocular rivalry data

collection. In addition, this was across two different binocular rivalry stimulus

conditions.

3.6.2 Monocular rivalry rates in schizophrenia.

No differences were found when rivalry rates and dominance durations of the

two perspectives of the Necker Cube were compared between the two groups. These

results suggest that perceptual rivalry may be a product of different mechanisms than

binocular rivalry. Meng and Tong (2004), Tong (2001) and Van Ee et al., (2006)

propose a higher cortical based mechanism of binocular rivalry. However, in terms

of rate, healthy control participants recorded slower Necker Cube rates than

binocular rivalry rates. This effect in healthy participants has been found previously

by Breese who reported that monocular rivalry alternations tended to occur at a

slower rate than binocular rivalry alternations and tended to be less vivid (Breese,

1899). Slower Necker Cube alternations or monocular rates were not observed in

participants with schizophrenia. It could be that the slow binocular rivalry rate

observed in the group with schizophrenia limits the ability to detect further slowing

in the monocular task. A more likely explanation is that the features of

schizophrenia that effects higher cortical processing (for example attention, visual

and verbal learning and memory, working memory and executive functioning), also

effect processing in the visual cortex. Recent models suggest that monocular rivalry

(or alternation between alternative images in ambiguous figures) involves

competition for visual awareness between the monocular neurons higher in the visual

cortex (V2 and beyond), whereas binocular rivalry involves both bottom-up and top-

Chapter 3: Slower Binocular Rivalry Rates in Individuals with Schizophrenia Compared to Healthy Controls101

down processing (Struber, 1999) that includes processing as early as V1 (Tong &

Engel, 2001). That is, inter-ocular competition between binocular neurons earlier in

visual processing are influenced by local stimulus characteristics (contrast, temporal

frequency) that drive binocular and monocular neurons higher in cortical visual

processing (V1 and beyond) are responsible for bringing the opposing images into

consciousness (Kornmeier & Bach, 2005; O’Shea et al., 2009; Tong, 2001).

Therefore, abnormal monocular neurons in the higher visual cortex may affect the

rate in which opposing images are brought into conscious in both binocular and

monocular rivalry in schizophrenia).

3.6.3 Distributions, gamma plots.

The distributions of dominance durations between the two groups were directly

compared using the Smirnov test. No statistical differences were found in the

distributions of dominance duration between participants with schizophrenia or

healthy controls for either the binocular rivalry task or the perceptual rivalry task.

Thus the characteristics of binocular rivalry in terms of dominance durations were

similar, with the two groups only showing differences in binocular rivalry rates.

These data are at odds with the findings of Miller et al., (2003). These authors

reported normalised dominance durations produced by healthy participants, those

with BPD and those with depression fitted a gamma distribution (with R2 values of

greater than 0.96), while those produced by participants with schizophrenia fitted less

well (R2 = 0.92). These differences between the two studies in reported dominance

durations in schizophrenia may be due to the statistical methods employed. Miller et

al., (2003) fitted dominance durations of the respective groups to Gamma

distributions using the Kolmogorov-Smirnov test. This was not attempted here as it

was reported in Chapter 2 that dominance durations reported by the sample of control


participants in this study did not generally fit Gamma distributions (see Section

2.7.1). Here the ‘Two Sample Smirnov Test’ was used to compare distributions of

dominance durations reported by controls and participants with schizophrenia.

Although there was no difference in the cumulative dominance distributions,

allowing one to assume that both groups recorded binocular rivalry dominance

distributions that were ‘normal’ and ‘expected’, it is impossible to distinguish

whether either group’s distributions fitted a Gamma distribution. Although unlikely,

based on the study reported in Chapter 2, it possible that both controls and

participants with schizophrenia recorded binocular rivalry dominance durations that

fitted a Gamma distribution, or they both deviated from the Gamma distribution to

the same degree.

3.6.4 Effect of stimulus strength.

It was expected that a significant increase in binocular rivalry rate would be

seen in both groups as stimulus strength increased, as it has been repeatedly reported

that increasing the strength of the binocular rivalry stimulus increases binocular

rivalry rate in healthy controls (Breese, 1899; Fahle, 1982; Levelt, 1968; O’Shea,

1997; O’Shea & Williams, 1996; Rogers et al., 1977). The stimulus strength for

high- and low-stimulus used here were the same as those reported by Miller et al.,

(2003) and Pettigrew and Miller, (1998). However, binocular rivalry rates were

unchanged by alterations to stimulus strength in both participant groups. This

contrasts with the results for healthy control participants in Miller et al., (2003), who

reported binocular rivalry rates of 0.42 Hz (n = 30) in a lower-strength stimulus, and

in Pettigrew and Miller (1998), who reported rates of 0.60 Hz (n = 63) with the

higher strength stimulus. Binocular rivalry rates here are approximately 0.54 Hz for

both stimulus strengths.


While moving rivalrous stimuli presented at equal strength to each eye, lead to

a greater suppression, and therefore faster binocular rivalry rates, than static patterns

(Norman, Norman & Bilotta, 2000; Cobo-Lewis, Gilfory & Smallwood, 2000), it is

unlikely that a change in spatial frequency from 4 cpd to 8 cpd or a 10% difference in

luminance contrast (0.9 compared to 1.0) would contribute to an increase in

binocular rivalry rate. Thus, it is not surprising that there was no difference in

binocular rivalry rate observed with stimulus strength. This is most likely due to the

inclusion of movement and a modest increase in luminance contrast in the higher-

strength task. Previous data (Liu et al., 1992) suggest that stimulus luminance

contrast would need to be reduced to below 0.5 for a change in binocular rivalry rate

of the magnitude observed by Miller et al., (2003) and Pettigrew and Miller (1998),

when measured in the same participants.

3.6.5 Diagnostic value of binocular rivalry rate.

Prior research has proposed that binocular rivalry rate is able distinguish those

with schizophrenia from non-psychotic illness. The current data, taken together with

previous findings, suggest binocular rivalry rate may distinguish those with major

psychiatric illness from healthy individuals. The classic ‘Kraepelin differentiation of

schizophrenia and bipolar disorder’ is questionable (see Greene (2007) for a review).

It is possible that differences in binocular rivalry rate reflect general cognitive

deficits or abnormal neurotransmitter function within the central nervous system. As

previously noted, neurotransmitter involvement in binocular rivalry has been

demonstrated using the traditional hallucinogenic beverage ‘Ayahuasca’ (Carter et

al., 2005; Frecska, White & Luna, 2003; Frecska, White et al., 2003). The active

ingredient is Psilocybin, a (serotonin) 5HT1A and 5HT2A agonist, decreases

binocular rivalry rate in a dose-dependent manner (Carter et al., 2005; Carter et al.,


2007; Nagamine et al., 2007). Similar results have been reported using

Tandospurone, a 5HT1A agonist (Nagamine et al., 2008).

3.6.6 Physiological mechanisms for the slowing of binocular rivalry rate.

While the exploration of serotonin agonists’ effects on binocular rivalry rate is

logical based on Pettigrew and Miller’s suggestion that slow binocular rivalry rate is

a trait maker for BPD, this is not direct evidence to support this suggestion.

Although serotonin is related to the pathogenesis of BPD other neurotransmitters also

play a role, for example the glutamatergic and cholinergic systems (muscarinic and

nicotinic systems) and melatonin (Zarate, 2008). Pettigrew and colleagues suggest

the slow binocular rivalry rate is due to the effect of serotonin on oscillatory

mechanisms within the brainstem, where there is a high concentration of serotonin

receptors. However, serotonin receptors are widely throughout the human brain

including the mesolimbic regions. In these regions agonism of serotonin (particularly

5HT2A) receptors is likely to stimulate dopamine release. Psilocybin ingestion has

been shown, using positron emission tomography (PET) to enhance striatal dopamine

release in healthy volunteers (Vollenweider et al., 1999). Modifications in qEEG

with ingestion of Tandospurone are reported to be in line with other pro-

serotoninergic and pro-dopaminergic drugs (Riba, Rodriguez-Fornells & Barbanjo,

2002). These effects on binocular rivalry rate can as easily be accounted for in the

serotonin-mediated release of dopamine in the striatum. Furthermore, stimulation of

5HT2A receptors has also been implicated in dopamine release through the action of

GABA pathways (Vollenweider et al., 1999). Dopamine has also been implicated in

BPD (Pearson et al., 1995; Yatham et al., 2005) and post-traumatic stress disorder

(PTSD), depression and anxiety (Barnes et al., 2006; Freeman, Freeman & McElroy,

2002; Seeman et al., 2002). Neurotransmitters have complex interactions within the


central nervous system; it is likely that most mental illnesses will involve common

neurotransmitter activity, which is reflected in the overlapping of symptoms and

treatment modalities.

3.6.7 Effect of schizophrenia medication dose.

Slow binocular rivalry rates were found in participants with schizophrenia, a

disorder hypothesised to be caused by abnormally high levels of dopamine in the

central nervous system, with major treatments consisting of agents that block

dopamine (Abi-Dragham, 2004; Fudge & Emiliano, 2003; Kapur & Mamo, 2003).

In the current study significant differences were seen in binocular rivalry rate by dose

of anti-psychotic agents, with slower binocular rivalry rates seen at higher doses.

Furthermore, severity of symptoms of schizophrenia (measured by PANSS scores)

was associated with increased anti-psychotic dose (in CPZE) (Z = -3.93, p < .001),

suggesting that participants with schizophrenia experiencing more symptoms of their

illness recorded slower binocular rivalry. These factors suggest a role of dopamine

activity in binocular rivalry. Dopamine involvement in binocular rivalry seems

likely as factors known to be related to dopamine such as age (Tarita-Nistor et al.,

2006), visual acuity and luminance contrast have also been demonstrated to alter

binocular rivalry rate in groups of individuals (Fahle, 1982; Hollins, 1980; Mueller,

1990; O’Shea, Blake, & Wolfe, 1994). It is acknowledged that our results do not

argue against a role of serotonin per se, as the majority of participants with

schizophrenia in our sample were taking medications that interact with both

dopamine and serotonin receptors. Anti-psychotic medications vary in their

serotoninergic and dopaminergic affinities, with some typical anti-psychotic drugs

having little or no influence on serotonin (for example, Haloperidol) while other have

specific Serotonin (5-HT2A) affinity (for example, Olanzapine) (Seeman, 2002).


While most antipsychotic agents block dopamine (for example, Risperidone), others

are dopamine agonists (for example, Aripiprazole) (Seeman, 2002). Slower

binocular rivalry rate may be associated with reduced dopamine release in the visual

pathways, either by known dopaminergic processes within the primary visual

pathways or by the stimulatory effect of serotonin receptors on striatal dopamine

release.

3.7 Conclusion

The main finding of this study was that binocular rivalry rates were

significantly slower in participants with schizophrenia than in healthy controls. This

was evident for both low-strength and high-strength binocular rivalry stimuli.

However, no difference in binocular rivalry rate was found in the rate of perceptual

alternations in a monocular task (Necker Cube). These data suggest that slow

binocular rivalry rate is not specific to BPD as previously reported, but may be a

feature of major psychiatric disorders more broadly. High-dose anti-psychotic

medication affected binocular rivalry rate, suggesting that slow binocular rivalry rate

may indicate increased dopamine release within the striatum or visual pathways.

This effect may be moderated by dopamine release.

Although not sensitive enough to separate diagnostic groups within those

with schizophrenia, the binocular rivalry task may be an appropriate measure to

include in a battery of tasks to investigate neurotransmitter involvement in psychosis

including schizophrenia and other mental illnesses. It is also possible that there are

more fundamental differences in binocular rivalry in schizophrenia that can be

attributed to abnormal visual processing within specific visual pathways.

Differences within the ‘transient visual pathway’ (closely associated to the

magnocellular system) and the ‘sustained visual pathway’ (associated with the


parvocellular visual system) (Bretmeyer & Ganz, 1976) require further exploration in

this regard.

Chapter 4: Binocular Rivalry and Backward-Masking Tasks Reveal Pathway-Specific Abnormalities in Schizophrenia 108

4.1 Magnocellular and Parvocellular Pathways in Schizophrenia

The most prominent theory related to visual abnormalities in schizophrenia is

the ‘Transient Channel Hypothesis’ (Breitmeyer & Ganz, 1976; Butler et al., 2003;

Green, Neuchterlein, Breitmeyer, Tsuang & Mintz, 2003; Keri, Antal, Szekeres,

Bebedek & Janka, 2000; Schechter et al., 2005). The Transient Channel Hypothesis

proposes that the neuronal pathway that integrates dynamic visual information (i.e.

the magnocellular pathway), such as the position and spatial relationships of visual

stimuli and the attention-capturing mechanism, is impaired in schizophrenia. Over

activity may interrupt the neural processing of the sustained (or parvocellular) visual

pathway (Butler et al., 2003). There is general agreement that the anomalous

perceptual abnormalities observed in schizophrenia (seen in both medicated and

medication-näive first-episode schizophrenia) are associated with the heightened

sensitivity of the magnocellular pathway (Kiss, Fabian, Benedek & Keria, 2010). It

is possible that early visual processing deficits occur in both magnocellular and

parvocellular systems; however it is considered that those with predominantly

magnocellular input contribute to down-stream processing (Brittain, Surguladze,

McKendrick & Ffytche, 2010).

Transient visual-pathway (or magnocellular-pathway) abnormalities in

schizophrenia have been reported to account for altered backward-masking task

performance (Breitmeyer & Ganz, 1976; Butler et al., 2003; Candenhead et al., 1998;

Green et al., 1999; Green et al., 1994a, 1994b; Green et al., 2003; Keri et al., 2000;

Schechter, Butler, Silipo, Zemon & Javitt, 2003; Slaghuis, 1998, 2004), impaired

motion-defined letter task performance (Schwartz et al., 1999a), inaccurate smooth

Chapter 4: Binocular Rivalry and Backward-Masking Tasks Reveal Pathway-Specific

Abnormalities in Schizophrenia


pursuit tracking (Schwartz et al., 1999b) and reduced amplitudes and increased

latency of components of the transient visual-evoked potential (tVEP) (Schechter, et

al., 2005).

Exploring binocular rivalry using stimuli that bias task processing to either

the magnocellular or parvocellular pathways in this group of individuals provides a

unique opportunity to explore the ‘visual pathway’ theories of binocular rivalry,

while investigating further visual awareness functions in schizophrenia. While it is

not possible to completely separate the magnocellular and parvocellular pathways

during psychophysical testing, due to considerable inter-play between them

(Livingstone & Hubel, 1987; Shapley, 1992), it is possible to use binocular rivalry

stimuli biased to preferentially stimulate either pathway. Changing the

characteristics of stimuli used to bias the task to a particular anatomical visual

pathway is an approach taken by other researchers using other neurophysiologic

measures. For example, magnocellular and parvocellular selective stimuli have been

used to elicit differential components in measuring tVEP (Crewther, Crewther,

Klistorner & Kiely, 1999; Foxe, Strugstad, Sehatpour, Molholm, Pasieka, Schroede,

& McCourt, 2008; Klistorner, Crewther, & Crewther 1996; Klistorner, Crewther &

Crewther, 1997; Lalor, Yeap, Reilly, Pearlmutter & Foxe, 2008; Schechter et al.,

2005) in backward-masking tasks (Breitmeyer & Ganz, 1976; Butler et al., 2003;

Cadenhead et al., 1998; Green et al., 1994a, 1994b; Green et al., 1999; Keri et al.,

2000; Schechter et al., 2003), in motion-defined letter tasks (Schwartz et al., 1999a)

and in smooth pursuit tracking tasks (Schwartz et al., 1999b). Using tasks for

selective biasing of the parvocellular and magnocellular systems is an approach that

has been endorsed by the Cognitive Neuroscience Treatment Research to Improve

Cognition in Schizophrenia (CNTRICS) (Green et al., 2009).

110 Chapter 4: Binocular Rivalry and Backward-Masking Tasks Reveal Pathway-Specific Abnormalities in Schizophrenia

4.1.1 Physiological differences in the magnocellular and parvocellular

pathways.

Parvocellular neurons show a sustained response when presented with long-

duration stimuli. Magnocellular neurons respond to the same stimuli in a transient

fashion, with only a brief burst of activity at stimulus onset and offset (Schwartz,

1999). These time-course differences suggest that parvocellular and magnocellular

neurons play different roles in processing temporal information. The magnocellular

neurons that constitute the transient (magnocellular) pathway have large axons that

transfer information quickly to cortical areas (with conduction velocities of

approximately 4 m/s (Kolb, Ferandez & Neslon, 2009), therefore are more suited to

carry information regarding the onset and offset of stimuli. They respond rapidly to

changes in illumination, and can resolve high-temporal-frequency stimuli and

moving or flickering stimuli. Magnocellular-biased binocular rivalry stimuli should

therefore be moving or flickering. However, the smaller parvocellular neurons of the

sustained parvocellular pathway transfer temporal information more slowly (at

conduction velocities of approximately 2 m/s (Kolb et al., 2009), so are best suited to

code low temporal frequencies and stationary, or near-stationary, stimuli

(Livingstone & Hubel, 1988). Thus, stationary binocular rivalry stimuli are most

appropriate to stimulate parvocellular processing.

In terms of the colour of the binocular rivalry stimuli, parvocellular neurons

display colour opponency while magnocellular neurons do not (Shapley, 1992). That

is, stimuli of a particular wavelength may either stimulate or inhibit parvocellular

neurons, thus these cells are thought to play a large role in colour perception

(Schwartz 1999; Shapley, 1990). In contrast, the majority of magnocellular neurons

show little or no colour opponency. The magnocellular neurons’ responses to a


stimulus are the same regardless of the wavelength; these cells are monochromatic

and do not contribute to wavelength-based discriminations (Schwartz, 1999).

However, a small portion of magnocellular cells have an inhibitory mechanism

selective to long wavelength red light (Shapley, 1990; Wiesel & Hubel, 1990; Wiesel

& Hubel, 1966). Therefore, red light inhibits some magnocellular processing

(Shapley, 1990). Using red stimuli for the parvocellular binocular rivalry (BR) task

and colourless (black and white) stimuli for the magnocellular BR task exploits this

property and allows greater relative separation of the pathways.

Magnocellular and parvocellular cells are 'tuned' (i.e. respond best) to objects

of particular sizes or with particular spatial frequency distributions. Parvocellular

cells are small (often referred to as midget cells) with small receptive fields (a term

that describes the spatial properties of retinal ganglion cells) (Kolb et al., 2009). The

smaller diameter of the parvocellular neurons manifest higher spatial frequency

resolution, allowing these cells to discriminate the fine detail of a stimulus, including

coding for colour and spatial detail. Magnocellular cells (parasol cells) are large

cells with broader dendritic fields and larger receptive fields, and are less responsive

to spatial detail. These large cells operate when there is low luminance contrast; that

is when there is only a small difference in the brightness of the image compared to

its background (Skottun & Skoyles, 2007). Therefore, using stimuli of high spatial

frequency for the parvocellular binocular rivalry task and low spatial frequency

stimuli for the magnocellular binocular rivalry tasks are appropriate.

Parvocellular cells are generally receptive to colour, but not to fast movement,

and are concerned with the spatial detail of objects. Contrastingly, magnocellular

cells are ‘colour blind’, sensitive to movement at low luminance contrast but do not

possess fine spatial discrimination (Shapley, 1992). The transient (or magnocellular)


visual pathway is considered to be concerned with the ‘Where is it?’ component of

vision, while the sustained (or parvocellular) visual pathway is concerned with the

‘What is it?’ component (Livingstone & Hubel, 1988; Schwartz, 1999). The

experiments described in this chapter use binocular rivalry stimuli with different

characteristics to produce a relative processing bias toward either the magnocellular

or parvocellular system, as described in Section 4.2.1.1.

4.1.2 Magnocellular and parvocellular pathways in binocular rivalry.

There is debate about the nature of the binocular rivalry process, particularly in

terms of localisation. There are two widely-held arguments: ‘pattern rivalry’ and

‘eye rivalry’ (reviewed in Blake, 2001 and Tong, 2001). Proponents of ‘pattern

rivalry’ theories suggest that binocular rivalry occurs with competition between the

monocular neurons in the extra striate visual cortex V1 (Blake, 1989) or in the lateral

geniculate nucleus (LGN) (Lehky, 1988). Supporters of an ‘eye rivalry’ theory

assert binocular rivalry arises from competition between the cortical representations

of each image in higher visual cortical areas (Leopold & Logothetis, 1996;

Logothetis & Schall, 1989; Sheinberg & Logothetis, 1997). The ‘eye rivalry’ theory

proposes that binocular rivalry occurs within both lower- and higher-visual

processing areas, and that binocular rivalry is a consequence of the actions of either

the magnocellular (Livingstone & Hubel, 1987) or parvocellular visual pathways

(Carlson & He, 2000; He et al., 2005). This view suggests that binocular rivalry

results from neuronal processes that occur at all stages of visual processing. This

includes magnocellular and parvocellular cells in the monocular neurons of the

LGN, superior colliculi (Livingstone & Hubel, 1988) and V1, as well as higher

processing areas in the cortex, such as the ventral and dorsal streams carrying

information to parietal and temporal cortical areas (Wandell, 1995).


The findings of the few studies that have investigated magnocellular and

parvocellular pathway contributions to binocular rivalry have not been consistent

(Blake, 2001). For example, Hollins and Hudnell (1980) speculated that rivalry was

dependent on the transient or magnocellular pathway, as the spatial frequencies of

patterns that resulted in the strongest rivalry percept were within the range usual for

magnocellular processing. This notion was supported by Livingstone and Hubel

(1987) who found that stimuli with characteristics thought to be processed via the

parvocellular pathway yielded fusion rather than rivalry. To further support the case

for magnocellular involvement, rivalry occurs for competing stimuli presented at

alternation rates that favour the magnocellular pathway (Blake & Boothroyd, 1985).

Furthermore, rivalry can occur between competing motion after-effects (Blake, et al.,

1998) which are generally thought to arise from magnocellular processing (Tootell et

al., 1995). However, some studies using stimuli that strongly activate the

magnocellular pathway have failed to generate rivalry (Liu et al., 1992; O’Shea &

Blake, 1986) or have (at best) yielded weak rivalry (Carlson & He, 2000).

Furthermore, the work of Kulikowski, (1992) and O’Shea (1996) demonstrated that

stimuli that are processed primarily by the parvocellular pathway could yield clear,

crisp rivalry, and stimuli with luminance contrasts above the saturation of

magnocellular cells also produced crisp binocular rivalry (Alexander, 1951; Levelt,

1965, 1967). Flickering stimuli (Wade, 1975; Wolfe, 1983a; Wolfe, 1983b), and

those that differ in the temporal characteristics of two stimuli, tend to fuse (O’Shea

& Blake, 1986) whereas colour conflict stimulates crisp binocular rivalry

(Kulikowski, 1992; Wade, 1975). This also suggests that parvocellular pathways

are involved in binocular rivalry (He et al., 2005). The observation that motion

information can be integrated at the same time as form rivalry (Andrews &


Blakemore, 1999; Carlson & He, 2000) and colour rivalry (Carney et al., 1987) has

led to the hypothesis that both pathways are necessary for binocular rivalry (He et

al., 2005).

This chapter is divided into two sections. The first measures binocular rivalry

rates and dominance durations in participants with schizophrenia and healthy

controls, using visual stimuli biased towards the magnocellular and parvocellular

visual pathways. The second compares this binocular rivalry task with a visual

backward-masking task, a task that has been used extensively to investigate

magnocellular pathway abnormalities in participants with schizophrenia (Butler et

al., 2003; Cadenhead et al., 1998; Green et al., 1994b; Green, Nuechterlein,

Breitmeyer & Mintz, 2005; Green, Nuechterlein, Breitmeyer & Mintz, 2006). A

model of binocular rivalry is proposed based on the sustained-transient theory of

visual backward masking.

4.2 Study 3, Experiment 1: Assessing Binocular Rivalry in Schizophrenia Using

Stimuli that Bias the Magnocellular and Parvocellular Visual Pathways

The aim of the first study was to measure binocular rivalry rates in participants

with schizophrenia and healthy controls, using visual stimuli biased towards the

magnocellular and parvocellular visual pathways. It was predicted that binocular

rivalry rates in participants with schizophrenia would be slower than that of healthy

controls, with the greatest abnormality observed using stimuli biased towards the

magnocellular pathway, given that deficits in the magnocellular pathway are reported

in schizophrenia (Breitmeyer & Ganz, 1976; Butler et al., 2003; Cadenhead et al.,

1998; Keri et al., 2000; Green et al., 1999; Green et al., 1994a, Green et al., 1994b;

Green et al., 2003; Schechter et al., 2003; Schechter et al., 2005; Schwartz et al.,

1988; Schwartz et al., 1999b, Slaghuis, 1998; Slaghuis, 2004).


4.2.1 Method.


Twenty individuals with schizophrenia, who participated in the study described

in Chapter 3, were recruited to the study; however three were excluded due to

insufficient contrast sensitivity to reliably perform the magnocellular BR task,

leaving 17 remaining participants. Six participants met the schizophrenia sub-type

classification of paranoid schizophrenia, with the remaining 11 categorised as

undifferentiated schizophrenia sub-type (Structured Clinical Interview for the DSM-

IV). Six participants had positive symptoms of schizophrenia, nine had negative

symptoms and two had equal positive and negative symptoms as assessed by the

PANSS (Kay et al., 1988). Fourteen participants were taking atypical anti-psychotic

medication (four taking Olanzapine, three taking Risperidone, five taking Clozapine,

one taking Quetiapine and one taking Amisulphride) and three were taking typical

anti-psychotic medication. The CPZEs of their dosages ranged from 200-800

mg/day, with the average being 479.4 mg/day. All participants had normal vision and

6/6 visual acuity (corrected or uncorrected) in each eye, as assessed by Snellen visual

acuity testing.

4.2.1.2 Control participants.

Twenty-five control participants were recruited to the study. Of the 25 control

participants, 17 had participated in the study described in Chapter 2, and eight new

participants were recruited. One male participant was excluded as he had

insufficient contrast sensitivity to reliably perform the magnocellular BR task

leaving 24 participants. All participants had normal vision and 6/6 visual acuity

(corrected or uncorrected) in each eye measured by Snellen visual acuity testing.

Participant characteristics are detailed in Table 4.1.


Table 4.1: Age, gender, eye dominance and NART score of participants with schizophrenia and controls

Controls (n=24)

Schizophrenia(n=17)

χ2 df p

Age Mean (yrs) 38.4 36.5 Range 21-64 23-54 24.382 23 0.383 Gender Male 4 13 Female 20 4 14.664 1 <0.001 Eye Dominance R)eye 15 11 L)eye 9 6 0.021 1 0.575 NART Score Mean 116.4 113.7 Range 102-122 101-124 19.514 16 0.243

4.2.1.3 Binocular rivalry stimuli to bias the magnocellular and parvocellular

pathways.

The binocular rivalry stimuli were presented in the same manner as described

in Chapter 2 (Section 2.2.2.1). The stimuli to bias task processing to the

magnocellular pathway (herein referred as magnocellular BR stimulus) consisted of

achromatic horizontal and vertical lines of low spatial frequency (1 cpd), at low

luminance contrast (8%) moving at approximately 4 Hz presented in a circular

aperture measuring 1.5 degrees of visual angle. The stimuli biasing the task to the

parvocellular pathway (herein referred to as parvocellular BR stimulus) consisted of

stationary red vertical and horizontal lines of high spatial frequency (10 cpd) and at

high luminance contrast (90%). Red vertical and horizontal lines were chosen for

the parvocellular BR tasks as it been demonstrated that red light or red backgrounds

can suppress magnocellular neural function (Bedwell, Brown & Miller, 2003;

Breitmeyer & Williams, 1990; Breitmeyer & Breier, 1994; Edwards, Hogben, Clark

& Pratt, 1996; Pammer & Lovegrove, 2001; Skottun, 2004).


While every effort has been made to produce binocular rivalry stimuli that

bias the magnocellular and parvocellular pathway, complete separation cannot be

assured. It is difficult to produce a stimulus that biases only the parvocellular visual

system as the two pathways overlap in their spatial frequency selectivity (Ellemberg,

Hammarrenger, Lepore, Roy & Guilemot, 2001). Although the sensitivity of

magnocellular neurons is lower than parvocellular neurons at higher spatial

frequency, allowing free eye movements which generate transients suggests that the

magnocellular neurons may potentially respond to the stimuli presented in the

parvocellular BR task.

4.2.1.4 Recording binocular rivalry.

Each participant completed three two-minute blocks of binocular rivalry using

the magnocellular- and parvocellular-biased binocular rivalry stimuli described

above. The methods for recording the binocular rivalry data were the same as

described previously in Chapter 2 (see Section 2.4, procedure).

4.2.2 Statistical analyses.


participants required to demonstrate a difference in binocular rivalry rates between

the two groups. The findings from the studies presented in Chapters 2 and 3 were

entered into the G*power3 program (Faul et al., 2007). It was estimated that a

sample size of 14 in each group was required for a two-sided 5% significance level

and power of 80 to demonstrate a difference in binocular rivalry rate in the

magnocellular and parvocellular BR tasks in the two groups.

The effects of group, gender, age, education and NART score on binocular

rivalry rate were determined by Kruksal-Wallis one-way non-parametric analyses of

variance. Planned comparison Mann-Whitney U tests were performed to determine


the differences in binocular rivalry rate between participants with schizophrenia and

controls in both the magnocellular and parvocellular BR tasks. Analyses of three

factors unique to the schizophrenia group (diagnostic sub-group, dose of

antipsychotic medication measured in CPZEs, and positive and negative symptoms

of schizophrenia) were conducted, to more-fully examine influences on binocular

rivalry rate in participants with schizophrenia. These contrasts utilised the Mann-

Whitney U test.

Dominance durations, i.e. the time between button pushes (time intervals spent

viewing horizontal lines and vertical lines) were normalised for each participant (by

dividing each time interval by the grand mean for each participant) and then each

group was compared using the Smirnov test (Conover, 1971). The resulting

distributions were considered significant at the p<0.05 level of significance where α

is if T1 exceeds its 1 – α quantile. The 0.95 quantile of T1 is given by w0.95 ≈1.36√

m+n/ mn (Conover, 1971) (see previous chapter, Section 2.5.1 for details).

4.2.3 Results.

4.2.3.1 Binocular rivalry rate.

There was a significant between-group difference in binocular rivalry rate for

both the magnocellular and parvocellular BR tasks (χ2 [1, 41] = 10.6-6, p = .001 in

the magnocellular BR task and χ2 [1, 41] = 14.761, p < .001 in the parvocellular BR

task). Gender also had an effect on binocular rivalry rate in both tasks, with males

showing slower rates (magnocellular BR task gender χ2 [1, 41] = 4.486, p = .034 and

parvocellular BR task χ2 [1, 40] = 9.775, p= .002). Age and NART score had no

effect on binocular rivalry rate in either task (age; magnocellular BR task χ2 [1, 23] =

21.283, p = .564, parvocellular BR task χ2 [1, 23] = 23.383, p <.283, and NART;


magnocellular BR task χ2 [1, 15] = 17.557, p = .287, parvocellular BR task χ2 [1, 15]

= 17.206, p = .307).

In the magnocellular BR task, binocular rivalry rates were significantly slower

in the group with schizophrenia (n = 17, mean rate 0.22Hz, SD= 0.11) compared to

healthy controls (n = 24, mean rate 0.38Hz, SD=0.17, Z = -3.257, p< .001).

Participants with schizophrenia were on average 0.16 Hz slower than healthy

participants (range group with schizophrenia 0.092-0.438 Hz; healthy 0.192-0.775

Hz) in the magnocellular BR task. Those with schizophrenia also recorded

significantly slower binocular rivalry rates in the parvocellular BR task (n = 17,

mean rate 0.24Hz, SD= 0.09) compared to controls (n = 24 mean rate 0.46Hz, SD=

0.22, Z = -3.842, p< .001). Participants with schizophrenia were 0.22 Hz slower than

control participants on average (range for schizophrenia 0.125-0.392 Hz, healthy

participants 0.217-1.050 Hz) in the parvocellular BR task. These data are presented

in Figure 4.1.

Control participants recorded significantly faster binocular rivalry rates in the

parvocellular, compared to the magnocellular BR task (n = 24), mean rate 0.457 Hz,

SD = 0.22 compared to 0.384 Hz, SD = 0.17 respectively (Z = -2.387, p =. 017).

This effect was not observed in the participants with schizophrenia, (n = 17) mean

rate 0.237 Hz, SD = 0.088 compared to 0.224 Hz, SD = 0.113 respectively (Z = -

0.621, p =. 535).

Planned comparisons revealed that females recorded significantly faster

binocular rivalry rates than males in both tasks. For the magnocellular BR task, the

oscillation rate was 0.64 Hz for females (n =2 4, M = 0.636 Hz, SD = 0.178) and 0.25

Hz for males (n = 17, M = 0.253Hz, SD = 0.137; Z = -2.188, p = .034). For the

parvocellular BR task the rate was 0.45 Hz in females (n = 24, M = 0.445 Hz, SD =


0.23) and 0.25 Hz in males (n = 17, M = 0.254 Hz, SD = 0.07; Z = -3.127, p = .002).

Females recorded significantly faster binocular rivalry rates in the magnocellular BR

tasks than in parvocellular BR tasks (Z = -2.601, p = .009), however no differences

were found in magnocellular verses parvocellular binocular rivalry rates in males (Z

= -0.388, p = .698). Females with schizophrenia (n = 4) recorded slower binocular

rivalry rates in the parvocellular BR task (n = 4, M = 0.191 Hz, SD = 0.06) than

healthy controls (n = 20, M = 0.495 Hz, SD = 0.217) (Z = -2.983, p < .001), but not

in the magnocellular BR task (M = 0.249 Hz, SD = 0.175 compared with M =

0.249Hz, SD = 0.161, Z = -1.822, p = .068). The low participant numbers in some

sub-groups warrant a cautious interpretation of these findings.

Figure 4.1: Binocular rivalry rates recorded in participants with schizophrenia (black triangles) compared to healthy controls (black diamonds).

Diagnostic sub-group, medication dose and negative and positive symptoms of

schizophrenia had no effect on binocular rivalry rates in either the magnocellular or

parvocellular tasks in participants with schizophrenia (Mann-Whitney U tests).

Diagnostic sub-group (paranoid schizophrenia [n = 6] versus undifferentiated

schizophrenia [n = 11] ); magnocellular BR task (Z = -0.453, p = .66) and

0.224 0.237

0.384

0.457

0

0.1

0.2

0.3

0.4

0.5

0.6

Magnocellular BR Task Parvocellular BR Task

BR

Rat

e in

Hz

(but

ton

pus

he

s/se

c)

Schizophrenia (n=17)

Healthy Control (n=24)


parvocellular BR task (Z = -0.605, p = .591), low (<425 mg, n = 8) versus high dose

(>425mg, n = 9) of anti-psychotic medication (quantified higher or lower than

median dose in CPZEs; magnocellular BR task (Z = -1.398, p = .167) and

parvocellular BR task (Z = -0.097, p = .963), and positive symptoms (n = 6) versus

negative symptoms (n = 9); magnocellular BR task (Z = -1.003, p = .328) and

parvocellular BR task (Z = -0.413, p = .689). Two participants had equal positive

and negative scores, and were excluded from the analyses.

4.2.3.2 Dominance intervals.

One-way Smirnov tests revealed significant differences in the distribution of

normalised dominance intervals of participants with schizophrenia compared with

healthy controls in both the magnocellular BR task and the parvocellular BR task

(Table 4.2).

Table 4.2: Smirnov test results indicating differences in the distribution of dominance durations between participants with schizophrenia (n=17) and controls (n=24) for both magnocellular and parvocellular binocular rivalry (BR) tasks.

. Schizophrenia

m Control n

Critical Value -Smirnov Test 1.36√ m+n/ mn

Smirnov T (T1)

Reject Ho? Reject if T1>CV-ST

Magnocellular BR Task

1551 3978 0.070515 0.115485

Yes

Parvocellular BR task

1494 3342 0.07331 0.096773

Yes

As can be seen in Table 4.2, there were significant differences in the

distribution of dominance intervals produced in both the magnocellular and

parvocellular BR tasks at the p < 0.05 level. The greatest differences in the

distribution functions for both magnocellular and parvocellular BR tasks occurred at


the 0.5 second time interval, as seen in Figure 4.2. This reflects significantly more

dominance intervals of 0.5 seconds in duration being recorded in participants with

schizophrenia. It is notable that although participants with schizophrenia recorded

more dominance durations of less than one second in the magnocellular BR task,

they recorded fewer dominance durations from 1.5 to 4 seconds compared to those

recorded in controls, resulting in a slightly flatter distribution (Figure 4.2a). A

significant separation between any two points on each curve indicates a significant

difference in mean normalised dominance durations. There are significant

differences in the number of dominance durations recorded of 0.5 seconds for both

the magnocellular and parvocellular BR tasks.

4.2.4 Discussion related to magnocellular and parvocellular tasks.

4.2.4.1 Binocular rivalry rates.

Binocular rivalry rates recorded by participants with schizophrenia were

significantly slower for both the magnocellular and parvocellular BR tasks (p <

.001). Slower binocular rivalry rates (or increased mean dominance intervals) in

participants with schizophrenia have been reported elsewhere (Fox, 1965; Frecska,

White et al., 2003; Sappenfield & Ripke, 1961; White et al., 2001; Wright et al.,

2003), suggesting a general finding of slower binocular rivalry rates in

schizophrenia. These data suggest an overall visual abnormality in binocular rivalry

consistent with the findings of backward masking, motion-defined letter tasks,

smooth pursuit eye movement tracking tasks and VEPs (Breitmeyer & Ganz, 1976;

Butler et al., 2003; Cadenhead et al., 1998; Green et al., 1999; Green et al., 2003;

Green et al., 1994a, 1994b; Keri et al., 2000; Schechter et al., 2003; Schechter et al.,

2005; Schwartz, 1999a 1999b; Slaghuis, 1998; Slaghuis, 2004). In this study the

greatest difference in binocular rivalry rates between participants with schizophrenia


and healthy controls was recorded in the parvocellular BR task, rather than the

magnocellular BR task (difference in binocular rivalry rate of 0.22 Hz compared to

0.16 Hz).

Some authors have suggested that the parvocellular visual pathway is

responsible for binocular rivalry (Carlson & He, 2000; He et al., 2005; O’Shea &

Williams, 1996), however one earlier study suggested the opposite (Livingstone &

Hubel, 1987). Therefore, it would be expected that stimuli that bias the binocular

rivalry task to the parvocellular pathway would yield crisp alternations of opposing

images, with few composite images, and thus a faster alternation rate. Conversely,

stimuli that bias the binocular rivalry task to the magnocellular pathway would be

expected to elicit more mixed images where the vertical and horizontal lines attempt

to fuse into a stable percept, leading to longer inter-stimulus intervals and a slower

binocular rivalry rate. It can be seen from Figure 4.1 that control participants

recorded significantly faster binocular rivalry rates in the parvocellular BR task

compared to the magnocellular BR task (magnocellular and parvocellular BR tasks

respectively; M = 0.38 Hz, SD = 0.17 and M = 0.46 Hz, SD = 0.22, Wilcoxon signed

ranks test Z = -2.387, p = .017), which is consistent with the binocular rivalry

literature.

4.2.4.2 Dominance duration intervals.

There was a significant difference (p< .05) in the distribution of dominance

durations recorded by participants with schizophrenia compared to healthy controls

in both binocular rivalry conditions (Conover, 1971). Participants with

schizophrenia recorded significantly more short dominance durations of less than

one second (see Figures 4.2a and 4.2b), resulting in an overall statistical difference in

the distribution of dominance durations between the two groups, and less dominance


durations between 1.5 to 4 seconds. This was reflected in a flatter dominance

distribution curve. The short dominance durations recorded in participants with

schizophrenia did not correlate with faster alternations of rivalling images (i.e. the

binocular rivalry rate). In fact, participants with schizophrenia recorded significantly

slower binocular rivalry rates in both binocular rivalry tasks compared to control

participants. This is likely due to the greater number of dominance durations greater

than 4 seconds recorded by participants with schizophrenia in each task.

a.

Cumulative Frequency Normalised Dominance Durations - Magnocellular BR Task

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Time in seconds

Cu

mu

lati

ve P

rob

abili

ty

Schizophrenia Controls

b.

.

Cumulative Frequency Normalised Dominance Durations - Parvocellular BR Task

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

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0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Time in Seconds

Cu

mu

lati

ve P

rob

abili

ty

Schizophrenia Controls

Figure 4.2: Difference between the dominance durations of participants with schizophrenia (n=17) (black lines) and control participants (n=24) (grey lines) for (a) the magnocellular binocular rivalry (BR) task and (b) the parvocellular BR task.


These data are consistent with the idea that individuals with schizophrenia

have abnormal processing in both the magnocellular and parvocellular visual

pathways. If magnocellular processing is ‘overactive in individuals with

schizophrenia, they would be likely to perceive more visual information arising from

short bursts of activity of the magnocellular neurons, interrupting parvocellular

processing further along the visual pathway. This would result in more frequent short

dominance durations. Abnormalities in parvocellular processing may account for the

abnormally long dominance durations in the schizophrenia group that act to slow the

binocular rivalry rate.

The method of binocular rivalry recording employed here requires that

participants ignore mixed or composite images and only record the change in

perception to the opposing image (that is, to record the change from a horizontal or

mixed image to one that is exclusively vertical, or a vertical or mixed image to one

that is exclusively horizontal). There are few stimuli that will produce perfect

binocular rivalry alteration of opposing images. Generally all participants

experiencing binocular rivalry perceive alternation of opposing images interspersed

with periods of mixed or composite image (Burke et al., 1999; Liu et al., 1992;

Mueller & Blake, 1989). As this experiment presented opposing images to each eye

in a continuous fashion, the parvocellular system had sufficient time to process the

spatial and chromatic details of stimuli to produce fast, crisp binocular rivalry

alternations. It has been posited that that one of the functions of the magnocellular

pathway may be to gate parvocellular signals to the cortex (Shapley, 1992) (based on

the observation that the detection of iso-luminant colour patterns is facilitated by

luminance patterns (Switkes, Bradely & De Valois, 1988). It is possible that the

magnocellular pathway simultaneously attempts to fuse the images into a single


percept based on the temporal and luminance properties of the images. Thus the

resulting phenomenon is a period where a single stable image is perceived, followed

by a period of mixed image before a change in perception of the alternative image.

Binocular integration and binocular rivalry have been demonstrated to coexist

in the same spatial location in the visual pathways (Carlson & He, 2000). Carlson

and He (2000) demonstrated that observers were able to perceive binocular rivalry

with respect to the colour and shape of the opposing triangles, while integrating two

temporal frequencies into a ‘slow flicker’ amplitude modulation (beat) using

information from the suppressed stimulus. It is accepted that two flickering

frequencies close together do not lead to binocular rivalry in participants with normal

stereovision; rather a slow flicker amplitude modulation (beat) that corresponds to

the difference between the primary frequencies is seen (Baitch & Levi, 1989; Karrer,

1967). These observations were explained by the authors as being the consequence

of the independent processing of the different attributes in the magnocellular and

parvocellular pathways. They posited that the parvocellular pathway, which

preferentially processes information regarding colour and shape of the stimulus,

leads to binocular rivalry. Carlson & He (2000) and He et al., (2005) suggest that

because the magnocellular pathway was more likely responsible for processing

flicker and temporal features of the stimulus that leads to fusion. Both of these

phenomena could occur at the same time within the same visual location. It could be

argued that the two visual pathways contribute to binocular rivalry, but are both

necessary to process the opposing images presented in binocular rivalry tasks. It can

be seen that participants with schizophrenia and controls were able to maintain crisp

perceivable binocular rivalry in both stimulus conditions. Therefore, if both

pathways contribute to the alternation of perceptual images seen in binocular rivalry


it may be the case that they occur between processes well beyond V1, and after the

computations between stimuli attributes have occurred.

It is possible that significant differences in binocular rivalry rates recorded by

participants with schizophrenia for both the magnocellular and parvocellular BR

tasks demonstrate an abnormality in both pathways, as there is considerable interplay

between the pathways. Although the pathways have been discussed as being quite

distinct, they do interact higher in the visual pathway, in particular in V1 and V2 of

the visual cortex (Shapley, 1990; Livingstone & Hubel, 1987). Schizophrenia

researchers have suggested cognitive disability is related to parvocellular pathway

functioning (Vidyasagar, 1999), while the magnocellular input may be vital for

controlling sequential attention (Kessels, Postma & de Haan, 1999). Hyperactive

magnocellular pathways have also been proposed as being responsible for some

anomalous perceptual experiences, including abnormal intensity of environmental

stimuli, feelings of being flooded and inundated and the inability to focus attention

on relevant details (Keri & Bemedek, 2007).

4.2.4.3 Gender differences.

There is little published research reporting gender differences in binocular

rivalry, with two studies reporting that females recorded faster binocular rivalry rates

than males (Cogan, 1973; Goldstein & Cofoid, 1965). Data from developmental

studies (Gwiazda, Bauer, & Held, 1989) indicate that female infants prefer to view a

rivalrous stimulus (rather than a fusible stimulus) until a mean age of 9.9 weeks; this

preference ceasing significantly earlier than in male infants (averaging 13.8 weeks).

Similarly, females showed evidence of stereopsis at an earlier age (9.1 weeks,

compared with 12.1 weeks for males). No studies could be located where males

were reported to have faster binocular rivalry rates than females. Miller et al., (2003)


found no overall gender effects in their sample of 18 participants with schizophrenia

(males n = 9, females n = 9). Gender effects in subjects with schizophrenia were not

reported in Sappenfield and Ripke (1961), males n = 21, females n = 9, Fox (1965)

males n = 10, females n = 5, and White et al., (2005) males n = 21, females n = 3.

The gender of 24 participants with schizophrenia tested in Frecska et al., (2003) was

not specified. Although statistically significant, the gender differences found in the

current study require replication, given the small number of female participants with

schizophrenia included in the sample (n = 4).

It is possible that the gender-related differences in binocular rivalry observed

here are due to hormonal changes associated with the menstrual cycle. The actions

of oestrogen, progesterone, and androgen have been suggested to contribute to

improved colour vision performance at ovulation (Giuffre, Di Rosa & Fiorino,

2007), increases in visual sensitivity during menstruation (Barris, Dawson & Theiss,

1980) and decreases in pattern reversal evoked potentials (Yilmaz, Erkin, Mavioglu

& Sungurtekin, 1998). Hormonal changes, and the use of oral contraceptives, have

been linked to alterations in retinal function and sensitivity changes in some women

(Eisner, Burkes & Toomey, 2004), however these alterations are not the same for all

visual pathways, and there were pronounced individual differences with individual’s

visual adaptation capabilities varying substantially over periods of weeks (Eisner et

al., 2004). The gender effect observed in the current study may be related to

hormonal effects in the small number female participants included in the sample.

Future studies should control for menstrual cycle variations or use of the

contraceptive pill.


4.3 A Backward-Masking Task Utilising Stimuli that Bias the Magnocellular and

Parvocellular Visual Pathways

4.3.1 Introduction.

Based on a comprehensive review of published literature, no binocular rivalry

studies were identified that used a similar method employing stimuli that bias the

magnocellular and parvocellular visual pathways outlined in Experiment 1 (Section

4.2). Consequently, there are no normative data with which to compare the results

presented in Section 4.2. The current study conducted to validate these results using

another visual task that is widely accepted to reliably bias the magnocellular and

parvocellular visual pathways, using a ‘within-subject design’.

4.3.1.1 Comparing binocular rivalry with other neurophysical tasks.

A search of the literature revealed that a variety of methods have been used to

investigate magnocellular and parvocellular processing in schizophrenia. These

include: contrast sensitivity tasks (Keri & Benedek, 2007; Slaguis, 1998), luminance-

flicker sensitivity (Slaghuis & Bishop, 2001) luminance discrimination tasks

(Delord et al., 2006), random dot patterns and global motion tasks (Chapman, Hoag

& Giaschi, 2004), spatial alignment of dots and gratings and frequency-doubling

(Keri et al., 2004), smooth pursuit tracking where participants were asked to track

dots moving a varying speeds (Schwartz et al., 1999b) and visual backward masking

(Bedwell & Orem, 2008; Birch, 1997; Butler et al., 2003; Buttner et al., 1999;

Cadenhead et al., 1998; Green et al., 1994b; Birch, 1997; Green et al., 2003; Green et

al., 2005; Green et al., 2006; Holzman, 1987; Keri et al., 2000; Keri, Benedek et al.,

2001; Keri, Szendi et al., 2001; McClure, 2001; Slaghuis & Curran, 1999; Weiss,

Chapman, Strauss & Gilmore, 1992). There have also been a number of

electrophysiological studies; VEPs (Butler et al., 2001; Butler et al., 2005; Butler et


al., 2007; Schechter et al., 2005), event related potentials (ERPs) (Butler et al., 2007;

Doniger et al., 2002), along with functional MRI (Martinez et al., 2008).

Visual backward-masking (VBM) tasks have been used most extensively,

with many researchers reporting transient channel or magnocellular pathway

abnormalities in participants with schizophrenia (Butler et al., 2003; Cadenhead et

al., 1998; Green et al., 1994b; Green et al., 2005; Green et al., 2006). Some authors

suggest both pathways are abnormal in participants with schizophrenia (Green et al.,

2003; Keri et al., 2000; Slaghuis & Curran, 1999), unaffected siblings (Birch, 1997;

Green et al., 2005), remitted patients (Butler et al., 2003; Buttner et al., 1999), and

individuals prone to psychosis. Backward masking is thus a promising indicator of

vulnerability to schizophrenia, with backward-masking abnormalities being

suggested as a trait marker for the disease (Bedwell & Orem, 2008; Buttner et al.,

1999; Green et al., 1997; Holzman, 1987; Keri, Benedej et al., 2001; Keri, Szendi, et

al., 2001; McClure, 2001).

There are a number of attributes of VBM that make this an attractive task to

compare with binocular rivalry. Firstly, the stimulus characteristics of the task can

be altered to bias the task for processing via the magnocellular or parvocellular

pathways with the use of colour, luminance contrast, and movement in a similar way

to binocular rivalry. The VBM task can be presented to participants using a

computer and response keypad with minimal specialist training required for the

researcher. Both binocular rivalry and visual backward masking involve suppression

of one image and dominance of an alternative image (image presented to the left

versus right eye in binocular rivalry, the target by the mask in VBM), and abnormal

visual processing has been demonstrated in participants with schizophrenia.


4.3.1.2 Development of the visual backward masking task.

A VBM task was developed based on the task described in Cadenhead et al.,

(1998). Like Cadenhead et al, (1998) a location task for process bias via the

magnocellular visual system (transient pathway) and an identification task for

process bias via the parvocellular visual system (sustained pathway) was adopted.

Identification versus location VBM tasks along with centrally- or peripherally-

located tasks have been used by others in VBM research (Koelebeck, Ohrmann,

Hetzel, Arolt & Suslow, 2005: Saccuzzo, Cadenhead & Braff, 1996). To further

bias the location task to the magnocellular pathway, dark grey letters (chromaticity

x= 0.2751, y= 0.3262, luminance 7.155 cd/m2) were presented at four spatial

locations on a lighter grey background with a 6.9% luminance contrast (chromaticity

x= 0.2756, y= 0.331, luminance 8.245 cd/m2). To further bias the task for the

parvocellular (sustained) pathway red letters (chromaticity x= 0.2967, y= 0.5853,

luminance 2.306 cd/m2) that were 30 pixels (or 8 mm high) were presented centrally

on a green iso-luminant background (chromaticity x=0.5548, y=0.3883, luminance

2.306 cd/m2). Iso-luminance was determined by flashing a test patch of the red and

green patches available on the computer at temporal frequencies of around 20 Hz the

point at which the flicker cannot be detected. When green and red are of equal

luminance, rather than perceiving flashes of green and red, a yellow sheen results

(this is a minimum flicker test) (Anstis & Cavanagh, 1983; Dobkins, Gunther &

Peterzell, 2000). The author and the programmer acted as participants in the

preliminary testing during the development of the backward-masking tasks.

The target letters used in Cadenhead et al., (1998) were changed from A, V, W

and Y to A, V, Y and T as the target letter W was spatially larger to the other three

letters and was unable to be sufficiently masked. Cadenhead et al., (1998) used


overlapping upper case Xs as the mask. Limitations in the software allowed for only

a single letter or symbol to be used as the mask in our task, so overlapping Xs were

not able to be achieved. A single upper-case letter X masked the V and the Y more

effectively than it did the A or T, allowing for the A and T to be more readily

identified in preliminary testing by both the author and programmer. Each letter and

symbol on the computer keyboard was then trialled as the mask letter/symbol. This

showed that the upper case S masked the target letters to the same degree and yielded

more consistent results, with A, T, V and Y targets being identified with equal

proficiency by the author and programmer.

The resulting VBM task was presented on a standard colour computer monitor

in two conditions; an identification task to bias the parvocellular pathway (herein

referred to as the parvocellular VBM task) and a location to bias the magnocellular

pathway (herein referred to as the magnocellular VBM task). The target stimuli in

each task consisted of one of four letters (A, T, V, or Y) presented either centrally in

the parvocellular VBM task, or in one of four locations (up, down, left or right) in

the magnocellular VBM task. The targets were presented at 2.1 degrees of visual

angle from the fixation point (a small black +). The mask consisted of the letter S

that was of equal size to the target letters, positioned so that it spatially overlapped

the target stimuli, centrally in the parvocellular VBM task and in the all four possible

locations in the magnocellular VBM task. In order to keep the VBM task as close to

the binocular rivalry tasks as possible, the target letters and masks were presented for

the same duration in each task. This differed from the tasks administered by

Cadenhead et al., (1998), who used an equal-strength target and mask in the

identification task but increased the energy of the mask in the location task by

presenting the mask for double the duration of the target. In the current study, the


duration of the target stimuli and the mask was 10 msecs. The mask was presented

after each target letter (A, T, V, or Y) or in all locations (up, down, left or right) at

four different inter-stimulus intervals (ISI); 27, 53, 107 and 213 msec (rounded up to

the nearest frame during presentation). Letter/letter location and inter stimulus

interval were counterbalanced over the duration of the task resulting in 64 trials of

stimulus target followed by mask. In each trial a fixation point was presented on the

screen (for 10 msec) following a short tone to indicate the onset of each trial.

4.3.1.3 The visual backward masking task procedure.

Written instructions were developed to ensure that each participant was given

the same information (see Appendix 1 and 2).

A pilot test to trial the backward-masking task was undertaken. Five

participants took part in the pilot test; all participants were female, aged between 27

and 40 years (average age 36.8 years). All were right handed and right-eye dominant

(as determined by a keyhole task), with 6/6 visual acuity.

Each participant completed 256 trials (representing four runs) of both the

magnocellular VBM task and parvocellular VBM tasks. In the parvocellular VBM

task the mask (S) was presented after each target letter (A, T, V, or Y) at four

different inter-stimulus intervals; 27, 53, 107 and 213 msec. This allowed each

target letter to be presented at each inter-stimulus interval on 16 occasions. Letters

and inter-stimulus intervals were counterbalanced over the duration of the task.

Similarly, in the magnocellular VBM task the mask was presented after the target

location (up, down, left or right) at four different inter-stimulus intervals; 27, 53, 107

and 213 msec, and counterbalanced over the duration of the task.


4.3.1.4 Results of preliminary testing.

In the magnocellular VBM task each participant identified the correct location

of each target more than 80% of the time (see Table 4.3). Paired sample t-tests

revealed no significant differences in the number of correct scores between the four

target locations in the magnocellular VBM task (t > 0.05). However, in the

parvocellular VBM task the letters A and V were correctly identified more than 80%

of the time, while the letters T and V were more difficult to locate with correct scores

of less than 80%. Paired t-tests revealed that there were significant differences in the

number of correct scores when comparing A and T (t = 4.0 df = 4, p = .016) and A

and Y (t = 3.64, df = 4, p = .022).

Although there was a significant difference in correct scores between the letter

A and the letters T and Y, it was decided not to change the target or the mask as

preliminary testing identified these letters as the optimal letters to be used within

programming limitations.

A significant practice effect was seen where each of the five participants were

able to almost complete each task without error (reaching a ceiling for near-perfect

scores) in the last 64 trials. A significant improvement in the scores was observed

when comparing the first 64 trials with the last 64 trials in our group; 201 out of a

possible 320 (5 x 64 trials) correct scores (62.5%) in the first 64 trials compared with

310 (96.87%) in the last. This practice effect reflects what is reported in the literature

(Maehara & Goryo, 2003; Wolford, Marchak & Hughes, 1988; Braffin Saccuzzo,

Ingram, McNeill & Langford, 1980). These five pilot participants were excluded

from the later comparison between binocular rivalry and VBM tasks.


Table 4.3: Correct target letter identification by location and letter in a preliminary test of the magnocellular and parvocellular visual backward masking (VBM) task (n = 5).

Magnocellular VBM task Parvocellular VBM task

Location of Target Correctly identified Target Letter Correctly Identified

Down 85% A 93.75%

Left 87.5% T 73.75%

Right 86.25% V 86.25%

Up 81.25% Y 61.25%

Because the VBM tasks were designed to be at (or near) visual threshold, it

was expected that nãive participants would not be able to achieve scores of 100%

correct. A practice non-masking task was developed to ensure that participants had

adequate contrast sensitivity to complete the task, and so that that each participant

understood the task and could accurately identify the targets without introducing a

practice effect. During the development of this task it was evident that the target

letters used in the parvocellular VBM task were more easily identified than the

letters of the magnocellular VBM task. In order to simplify the magnocellular VBM

task to improve the consistency of results, the target letters could either be darkened

to increase the luminance contrast or the letter size could be increased. The letter

size was increased to 40 pixels, as this could be done without fear of reducing the

bias toward the magnocellular visual pathway, as increasing the luminance contrast

to more than 6.9% was more likely to reduce the desired pathway bias.

In the non-masking practice task, participants were asked to identify letters in

the parvocellular VBM task and locate the letters briefly presented on the screen

under the same stimulus conditions as those to be used in the final VBM task. That


is, red letters of 30 pixels on a green iso-luminant background for the parvocellular

non-VBM task, and darker grey letters of 40 pixels presented on a lighter grey

background in for the magnocellular non-VBM task. Each letter was presented on

the screen for 10 msec. An 85% accuracy score was required for the participant to

be considered sufficiently reliable and having adequate visual sensitivity to complete

the VBM task.

4.4 Experiment 2: Comparing Visual Backward Masking and Binocular Rivalry

Tasks to Investigate Magnocellular and Parvocellular Processes.

The aim of Experiment 2 was to compare task performance of participants with

schizophrenia and controls on the magnocellular and parvocellular BR tasks (using

the same stimuli and binocular rivalry method as in Experiment 1) with the

magnocellular and parvocellular VBM tasks (as described in Section 4.3.1.2).

4.4.1 Methods.

4.4.1.1 Schizophrenia participants.

Of the 17 participants with schizophrenia that participated in the magnocellular

and parvocellular BR tasks, one participant was unable to complete the backward

masking task due to an increase in psychotic symptoms associated with their illness,

one participant was unable to achieve 85% correct responses in the non-masking task

and one participant was unable to identify the letters in the parvocellular VBM task

as he was red-green colour blind. This was later confirmed with Ishihara Test for

Colour Blindness (Birch, 1997). This resulted in 14 participants with schizophrenia.

Five participants met the schizophrenia sub-type classification of paranoid

schizophrenia with the remaining nine categorised as undifferentiated schizophrenia

sub-type. Four participants displayed positive symptoms of schizophrenia, eight

negative symptoms and two had equal positive and negative symptoms as assessed


by the PANSS (Kay et al., 1988). Eleven participants were taking atypical anti-

psychotic medication (two on Olanzapine, two taking Risperidone, five on Clozapine

and one on Quetiapine) and three were taking typical anti-psychotic medication.

Their CPZE dosages ranged from 200-800 mg/day, with the average CPZE being

517.9 mg/day.

4.4.1.2 Healthy controls.

Of the 24 healthy control participants who participated in the magnocellular

and parvocellular BR tasks, one participant was not available to complete the second

task, and five participants were excluded as they took part in the development of the

backward-masking task (this was necessary to eliminate any practice effect); 18

control participants took part in the study. The characteristics of participants are

detailed in Table 4.4.

Table 4.4: Age, gender, eye dominance and NART score of controls and participants with schizophrenia.

Controls (n=18)

Schizophrenia(n=14)

χ2 df p

Age Mean (yrs) 36.3 33.9 Range 21-58 23-50 21.029 14 0.278 Gender Male 4 10 Female 14 4 7.748 1 0.011 Eye Dominance R)eye 10 10 L)eye 4 8 0.847 1 0.292 NART Score Mean 116.7 104.5 Range 102-122 101-124 18.194 14 0.198

4.4.2.2 Binocular rivalry and visual backward masking stimuli.

The method of collecting binocular rivalry data for this study was undertaken

as previously described in Experiment 1 and the VBM task as described in Section


4.3.1.2 (see Appendix 1 and 2 for the written and verbal instructions given to each

participant).


Binocular rivalry rate (button pushes per second, Hz), binocular rivalry

dominance intervals (the time from onset of perceiving one eye’s image to the onset

of the opposing image (measured in msec), and VBM correct scores (number correct

total and at each inter-stimulus-interval) were entered into a computerised statistical

package (SPSS – Student Version 14) for analysis. Kolmogorov-Smirnov and

Shapiro-Wilks statistics for normality were calculated for both binocular rivalry and

VBM tasks.

Kruksal-Wallis one-way non-parametric ANOVAs were performed to

determine the effect that group, gender, age, education and NART score had on

binocular rivalry rate in the binocular rivalry tasks and number of correct VBM

scores. Planned comparison Mann-Whitney U tests were performed to determine

differences in binocular rivalry rate and visual backward masking scores between

participants with schizophrenia and healthy controls in both the magnocellular and

parvocellular tasks. Plotted normalised dominance intervals for the BR tasks were

compared using a one-way Smirnov test.

4.4.3 Results.

4.4.3.1 Binocular rivalry rates.

As the binocular rivalry rate data were not normally distributed, Kruksal-

Wallis one-way non-parametric ANOVAs were performed. It was revealed that

group had a significant main effect on binocular rivalry rate for both the

magnocellular and parvocellular BR tasks; χ2 (1, 41) = 5.374, p<.02 magnocellular

BR task and χ2 (1, 41) = 7.498, p<.006 in the parvocellular BR task. Age and gender


had no effect on binocular rivalry rate in either task (age χ2 [18, 41] = 15.210, p=

.648 and χ2 [18, 41] = 19.656, p= .353; gender χ2 [1, 41] = 1.977, p =. 16 and χ2 [18,

41] = 0.925, p = .335 for magnocellular BR task and parvocellular BR tasks,

respectively). The gender effect reported in Experiment 1 was not replicated here.

Six female healthy control participants and three male participants with

schizophrenia were excluded from participating in the second experiment, which was

likely to account for this.

Participants with schizophrenia recorded significantly slower binocular rivalry

rates in both the magnocellular and the parvocellular BR tasks compared to controls

(see Figure 4.3). Mean binocular rivalry rate for the magnocellular task in the group

with schizophrenia was 0.24 Hz (SD = 0.12) compared with 0.39 Hz (SD = 0.16) in

healthy controls (Mann-Whitney U test, Z = -2.318, p < .02). In the parvocellular BR

task, the mean binocular rivalry rate in the schizophrenia group was 0.24 Hz (SD =

0.09), compared to 0.44 Hz (SD = 0.24) in healthy controls (Mann-Whitney U test, Z

= -2.738, p < .005).

A significant difference in binocular rivalry rates for the magnocellular and

parvocellular tasks was found in healthy participants (magnocellular mean rate 0.39

Hz, SD = 0.156, versus parvocellular 0.44Hz, SD = 0.24, Z = -1.47, p= .047).

Participants with schizophrenia showed no difference in binocular rivalry rates

between the magnocellular and parvocellular BR tasks (mean rate 0.24 Hz, S =. 0.09

and mean rate 0.22 Hz, SD = 0.11 respectively, Z = -0.621, p= .535).


Figure 4.3: Mean binocular rivalry (BR) rates recorded in participants with schizophrenia (black triangles) compared to healthy controls (black diamonds).

Note: Error bars show standard errors of the mean.

Diagnostic sub-group, medication dose and negative and positive symptoms of

schizophrenia had no effect on binocular rivalry rate for either the magnocellular or

parvocellular tasks (Mann-Whitney U tests): diagnostic subgroup (paranoid

schizophrenia [n = 5] versus undifferentiated schizophrenia [n = 9] magnocellular

BR task Z = -0.468, p= .699) and parvocellular BR task [Z = -1.470, p= .147]; low-

[<425 mg, n = 4] versus high-dose [>425 mg, n = 8] of anti-psychotic medication

magnocellular BR task [Z = -0.142, p = .945] and parvocellular BR task [Z = -0.354,

p = 9.733] and positive symptom [n = 4] versus negative symptom [n = 8]

schizophrenia magnocellular BR task [Z = -0.595, p= .507] and parvocellular BR

task [Z = -0.766, p = .461]). Two participants had equal positive and negative

symptom scores, and were excluded from the analyses.

4.4.3.2 Dominance intervals.

One-way Smirnov tests revealed significant differences in the distribution of

normalised dominance intervals in participants with schizophrenia compared with

healthy controls in both the magnocellular and the parvocellular BR tasks.

0.390.44

0.24 0.24

0

0.1

0.2

0.3

0.4

0.5

0.6

Magnocellular BR Task Parvocellular BR Task

BR

rat

e in

Hz

(b

utto

n p

ush

es/

seco

nd)

Key Control (n=18)

Schizophrenia (n=14)


Significant differences in the distributions of dominance intervals occurred in both

the magnocellular and parvocellular BR tasks at the p < .05 level of significance (as

T1>CV-ST). See Table 4.5.

Table 4.5: Differences in the distribution of dominance durations between participants with schizophrenia and controls in magnocellular and parvocellular binocular rivalry (BR) tasks: Smirnov test outcomes of dominance duration distributions.

Schizophrenia Participants

m

Healthy Controls

n

Critical Value -Smirnov Test

1.36√ m+n/ mn

Smirnov T

(T1)

Reject Ho? Reject if

T1>CV-ST

Magnocellular BR Task

1332 2592 0.045849 0.08552

Yes

Parvocellular BR task

1314 2991 0.045011 0.07690

Yes

The greatest differences in distribution functions in both magnocellular and

parvocellular BR tasks occurred at the 0.5 second time interval (see Figure 4.2).

Thus participants with schizophrenia recorded significantly more dominance

intervals of 0.5 seconds duration than healthy controls. Although participants with

schizophrenia recorded more dominance durations of less than one second in the

magnocellular BR task, they generally recorded few dominance durations from 1.5 to

5 seconds compared to control participants, resulting again in a slightly flatter

distribution (Figure 4.4a).

4.4.3.3 Visual backward masking (VBM).

Kruksal-Wallis one-way non-parametric ANOVAs were performed on the

correct scores for both VBM tasks. Group had a significant main effect on VBM

scores in both the magnocellular and parvocellular VBM tasks (magnocellular VBM

task: group χ2 [18, 41] = 6.677, p= .01; parvocellular VBM task: χ2 [18, 41] =

10.345, p < 0.001). Age and gender had no effect on binocular rate for either task

(Kruksal-Wallis χ2, p>0.05). Thus, participants with schizophrenia identified the


location of the target in the magnocellular VBM and the identity of the target in the

parvocellular VBM task less frequently than controls at all inter-stimulus intervals

(however these differences only reached statistical significance [Mann-Whitney U

test] for inter-stimulus intervals of 27, 53 and 107 msecs in the parvocellular VBM

task). See Table 4.6 for results.

Table 4.6: Differences in correct identification of a target scores in magnocellular and parvocellular visual backward- masking (VBM) tasks between participants with schizophrenia and healthy controls at four inter-stimulus intervals (ISI)

Magnocellular VBM Task Controls

(n = 18) Schizophrenia

(n = 14)

M SD M SD U Z p ISI 27msec 7.4 3.2 7.5 3.4 125.5 -0.190 .985 ISI 53msec 10.0 3.9 8.5 3.8 100.5 -0.973 .330 ISI 107msec 11.3 4.0 9.1 3.9 85.0 -1.565 .118 ISI 213msec 11.8 3.9 10.6 5.3 114.0 -0.460 .646 Parvocellular VBM Task Controls

(n = 18) Schizophrenia

(n = 14)

M SD M SD U Z p ISI 27msec 9.7 2.3 7.4 2.7 64.0 -2.376 .018* ISI 53msec 11.6 2.3 8.6 3.3 61.0 -2.499 .012* ISI 107msec 12.7 2.8 9.9 4.3 70.0 -2.138 .032* ISI 213msec 12.5 2.4 12.2 3.6 122.0 -0.153 .878 ISI 27msec 9.7 2.3 7.4 2.7 64.0 -2.376 .018* Note: * indicates p < .05 significance

Mann Whitney U tests revealed no significant effect of medication dose or

positive and negative symptom ratings in either the magnocellular or

parvocellularVBM task (p < .05). However, a significant effect of schizophrenia

sub-type (un-differentiated or paranoid schizophrenia) was found in the

magnocellular VBM task at inter-stimulus intervals of 27 msec and 53 msec (Z = -

2.665, p = .007, and Z = -2.094, p = .042 respectively), with no effect observed in the

parvocellular VBM task at these inter-stimulus intervals.

Dose level had a significant effect on VBM score for inter-stimulus intervals of

27 msec in the magnocellular VBM task (Z = -2.030, p= .042) and DSM-IV


diagnostic sub-group had a significant effect on VBM score for inter-stimulus

intervals of 27 msec and 53 msec in the magnocellular VBM task (Z = -2.665, p =

.008 and Z = -2.094, p= .036 respectively). However, DSM-IV diagnostic sub-group

(paranoid schizophrenia versus undifferentiated schizophrenia as per DSM-IV

classification) and medication dose had no effect on the remaining VBM scores.

Negative and positive symptoms of schizophrenia had no effect on VBM scores in

the remaining inter-stimulus intervals in the magnocellular VBM task or at any inter-

stimulus intervals in the parvocellular VBM task for participants with schizophrenia

(Mann-Whitney U tests) (See Table 4.5, Appendix C).

a.

b.

Figure 4.4: The dominance durations between participants with schizophrenia (n=14; black lines) compared to control participants (n=18; grey lines) for (A) magnocellular binocular rivalry (BR) task and (b) parvocellular BR task.

Note: A separation in location of any two time points on each curve indicates a significant difference in mean normalised dominance durations.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Time in Seconds

Cum

ulat

ive

Pro

babi

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Schizophrenia Control

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Mean correct responses were plotted against inter-stimulus interval for each

task and these masking functions are presented in Figure 4.5.

a.

b.

Figure 4.5: Number of correct responses as a function of inter-stimulus interval in controls and participants with schizophrenia for (a) magnocellular visual backward-masking(VBM) and (b) parvocellular VBM tasks.

Note: Error bars show standard error.

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4.4.3.4 Comparing binocular rivalry and visual backward masking results.

To be confident in the binocular rivalry data presented in Experiments 1 and 2

and validating the use of pathway-biased stimuli in binocular rivalry, it would be

expected that magnocellular binocular rivalry and VBM, and parvocellular binocular

rivalry and VBM tasks would be significantly associated. Correlation coefficients

are presented in Table 4.7.

When VBM correct scores were compared with the binocular rivalry rates (in

Hz) it can be seen that participants with schizophrenia performed more poorly in

both magnocellular and parvocellular tasks compared to the control participants, with

the greatest differences recorded in the parvocellular tasks. Correlations between

correct VBM scores and binocular rivalry rates were examined. Significant

correlations were evident between parvocellular binocular rivalry rates in

parvocellular VBM task scores at inter-stimulus intervals of 27, 53, 107 and 213

msec and between magnocellular binocular rivalry rates and parvocellular visual

backward masking task scores at inter-stimulus intervals of 53, 107 and 213 msec in

healthy control participants. Thus control participants with slower binocular rivalry

rates, in both magnocellular and parvocellular BR tasks, performed more poorly on

parvocellular VBM tasks than participants with faster binocular rivalry rates.

Participants with schizophrenia did not show any significant correlations

between binocular rivalry rates and visual backward masking scores in either

parvocellular or magnocellular tasks (with the exception of a near significant

correlation of p= .053 at inter-stimulus interval 53 msec in parvocellular binocular

rivalry and VBM tasks).


Table 4.7: Correlations between magnocellular and parvocellular binocular rivalry (BR) rates (in Hz) with magnocellular and parvocellular visual backward masking (VBM) correct scores (Spearman’s correlation coefficient rho).

Controls (n=18)

Magnocellular BR task

(rate in Hz) Parvocellular BR task

(rate in Hz) r2 p r2 p Magnocellular VBM Task (correct scores) ISI 27msec 0.205 .414 0.301 .224 ISI 53msec 0.104 .680 0.269 .281 ISI 107msec 0.142 .575 0.283 .256 ISI 213msec 0.147 .560 0.066 .795 Parvocellular VBM task (correct scores) ISI 27msec 0.353 .151 0.474 .047* ISI 53msec 0.518 .028* 0.581 .011* ISI 107msec 0.501 .034* 0.484 .042* ISI 213msec 0.655 .003* 0.587 .010* Schizophrenia (n=14)

Magnocellular BR task

(rate in Hz) Parvocellular BR task

(rate in Hz) r2 p r2 p Magnocellular VBM Task (correct scores) ISI 27msec 0.016 .957 0.248 .392 ISI 53msec -0.039 .895 0.025 .934 ISI 107msec -0.243 .403 -0.208 .477 ISI 213msec -0.235 .418 -0.089 .763 Parvocellular VBM task (correct scores) ISI 27msec -0.161 .583 -0.443 .113 ISI 53msec -0.333 .244 -0.526 .053* ISI 107msec -0.226 .436 0.020 .946 ISI 213msec -0.129 .661 -0.154 .598 Note. * indicates p < .05 significance (two tailed).

With respect to the magnocellular VBM and binocular rivalry tasks, no

correlations were evident in either healthy control participants or participants with

schizophrenia when the magnocellular VBM task was compared with magnocellular

and parvocellular BR tasks. It is also possible that methodological differences


between the tasks reduced correlations in the magnocellular tasks. For example,

equal strength mask and stimuli were used in this study in the magnocellular VBM

(as previously discussed), and moving stimuli at low spatial frequency were used in

the binocular rivalry task compared with stationary peripherally-located targets and

mask in the VBM (chromaticity and luminance contrast were relatively matched

between the tasks). An alternative interpretation of these data is that only the

parvocellular pathway contributes to binocular rivalry, or that binocular rivalry rate

reflects only the activity of the parvocellular visual pathway.

4.4.4 Discussion relating to visual backward masking.

Slower binocular rivalry rates were recorded in participants with schizophrenia

compared with controls (see Figure 4.3), with the greatest difference being recorded

in the parvocellular BR task, replicating the results found in Experiment 1. No

significant differences in binocular rivalry rates were recorded in participants with

schizophrenia between the magnocellular and parvocellular BR tasks (Z = -0.621, p=

.535), while control participants recorded significantly faster binocular rivalry rates

in the parvocellular BR than the magnocellular BR task (Z = -1.47, p= .047).

Significant differences were found in the distribution of dominance durations

between participants with schizophrenia and controls in both binocular rivalry

conditions. Participants with schizophrenia recorded more dominance intervals of

less than one second than controls and fewer dominance durations of 1.5 to 5

seconds duration. This was particularly evident in the magnocellular BR task on

visual inspection of the dominance duration functions. Slower binocular rivalry rates

in the group with schizophrenia taken together with a significant difference in the

distribution of dominance durations, is suggestive of an abnormality in one of both

of the visual pathways in schizophrenia. These data do not allow conclusions to be


drawn as to which pathway, or whether both pathways are contributing to abnormal

binocular rivalry rates and dominance distributions in schizophrenia. A plausible

explanation is that over-active magnocellular neurons distributed across the retina

send rapid transient responses to visual stimuli during binocular rivalry (as evidenced

by the increased number of short dominance durations), interrupting the sustained

response of the parvocellular neural processing (Butler et al., 2003).

In participants with schizophrenia, increased numbers of short dominance

durations do not correspond with faster binocular rivalry rates, thus an overall slower

rate must be accounted for by some abnormally long dominance durations (more 1.5-

5 second dominance durations were recorded in the schizophrenia group). Slower

binocular rivalry rates in participants with schizophrenia may reflect more “sluggish”

or prolonged processing by parvocellular neurons in schizophrenia. The data

presented here are suggestive of abnormalities in both the magnocellular and

parvocellular pathways. Further investigation is needed to determine whether

abnormalities is the two pathways is responsible for the atypical dominance

durations and slower binocular rivalry rates in schizophrenia.

Participants with schizophrenia performed more poorly on VBM tasks than

healthy participants, consistent with previous reports (Braff, Saccuzzo & Geyer,

1991; Green et al., 2003; Green et al., 1994b; Koelkebeck et al., 2005). Participants

with schizophrenia generally identified the location of the target in the magnocellular

VBM task and the identity of the target in the parvocellular VBM task less

frequently than healthy participant’s at all inter-stimulus intervals. Overall group

differences in correct scores were observed in both the magnocellular and

parvocellular VBM tasks; however the greatest difference in mean scores was

recorded in the parvocellular VBM task (2.3 at inter-stimulus of 27 msec, 3 at 53


msec, and 2.6 at 107 msec). Statistical significant for inter-stimulus intervals of 27

msec (p= .018), 53 msec (p = .012) and 107 msecs (p= .032) in the parvocellular

VBM task (Table 4.4). The lack of effect in the magnocellular task may be due

narrow range of ISI’s selected for this task. It is likely that greater difference in the

magnocellular task would have been observed between participants with

schizophrenia and controls at ISI’s of greater than 400 – 800 msec. Longer ISI’s are

necessary for individuals with schizophrenia to escape the masking effects in VBM

tasks (Schechter, et al., 2003). Future studies that incorporate VBM tasks biased to

include a greater range of ISI’s are needed.

Abnormalities in VBM in schizophrenia have typically been attributed to

magnocellular rather than parvocellular pathway processing (Cadenhead et al., 1998;

Green et al., 1994b, Koelkebeck et al., 2005; Schechter et al., 2003). Methodological

differences may account for the different results reported here. To bias the

magnocellular visual pathways, researchers have typically developed VBM tasks

where the mask is of greater energy than the target. By increasing the presentation

duration time (Cadenhead et al., 1998; Green et al., 2003), luminance contrast

(Schechter, et al., 2003) and spatial frequency (Butler, 2003; Butler et al., 2005;

Slaghuis & Curran, 1999) the mask is presented at greater energy than the target.

This is based on the observation that the contrast range over which transient

(magnocellular) neurons responds dynamically (give an increase in response to an

increase in stimulation) is smaller than that of sustained (parvocellular) neurons, and

that transient neurons saturate sooner than sustained neurons (Breitmeyer & Ganz,

1976). Thus, if a mask is presented at greater duration, at greater luminance contrast

or spatial frequency to the target, the mask is considered to stimulate sustained rather

than transient pathway processing, with the brief duration of the preceding target


stimulating transient pathway processing. Because the primary interest in this

experiment was to develop a task that preferentially biased the transient and

sustained pathways to compare with a binocular rivalry task, the mask and targets

were of the same energy in terms of stimulus duration, luminance contrast and

spatial frequency to match the stimulus characteristics of the binocular rivalry tasks.

The binocular rivalry stimuli only differed in terms of line orientation (vertical

versus horizontal lines).

The lack of a medication effect on VBM performance observed here is

consistent with other studies (Butler et al., 2003, Braff & Saccuzzo, 1992;

Cadenhead et al., 1998). However, the absence of a finding related to positive and

negative symptoms of schizophrenia has not been reported previously, where VBM

information processing deficits have been consistently reported in groups with more

negative rather than positive or disorganised symptoms of schizophrenia (Butler et

al., 2003; Cadenhead et al., 1997; Schechter et al., 2003; Slaghuis & Bakker, 1995;

Slaghuis & Curran, 1999). This may be due to the small sample size (four

participants with positive symptoms compared to eight with negative symptoms) and

the fact that this sample comprised a group of out-patient participants who did not

have acute symptoms of illness at the time of testing.

4.5 General Discussion

The key to the sustained versus transient (or magnocellular versus

parvocellular) explanations of visual masking is the difference in transmission time

from the retina to the cortex of the two pathways (May, Grannis & Dunlap, 1988).

Breitmeyer and Ganz (1976) demonstrated that transient (magnocellular) channel

neurons respond to the onset and offset of a stimulus 50-80 msecs before the

sustained (parvocellular) channel neuron, with the response of the sustained channel


neuron dependent on the spatial frequency of the stimulus (although Laycock et al.,

(2008) suggests that the magnocellular advantage in humans is approximately 25 –

30 msecs). A stimulus of high spatial frequency has a long latency in response and

lower response amplitude than one of lower spatial frequency. Breitmeyer and Ganz

(1976) explain the time course difference in responses of transient and sustained

neurons in the retina, LGN and primary visual cortex in the following diagram.

Figure 4.6 demonstrates the time course differences between transient and sustained

responses to a brief presentation of a stimulus.

Figure 4.6: The hypothesised time course of activation of transient and sustained channels after a brief presentation of a stimulus.

Note: In the sustained channels, the solid line indicates activity of the intermediate spatial frequency channels, the dashed line high spatial frequency channels and the dotted line very high spatial frequency channels.

In VBM tasks Breitmeyer & Ganz (1976) suggest that the time difference in

response of the transient and sustained neurons in the retina and LGN account for the

masking effects seen in VBM tasks. They suggest that transient neurons react

rapidly to the onset of the target stimulus, to locate the stimulus and stimulate eye

movements to secure the target in the visual scene. The slower responding sustained


neurons then processes the spatial and colour features of the stimulus to identify the

stimulus. If a mask is presented a short time after the target the response from the

transient channels may inhibit (or interrupt) the processing of the sustained channel,

or if the sustained channel has partially responded, integrate with the response.

These authors presented a model of visual masking outlined in Figure 4.7.

Figure 4.7: The time course of the transient and sustained channels when the target precedes the mask (backward masking).

T = transient channel, S = sustained channels. Arrows indicate the direction of the masking interaction. A minus sign indicates that the interaction is inhibitory, and a positive sign indicates that the interaction is one of sensory integration.

Contemporary schizophrenia researchers typically subscribe to one of two

interpretations of the visual abnormalities attributed to transient channel or

magnocellular pathway from this model. One suggests that the transient channel is

over-active in schizophrenia and interrupts the processing of the parvocellular

pathways, while the other suggests that the over-active transient channel affects the

integration of images into stable precepts. Interruption has been demonstrated in

100 200 3000

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Adapted from Breitmeyer, B. G. and L. Ganz (1976). "Implications of sustained and transient channels for theories of visual pattern masking, saccadic suppression, and information processing." Psychological Review 83(1): 1-36.

Target

Mask

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VBM tasks where the sustained channel sensitive to stimuli that is moderate-to-high

spatial frequency and slow temporal frequency codes fine detail necessary for object

recognition (the target) is interrupted by faster responding transient channel activity

elicited by the mask (Cadenhead et al., 1998; Green et al., 1994a; Green et al.,

1994b; Rassovsky, Green, Nuechterlein, Breitmeyer & Mintz, 2004). This theory

has been put forward to describe the visual and auditory hallucinations that are

commonly seen in schizophrenia. The second theory suggests that the transient

pathway is defective in schizophrenia, needing abnormally long periods of time

between the presentation of images in order to recognise and code them. When

images are seen in quick succession (with short inter-stimulus intervals) the

information from both images is integrated or fused. Individuals with schizophrenia

may therefore be creating ‘false’ or ‘incorrect’ visual images and be mis-interpreting

visual information contributing to the paranoia and perceptual disturbances

commonly experienced in this illness. Impairments in visual integration have been

linked to increases in disorganised symptoms (Butler, Silverstein & Dakin, 2008;

Uhlhaas, Phillips & Siverstein, 2005; Uhlhaas, Phillips, Mitchell & Silverstein,

2006), poorer pre-morbid social functioning (Chen, Nakayama et al., 2003) and

increased illness severity and chronicity (Silverstein et al., 2006). Deficits in

integration have also been reported in first-episode participants (Javitt, 2009;

Uhlhaas et al., 2006) and deficits in the magnocellular system correlate significantly

with global outcome and level of community functioning (Schechter et al., 2005).

Although it remains unresolved whether the VBM dysfunction in

schizophrenia reflects the abnormality of sub-cortical transient channels or deficient

cortical mechanisms (Keri et al., 2000), data from fMRI studies show that

participants with schizophrenia have markedly lower activation to low spatial


frequency stimuli in regions of the occipital, parietal and temporal lobes (Martinez et

al., 2008), suggesting cortical regions are involved, especially when the LGN is

functioning normally. It is possible that the initial abnormality may occur earlier in

the pathway. Deficits in early-stage visual processing predict higher cognitive

deficits in schizophrenia (Butler et al., 2005) and may contribute to higher-order

cognitive deficits in working memory, executive functioning and attention (Martinez

et al., 2008).

4.5.1 A model of binocular rivalry based on visual backward masking theory.

According to the sustained-transient theory in VBM, if the mask and test

stimuli are similar in orientation and spatial frequency, maximum masking will occur

at stimulus onset synchrony. This prediction stems from the assumption that when

the mask and target are similar, equal proportions of magnocellular and parvocellular

cells are stimulated and masking effects derive from ‘within channel’ inhibition

(transient on transient and sustained on sustained) (May et al., 1988). Breitmeyer

and Ganz (1976) postulated that transient neurons inhibited sustained ones via

internuncial neurons at the LGN and cortex based on their response duration. See

Figure 4.8.

It is conceivable that binocular rivalry processing may occur in a similar way.

Visual information from the left and right eyes travels via monocular neurons and

binocular neurons to the LGN and to the left and right visual cortex. Visual

information is carried more rapidly to the cortex by monocular than binocular

neurons, and both types contain magnocellular and parvocellular cells, with

parvocellular neurons concentrated around the fovea while the density of

magnocellular neurons increases with foveal eccentricity (Livingstone & Hubel,

1987).


Figure 4.8: Transient (magnocellular) neurons inhibit sustained ones via internuncial neurons at the lateral geniculate nucleus (LGN) and cortex. The impulse response by the internuncial neuron is inhibitory at the postsynaptic potential and integrates with the sustained neuron at either the LGN or cortex.

‘Inter-ocular grouping’ occurs during rivalry, where many small targets

scattered through the visual field can engage in synchronised alternation (Alais &

Blake, 1999). When patchwork rival figures are presented to each eye (for example,

grating patches of different orientation, or composite images of a monkey face and

text), observers are able to see two globally coherent figures (Kovacs et al., 1996;

Blake, 2001), indicating that rivalling zones are not independent and they may be

grouped by lateral connections between cortical hypercolumns (Alais & Blake,

1999).

When stimuli are continuous the image fades as the neurons in the visual

pathways saturate; this is known as Troxler effect (Levelt, 1968) or ‘Troxler fading’.

Troxler fading can either be disrupted by large voluntary or slight involuntary eye

movements or micro saccades (Martinez-Conde et al., 2006). Micro saccades cause

the eyes to shift slightly across the visual field, so that an image is never entirely

stable on the retina for any appreciable time. Burr, Ross and Murrone (1994)

Transient Transient

Sustained Sustained

Retina LGN Cortex

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suggest that during these micro saccades saccadic suppression occurs to create a

stable continuous image so that humans perceive a single stable image. They

suggest that this suppression is selective for patterns modulated in luminance at low

spatial frequencies (magnocellular or transient pathways). Patterns of higher spatial

frequency and equiluminant patterns (those stimulating parvocellular or sustained

pathways) are not suppressed during saccades, but enhanced, setting up a situation of

magnocellular suppression and parvocellular dominance in early in visual

processing, possibly as early as the lateral geniculate nucleus. The disruption from

micro saccades interrupts the Troxler fading (Martinez-Conde et al., 2006) and

triggers dominance changes during binocular rivalry (Blake et al., 1990, 2003; Carter

and Cavanagh, 2007; Alais et al., 2010).

This model suggests that the magnocellular pathway gates, (Javitt, Liederman,

Cienfuegos & Shelley, 1999) or acts as a ‘switch’, with its rapid response to local

visual information turning off or interrupting cortical processing the parvocellular

neurons in the cortex derived from parvocellular neurons located in corresponding

retinal location in the opposite eye. The magnocellular neurons saturate quickly,

before the slower parvocellular neuron responds, allowing the observer to ‘see’ the

image being processed by the parvocellular pathway. This activity occurs over the

entire retinotopic area with small patches of activity denoting each hypercolumn,

which are connected together by lateral connections (Alais & Blake, 1999).

This revised model combines two prevailing models of binocular rivalry; that

of pattern rivalry (where the conflicting stimuli presented to each eye compete for

dominance from interactions between monocular and binocular neurons in the visual

cortex, see (Blake, 2001) and the pathway model of binocular rivalry that suggests

that binocular rivalry is related to the actions of the parvocellular, magnocellular


pathway processing, or both in the retina, LGN and cortex (Blake, 1991; He et al.,

2005).

In Experiments 1 and 2 control participants recorded significantly faster

binocular rivalry rates using stimuli biased to the parvocellular pathway compared to

a binocular rivalry task biased to the magnocellular pathway. This revised model

predicts that in the parvocellular binocular rivalry condition, where the parvocellular

visual pathway response is stronger than the magnocellular response, the image is

able to be identified based on its colour and spatial information before the

magnocellular response from the opposite eye interrupts processing; thus allowing

crisp alternation between the left and right eye’s visual images. In the

magnocellular-biased condition the magnocellular response is stronger so the

interruption of the response from the opposing eye occurs quickly after the saturation

of the first eye’s response so processing of the response of the parvocellular neurons

occur after the saturation of the magnocellular neurons of both eyes, slowing down

the binocular rivalry alternation rate.

No significant differences were found between rates in binocular rivalry tasks

that biased the magnocellular and parvocellular pathways in participants with

schizophrenia. It has been postulated that abnormal magnocellular pathways in

participants with schizophrenia interrupt or abnormally integrate with the processing

of parvocellular pathways (Green et al., 1994b; Green et al., 1994a; Green et al.,

2009; Keri et al., 2004). Over-active magnocellular pathways in the model would

lead to a rapid response and saturation of magnocellular neurons which interrupt the

parvocellular pathways’ response to the finer details of the image and the perception

of the opposing image. This would shorten the dominance duration.


Figure 4.9: A revised model of binocular rivalry with rapid magnocellular response followed by the parvocellular response to continuous stimuli (vertical and horizontal lines) in the right and left eyes respectively at corresponding retinotopic areas.

Note: Arrows indicate if the masking interaction is interruption or integration. The bottom axis denotes the fluctuating images seen during binocular rivalry over time. Note that the duration of the image is not constant.

If the magnocellular neurons response by the opposite eye occurs as the

parvocellular neurons saturate no interruption would occur, with integration

lengthening the dominance duration thus slowing the rate. An interpretation of this

would be that the magnocellular pathway is responsible for triggering the alternation

of images seen in binocular rivalry by the action of the magnocellular afferent

neurons in the LGN inhibiting parvocellular neurons in the cortex. It may be the

action response of the parvocellular neurons in the cortex that determine the duration

of the dominance duration of the image, and thus the rate. If the magnocellular

pathway is overactive, cortical activity of the parvocellular pathway is disrupted,

thus binocular rivalry rate slows. The higher number of shorter dominance durations

recorded by participants with schizophrenia may reflect early magnocellular

processing, while the abnormally long dominance durations seen in participants with


schizophrenia (and not healthy participants) may reflect abnormal parvocellular

processing at the cortical level.

A limitation of the binocular rivalry task is that it relies on self-report reporting

of perceptual alternation is effected by reaction time. It is not possible to be sure that

the participant is accurately report what they perceive. Participants that experience

quicker perceptual alternations during binocular rivalry may not have sufficient time

to respond pressing a response key before the opposing image becomes dominant. In

humans recognition of an object generally occurs prior 180 msec with a motor

response intiated from 540-720 msec (Castelo-Branco, Neuenschwande & Singer,

1998). If a change in perceptual dominance occurs around 500 msec, it is possible

that an individual with schizophrenia may not be able to register their perception of

the image before the next alternation occurs. Measuring participant’s reaction times

in future studies to ensure no confound related to reaction time (slower in

schizophrenia) would be a useful methodological advance (Ngan & Liddle, 2000).

Furthermore, Braff and Saccuzzo (1985) note that information-processing

deficits in individuals with schizophrenia occur at ISI’s between 60 msec and 500

msec in VBM tasks. Future VBM studies that include longer ISIs between target and

mask, that reflect the temporal characteristics of perceptual alternations or

dominance durations in binocular rivalry, may allow greater exploration of

magnocellular and parvocellular processing in schizophrenia. VBM tasks that

include greater ISI’s (of 400 – 800 msec) may revealed greater seperation between

participants with schizophrenia and controls.

4.6 Conclusion

Participants with schizophrenia recorded slower binocular rivalry rates than

healthy controls in two binocular rivalry tasks that were biased to processing via the


magnocellular and parvocellular pathways, with the greatest difference in binocular

rivalry rates being observed in the parvocellular binocular rivalry task. Two

backward-masking tasks were developed; a location task to access magnocellular

processing, and an identification task to access parvocellular processing, to compare

performance with the binocular rivalry tasks. Participants with schizophrenia

performed more poorly in both the magnocellular and parvocellular backward

masking conditions, with the greatest difference being in the parvocellular backward-

masking task.

A revised model of binocular rivalry that combines pattern rivalry theory with

a pathway theory was proposed to explain the results. However further investigation

into this model of binocular rivalry are needed. Future studies that include binocular

rivalry tasks that are biased toward the magnocellular and parvocellular visual

pathways compared VBM studies that include longer ISIs between target and mask

(400-1200msec), that reflect the temporal characteristics of perceptual alternations or

dominance durations in binocular rivalry, may allow greater exploration of

magnocellular and parvocellular processing in schizophrenia.

Chapter 5: Benton’s Judgment of Line Orientation - An Indicator of Visuospatial Ability in Schizophrenia 161

5.1 The Right Hemisphere and Visuospatial Dysfunction

Pettigrew and Miller (1998) and Miller et al., (2003) suggested that binocular

rivalry is the result of competition between the two cortical hemispheres that occurs

by virtue of an ‘inter-hemispheric switching’ mechanism (see Chapter 3 for further

discussion). This theory assumes that visual information originating from both eyes

combines to form a stable percept within each hemisphere that competes for

dominance over the other. Thus, if visual processing within one hemisphere was

abnormal (or one hemisphere was damaged) binocular rivalry processing would be

impaired. Right hemisphere processing abnormalities have been observed in

individuals with schizophrenia during neuro-psychological testing, such as a

lateralised lexical decision task (Endrass et al., 2002; Evans & Schwartz, 1997;

Gastaldo et al., 2002; Lieb et al., 1996; O’Donnell et al., 2002) a two-pulse temporal

discrimination task (Schwartz, et al., 1984) backward masking tasks (Lieb et al.,

1996; Wynn, Light, Breitmeyer, Nuechterlein & Green, 2005). To determine

whether the slow binocular rivalry rates observed in individuals with schizophrenia

(see Chapters 3 and 4) can be attributed to dysfunction in the cortical hemispheres,

results for binocular rivalry were compared to task performance on the Benton’s

Judgment of Line Orientation (BJLO) task (Benton et al., 1978); the BJLO task is

widely accepted to be processed within the right cortical hemisphere.

The BJLO task (Benton et al., 1978) has most frequently been used to test the

presence of visuospatial abnormalities and right hemisphere dysfunction (Benton,

Hannay & Varney, 1975; Benton et al., 1978, Hamsher, Capruso & Benton, 1992;

Hannay, Varney & Benton, 1976; Treccani, Torri & Cubelli, 2005; Trahan, 1998).

Chapter 5: Benton’s Judgment of Line Orientation - An Indicator of Visuospatial

Ability in Schizophrenia

162 Chapter 5: Benton’s Judgment of Line Orientation - An Indicator of Visuospatial Ability in Schizophrenia

Benton, Hannay and Varney (1975) observed that right-handed, right-brain-damaged

individuals were poorer at line orientation tasks compared to their healthy

counterparts, with left-brain-damaged individuals performing no differently to

healthy controls. These data have been replicated in a number of studies and are

supported by neurophysiological studies in both brain-diseased and healthy adults

(Hamsher et al., 1992; Isaacs, Edmonds, Chong, Lucas & Gadian, 2003; Finton,

Lucas, Graff-Radford & Uitti, 1998; Ng et al., 2001). Imaging studies (fMRI) reveal

that performing judgments of line orientation activate the right ventral extrastriate

cortex (Deutsch, Bourbon, Papanicolaou & Eisenberg, 1988; Hamsher et al., 1992;

Hannay et al., 1976; Isaacs et al., 2003; Ng et al., 2001; Tranel, Vianna, Manzel,

Damasio & Graowski, 2009) and increased blood flow in the right tempro-occipital

region has been observed using blood-oxygen-level dependent BOLD fMRI

(Deutsch et al., 1988; Hannay et al., 1976; Finton et al., 1998). In contrast, one fMRI

study reported robust bilateral cortical activation of equal strength in both right and

left superior parietal lobes, suggesting that both hemispheres were involved

(Nurnberger et al., 2000). This was corroborated by lesion data. However, when

these authors analysed wavelet data they observed an earlier and stronger high-

frequency signal over the right parietal lobe (four times stronger than those recorded

from the left), suggesting the right lobe has a ‘priming’ effect in visuospatial

processing. More recently, Tranel et al., (2009) found defective performance on the

BJLO task to be associated with damage to the right posterior parietal region

(specifically, in the angular gyrus and posterior supramarginal gyrus) and

occipitoparietal region (specifically, extending into the lateral superior occipital

gyri). These findings, using detailed modern lesion analysis techniques, are

consistent with the traditional proposed hemispheric underpinning of the BJLO (e.g.


Benton et al., 1994). Cortical processing observed by fMRI during the BJLO tends is

hypothesised to reflect ‘dorsal stream’ processing systems, occurring within the

posterior sector of the supramarginal gyrus, generally related to spatial functions.

Tranel et al., (2009) suggests the BJLO task is thus as an ‘occipitoparietal’ test,

consistent with the dorsal ‘where’ visual processing stream. In summary, the BJLO

provides an indication of right hemisphere cortical processing and is a relatively pure

visuospatial task. A large body of evidence supports the right hemisphere being the

‘dominant’ or ‘preferred’ system for processing visuospatial information (Tranel et

al., 2009). It is noteworthy that no parietal activation was observed (with fMRI) in a

non-spatial visual perception task; the Facial Recognition Test (Benton & Van Allen,

1968), suggesting parietal lobe activation may be specific to visuospatial processing

(Nurnberger et al., 2000; Tranel,et al., 2009).

In this chapter, two experiments are described. The first being the

development of a computer version of the BJLO and data collection tool; the second

comparing BJLO performance in a group of individuals with schizophrenia

compared to a group of healthy control participants.

5.2 The Benton’s Judgment of Line Orientation Task

As described, the BJLO is a relatively pure visuospatial task. It requires

minimal motor involvement and has good validity and reliability (Benton, 1983;

Eden, Stein, Wood & Wood, 1996; Woodard et al., 1996). The BJLO is performed

under free-space viewing conditions; it is easily administered and has no time

restrictions (Benton, 1978; Benton, 1983). The task has a test retest reliability of r =

0.90 (Benton et al., 1978). Task performance has been associated with gender and

age; with performance declining with increasing age and females on average,

performing more poorly than males (Benton et al., 1978; Benton, 1983; Benton,


1994; Caparelli-Daquer, Oliveira- Souza & Filho, 2009). Population norms and

adjustments for group comparisons have been established. See Benton (1983) and

Benton (1994).

The BJLO task comprises 30 different items. Presented in the lower portion of

each item is a reference image comprising an array of lines numbered 1 through 11,

3.8 cm in length which are separated by an angle of 18 degrees arranged in a semi-

circular fashion around an imaginary locus (Benton et al., 1978). Above each

reference image a pair of stimulus black lines measuring 1.9 cm are drawn in a

position that represents the proximal, middle or distal half of one of the reference

lines appearing below. The task is to indicate (by number) the two lines in the

reference array that have the same angle and the same location as the two stimulus

lines (Figure 5.1 depicts an example of a test item).

5.2.1 Scoring the Benton’s Judgment of Line Orientation task.

5.2.1.1 Global score.

Performance on the BJLO is typically reported using global scores (a

maximum possible score of 30) (Benton, 1983). Benton, Varney and Hamsher

(1978) demonstrated that individuals with lesions in the right hemisphere had lower

global scores than those with lesions in the left hemisphere when using global scores.

Those with left hemisphere lesions showed a performance comparable to that of

healthy participants. It is expected that individuals with schizophrenia would

perform more poorly on the BJLO as visual abnormities observed in schizophrenia

are generally associated with right hemisphere dysfunction (Endrass et al., 2002;

Frecska, Symer, White, Piscanu & Kulcsar, 2004; Lee et al., 2005; McCourt et al.,

2008; O’Donnell et al., 2002; Park, 1999; Wynn et al., 2005).


Figure 5.1: An item from the Benton’s Judgement of Line Orientation (BJLO) task.

Note: The participant is required to identify the two lines from the 11-line array below that match the slope and thus orientation of the two line segments presented above.

However, the published data relating to BJLO task performance in schizophrenia are

inconsistent. Some studies report poorer BJLO performance in participants with

schizophrenia than control participants (Blanchard & Neale, 1994; Halari, Mehrotra,

Sharma, Ng & Kumari, 2006; Harody et al., 2004; Lee et al., 2005), whereas others

report similar performance (Fleming et al., 1997; Riley et al., 2000). In these studies

schizophrenia data are reported as global scores out of 30 (Benton et al., 1978), with

no further line- or error-type analysis reported. It is possible that a closer

examination of judgment of line-orientation performance may reveal diminished

performance associated with right hemisphere dysfunction, with more errors

resulting from left hemi-space lines (lines 1-5) and more horizontal and vertical line

errors.

Other clinical populations have successfully been separated from controls by

analysing line errors or error types in situations where between-group differences


were not observed when comparing global BJLO scores alone (Finton et al., 1998;

Montse, Pere, Carne, Francesc & Eduardo, 2001; Ska, Poissant & Joanette, 1990).

Differences in Alzheimer’s disease (Finton et al., 1998; Ska et al., 1990), Parkinson’s

disease (Montse et al., 2001) and alcohol-related disorders (Berman & Noble, 1995)

have been identified using alternative methods to analyse BJLO data. Using

alternative scoring systems, similar to those proposed by (Ska et al., 1990), may

prove more informative than global scores analysis reported in the schizophrenia

literature to date.

5.2.1.2 Error type.

Ska, Poissant and Yves (1990) devised a method of analysing BJLO data by

error type (see Table 5.1 for a detailed description). Based on the assumption that

line orientation is related to dysfunction of the right hemisphere, these authors

suggested it would be reasonable to expect that the cortical decline in normal ageing

would affect line orientation judgment task performance. They noted from previous

studies that normal ageing was associated with a moderate-but-steady decline in line

orientation performance (Eslinger & Benton, 1983; Eislinger, Damasio, Benton &

Van Allen, 1985). Ska, Poissant and Yves (1990) compared global BJLO scores in a

group of patients with dementia (Alzheimer’s disease) n = 11 with 95 healthy

volunteers divided into three groups according to age (55-64 years, 65-74 years and

75-84 years). Global BJLO scores revealed no significant differences between

groups. However, the analysis according to error type (described in Table 5.1)

separated those with dementia from normal aged individuals. Chi-square analyses

revealed significant differences in QO2 (an oblique confused with another oblique

different by two or three spacings of 18 degrees), QO4 (both oblique lines displaced

without maintaining the initial spacing) V (a vertical error involving an incorrect


identification of the vertical line numbered 6), H (a horizontal error involving an

incorrect identification of the horizontal lines numbered 1 or 11), IQOV (a combined

oblique inter-quadrant and vertical error involving the incorrect answer in

combination) and IQOH (a combined oblique inter-quadrant and horizontal error

involving the incorrect answer in combination ) error scores for the two groups; no

healthy control participants made errors in VH, IQOV and IQOH, whereas these

were common errors for participants with dementia. Ska, Poissant and Yves (1990)

concluded that when a V, H, IQOV or IQOH error occur, or more than two V, H, or

IQO1 occur in a participant without visual impairment, brain dysfunction may be

suspected. These results have since been replicated in other studies (Finton et al.,

1998; Simard, van Reekum & Myran, 2003) and similar findings, using this type of

analysis have been reported for Parkinson’s disease (Finton et al., 1998; Montse et

al., 2001).

5.2.1.3 Individual line errors.

Berman and Noble analysed individual line errors (a possible score of 60)

rather than BJLO item errors (a score of 30) (Berman & Noble, 1995). Correctly

identifying both lines in each item provides a measure of ‘local’ rather than ‘global’

visual information processing. Berman and Noble (1995) in examining the Taq 1A

polymorphism of the DRD2 receptor gene found that boys who were A1+ (A1/A1

and A1/A2 genotypes) made a higher proportion of errors on all lines compared to

those carrying the A1- (A2/A2 genotype). Thus A1+ participants were more

influenced by ‘local’ than ‘global’ details based on their total line error scores.

5.2.1.4 Hemi-space errors.

Berman and Noble (1995) also grouped lines according to hemi-space as a

measure of laterality differences between the groups, (left, lines 1-5 compared with


right, lines 7-11). Hemi-space differences were then compared according to allele

status. Generally A1+ participants made more errors for the lines presented in the

right hemi-space than the left, with significant between-group differences observed

for right hemi-space errors. In contrast Eden et al., (1996) analysed BJLO by using

hemi-space in a study to distinguish children with reading disabilities from poor

readers and normal readers. They found that children with reading disabilities

performed more poorly on lines presented in the left hemi-space compared to normal

and poor readers. Those with reading disabilities scanned the BJLO task from the

opposite direction (left to right) to that of normal readers (right to left).

5.3 Pilot Testing the Computer Version of BJLO and Alternative Scoring Systems

A computer version of the BJLO was developed along with a method of

collecting and scoring BJLO data that could easily be entered into a computer

database for analysis (see Appendix D for an example). A computer version of the

task was considered necessary for the current study as this allowed all visual data to

be collected using the same medium, under standard conditions (stimuli presented on

a computer screen under laboratory conditions). This allowed the researcher to be

confident that all tasks were performed using similar methods to those used in the

binocular rivalry and backward-masking tasks.


Table 5.1: Method of analysing Benton’s Line of Judgement Orientation (BJLO) results as per (Ska et al., 1990)

QO1 An oblique confused with another oblique different by only one spacing of 18

degrees

QO2 An oblique confused with another oblique different by two or three spacings of 18

degrees

QO3 Both oblique lines displaced by one or two spacings in the same direction respecting

the initial spacing

QO4 Both oblique lines displaced without maintaining the initial spacing

V A vertical error involving an incorrect identification of the vertical line numbered 6

H A horizontal error involving an incorrect identification of the horizontal lines

numbered 1 or 11

VH A vertical and horizontal error involving the simultaneous incorrect identification of

the vertical and one horizontal line

IQO1 Intra-quadrant oblique errors involving the displacement of one line from quadrant to

another quadrant

IQOV Combined oblique inter-quadrant and vertical error involving the incorrect answer in

combination (V + IQO)

IQOH Combined oblique inter-quadrant and horizontal error involving the incorrect answer

in combination (H + IQO)


5.3.1 Method.

5.3.1.1 Participants.

To confirm that the computer version of the BJLO yielded the same error rates

as a paper version, 14 right-handed healthy volunteers were recruited from available

staff at Royal Brisbane Hospital. Seven males and seven females, ranging in age

from 17 to 71 years (M = 41.6 years), who all had normal vision (two had spectacle-

lens-corrected vision) were presented with both the paper version and the computer

version of the task.

5.3.1.2 Procedure.

The computer version of the BJLO task was presented on a personal computer

monitor at a distance of one metre from the participant. The background luminance

was 1.398 cd/m2 (measured by Topcon BM7 Luminance Colorimeter, Japan). The

paper version, in booklet form, was placed on a table in front of the participant at a

distance of approximately 40 cm (comfortable working distance for the participant).

The 30 items comprising the BJLO were presented in the original prescribed

order for paper version of the test (1 through 30). However, the order of the items

presented in the computer version was altered to reduce the practice effect. The

order of BJLO tasks (paper or computer versions) was counterbalanced across the

participants to prevent potential order effects (that is, seven participants performed

the computer version first, and seven the paper version first). The task was performed

under free space viewing conditions with no time limit set for task completion.

To limit potential practice effects, each participant completed five practice

items prior to the commencement of the task. Participants were instructed to

verbally identify each line by identifying the corresponding number in the reference

diagram presented below. Verbal responses were recorded by the researcher onto a


data collection score sheet designed to enable BJLO data to be scored according the

three alternative scoring systems, that of (Benton et al., 1978; Ska et al., 1990:

Berman & Noble, 1995). This data recording system eliminated unnecessary motor

involvement or interruptions in concentration by the participant, providing the

researcher confidence that the results were purely related to visuospatial processing.

5.3.2 Results of pilot test

No significant difference between total number of errors were made by each

participant on the computer version of the BJLO task compared with the paper

version (257 and 256 respectively; t [32] = 0.50, p = .960). All participants obtained

global scores that were average or better (range 26-30), according to the scoring

system adopted by Benton et al., (1978), on both the computer and paper versions of

the BJLO.

All participants obtained normal error scores using the scoring system

developed by Ska, Poissant and Yves (1990) and had error scores consistent with

those found previously for healthy participants (Finton et al., 1998; Montse et al.,

2001; Ska et al., 1990). Participants made either QO1 errors (line confused with

another oblique line different by only one spacing of 18 degrees) or QO3 errors

(where both oblique lines are displaced one or two spacings in the same direction of

the initial spacing) which are not suggestive of a visuospatial abnormality (Ska, et

al., 1990). Participants made an average of 2.21 (SD = 1.88) QO1 errors on the

computer version of the BJLO compared with 1.64 (SD = 1.78) on the paper version

(t [26] = 0.467, p = .494) and 0.07 (SD = 0.267) QO3 errors on both the computer

and paper versions (t [26] = 0.00, p = 1.000).

Total number of line errors (a possible of 60 per participant), line number on

which these errors occurred (1 through 11), and hemi-space errors were not


statistically different between the computer and paper versions of the BJLO (p>.05).

All were within the range reported in control participants by Berman and Noble

(1995). A protocol incorporating all three systems of scoring (Appendix 4), a score

sheet and analyses were adopted for the major study investigating performance in

schizophrenia.

5.4 Study 4, Benton’s Judgment of Line Orientation in Participants with

Schizophrenia

Based on the neurophysiologic processes underlying BJLO (for example,

(Brown, 2009; Butler & Javitt, 2005; Cadenhead et al., 1998; Goodale et al., 1994;

Ng et al., 2001; Shapiro, Hillstrom & Husain, 2002) and results described in Chapter

4, it was predicted that participants with schizophrenia would demonstrate poorer

performance on the BJLO task compared to control participants. In addition, it was

predicted that performance for binocular rivalry magnocellular biased stimuli and

BJLO would be correlated.

5.4.1 Aims.

There were two aims of the study. The first aim was to compare performance

on a computer version of the BJLO, with respect to global scores (maximum possible

score 30), line segment scores (Benton et al., 1978), individual-line error scores,

hemi-space error scores (Berman & Noble, 1995), and line-type scores (Ska et al.,

1990), as an indicator of visuospatial ability in participants with schizophrenia

compared to healthy controls. The second aim was to compare BJLO scores with

binocular rivalry rates recorded using stimuli biased to magnocellular and

parvocellular visual pathways.


5.4.2 Method.


Twenty-five participants with schizophrenia were recruited to the study, 20

males and five females. Of the 25 participants 17 had participated in the study as

presented in Chapter 4; a further 8 participants were recruited from the outpatient

clinic at Royal Brisbane Hospital. All had a DSM-IV diagnosis of schizophrenia; 11

participants had a diagnosis of paranoid schizophrenia and 14 had undifferentiated

schizophrenia. Eleven participants had positive symptoms of schizophrenia, 11

negative and three had equal positive and negative symptoms (as assessed by the

PANSS). All participants with schizophrenia were taking a single dose of anti-

psychotic medication (four were taking Olanzapine, six Risperidone, seven

Clozapine, three Quetiapine and five were taking typical anti-psychotics); the mean

dose in chlorpromazine equivalents (CPZE) was 512 mg (SD = 286 mg).

5.4.2.2 Healthy control participants.

A total of 26 healthy control participants took part in the study.

Characteristics of participants are detailed in Table 5.2.

5.4.2.3 Procedures.

The BJLO computer-based task was performed as described in Section 5.4. All

participants were näive to the BJLO task and received the same instructions to

complete the task. Participants were asked to verbally report the position of two lines

by indicating the number of each line with respect to a reference array of lines

presented directly below (see Figure 5.1). The researcher recorded the responses on

the score sheet (see Appendix D). All participants completed five practice items

prior to the commencement of the BJLO task. The data from the practice items were

discarded.


Table 5.2: Age, gender, eye dominance and NART score of participants with schizophrenia and Controls.

Controls (n=26)

Schizophrenia(n=25)

χ2 df p

Age Mean (yrs) 35.9 35.6 Range 18-58 21-54 29.525 26 .288 Gender Male 8 20 Female 18 5 12.476 1 <.001 Eye Dominance R)eye 13 17 L)eye 13 8 1.705 1 .258 NART Score Mean 117.3 116.2 Range 102-124 96-125 26.118 20 .162



participants required to demonstrate a difference in BJLO performance scores

between participants with schizophrenia and healthy control groups. Data reported

in (Hardoy et al., 2004) were entered into the G*power3 program (Fual et al., 2007).

It was estimated that a sample size of approximately 11 in each group was required

for a two-sided 5% significance level and power of 80 to demonstrate a difference in

global BJLO performance scores in schizophrenia participants compared to healthy

controls.

As BJLO data was normally distributed an analysis of variance (one-way

ANOVA) was conducted. One-way ANOVA with ‘group’ as the dependent

variable, revealed significant differences between the groups with respect to gender

(F[1] = 16.213, p < .001); with greater males in the schizophrenia group. There were

no differences between the groups with respect to age (F [40] = 0.014, p = .907),

NART score (F [38] = 2.244, p = .142) or eye dominance (F [1] =1.695, p = .199).


One-way ANOVAs with ‘group’ as the dependent variable and global scores

and line error scores as independent variables (adjusted for gender as per Benton,

1983) were conducted to determine group differences between global scores (Benton

et al., 1978), individual line error scores, left and right hemi-space error scores

(Berman & Noble, 1995), and line type scores (Ska et al., 1990). Pearson’s

correlation coefficients were used to establish whether there was an association

between BJLO performance scores and binocular rivalry rates using stimuli that

biased the magnocellular and parvocellular pathways. The effect of DSM-IV

diagnosis and medication dose in the schizophrenia group on global score, line error

scores, line segment scores, and hemi-space errors was assessed. Due to the small

number of participants in each of these schizophrenia sub-groups the Chi Square (χ2)

statistic was used.

5.4.4 Results.

5.4.5.1 Global score analysis.

There was a significant between-group difference in BJLO correct global score

(out of a possible 30 points) (Benton, et al., 1978). Participants with schizophrenia

had lower average correct global scores on the BJLO task (ANOVA) than control

participants; M = 20.92 (SD = 5.6) compared with M = 25 (SD = 2.87) for

participants with schizophrenia and healthy control participants respectively (F[(1,

49] = 10.764, p = .002). When scores were adjusted for gender (as per (Benton,

1983), the overall difference increased as there were more females in the control

group; schizophrenia mean correct score was 21.48 (SD = 2.96) compared with 26.46

(SD = 2.96) for healthy control participants (F[1, 49] = 5.933, p < .001). As

adjustment for gender favoured the control group, increasing the already large effect,

further analyses regarding line and spatial errors were conducted using raw scores.


Unlike previously-reported data (Benton et al., 1978; Benton, 1994; Caparelli-

Daquer et al., 2009), age, gender, NART score and eye dominance had no effect on

global BJLO scores; age F(26, 24) = 0.785, p = .727, gender F(1, 49) = 0.563, p

=.457, NART score F(20, 22) =1.602, p = .142, and eye dominance F( 1, 49) =

1.116, p = .296.

Medication dose, DSM-IV diagnosis and symptom ratings (PANSS) had no

effect on BJLO global scores in the schizophrenia group; (F = 0.333, df = 13, p =

.968, F = 2.13, df = 13, p = .108, F = 0.776, df = 13, p = .670, respectively).

5.4.5.2 Error type analysis.

Significant between-group differences were observed for QO1 errors (F [1, 49]

= 6.515, p = .014) and (H) horizontal errors (F[1, 49] = 4.163, p = .047) (Ska et al.,

1990). Although no other error type reached significance, participants with

schizophrenia generally made more QO2 and QO4 errors than controls (F[1, 49] =

3.232, p = .078, and F[1, 49] = 3.012, p = .089 respectively). Only participants with

schizophrenia made V, H, 1QOV and 1QOH errors (as reported for participants with

Alzheimer’s disease (Ska et al., 1990) and Parkinson’s disease (Montse et al., 2001).

5.5.5.3 Line error analysis.

Analyses with respect to line errors, with a maximum score out of 60 (Berman

and Noble, 1995), revealed significant group differences; schizophrenia M = 48.60,

SD = 8.91) correct responses, control participants M = 54.31, SD = 3.53, F(1, 49) =

9.183, p = .004. Analyses of individual lines revealed significant group differences

in error scores for Line 2, F(1, 49) = 4.294, p = .044, Line 3, F(1, 49) = 11.746, p =

.001, Line 4, F(1, 49) = 7.043, p = .011, and Line 9, F(1, 49) = 5.582, p = .022. No

errors were made for Lines 1 and 6 in either group.


5.5.5.4 Hemi-space analyses.

To explore possible laterality differences, separate line analyses of left hemi-

space (Lines 1-5) and right hemi-space (Lines 7-11) (Berman & Noble, 1995) were

undertaken. There were significant group differences in both left and right hemi-

space error scores. Participants with schizophrenia had lower scores in both hemi-

spaces; left hemi-space mean errors, schizophrenia M = 5.0, SD = 3.81, controls M =

2.12, SD = 1.56, F(1, 49) = 12.72, p = .001; right hemi-space errors, schizophrenia M

= 6.2, SD = 4.8, controls M = 3.54, SD = 2.6), F(1, 49) = 6.12, p = .017. Participants

with schizophrenia made significantly more errors in the right hemi-space (M = 6.2,

SD = 4.8) compared to the left hemi-space (M = 5.0, SD = 3.8) t (24) = -2.502, p =

.02. See Tables 5.3 and 5.4 for a summary of the results.

5.5 Association between Benton’s Judgment of Line Orientation and binocular

rivalry

Significant negative correlations between binocular rivalry rate for the

magnocellular biased stimulus condition and BJLO global scores (rho =-0.471, n =

17, p = .056), and line error scores (rho = -0.483, n = 17, p = .05) were observed in

participants with schizophrenia (non-parametric correlations (spearman’s rank order

- rho) were used as binocular rivalry data was not normally distributed). However,

no correlations between binocular rivalry rates elicited by parvocellular biased

stimuli and global BJLO scores were observed in the group with schizophrenia. No

correlations were found between binocular rivalry rates (magnocellular biased and

parvocellular biased) and BJLO global scores and line error scores in control

participants (see Table 5.4).


5.6. Global score

Based on the neurophysiological processes underlying BJLO (Brown, 2009:

Butler & Javitt, 2005; Cadenhead et al., 1998; Goodale et al., 1994; Ng et al., 2001;

Shapiro et al., 2002) and results described in Chapter 4, it was predicted that

participants with schizophrenia would demonstrate poorer performance on the BJLO

task compared to healthy participants. Consistent with these predictions, participants

with schizophrenia had significantly lower BJLO global performance scores than

participants without schizophrenia (Benton et al., 1978). These data are consistent

with previous studies in participants with schizophrenia (Blancharf & Neale, 1994;

Halari et al., 2006; Hardoy et al., 2004; Lee et al., 2005: Silver & Goodman, 2008).

The significant differences in global BJLO performance between participants

with schizophrenia and controls observed in this study are consistent with processing

in the right (and possibly left) hemisphere involving the superior parietal lobes right

temporo-occipital region (Benton et al., 1975; Benton et al., 1978; Deutschm et al.,

1988; Hamsher et al., 1992; Isaacs et al., 2003; Hannay et al., 1976; Treccani et al.,

2005; Trahan, 1998; Ng et al., 2001). Low BJLO scores (< 19) have been most-

frequently associated with right hemisphere dysfunction (Benton et al., 1975; Benton

et al., 1978; Deutsch et al., 1998; Hamsher et al., 1992; Hannay et al., 1976; Treccani

et al., 2005; Trahan, 1998; Ng et al., 2001).


Table 5.3: Benton’s Judgement of Line Orientation (BJLO) data for control participants and participants with schizophrenia: mean global scores (out of 30 and 60), line error scores and hemi-space errors for the BJLO task.

Controls

Schizophrenia

ANOVA (n = 26) (n = 25)

M SD. M SD df F p

Benton (1978)

Global Score

(30) 25 2.87 20.92 5.63 1 10.76 .002*

Berman & Noble (1995).

Total line

errors (60) 54.31 3.53 48.60 8.91 1 9.183 .004*

Line 1 0 0 0 0 1 - -

Line 2 0.23 0.43 0.84 1.43 1 4.294 .044*

Line 3 0.69 0.88 1.76 1.30 1 11.84 .001*

Line 4 0.88 0.99 1.68 1.14 1 7.043 .011*

Line 5 0.27 0.45 0.44 0.71 1 1.054 .310

Line 7 0.23 0.43 0.68 1.18 1 3.312 .075

Line 8 1.77 1.37 2.44 1.83 1 2.216 .143

Line 9 1 1.06 1.88 1.56 1 5.582 .022*

Line 10 0.58 1.14 1.12 1.64 1 1.899 .174

Line 11 0.08 0.27 0.28 0.68 1 1.999 .164

L Hemi-space

Lines 1 -5 2.12 1.56 5.00 3.81 1 12.72 .001*

R Hemi-space

Lines 7 - 11 3.54 2.6 6.20 4.80 1 6.12 .017*

Note: * Indicates p < .05 significance (two tailed).


Table 5.4: Benton’s Judgement of Line Orientation (BJLO) data for healthy control participants and participants with schizophrenia: error type in the BJLO task

Controls Schizophrenia

ANOVA (n = 26) (n = 25)

M SD. M SD df F p

Ska et al., (1990).

QO1 4.04 2.49 5.96 2.49 1 6.515 .014*

QO2 0.23 0.81 0.80 1.38 1 3.232 .078

QO3 0.54 0.86 1.08 1.63 1 2.225 .142

QO4 0.12 0.37 0.68 1.63 1 3.012 .089

V 0 0 0.8 4.0 1 1.041 .313

H 0 0 0.20 0.50 1 4.163 .047*

IQO1 0.04 0.19 0.32 1.41 1 1.023 .317

IQOV 0 0 0.08 0.40 1 1.041 .313

IQOH 0 0 0.08 0.40 1 1.041 .313

Note: * Indicates p < .05 significance (two tailed).

In addition, it was predicted that performance would be correlated for binocular

rivalry magnocellular biased stimuli and BJLO. This association supports the notion

that the dorsal stream influences the rate of alternation of perceptual images in

binocular rivalry, thus supporting the notion of ‘bottom up’ visual processing (Butler

et al., 2007). Although this is a simplistic view, as there is much interaction between

the magnocellular and parvocellular pathways with the dorsal and ventral streams

each receiving inputs from both pathways (Goodale & Milner, 1992; Shapley, 1990;

Shapiro et al., 2002), these data add to a large body of work that demonstrates

functional and behavioural divisions for processing spatial relationships and object

recognition (Brown, 2009; Butler & Javitt, 2005; Cadenhead et al., 1998; Goodale et

al., 1994; Popken, Bunney, Potkin & Jones, 2000). Furthermore, characteristic

visuospatial deficits in schizophrenia are largely attributed to the magnocellular or


dorsal stream (Cadenhead et al., 1998; Doinger et al., 2002; MClure, 2001; Schechter

et al., 2003).

Table 5.5: Correlations between global Benton’s Judgement of Line Orientation (BJLO) scores and binocular rivalry (BR) rates for stimuli that bias the BR task for either the magnocellular or parvocellular visual pathways (spearman rank order).

BR rate - Magnocellular

Stimuli

BR rate - Parvocellular

Stimuli

rho p n rho p n

Control participants

Global scores (30) 0.183 .426 21 0.360 .109 21

Line error scores (60) 0.181 .432 21 0.411 .064 21

Schizophrenia Participants

Global scores (30) -0.502 .04* 17 -0.282 .257 17

Line error scores (60) -0.483 .05* 17 -0.312 .207 17

Note. * Indicates p < .05

The findings of other studies indicate that participants with schizophrenia have

abnormalities in one (or both) of these visual pathways (Brown, 2009; Butler &

Javitt, 2005; Cadenhead et al., 1998; Doinger et al., 2002; Goodale et al., 1994;

McClure, 2001; Popken et al., 2000;Schechter et al., 2003) and one (or both) of the

cerebral hemispheres (Endrass et al., 2002; Evans & Schwartz, 1997; Frecska, Symer

et al., 2004; Gastaldo et al., 2002; Levander et al., 1985; McCourt et al., 2008; Narr,

Green, Capetillo-Cunliffe, Toga & Zaidel, 2003; O’Donnell et al., 2002; Park, 1999;

Schwartz et al., 1984; Wynn et al., 2005). Data presented in Chapter 4 of this thesis

provides further evidence for this position.


5.7.1.1 Error type.

Significant between-group differences were observed for QO1 errors

suggestive of poorer overall global processing in schizophrenia. Although no other

error type reached significance, participants with schizophrenia generally made more

QO2 and QO4 errors than controls. A previous study noted that QO2 and QO4

errors distinguished participants with dementia from controls (Ska et al., 1990), thus

some degeneration of cortical visual processing may occur in Schizophrenia. Only

participants with schizophrenia made V, H, 1QOV and 1QOH errors, consistent with

previous reports in Alzheimer’s disease (Simard et al., 2003; Ska et al., 1990) and

Parkinson’s disease (Montse et al., 2001). Ska et al., (1990) suggest that a

participant without primary visual impairment may be suspected to have some brain

dysfunction when type VH, 1QOV, or 1QOH errors occur, or more than two, type V,

H or 1QO1 errors occur. Two participants with schizophrenia made errors that

would indicate some form of brain dysfunction consistent with the position made by

(Ska et al., 1990); one participant with schizophrenia made two H and two 1QOH

errors, and another made two 1QOH errors and seven 1QO1 errors.

It is generally agreed that the visuospatial abnormalities elicited by the BJLO

task observed in ageing populations, such as Alzheimer’s and Parkinson’s Disease,

are related to dopamine depletion (Finton,et al., 1998; Montse et al., 2001; Ska et al.,

1990). Participants with Parkinson’s disease, a condition where reduced dopamine is

neuropathological, are reliably separated from normal participants with the BJLO

task. Schizophrenia is also considered to be a disease related to dopamine, with

many authors suggesting schizophrenia to be a hyper-dopaminergic disorder

(Hirvonen et al., 2005; Seeman & Kapur, 2000). It would be reasonable to assume


that specific intra-quadrant errors on the BJLO task made by participants with

schizophrenia were indicative of dopamine related visuospatial abnormalities.

5.7.1.2 Hemi-space.

Participants with schizophrenia made significantly more errors in each hemi-

space than did healthy controls. These results are consistent with a large body of

work indicating overall visual abnormalities in schizophrenia related to hemi-space

presentation of visual data to stimulate the left and right visual hemispheres. Deficits

in left and right hemispheric visual processing in schizophrenia have been noted in a

variety of visual tasks associated with spatial perception and attention (O’Donnell et

al., 2002), sustained attention (Evans & Schwartz, 1997) selective attention

(Holzman, 1987) working memory, (Park, 1999), and detecting visual information

(Schwartz et al., 1994).

Participants with schizophrenia in this sample made significantly more right

hemi-space errors compared to left, however control participants also made more

right than left hemi-space errors. Right hemi-space errors are generally processed by

the left hemisphere, and this is opposite to the hemisphere thought to be typically

most effected in schizophrenia. However, it should be noted that significant

differences were found between the groups for Lines 2, 3 and 4, which are left hemi-

space presentations and only one of right hemi-space presentation, Line 9. The

results reported here support the notion that visuospatial information is processed

within each cortical hemisphere. Tranel et al., (2009) make the point that although

the BJLO is considered to be subjected to predominantly processing in the right

hemisphere, fMRI and lesion studies also indicate some left hemisphere

involvement. There is a large body of evidence to support the right hemisphere

being the ‘dominant’ or ‘preferred’ system for processing visuospatial information.


5.7.2 Potential Impact of BJLO Performance

5.7.2.1 Age and gender.

The results recorded by controls were within previously established population

norms (Benton, 1983). No age or gender effects were seen on global performance

scores or individual line and line spacing errors in this study, although age and

gender have been reported to impact on BJLO in previous studies (Collaer & Nelson,

2002; Montse et al., 2001; Woodard et al., 1998). Normative standards of

performance for the BJLO for age and sex have been established by Benton and

correcting global scores for age and gender increases these group differences further

(Benton, 1983). Interpreting BJLO performance data on the basis of age and gender

is limited as age- and sex-matched samples were not used in this study.

5.7.2.2. Medication effects.

The type of anti-psychotic medication taken and anti-psychotic dose, based on

CPZEs had no effect on BJLO scores in participants with schizophrenia. These data

are consistent with other studies reporting no medication effect on BJLO

performance (Buchanan, Holstein & Breier, 1994; Halari et al., 2006; Riley et al.,

2000; Sweeney, Hass, Keilp & Long, 1991). Double-blind studies have also observed

that BJLO performance was not different in participants with schizophrenia either

after twelve weeks of treatment with Clozapine or Haloperidol, or after twelve

months of treatment with Clozapine (Buchanan et al., 1994).

5.7.2.3 Schizophrenia sub-types and symptom ratings.

Schizophrenia sub-types (whether the participant had paranoid schizophrenia

or undifferentiated schizophrenia) and symptomology (negative or positive

schizophrenia measured by PANSS) had no effect on BJLO scores. This was

expected as BJLO performance has been found not to be related to the symptoms of


schizophrenia (Buchanan et al., 1994; Riley et al., 2000). Furthermore, all the

participants with schizophrenia in this cohort were relatively stable on current

medication and living in community settings. Greater differences may have been

seen in a more symptomatic cohort of participants.

5.7.2.4 Cognitive ability.

It may be that differences in BJLO performance scores are related to general

cognitive decline in schizophrenia (Fleming et al., 1997; Halari et al., 2006; Lee et

al., 2005; Trahan, 1998). It is unlikely that the differences in BJLO are attributed

solely to cognitive ability as NART (a measure of pre-morbid cognitive functioning)

scores were not found to be significantly different between the two groups in this

sample (as found in the previous chapters).

5.7.3 Comparing Benton’s Judgment of Line Orientation with Binocular Rivalry

Significant negative correlations between binocular rivalry rate in the

magnocellular stimulus condition and BJLO global scores were found only in

participants with schizophrenia. This faster binocular rivalry rate in participants with

schizophrenia was associated with fewer BJLO errors. In the previous three

chapters, a slower binocular rivalry rate was demonstrated over a range of stimulus

conditions in participants with schizophrenia, which has been interpreted as an

abnormal binocular rivalry rate. Taking this together with the results of the current

chapter suggest that this slower binocular rivalry rate is an indication of reduced

visuospatial ability in schizophrenia largely attributable to magnocellular processing

or functions of the dorsal visual pathway (Butler & Javitt, 2005; Doniger et al., 2002;

McClure, 2001; Schechter et al., 2003). In participants with schizophrenia, no

significant correlations were evident between binocular rivalry rates elicited by

parvocellular binocular rivalry stimuli, perhaps suggesting that ventral visual


processing was not a feature of binocular rivalry. However, this is unlikely as slow

binocular rivalry rate and abnormal backward-masking performance were observed

in schizophrenia when using stimuli that biased the parvocellular pathways in the

previous chapter. Previous published studies (Brown, 2009; Butler & Javitt, 2005;

Cadenhead et al., 1998; Doniger et al., 2002; Goodale et al., 1994; McClure, 2001;

Popken et al., 2000; Schechter et al., 2003) also indicate that participants with

schizophrenia have abnormalities in one (or both) of these visual pathways and one

(or both) of the cerebral hemispheres (Endrass et al., 2002; Evans & Schwartz, 1997;

Ferecska, Symer et al., 2004; Gastaldo et al., 2002; Levander et al., 1985; McCourt,

et al., 2008; Narr et al., 2003; O’Donnell et al., 2002; Park, 1999; Schwartz et al.,

1984; Wynn et al., 2005).

5.7.4 Cortical Pathway and Hemispheric Models of Involvement

5.7.4.1 Dorsal and Ventral Pathways

No association was found between binocular rivalry rates for both the

magnocellular or parvocellular biased tasks and BJLO global or hemi-space scores in

control participants. To be confident that binocular rivalry rate was attributable to

processing via the dorsal stream it would be expected that binocular rivalry rates

elicited from magnocellular binocular rivalry stimuli would also correlate with BJLO

global scores in these participants. This lack of correlation must therefore be

interpreted cautiously. Although the ventral stream receives some magnocellular

input, the magnocellular pathway provides the dominant initial input to the dorsal

necessary for processing movement and spatial location information; the prominent

feature of the dorsal stream (Brown, 2009). Moreover, it has been noted using brain

mapping techniques that the normal adult dorsal stream in humans has additional

intra- and inter-hemispheric connections (Loenneker et al., 2010). Dorsal fibres


penetrate into contralateral hemispheres via commissural structures and projection

fibres that extend to the superior temporal gyrus and ventral association pathways,

with intra-hemispheric connectivity being particularly strong in the dorsal stream of

the right hemisphere (Loenneker et al., 2010). If binocular rivalry is subject to

magnocellular or dorsal stream processes, it is conceivable that the slow binocular

rivalry rate in schizophrenia may be related to the slow exchange of visuospatial

information from one hemisphere to the other.

As stated previously, the BJLO is considered a task involving predominantly

right cortical hemisphere processes. Performance on the BJLO in individuals with

schizophrenia was poorer than in control participants, suggesting abnormal

processing of the ‘Where is it?’ system, the magnocellular pathway/dorsal stream.

Although it is likely the parvocellular or ventral system is also involved in binocular

rivalry. The results presented in Chapter 4 and in the current chapter suggest that the

magnocellular or dorsal stream plays a prominent role in visuospatial processing in

schizophrenia. Binocular rivalry may therefore be reliant on intact magnocellular or

dorsal systems, with abnormalities slowing the alternation between opposing

perceptual images.

5.7.4.2 The Cortical Hemispheres

Poorer performance on BJLO task was suggestive of impaired right hemisphere

processing in schizophrenia. Individuals with schizophrenia also performed more

poorly in binocular rivalry tasks. Rather than an ‘inter-hemispheric switch’ driving

binocular rivalry (Funk & Pettigrew, 2003; Miller et al., 2000; Miller, 2001;

Pettigrew & Miller, 1998), it may be that interactions between magnocellular (or

dorsal stream) and parvocellular (or ventral stream) processing spatial and temporal

information from the rival stimuli within the hemisphere drive binocular rivalry.


Prefrontal cortical involvement is not necessary to generate binocular rivalry,

suggesting this is a locally-driven process resolved ‘lower down’ in the visual

pathway within each hemisphere (Calle-Inclan & Gallego, 2006). Interaction

between the ventral and dorsal streams lower in the visual pathways would explain

why binocular rivalry is able to occur in split-brain observers (O’Shea, Corballis,

2005b; O’Shea & Corballis, 2003).

5.6 Conclusion

A significant difference was measured between participants with schizophrenia

and control participants in BJLO global scores (Benton et al., 1978; Berman &

Noble, 1995), individual line error scores, line segment scores (Berman & Noble,

1995), hemi-space error scores (Benton et al., 1978), and line type scores (Ska et al.,

1990). These data suggest overall abnormalities in visuospatial ability in participants

with schizophrenia. Cognitive ability (measured by the NART), age, medication

dose, DSM-IV diagnosis and symptom ratings (PANSS) had no effect on BJLO

global scores, line error scores, line segment scores, and hemi-space errors in the

schizophrenia group, suggesting that the abnormalities demonstrated are due to

visuospatial processing in schizophrenia. Visuospatial processing is considered to be

predominantly processed by structures within the right cortical hemispheres,

involving the magnocellular or dorsal pathway systems. These results are consistent

with previous studies in schizophrenia.

These results presented in this chapter, considered together with the results of

the previous chapter, indicate that the binocular rivalry may be initiated by

competition between the magnocellular and parvocellular pathways within (rather

than between) each cortical hemisphere. If this is the case the mechanisms involved

in binocular rivalry would be distributed throughout the visual hierarchy. Abnormal


binocular rivalry rate thus indicating processing and information transfer

abnormalities at all levels of visual processing (i.e. involving occipital, parietal,

temporal and frontal cortical structures). It is pertinent to investigate the role that

neurotransmitters would have in these processes.

The neurotransmitter most frequently associated with schizophrenia is

dopamine. Given that dopamine is also responsible for moderating many functions

within the visual system, it is reasonable to expect that some of the visual

abnormalities seen in schizophrenia, and perhaps binocular rivalry to be associated

with dopamine. In the following chapter (Chapter 6), the role of dopamine in visual

processing is examined.

Chapter 6: Taq1 allele of the DRD2 dopamine receptor gene, binocular rivalry, visual backward masking and Benton’s Judgment of Line Orientation 190

6.1 Dopamine in Vision

It is well established that dopamine plays a role in human visual processing

(Brandies & Yehuda, 2008; Bodis-Wollner, 2009; Djamgoz, Hankins, Hirano &

Archer, 1997; Masson et al., 1993; Witovsky, 2004). Many patients with

Parkinson’s disease, a disorder of diminished dopamine function are demonstrated to

have abnormal VEPs, and therapy with dopamine precursors has been shown to

improve the evoked potentials (Bodis-Wollner, 1997). Conversely, drugs with

dopamine-blocking properties delay the normal VEPs in sufferers of schizophrenia

(Bodis-Wollner, 1988). Using animal models (monkeys), when VEPs were

measured pre- and post-administration of sulpiride (a dopamine D2 antagonist), the

P100 component of the VEP decreased, while the amplitude of the cognitive P300

component decreased (Antal, Keri & Bodis-Wollner, 1997). This suggests that D2

receptors play a major role in visuo-cognitive processes in dopamine-related

conditions, such as Parkinson's disease and schizophrenia. The progressive loss of

colour discrimination and contrast sensitivity in Parkinson’s disease (Crevits, 2003;

Diederich, Raman, Leurgans & Foetz, 2002; Zahodne & Fernandex, 2008) that

occurs with depletion of dopamine receptors in the retina and visual pathways with

age has also been suggested to be due in part to D2 depletion.

Animal models have provided evidence that density and frequency of D2

dopamine receptors found in the retina and primary visual pathway are similar to

those in the primate striate cortex (Djamgoz et al., 1997; Schorderet & Nowak, 1990;

Witkovsky, 2004). Therefore, a better understanding of function of dopamine and

D2 receptors in the retina and striatum provides a unique opportunity to examine

Chapter 6: Taq1 allele of the DRD2 dopamine receptor gene, binocular rivalry, visual

backward masking and Benton’s Judgment of Line Orientation


neurotransmitter involvement in visual neurocognitive processing along the visual

pathways (Bodis-Wollner & Antal, 1995).

6.1.1 The A1 allele of the DRD2 receptor gene.

Given this interest in D2 receptors within the visual system, and that

schizophrenia has been associated with abnormal D2 receptor density and

functioning, it is plausible to examine visual processing according to genetic

variations in D2 receptors. Dopamine receptor genes that have commonly been

investigated in neuropsychiatric diseases, including schizophrenia, include DRD2,

DRD3 and DRD4 receptor genes and their polymorphisms (Talkowski, Bamme,

Hader & Nimgaonkar, 2007; Ohara, 1996). The TaqI A of dopamine D2 receptor

(DRD2) gene is a commonly investigated gene in schizophrenia (Behravan,

Hemayatkar, Toufani, & Abdollahian, 2008), with data available relating to

functional interactions of the gene (Matsumoto et al., 2005: Mihara et al., 2003),

making it a promising genetic variant to explore. The TaqI A of dopamine D2

receptor (DRD2) gene has been mapped to an adjacent kinase gene and is also

sometimes referred to as ANKK1.

Carriers of TaqI A of dopamine D2 receptor (DRD2) gene (A1+ individuals

with A1/A1 or A1/A2 genotypes) typically have a lowered DRD2 density and

diminished function of DRD2 in the striatum, (Kondo et al., 2003; Mihara, Kondo et

al., 2000; Nobel, 2000). The human dopamine D2 receptor gene (DRD2) has been

posited as a candidate gene for neuro-psychiatric disease (Finckh et al., 1996; Noble,

2000; Noble, 2003). This has been associated with Tourette's syndrome, post-

traumatic stress disorder (PTSD) and certain symptoms associated with affective

disorders and schizophrenia, Parkinson's disease and iatrogenically-induced

movement disorders (Noble, 2000). It is hypothesised that the DRD2 is a

192Chapter 6: Taq1 allele of the DRD2 dopamine receptor gene, binocular rivalry, visual backward masking and Benton’s Judgment of Line Orientation

reinforcement or reward gene, as variants of the DRD2 gene have been associated

with addictive disorders, including alcoholism (Blum et al., 1991; Blum et al., 1993),

cocaine, nicotine and opioid dependence (Laruelle, Gelenter & Innis, 1998; Noble,

2003; Young, Lawford, Nutting & Noble, 2004) and obesity (Noble, 2003).

The A1 allele of the DRD2 gene has been found in post-mortem studies to be

over represented in patients with schizophrenia (Noble, 2000; Noble, 2003).

However association studies in schizophrenia generally show no relationship

(Behravan, Hemayatkar, Toufani & Adbollahian, 2008; Suzuki, Kondo et al., 2000;

Parsons et al., 2007; Ohara et al., 1996; Kishida et al., 2003), suggesting the A1

allele acts as a modifying gene in schizophrenia rather than being of primary

aetiological significance (Comings et al., 1991).

A1+ individuals generally have more symptoms of schizophrenia (Ohara et al.,

1996; Sanjuan et al., 2004) and are at greater risk of significant adverse effects

(Alenius et al., 2008; Kaiser, Tremblay, Klufmoller, Roots & Brookmoller, 2002).

They tend to suffer more extra-pyramidal symptoms (Guzey, Scordo, Spina,

Landsem & Spigset, 2007; Mihara, Suzuki et al., 2000, Kaiser et al., 2002;

Hedenmalm, Guzey, Dahl, Yue & Spigset, 2006; Young, Lawford et al., 2004), and

are more at risk of tardive dyskinesia (Chen, Wei, Koong & Hsiao, 1997), polydipsia

(Matsumoto, et al., 2005) and neuroleptic malignant syndrome (Mihara et al., 2003;

Suzuki et al., 2001). These findings have been confirmed in most studies. Mihara et

al., (2000) found that A1+ female patients were at greater risk of developing

neuroleptic-induced hyperprolactinemia, and had increased serum prolactin when

treated with bromocriptine (a dopamine agonist) (Mihara, Kondo et al., 2000; Mihara

et al., 2001).


Although A1+ individuals with schizophrenia tend to experience more adverse

effects, the general consensus is they also tend to have more favourable responses to

medication (Schargetter, 2004). A1+ individuals show greater improvement in total

Brief Psychiatric Rating Scale (BPRS) scores and in positive symptoms with anti-

psychotic treatment (Suzuki, Mihara et al., 2000). A1+ individuals are also more

likely to benefit from anti-psychotics with weaker dopamine D2 receptor

antagonistic properties (Alenius et al., 2008).

Investigations into the effect of anti-psychotic medications in schizophrenia in

the presence of the A1 allele indicate that this polymorphism may modify the

efficiency of DRD2 antagonism of the drugs in the central nervous system (Suzuki,

Mihar, et al., 2000). Higher serum prolactin levels, as an indicator or dopamine D2

receptor blockade (Cotes et al., 1977; Gruen, 1978; Seeman, 2002), have been found

in A1+ carriers with schizophrenia receiving anti-psychotic medications compared to

those without. Furthermore, A1 + individuals were over-represented in those with

hyperprolactinemia (Young, et al., 2004).

In disorders associated with depleted dopamine, for example Parkinson’s

disease, the Taq1 A polymorphism has been investigated (Bartres-Faz et al., 2007;

Oliveri et al., 2000). Researchers investigating this gene in Parkinson’s disease

propose that the genetic variation in the DRD2 gene influences the risk of developing

Parkinson’s disease, and therefore is a susceptibility locus for Parkinson’s disease

(Oliveri et al., 2000; Grevle et al., 2000), rather than a modifying gene. However,

imaging (fMRI) studies have revealed that larger networks of bilateral cerebral areas,

including cerebellar and pre-motor regions, are involved in complex sequential motor

tasks in A1+ individuals with Parkinson’s disease than A1- individuals, regardless of

medication treatment (Bartres-Faz et al., 2007). This is more suggestive of a trait-


like feature, rather than a modifying effect of the allele. Furthermore, the presence of

the A1 allele had no significant impact on the efficacy of Pramipexole in treating

patients with Parkinson’s disease (Liu et al., 2009), again suggesting a trait-like

feature. In other memory-impaired older adults, for example those with Alzheimer’s

disease, the A1- Status has been associated with diminished cognitive performance

and increased atrophy in the striatum (Bartres-Faz et al., 2002). However, while the

A1 allele of the DRD2 receptor gene may be a trait marker for Parkinson’s disease, a

larger amount of evidence suggests that this gene acts as a modifying gene in

schizophrenia.

6.1.2 The A1 allele of the DRD2 receptor in vision.

The A1 allele may have a moderating effect on visuospatial processing in

schizophrenia. Berman and Noble (1995) reported significantly-reduced visuospatial

performance in children with the A1 allele of the D2 dopamine receptor (DRD2)

gene. A1 + boys made more errors than A1- boys (Berman & Noble, 1995; Berman

& Noble, 1997), whereas A1- boys showed latency in the P300 wave of VEPs

(Berman et al., 2006). Girls with the A1+ status have demonstrated poorer

visuospatial functioning than that of boys with the A1+ status (Berman et al., 2003).

Because no statistically significant association between the A1 allele and IQ has been

demonstrated (Petrill et al., 1997), these authors suggest that the DRD2 receptor gene

association is specific to visuospatial performance and independent of general

cognitive ability.

The Taq 1A polymrphism of the DRD2 dopamine receptor gene therefore

provides a putative model to investigate whether the differences in binocular rivalry

rate and poorer performance on VBM and BJLO tasks in the group of schizophrenia

subjects, compared with healthy controls.


6.2 Aims

The primary aim of this study was to determine whether DRD2 Taq 1A status

was associated with binocular rivalry, backward masking and BJLO tasks

performance. The second aim is to determine whether A1+ (A1A1 and A1A2

genotype) participants with schizophrenia performed more poorly on binocular

rivalry, backward masking and the BJLO tasks than those participants with

schizophrenia with A1- (A2A2 genotype) status.

6.3 Method

6.3.1 DNA collection and extraction.

Participants were asked to provide 2 mls of saliva for DNA extraction. Saliva

samples were collected using an Oragene.DNA® (DNA Genotek, Ontario, Canada)

collection tube. Collection tubes were stored at room temperature until the DNA was

extracted as per the manufacturer’s instructions.

Genomic DNA was extracted employing standard techniques and used as a

template for determination of Taq1 A DRD2 alleles by the polymerase chain reaction

(Grandy, Zhang & Civelli, 1993). A Perkin Elmer GeneAmp 9600 Thermocycler

was used in the amplification of DNA. Approximately 500 mg of amplified DNA

was digested with five units of Taq1 restriction enzyme (New England Biolabs) at

65oC overnight. The resulting products were separated by electrophoresis in a 2.5%

agarose gel containing ethidium bromide and visualized under ultraviolet light. The

Taq1 A DRD2 alleles were identified as described in Lawford, et al., (2005). Three

genotypes were obtained. The A1A2 genotype was revealed by three fragments: 310,

180 and 130 base pairs (bp), the A2A2 genotype was shown by two fragments: 180

and 130 bp and the A1A1 genotype was revealed by the uncleaved 310 bp fragment.


As noted, A1+ allele participants have either A1A1 or A1A2 genotypes whereas the

A1- participants have only the A2A2 genotype.

6.3.2 Participants.

Thirty-three control participants were recruited to participate in the study (20

participated in the study described in Chapter 2, of these 14 participated in the study

described in Chapter 3, with a further six participants recruited specifically for the

current study). Seven further participants were recruited to the current study from

the study detailed in Chapter 4. Of these, 29 provided a saliva sample and four

declined to provide a sample. One participant’s DNA sample had degenerated (due

to a compromised seal on the collection tube) so their DNA was unable to be

amplified.

Twenty-five participants with schizophrenia were recruited to the study.

Twenty participants completed the study described in Chapter 3, of these 17 provided

a sample of salvia for DNA extraction and three refused. A further five participants

were recruited to the studies detailed in Chapters 4 and 5, however only one

additional saliva sample was obtained; the four remaining participants did not

consent to DNA extraction.

Genotype and allelic information were available for 46 participants (18 with

schizophrenia and 28 controls). DNA data were not available for seven participants

with schizophrenia and five healthy subjects. The participants who did not provide

DNA did not differ to the larger group with respect to age, gender, dominant eye or

NART scores (Mann-Whitey U, p > .05).


6.3.2.1 Control participants who participated in the binocular rivalry tasks in

Study 1.

Of the 20 control participants who participated in Study One (Chapter 2) 16

were genotyped for the presence of the A1 allele of the DRD2 receptor gene; five

were identified as A1+ and 11 as A1-. Of the five who were identified as A1+, all

were female, three were right-eye dominant, two left-eye dominant, and had an

average age of 42.4 years (range 22-60 years) and an average NART score of 116.8

(range 114-122). Of the 11 as classified as A1-, four were male, seven female, seven

were right-eye dominant, four left-eye dominant with an average age of 39.3 years

(range 22-64 years), and average NART score of 116.1 (range 108-121). There were

no significant group differences in gender (U = 58, Z = -1.508, p =.132), eye

dominance (U = 49, Z = -1.891, p = .059), age (U = 78.5, Z=-0.79, p = .937) or

NART score (U = 56, Z = -0.260, p = .795).

6.3.2.2 Participants with schizophrenia and healthy controls who participated

in binocular rivalry, Studies 2 and 3 and the Necker Cube task in Study 2

(Chapters 3 and 4).

Of the 24 genotyped control participants who participated in the binocular

rivalry tasks described in Chapters 3 and 4, seven were A1+ and seventeen A1-; the

average age 39.8 years (range 18-64 years) with an average NART score of 116.9

(range 105-122).

Of the 17 genotyped participants with schizophrenia, five were A1+ and twelve

A1-; the average age 34.76 years (range 23-51years) with an average NART score of

111.6 (range 101-121). See Table 6.1 for the breakdown of age, gender, eye

dominance and mean NART score according to Allele status.



in visual backward masking tasks in Study 3 (Chapter 4).

Of the genotyped control participants who participated in the VBM tasks Four

were classified as A1+ and ten A1-; the average age 36.4 years (range 21-58) and an

average NART score was 113.5 (range 104-121).

Of the genotyped participants with schizophrenia who participated in the VBM

tasks, four were A1+ and eight were A1-; the average age 33.9 years (range 23-50

years) with an average NART score of 111.6 (range 101-121). See Table 6.1 for the

breakdown of age, gender, eye dominance and mean NART score according to

Allele status.


in Benton’s Judgment of Line Orientation in Study 4 (Chapter 5).

Of the 20 healthy participants genotyped, eight were A1+ and twelve were

A1-; the average age 35.9 years (range 18-58 years) with an average NART score of

116.4 (range 102-124).

Of the 18 genotyped participants with schizophrenia who participated in the

BJLO, six were A1+ and twelve A1- ; the average age 34.2 years (range 21-51 years)

with an average NART score of 111.9 (range 96-124). See Table 6.1 for the

breakdown of age, gender, eye dominance and mean NART score according to

Allele status.


Table 6.1: Demographic characteristics of participants genotyped for the presence of the Taq1 A DRD2 alleles receptor for studies 2, 3 and 4.

Study 2 Study 3 Study 4

Controls A1+ (n=7)

A1- (n=17)

A1+ (n=4)

A1- (n=10)

A1+ (n=8)

A1- (n=12)

Age (mean yrs) 38.5 39.8 33.6 37.8 38.4 38.7 Male 0 5 0 4 1 6 Female 7 12 4 6 7 6 L)eye dominant 4 6 3 2 7 4 R)eye dominant 3 11 1 8 1 8 NART (mean) 116.7 116.9 116.8 117.6 117.7 118.2

Schizophrenia A1+ (n=5)

A1- (n=12)

A1+ (n=4)

A1- (n=8)

A1+ (n=6)

A1- (n=12)

Age (mean yrs) 29.7 36.9 31 36.3 29.7 35.3 Male 2 9 3 6 3 10 Female 3 3 1 2 3 2 L)eye dominant 2 5 2 5 2 5 R)eye dominant 3 7 2 3 4 7 NART (mean) 110.7 114.8 111.8 114.4 110.7 112.3 CPZE (mg) 425 540 410 555.6 425 583.3

6.4 Results

6.4.1 Binocular rivalry results.

6.4.1.1 Binocular rivalry in control participants in 16 stimulus Conditions from

Study 1.

There were no differences in binocular rivalry rates recorded by A1+ control

participants (n = 5) and A1- control participants (n = 11) over the 16 stimulus

conditions in Study 1 described in Chapter 2 (Mann-Whitney U, p > .05). See Table

6.2 for results.


Furthermore, allelic status did not account for differences in the range of

binocular rivalry scores observed in Table 2.1 in Chapter 2. A1+ participants’

binocular rivalry rates ranged from 0.15 to 0.89 Hz, whereas those with A1- status

ranged from 0.23 to 1.0 Hz (Mann-Whitney U = 22.0, Z=-. 623, p=.583). The

median binocular rivalry rates for A1+ participants were 0.478 Hz, compared with

A1- median binocular rivalry rates of 0.453 Hz (Mann-Whitney U = 25.0, Z = -. 283,

p = .827).

6.4.1.2 Binocular rivalry rates in low- and high-strength, magnocellular and

parvocellular biased binocular rivalry tasks and the Necker cube.

There were no group differences in binocular rivalry rates recorded in A1+ (n =

13) and A1- (n = 28) participants (Mann-Whitney U, p > .05). When participants

with schizophrenia were considered separately from control participants, those who

were A1+ (n = 6) generally recorded slower binocular rivalry rates than A1- (n = 11)

participants, and there a statistical trend in the magnocellular biased binocular rivalry

task (Z = -1.764, p = .078). However, no other statistical differences were observed

in any other binocular rivalry stimulus. No differences in binocular rivalry rates

were observed between A1+ (n = 7) and A1- (n = 17) healthy participants (Mann-

Whitney U, p > .05). See Table 6.3 for results.

6.4.2 Backward masking results.

No differences between allelic groups were evident in the backward masking

scores in either participants with schizophrenia (A1+ n = 4, A1- n = 8) or control

participants (A1+ n = 4, A1- n = 10). See Table 6.4 and 6.5 for results.

6.4.3 Benton’s Judgment of Line Orientation Task results.

Subjects with schizophrenia in this sample who had A1+ (n = 6) status

performed more poorly on the BJLO than those who were A1- (n = 12); M = 45.17,


SD = 8.7 correct compared to M = 47.1 SD = 8.7, respectively. Analysis of

individual lines revealed that A1+ participants with schizophrenia made more errors

on Line 10 (M = 2.0, SD= 1.7 compared to M = 1.0, SD= 2.0; χ2 [1, 18] =13.95, p =

.016) than those with A1- status. A1- participants with schizophrenia made more

errors on Lines 3, 4, 8 and 9, but these differences failed to reach significance.

Table 6.2: Binocular rivalry rates recorded by A1+ healthy participants (n = 5) compared A1- healthy participants (n = 11) over the 16 stimulus conditions.

Healthy Controls

A1+ Allele (n=5) A1- Allele (n=11)

Median Range Median Range U Z p

L4AS 0.300 0.634 0.283 0.325 24 -0.397 .743

L4AM 0.350 0.841 0.400 0.516 21 -0.737 .510

L4CS 0.250 0.567 0.280 0.391 24 -0.397 .743

L4CM 0.400 1.009 0.408 0.498 26 -0.170 .913

L8AS 0.192 0.583 0.375 0.842 18 -1.077 .320

L8AM 0.275 0.700 0.500 0.558 23 -0.510 .661

L8CS 0.283 0.584 0.200 0.808 26 -0.170 .913

L8CM 0.233 0.775 0.317 0.633 27 -0.057 1.000

H4AS 0.333 0.734 0.467 0.800 22 -0.623 .583

H4AM 0.467 0.850 0.492 0.683 26 -0.170 .913

H4CS 0.530 0.608 0.400 0.866 26 -0.170 .913

H4CM 0.542 0.783 0.558 0.766 27 -0.057 1.000

H8AS 0.408 0.733 0.525 1.107 27.5 0.000 1.000

H8AM 0.483 0.925 0.583 0.927 22.5 -0.567 .583

H8CS 0.475 0.725 0.496 0.783 22 -0.624 .583

H8CM 0.458 0.833 0.575 0.858 26 -0.170 .913

Stimuli Legend: L low luminance, H high luminance, 4 spatial frequency of 4 c/d, 8 spatial frequency of 8 c/d, A achromatic white/black gratings, C coloured red/black gratings, S stationary 0c/s and M moving at 4 c/s.


Table 6.3: Binocular rivalry rates recorded by A1+ and A1- participants using binocular rivalry tasks with high and low strength stimuli, magnocellular and parvocellular biased stimuli and the Necker Cube

Schizophrenia

A1+ Allele

(n = 6 )

A1- Allele

(n = 11 )


High Strength

BR task 0.300 0.092 0.304 0.25 8.5 -1.524 .132

Low Strength

BR task 0.217 0.092 0.263 0.425 24.5 -0.856 .404

Magno BR task 0.242 0.059 0.288 0.25 15.5 -1.764 .078#

Parvo BR Task 0.120 0.028 0.200 0.308 30.5 -0.252 .808

Necker Cube 0.217 0.187 0.367 0.275 23 -0.472 .689

Controls

A1+ Allele

(n = 7)

A1- Allele

(n = 17)


High Strength

BR task 0.530 0.608 0.508 0.725 26 -0.170 .913

Low Strength

BR task 0.425 0.880 0.575 0.858 57.5 -0.127 .901

Magno BR task 0.458 0.875 0.492 0.916 54.5 -0.318 .757

Parvo BR Task 0.267 0.583 0.369 0.542 48 -0.731 .494

Necker Cube 0.288 0.284 0.258 0.300 37 -0.176 .898

Note. # indicates p <.1 significance (trend)


Table 6.4: Correct scores in backward masking tasks that bias magnocellular and parvocellular visual pathways at 4 inter-stimulus intervals (ISI) recorded by A1+ and A1- participants with schizophrenia A1+ Allele (n=4) A1- Allele (n=8)


Magnocellular VBM Task

ISI 27msec 8 8 7.5 12 8.5 -1.299 .194

ISI 53msec 8 9 7 11 10.5 -0.954 .340

ISI 107msec 9.5 11 6.5 11 11.5 -0.767 .443

ISI 213msec 13 15 10.5 14 13.5 -0.429 .668

Parvocellular VBM Task

ISI 27msec 6.5 2 7 8 11 -0.860 .390

ISI 53msec 9 7 8.5 10 15 -0.171 .864

ISI 107msec 12 8 10 14 12.5 -0.600 .549

ISI 213msec 13 9 12.5 10 14 -0.342 .732

In the control group, there were no differences in the error scores for Lines 1,

5, 6, 7 and 11 (Figure 5.2 b). Line error scores failed to reach statistical significance

in this group (see Appendix 5 for results). When total line error scores for all

participants (those with schizophrenia and healthy controls) were combined the

significant difference detected in line 10 between the alleles was preserved (M =1.1,

SD = 1.4 compared to M = 0.5, SD = 1.4; χ2 [1, 5] =14.583, p = .012). No other

significant differences were found.

Berman et al., (2003) observed a gender effect where girls carrying the A1+

allele had lower visuospatial functioning than that of boys with the A1+ allele.

Gender differences were not accounted for in the present study. In Berman’s study


the group of participants with schizophrenia comprised 15 males and three females,

and the control group comprised seven males and 13 females.

6.5 Discussion

In the samples reported here the proportion of A1+ to A1- participants with

schizophrenia were similar to those of control participants. Previous research has

reported that the A1+ status is over represented in patients with schizophrenia based

on post mortem studies (Noble, 2000; Noble, 2003). Equally, a lack of association

between the Taq1A allele of the DRD2 receptor and schizophrenia has been reported

in previous studies (Behravan et al., 2008; Kishuda et al,. 2003; Ohara et al., 1996;

Parson et al., 2007; Suzuki, Kondo et al., 2000). This lack of association suggests

that differences noted in performance on binocular rivalry, backward masking and

BJLO tasks may not be associated with the presence A1 allele of the DRD2 gene in

schizophrenia per se.

It has been reported that A1+ individuals generally have more symptoms of

schizophrenia (Ohara et al., 1996; Sanjuan et al., 2004) than those with A1- Status

and are at greater risk of significant side effects (Alenius et al., 2008; Kaiser et al.,

2002) and tend to have more favourable responses to medication that block D2

receptors (Scharfetter, 2004; Suzuki, Mihara et al., 2000). Those with schizophrenia

with A1+ status receiving anti-psychotic medication, which is considered to be an

index of dopamine D2 receptor blockade (Cotes et al., 1977; Gruen, 1978; Seeman,

2002), also have higher serum prolactin levels, than those with A1- status.


Table 6.5: Correct scores in backward masking tasks that bias magnocellular and parvocellular visual pathways at 4 inter-stimulus intervals (ISI) recorded by A1+ and A1- control participants

A1+ Allele (n=4) A1- Allele (n=10)


Magnocellular VBM Task

ISI 27msec 9 6 8 11 14.5 -0.784 .433

ISI 53msec 13.5 8 8.5 11 11 -1.287 .198

ISI 107msec 14.5 8 12 11 15.5 -0.645 .519

ISI 213msec 14.5 8 13.5 9 15.5 -0.648 .517

Parvocellular VBM Task

ISI 27msec 10.5 5 10.5 5 18.5 -0.219 .826

ISI 53msec 13.5 6 11 5 9 -1.578 .114

ISI 107msec 13.5 3 13 9 20 0.000 1.000

ISI 213msec 13 4 12 8 11 -1.290 .197

Studies in individuals with schizophrenia that utilise spatial, temporal, and

contrast sensitivities known to be mediated by dopamine and dopamine receptors,

indicate that dopamine-related abnormalities originating in the primary visual

pathway contribute to abnormalities detected at higher levels of visual processing in

schizophrenia (Chen, Levy et al., 2003; Harris et al., 1990; Keri, Antal et al., 2002;

Keri, Janka et al., 2002; Masson et al., 1993; Schwartz et al., 1988; Schwartz 1990;

Shermata & Chen, 2004; Slaghuis, 1998; Slaghuis & Curran, 1999).


a.

b.

Figure 6.1: Benton’s Judgement of Line Orientation (BJLO) line error scores according to the presence of the A1 allele in subjects with (a) schizophrenia and (b) healthy controls.

Note: * p < .05. Error bars indicate standard error.

Animal models suggest that density and frequency of D2 dopamine receptors

found in the retina and primary visual pathway are similar to those in the primate

striate cortex (Djamgoz et al., 1997; Schorderet & Nowak, 1990; Witkovsky, 2004)

and the genetic expression of D2 receptors in the retina reflects that of the striatum

Healthy Controls by Allele

0

1

2

3

4

L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L11

BJL

O L

ine

Err

ors

A1+ (n=8) A1- (n=12)

0

1

2

3

4

L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L11

BJL

O L

ine

Err

ors

A1+ (n=6) A1- (n=12)

Schizophrenia by Allele

*


(Stormann, Gdula, Weiner & Brann, 1990). Lower densities of D2 receptors in the

retina and primary visual pathway in A1+ individuals are likely to affect temporal

and luminance contrast discrimination and visuospatial processing in these

individuals. Although greater concentrations of exogenous dopamine may be present

in the visual pathway and striatum of individuals with schizophrenia, dopamine

binding will be diminished in those who carry the A1 allele due to the lower density

of D2 dopamine receptors, compared to their A1- counterparts. In the current study a

trend was noted in binocular rivalry rates between A1+ and A1- participants with

schizophrenia using stimuli that biased the magnocellular visual pathway. Although

no other statistical differences were observed between the two groups on other

binocular rivalry tasks or backward masking task, it may be speculated that this

effect is related to the action of dopamine on the magnocellular or dorsal pathway,

which may play a role in binocular rivalry. Replication in a larger sample may

provide better insights.

The density and function of D2 receptor sites in the striatum provide the

rationale for including studying this particular dopamine related gene. A1+ status

has been associated with diminished dopaminergic activity in the central nervous

system, as evidenced by prolonged P300 associated latency, (Noble et al., 1994),

reduced visuospatial function (Berman & Noble, 1995) and reduced glucose

metabolism in the brain (Noble, 1998). Thus the Taq 1A polymorphism of the

DRD2 gene may provide a useful tool to investigate dopaminergic involvement in

visual processing and binocular rivalry.

Visuospatial abnormalities have previously been associated with the A1+ status

Berman & Noble, (1995), Berman & Noble, (1997), and Berman et al., (1996) found

that A1+ boys made more errors than A1- boys on all eleven of the lines of the BJLO


task, with the effect being largest on the right in most presentations. Analysis of

individual lines in the current study revealed A1+ participants with schizophrenia

made fewer errors on lines 3, 4, 8 and 9 than their A1- counterparts and that A1+

participants with schizophrenia made more errors on Line 10 (χ2[1, 18] =13.95, p =

.016) than those with A1- status. However, it is impossible to tell if this difference in

Line 10 of the BJLO is artefact or a real effect. The data are difficult to interpret due

to the small sample size, as there are no prior comparative studies in schizophrenia

where visuospatial ability is investigated in relation to line errors.

The sample size in the current study was calculated on previous data to

determine if a difference in BJLO performance existed between subjects with

schizophrenia versus healthy controls, rather than between the alleles. Replication in

a larger sample is necessary. Future studies investigating visuospatial ability and

binocular rivalry that include analyses of an array of dopamine-related genes in a

larger sample may provide insights into these mechanisms.

Chapter 7: Overview, General Discussion and Conclusions 209

7.1 Overview and General Discussion

Binocular rivalry provides a unique opportunity to investigate visual awareness

and specific elements of visual processing in schizophrenia. Theoretical models of

binocular rivalry were examined in participants with schizophrenia and healthy

controls using a ‘within-subject between-groups’ design. The apparatus and method

of collecting binocular rivalry data (Miller et al., 2003) was able to be manipulated

so that specific stimulus characteristics (luminance contrast, spatial frequency,

colour, movement and stimulus strength) could be investigated.

7.1.1 Exploring binocular rivalry rate.

The first study explored the effect of stimulus characteristics on binocular

rivalry data in a group of healthy participants using a 2x2x2x2 repeated measures

‘within-subject’ design. Each participant completed 16 binocular rivalry tasks, to

investigate the effect that increasing luminance contrast, spatial frequency, colour

and movement had on binocular rivalry rate and dominance durations. Luminance

contrast and movement had a significant effect on binocular rivalry rate in this group,

however large individual variations in binocular rivalry rates were observed. When

participants were sorted into fast and slow alternators according to mean binocular

rivalry rates across the 16 stimulus conditions, fast alternators demonstrated a greater

increase in binocular rivalry rate as stimulus strength increased. These data provided

general support for an oscillation model.

Slow binocular rivalry rates were observed in participants with schizophrenia

using high- and low-strength binocular rivalry stimuli, extending the work of

Pettigrew and Miller (1998) and Miller et al., (2003). These results challenge the

assertion that slow binocular rivalry is a trait maker for bipolar disorder (Pettigrew &

Chapter 7: Overview, General Discussion and Conclusions


Miller 1998; Miller et al., 2003). It may be that slow binocular rivalry rate reflects

visual processing abnormalities associated with cognitive deficits in mental illness.

Significantly slower binocular rivalry rates were also observed in participants

with schizophrenia compared with healthy controls in binocular rivalry stimulus

conditions that biased the magnocellular and parvocellular visual pathways (p < .02

and p < .006 in the magnocellular and parvocellular binocular rivalry tasks,

respectively). These results were validated against VBM tasks widely accepted to

test magnocellular and parvocellular pathway processing, and to consistently

separate individuals with schizophrenia from healthy participants. Significant

differences in VBM performance between the groups were observed (magnocellular

VBM task p = .01; and parvocellular VBM task p < .001), with participants with

schizophrenia performing more poorly on both tasks.

The suggestion that binocular rivalry is related to competition between the two

cortical hemispheres was also investigated. Participants with schizophrenia

performed more poorly on the BJLO task, a relatively pure visuospatial task that is

processed predominately within the right cortical hemisphere, compared to healthy

controls (global score, p = .002), indicating theoretical abnormal right cortical

hemisphere processing. When these results were compared with binocular rivalry

rates, BJLO global scores correlated with binocular rivalry rates recorded by

participants with schizophrenia in the magnocellular biased condition.


Normalised dominance durations (time periods between button pushes,

measured in milliseconds, expressed as fractions of their means), have been

demonstrated to approximate a gamma-density function (Carter & Pettigrew, 2003;

Logothetis et al., 1996; Miller et al., 2003). When histograms of the normalised


dominance durations were drawn for each task, typical right-skewed distributions

resulted. However, few were able to be fitted to a gamma-density function using

Kolmogorov-Smirnov goodness-of-fit tests, making these data difficult to interpret.

As an alternative to fitting dominance durations to a theoretical gamma-density

function, the distribution of dominance durations between groups were compared

statistically using the Smirnov test statistic. Differences in cumulative dominance

distributions for schizophrenia participants and healthy control participants (m and n

respectively) were compared. Critical values, determined by w0.95 ≈1.36√ m+n/ mn

(CV-T for S), were compared to the Smirnov T (the greatest distance in values along

the distribution) across all test conditions. This allowed a direct comparison to

between groups in each task.

There were no differences in the cumulative dominance durations recorded by

participants with schizophrenia in the low- and high-strength binocular rivalry tasks

when compared to those of healthy participants. However, significant differences

were observed between the groups in the tasks that used stimuli to bias

magnocellular and parvocellular visual pathways. Participants with schizophrenia

recorded more 0.5-second dominance durations in both conditions, but less

dominance durations of 1.5 to 4 seconds compared to those recorded in control

participants in the magnocellular binocular rivalry task. This increased number of

shorter dominance durations recorded by participants with schizophrenia may be

interpreted as reflecting abnormal magnocellular processing early in the visual

pathway, while the abnormally-long dominance durations seen in participants with

schizophrenia (and not healthy participants) may reflect abnormal parvocellular

processing at the cortical level.


7.2 Neurotransmission and Binocular Rivalry: Does Dopamine Have a Role?

Investigating binocular rivalry, VBM and visuospatial ability in schizophrenia,

a disease associated with abnormal dopaminergic function (Hirvonen et al., 2005;

Seeman & Kapur, 2000), provides the opportunity to explore the potential role of

dopamine in human subjects. Animal models provide evidence that density and

frequency of D2 dopamine receptors found in the retina and primary visual pathway

are similar to those in the primate striate cortex, and that D2 receptors play a major

role in visuo-cognitive processes in dopamine-related conditions such as

schizophrenia (Djamgoz et al., 1997; Schorderet & Nowak, 1990; Witkovsky, 2004).

General support for the notion that dopamine plays a role in binocular rivalry

was provided as participants with schizophrenia consistently recorded slower

binocular rivalry rates than healthy participants. Additionally, higher doses of anti-

psychotic medication had an effect on binocular rivalry rates in response to higher-

strength stimuli. Slow binocular rivalry rates may indicate increased dopamine

release within the striatum or visual pathways. This effect may be direct or due to

the stimulatory effect of serotonin on dopamine release.

It was theorised that that a genetic variation in the density and distribution of

D2 receptors in the retina and cortex (the presence of the A1 allele of the Taq 1A

DRD2 receptor gene) may account for some of the individual variation in

performance in visual tasks reported here. It was hypothesised that A1+ individuals

would perform more poorly on binocular rivalry, backward masking and the BJLO

tasks than those with A1- status.

A trend was noted in binocular rivalry rates between A1+ and A1- participants

with schizophrenia using stimuli that biased the magnocellular visual pathway (p =

.78). However, no other statistical differences were observed between the two


groups on binocular rivalry tasks or backward-masking tasks were noted in either the

group with schizophrenia or the control group. The BJLO task revealed that A1+

participants with schizophrenia made significantly more errors for line 10 than those

without, but made fewer errors on lines 3, 4, 8 and 9 than their A1- counterparts.

These data are difficult to interpret and replication in larger groups is necessary.

Future studies investigating several alleles may provide more fruitful data.

7.3 Combining Theories to Produce a New Model of Binocular Rivalry

Studies have demonstrated that transient (magnocellular) channel neurons

respond to the onset and offset of a stimulus 50-80 msecs before the sustained

(parvocellular) channel neuron, with the response of the sustained channel neuron

dependent on the spatial frequency of the stimulus (Breitmeyer & Ganz, 1976). In

the VBM paradigm it is thought that magnocellular neurons inhibit parvocellular

neurons via internuncial neurons at the LGN and cortex based on their response

duration. Thus, when a mask stimulus follows a target stimulus the magnocellular

neurons carrying information regarding the mask interrupt the sustained

parvocellular response elicited from the target stimulus at the LGN cortical junction.

Breitmeyer & Ganz, (1976) presented a model of visual masking outlined in (recall

Figure 4.7 from Chapter 4).


Figure 4.7; The time course of the transient and sustained channels when the target precedes the mask (backward masking).

Key: T = transient channel, S = sustained channels. Arrows indicate the direction of the masking interaction. A minus sign indicates that the interaction is inhibitory, and a positive sign indicates that the interaction is one of sensory integration.

According to the sustained-transient theory in VBM, if the mask and test

stimuli are similar in orientation and spatial frequency, maximum masking will occur

at stimulus onset synchrony. This prediction arises from the assumption that, when

the mask and target are similar, equal proportions of magnocellular and parvocellular

cells are stimulated and masking effects derived from ‘within channel’ inhibition;

transient on transient and sustained on sustained (May et al., 1988). Breitmeyer &

Ganz (1976) postulated that transient neurons inhibited sustained neurons via

internuncial neurons at the LGN and cortex based on their response duration.

Applied to binocular rivalry, it could be that the magnocellular pathway is

responsible for triggering the alternation of images seen in binocular rivalry. Visual

information is carried more rapidly to the cortex by monocular than binocular

neurons, and both types contain magnocellular and parvocellular cells, with

parvocellular neurons concentrated around the fovea, while the density of

100 200 3000

+-

400 msec


Target

Mask

T

S


magnocellular neurons increases with foveal eccentricity (Livingstone & Hubel,

1987). Thus, during binocular rivalry monocular magnocellular channel neurons

from one eye reach the LGN, inhibit binocular neurons carrying information from

both eyes at the LGN and thus interrupt parvocellular neuronal processing in the

cortex. Thus, it is the action response of the parvocellular neurons in the cortex that

determine the dominance duration of the image, and thus the rate (recall Figure 4.9

from Chapter 4 below).

Figure 4.9A model of binocular rivalry with rapid magnocellular response followed by the parvocellular response to continuous stimuli (vertical and horizontal lines) in the right and left eyes respectively at corresponding retinotopic areas.

Note: Arrows indicate if the masking interaction is interruption or integration. The bottom axis denotes the fluctuating images seen during binocular rivalry over time. Note that the duration of the image is not constant.

This revised model combines the two prevailing models of binocular rivalry;

the pattern rivalry model and the pathway model. The pattern model suggests

binocular rivalry occurs where the conflicting stimuli presented to each eye compete


for dominance from interactions between monocular and binocular neurons in the

visual cortex (see Blake, 2001). The pathway model suggests that binocular rivalry

is related to the actions of the parvocellular, magnocellular pathway processing, or

both in the retina, LGN and cortex (He et al., 2005; Carlson & He, 2000; Blake et al.,

1991). This model suggests that the magnocellular pathway gates (Javitt, et al., 1999)

or acts as a ‘switch’, with its rapid response to local visual information ‘turning off’

or interrupting cortical processing the parvocellular neurons in the cortex derived

from parvocellular neurons located in corresponding retinal location in the opposite

eye.

7.4 Slower Binocular Rivalry and Visual Processing in Schizophrenia

The use of binocular rivalry enables questions regarding perceptual selection

and unconscious processing to be addressed experimentally (Carmel, Arcaro,

Kastners & Hasson, 2010). Binocular rivalry is a task that provides an objective

behavioural measure of the temporal characteristics of neural processes within the

visual system. The binocular rivalry stimuli can be manipulated to access specific

aspects of the visual system known to be abnormal in schizophrenia. Previous

studies have identified that individuals with schizophrenia have deficits when

processing low-luminance, temporally-modulated stimuli and abnormal processing in

the magnocellular pathway (Green et al., 2009). Using binocular rivalry to examine

visual processes in schizophrenia can be achieved by exploiting visual anomalies

known to exist in schizophrenia. Here, it has been demonstrated that individuals with

schizophrenia consistently record slow rates binocular rivalry alternations. Slow

binocular rivalry in schizophrenia may indicate slow processing of visual

information at a number of stages along the visual pathways that may contribute to


higher-order cognitive deficits in working memory, executive functioning and

attention (Martinez et al., 2008).

Investigating binocular rivalry in schizophrenia using stimuli to bias the

magnocellular and parvocellular visual pathways adds to a large body of research

undertaken in schizophrenia. Using tasks that selectively bias the parvocellular and

magnocellular systems to study schizophrenia is an approach that has been endorsed

by the CNTRICS (Green et al., 2009). Applying the above model to the

schizophrenia binocular rivalry data provided in this study indicates that the

perceptual abnormalities associated with schizophrenia are likely to be due to

abnormalities in parvocellular and magnocellular pathway processing, or in the

retina, LGN and cortex. An over-active magnocellular pathway, with its rapid

response to local visual information from the retina to the LGN, interrupts or gates

cortical processing of the parvocellular neurons in the cortex. Individuals with

schizophrenia may therefore be creating ‘false’ or ‘incorrect’ visual images and be

misinterpreting visual information contributing to paranoia and perceptual

disturbances commonly experienced in this illness. Binocular rivalry may be able to

provide new insights into the neural mechanisms involved in mental illness.

7.5 Limitations

It is not possible to be completely confident in the magnocellular and

parvocellular binocular rivalry tasks access the magnocellular and parvocellular

visual pathways. Although every effort was made to use stimulus parameters that

biased either the magnocellular or parvocellular pathway, it is acknowledged that

there is considerable overlap in the pathways (Ellemberg, Hammarrenger, Lepore,

Roy & Guilemot, 2001). The sensitivity of magnocellular neurons is lower than

parvocellular neurons at higher spatial frequency. Allowing free eye movements that


generate transients during binocular rivalry tasks introduces the possibility of a

response by magnocellular neurons in the parvocellular BR task. There is much

debate in the current literature regarding the degree of separation that can be

achieved by manipulating stimulus parameters (see Skottun & Skoyles, 2011).

Kuo, Schmid and Atchison (2011) suggest that the degree to which a low contrast

location task such as the Magnocellular VBM task used in this study creates bias

toward magnocellular processing is unclear. Lesions studies indicate damage to the

parvocellular system in the parvocellular layer of the LGN result greater contrast

sensitivity losses than leisions in the magnocellular layer (Skutton & Skoyles, 2011).

However it should be noted that although both pathways may be activated,

manipulations of the lumiance and spatial contrast vary the relative balance of the

activation to effectively bias either the magnocellular or parvocellular proccessing.

The resolution and refresh rates of the computer presentation screen also

limited the extent that luminance contrast and temporal frequency could be altered in

the binocular rivalry tasks, and luminance and ISI could be altered in the backward

masking task. This was an issue particularly for the magnocellular binocular rivalry

task and the magnocellular backward masking tasks. To be confident that adequate

separation between parvocellular and magnocellular pathways was achieved a more

sophisticated presentation monitor would need to be employed. Due to the financial

constraints of the project the available computer monitor was adopted as it

adequately biased the magnocellular and parvocellular pathways to allow sufficient

investigation of the pathways.

Reporting of perceptual alternation by pressing keys on a computer key pad

during the binocular rivalry task relies on the participant accurately reporting

changes in perception. It has been observed that in humans recognition of an object


generally occurs around 180msec with motor responses intiated from 540-720msec

(Castelo-Branco, Neuenschwander & Singer, 1998). It is possible that participants

who experience quicker perceptual alternations during binocular rivalry may not

have sufficient time to respond pressing a response key before the opposing image

becomes dominant. It possible that the slow binocular rivlary rate observed in

particpants with schizophrenia reflects slower reaction time rather than slower

alternation rate. This is unlikely, as particpants verbal reports during practice

sessions matched their key repsonses. However future studies may eliminate this

uncertainity by employing a task that assesses how well each participant responds to

known stimuli. For example Carter et al., (2007) employed ‘rivalry pre-test catch

trials’, where a ‘movie’ of perceptual alternations was played to assess accuracy of

responses and response time for each individual before they commenced the

binocular rivalry task.

All tasks used in this study required participants to attend to the task and some

level of concentration. However ‘attention’ was not controlled for in this study.

Deficits related to attention have been reported in individuals with schizophrenia

(Saccuzzo et al., 1996). It is possible that attention impacted on the performance in

VBM and BJLO tasks, and to a lesser degree the binocular rivalry tasks (which are

thought by many to be a perceptual task, or a pre-attentive task). Although every

effort to was made to ensure that participants attended to each task, and recorded

reliable data, the addition of a test to measure attention (for example the Span of

Attention Task, Kay & Sing, 1974), may have improved the study. Future studies

should control for attention.

Participants with schizophrenia were not well matched to controls with respect

to age and gender. An age effect was noted with respect to luminance contrast in


binocular rivalry in controls the second chapter. The effect that age has on

luminance contrast is well established in the vision literature, so the results reported

in Chapter 2 were not unexpected. Although age was not strictly controlled, and

some effects noted, this was minimised by only a small variation in mean ages

between the two groups.

With respect to gender, males out-numbered females in the group of

participants with schizophrenia while in the control group females’ out- numbered

males. Although no gender differences noted in binocular rivalry rates in the first

two studies; it was noted in Chapter 4 that female controls recorded faster binocular

rivalry rates than males in both magnocellular and parvocellular tasks. This is

consistent with a small number of reports that that indicate females record faster

binocular rivalry rates than males (Cogan, 1973; Goldstein & Cofoid, 1965). No

studies report males record faster binocular rivalry rates. However, it was noted in

Chapter 4 that females with schizophrenia recorded slower binocular rivalry rates

than their male counterparts on the binocular rivalry task that biased the

magnocellular pathway, but no differently to males on the parvocellular biased task.

This effect has not been previous reported.

It is possible that the gender-related differences in binocular rivalry observed

here are due to hormonal changes associated with the menstrual cycle. Hormonal

changes, and the use of oral contraceptives, have been linked to alterations in retinal

function and sensitivity changes in some women (Eisner et al., 2004). The actions of

oestrogen and progesterone may contribute to improved colour vision performance at

ovulation (Giuffre et al., 2007), increases in visual sensitivity during menstruation

(Barris et al., 1980) and decreases in pattern reversal evoked potentials (Yilmaz et

al., 1998). Hormonal alterations are not the same for all visual pathways, and


pronounced individual differences with individual’s visual adaptation capabilities

vary substantially over periods of weeks (Eisner et al., 2004). If the binocular

rivalry task is sensitive to these changes future studies should match participants with

respect to gender and in female participants control for menstrual cycle variations or

use of the contraceptive pill when luminance contrast and colour are measured.

It is important to note, that the gender effect noted in the first study reported in

Chapter 4 was not replicated in the second study in Chapter 4 where binocular rivalry

rates reported from rivalry tasks that biased the magnocellular and parvocellular

pathway were compared with magnocellular and parvocellular biased VBM. The

gender effect reported in the first may therefore be an artefact.

It is possible that the slower rate observed in participants with schizophrenia

may be related to medication. All participants with schizophrenia were relatively

symptom free at the time of testing largely due to the fact they were receiving

adequate doses of antipsychotic medication to treat their symptoms. In Chapter 3, a

medication effect was observed in the high-strength binocular rivalry task.

Participants taking lower doses of anti-psychotic medications recorded faster

binocular rivalry rates. However no difference was observed in the low strength

condition. No medication effects were observed in either the magnocellular and

parvocellular binocular rivalry task reported in Chapter 4. Similarly there was no

medication effect on BJLO scores in participants with schizophrenia in Chapter 5.

These results are consistent with other studies reporting no medication effect on

BJLO performance (Buchanan et al., 1994; Halari et al., 1994; Riley et al., 2000).

In this study, participants with schizophrenia were taking a variety

antipsychotic medication. To enable comparisons doses of antipsychotic medication

were converted to chlorpromazine equivalents (CPZE) and then categorised into high


and low by median split. Although the conversion of antipsychotic doses into

CPZE’s is generally accepted and widely practiced in schizophrenia research

(Centorrino et al., 2002; Hargreaves et al., 1987; Humberstonse et al., 2004; Owen et

al., 2002; Woods, 2003), it is acknowledged that these comparisons may be

inaccurate. Many newer antipsychotic medications have been compared in

comparative clinic trials with haloperidol and then converted to CPZE’s; 2mg

Haloperidol being comparative to 100mg Chlorpromazine (Wood, 2003).

The effect that dopamine and dopamine antagonists (antipsychotic

medications) on binocular rivalry is currently unknown. The observed effect of other

neurotransmitters suggests that dopamine has an effect on binocular rivalry.

Serotoninergic 5HT1A and 5HT2A agonist have been observed to decreases

binocular rivalry rate in a dose-dependent manner, (Carter et al., 2005; Frecska

White, et al., 2003) while Gamma-aminobutyric acid (GABA), is thought to be

involved in binocular rivalry, via suppression of dLGN inter-neurons (Bickford, et

al., 2008). Agents such as ethanol (Donnelly & Miller, 1995), sodium amytal and

caffeine have been observed to influence binocular rivalry rate in control participants

providing some suggestive evidence of a dopamine effect. The results presented in

this study are also suggestive of a dopamine effect. However due to the explorative

nature of this study and the many logistical and ethical issues surrounding the

collection of data from un-medicated participants with schizophrenia, a thorough

investigation of the role of dopamine and the effect of specific antipsychotics on

binocular rivalry was beyond the scope of this study. These issues require further

investigation in future studies.


7.6 Implications for Future Research

Although classical binocular rivalry does not appear sensitive enough to

separate individuals with schizophrenia from controls, it may be appropriate to

include a binocular rivalry task that biases the magnocellular and parvocellular

pathways in a battery of tests to aid the early detection of psychosis and

schizophrenia. Despite many years of research into schizophrenia, no single

causative factor has been determined. It is conceivable that schizophrenia is not a

disease that affects specific cortical areas or neural pathways, but a disease

associated with the integration of a number of neural processes, particularly the

integration of perceptual information into higher-order cognitions. Gains in future

research may be made by incorporating binocular rivalry methodologies with fMRI

and VEP technologies to investigate how visual information is integrated along the

visual pathway. A study utilising binocular rivalry and fMRI or VEPs may be

particularly useful to target the transfer of information in the thalamus, which is often

considered the transfer station of all cortical information.

Carefully designed binocular rivalry tasks combined with a battery of cognitive

tasks may provide unexplored insights into the visual aspects to cognitive processing.

Although cognitive deficits in schizophrenia are relatively stable over time (Gold,

2004), they are relatively independent of the symptomatic manifestations of the

illness (Gold, 2004; Heinrichs & Zakzanis, 1998). Future studies that compare

perceptual alternation rates during periods of illness (when a participant display

marked psychotic symptoms) with symptoms free periods may provide some insights

into the cognitive decline associated with schizophrenia.

The binocular rivalry task provides a unique opportunity to investigate visual

awareness in schizophrenia as manipulations can be made to the stimulus


characteristics to investigate specific components of the visual system without the

participant being aware. Adjustments to stimulus parameters in this study were

observed to effected binocular rivalry rate and dominance durations in participants

with schizophrenia and controls. It was noted that stimuli that biased the

magnocellular pathway slowed the binocular rivalry rate in controls to a greater

extent than in participants with schizophrenia. These data provide a platform on

which to base further research that are consistent with the recommendations from the

third meeting of the CNTRICS (Green et al., 2009).

Manipulations to the binocular rivalry task may also allow research to be

undertaken into neurotransmitter involvement in schizophrenia and other mental

illnesses. Testing samples of subjects with a variety of mental illnesses on and off

antipsychotic medications may advance what is known about neurotransmitter

involvement in binocular rivalry and visual information processing. There have been

many advances made in vision research utilising studies in Parkinson’s disease in to

explore the role of dopamine in retinal functioning, spatial and luminance contrast

(Bodis-Wollner, 2003; Harris et al., 1992; Haug, Trenkwalder, Arden & Paulus,

1994). Including participants with Parkinson’s disease both on and off dopamine

agonist medication may therefore provide valuable insights into binocular rivalry.

Furthermore, investigating the role of dopamine along with other neurotransmitters

such as GABA and glutamate in vision by including a binocular rivalry tasks may

provide new methods of investigating neurotransmitter involvement and the effect of

medication in visual processing in schizophrenia and other mental illnesses.

In this study a single allele for the DRD2 receptor gene was utilised to

investigate large individual and group differences in binocular rivalry rates observed

in this study and poorer performance on visuospatial tasks in this study in


participants with schizophrenia compared to controls. Although the results did not

provided conclusive evidence that the Taq1A dopamine gene for the DRD2 receptor

accounted for differences in visual processing, the role of dopamine was implicated.

Future studies that incorporate imagining studies with genetic studies may integrate

the basic biology with the disease mechanisms associated with schizophrenia.

Gene’s related to prefrontal brain functions associated with working memory and

executive function implicate genetic variation in dopaminergic systems. Genetic

variations in the dopaminergic system for example Catechol-O-methyl tranferase

(COMT) and downstream signalling molecules such as V-akt murine thymoma viral

oncogene homologue 1 (AKT1) repeatedly associated with schizophrenia (Mathur,

Law, Megson, Shaw & Wei, 2010; Tan, Callicott &Weinberger, 2009) may prove

useful sites for future binocular rivalry studies. Studies that include analyses of an

array of genes in a larger sample of healthy participants and participants with

schizophrenia may enable researchers to investigate aspects of visual processing

currently not investigated in the literature.

7.7 Conclusion

The research contributes empirical data and adds to what is known about

binocular rivalry in schizophrenia. Consistently slower binocular rivalry rates were

observed in participants with schizophrenia, indicating abnormally-slow visual

processing in this group. These data support previous studies reporting visual

processing abnormalities in schizophrenia and suggest that a slow binocular rivalry

rate is not a feature specific to bipolar disorder, but may be a feature of psychosis in

general.

Although the mechanisms of binocular rivalry remain unexplained, this

research provides a platform on which to base future studies. Binocular rivalry like


psychosis is an internal perceptual phenomenon experienced by the individual. The

only outward sign that the phenomena is occurring is the verbal or other report of

person’s visual experience. An objective behavioural measure of internal

perceptions allows the locus of awareness, perceptual selection and unconscious

processing (Carmel, Arcaro, Kastners & Hasson, 2010) to be investigated in

schizophrenia. Carefully designed binocular rivalry tasks combined with a battery

of cognitive tasks may provide unexplored insights into the visual aspects to

cognitive processing in schizophrenia.

The contributions of the magnocellular or dorsal pathways and parvocellular or

ventral pathways to binocular rivalry, and therefore to perceptual awareness, provide

a rich area of research. Slow binocular rivalry rates, recorded by participants with

schizophrenia when the stimuli biased the magnocellular and parvocellular visual

pathways, correlated with poorer performance on VBM tasks effective in separating

those with schizophrenia from controls. These data supported an alternative model

of binocular rivalry based on VBM theory. This alternative model suggests that the

magnocellular (or dorsal system) initiates perceptual awareness of an image and the

parvocellular (or ventral system) maintains the perception of the image, making it

available to higher cortical processing occurring within the cortical hemispheres.

Thus abnormalities in both the magnocellular and parvocellular pathways contribute

to perceptual disturbances that ultimately contribute to the cognitive dysfunction

associated with schizophrenia. Combining binocular rivalry tasks that bias

magnocellular and parvocellular pathways with fMRI or VEPs methodologies in

future research in schizophrenia may further advance what is currently known about

the fluctuating course and cognitive decline associated with the disorder.


Although this research was limited in terms of age and gender matching the use

of a within-subject between-group design provides some confidence in the results not

currently available in the literature. The results reported in the current study raise a

number of interesting questions that can be investigated in future studies. As

discussed, the group of participants with schizophrenia in this study was limited to an

out patient population with a relatively narrow range of presenting psychotic

symptoms, who all receiving therapeutic doses of antipsychotic medications. Future

studies that expand to sample population to include individuals with a number a

greater range of symptom profiles that include deficits associated with spatial

memory and executive functioning may allow further investigation into cognitive

processing in schizophrenia and other mental illnesses. The effect of the illness and

long term use of antipsychotic medication is yet to be determined in binocular

rivalry. Testing participants with schizophrenia using binocular rivalry tasks during

periods of illness and remission both on and off antipsychotic medication may

unlock some of the complex issues related to dopamine functioning within the visual

system provide some insights into the fluctuating course of the disorder.

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Appendices

APPENDICES

Appendix A: Backward Masking Task Instructions for Parvocellular VBM Task

For this task you are asked to identify which of four target letters, a capital A, T, V or Y, appears in the centre of the screen by pushing the corresponding letters on a computer keyboard. Each letter is presented for a very short time and is followed by a mask or a distracting letter, the letter S, which makes the task more difficult. You will first see a green screen on the computer monitor. You will then hear a short beep and a cross will appear at the centre of the screen.

This cross represents where the red target letters will appear. You are asked to look at the cross until the red target letter is presented on the screen. The target letter will be either capital A, T, V or Y.

A very short time after the target letter appears a mask letter appears. This is the letter S. This letter S should be ignored.

The next screen is the response screen. This screen asks you to ‘Select A T V Y’.

+

A

S

SelectA T V Y

Appendices 297

When this appears on the screen you are asked to record which letter (A T V or Y) appeared before the S, by pushing the corresponding letter on the computer keyboard. If you are unsure you are asked to guess. The task is designed so that most people get some wrong. Once you have selected your response on the computer keyboard, a blank green screen will appear and then the process is repeated. First you will hear a beep, then the cross will appear in the centre of the screen, then the target letter (A T V Y) will appear in the centre of the screen followed by the mask (the letter S) in the same location and then the screen that asks you to select your response appears. The process is repeated for 64 trials.

Appendices

Appendix B: Backward Masking Task Instructions for Magnocellular Visual Backward Masking (VBM) Task For this task a letter (A, T, V or Y) can appear in one of four locations, up, down, left or right. You are asked to record where you think the letters appear on the screen by pushing the arrow keys on a computer keyboard. Each letter is presented for a very short time and is followed by a mask, which consists of the letter S presented in all four possible locations which makes the task more difficult. You will first see a grey screen on the computer monitor. You will then hear a short beep and a cross will appear at the centre of the screen.

This cross marks the centre of the screen. You are asked to look at the cross until the grey target letters either to the right or to the left, or up or down of the centre of the screen. The target letter will be either capital A, T, V or Y.

A very short time after the target letter appears a mask appears, which consists of four letter S’s appearing in all four possible locations. These four S’s should be ignored.

The next screen is the response screen. This screen has four arrows on it representing the four possible positions of the target letter.

+

A

S S

S

S

Appendices 299

When this appears on the screen you are asked to record where the target letter appeared, by pushing the arrow keys on the computer keyboard. If you are unsure you are asked to guess. The task is designed so that most people get some wrong. Once you have selected your response on the computer keyboard, a blank grey screen will appear and the process is repeated for 64 trials. First you will hear a beep, then the cross will appear in the centre of the screen, then the target letter (A T V Y) will appear in one of four locations on the screen (up, down, left or right) followed by the mask (the four letter S’s, one in each of the four possible locations) and then the screen that asks you to select your response appears. Once you have responded by pushing the arrow keys the process is repeated.

Appendices

Appendix C: Effect of Schizophrenia Characteristics on Visual Backward Masking (VBM) Tasks Table A: Dose level had a significant effect on visual backward masking performance at 27msec inter-stimulus interval, and DSM-IV diagnosis had significant effects at 27 and 53 msec Dose levels (CPZE) Magnocellular VBM Task

<425mg CPZE

(n=4) >425mg CPZE

(n=10) M SD M SD U Z p ISI 27msec 4.5 3.42 8.7 2.63 6 -2.030 .042* ISI 53msec 6.3 5.19 9.4 2.95 9 -1.577 .115 ISI 107msec 6.8 3.59 10.0 3.74 9 -1.559 .119 ISI 213msec 7.3 7.09 12.0 4.14 11 -1.283 .200 Parvocellular VBM Task

<425mg CPZE

(n=4) >425mg CPZE

(n=10) M SD M SD U Z p ISI 27msec 8.3 2.63 7.1 2.73 15 -0.713 .476 ISI 53msec 7.0 4.24 9.2 2.94 15 -0.716 .474 ISI 107msec 8.0 5.94 10.6 3.53 14 -0.855 .392 ISI 213msec 11.0 5.77 12.7 2.58 19 -0.143 .887

DSM-IV diagnosis – SCID Magnocellular VBM Task

Paranoid

(n=5)

Undifferentiated

(n=9) M SD M SD U Z p ISI 27msec 10.4 2.61 5.9 2.62 3 -2.665 .008* ISI 53msec 11.4 3.65 6.9 2.93 7 -2.094 .036* ISI 107msec 11.0 4.00 8.0 3.57 11.5 -1.470 .142 ISI 213msec 13.8 2.59 8.9 5.75 10.5 -1.612 .107 Parvocellular VBM Task

Paranoid

(n=5)

Undifferentiated

(n=9) M SD M SD U Z p ISI 27msec 7.8 4.15 7.2 1.64 22 -0.067 .946 ISI 53msec 9.0 3.61 8.3 3.39 21.5 -0.135 .893 ISI 107msec 10.8 4.09 9.3 4.53 17 -0.739 .460 ISI 213msec 13.8 1.64 11.3 4.15 16 -0.874 .382

Appendices 301

Positive versus Negative Symptoms of Schizophrenia (PANSS) Magnocellular VBM Task

Positive

(n=4) Negative

(n=8) M SD M SD U Z p ISI 27msec 8.5 1.73 7.5 4.24 12 -0.706 .480 ISI 53msec 8.8 2.87 9.1 4.42 14.5 -0.257 .797 ISI 107msec 8.0 3.56 10.0 4.41 12.5 -0.595 .552 ISI 213msec 10.5 4.12 10.6 6.72 13 -0.516 .606 Parvocellular VBM Task

Positive

(n=4) Negative

(n=8) M SD M SD U Z p ISI 27msec 8.3 3.40 6.6 2.45 11 -0.858 .391 ISI 53msec 10.8 2.75 7.1 3.40 7.5 -1.456 .145 ISI 107msec 11.3 0.96 9.0 5.61 15 -0.171 .864 ISI 213msec 12.0 2.94 11.9 4.26 14 -0.342 .732

Appendices

Appendix D: Score Sheet - Benton’s Judgment of Line Orientation (BJLO) Date ………………………. Participant

Type of Line Error - Ska et al (1990) Benton (1978) Line 1 Line 2 Correct? Line 1 Line 2

Figure 1 Y N V H HV N R 6 11

Figure 2 Y N H QO QO1 QO2 IQOH R R 9 11

Figure 3 Y N QO1 QO2 QO3 QO4 IQO L R 4 7

Figure 4 Y N H QO QO1 QO2 IQOH L R 1 7


Figure 6 Y N QO1 QO2 QO3 QO4 IQO IQO L R 2 8

Figure 7 Y N H QO QO1 QO2 IQOH L L 1 3



Figure 10 Y N H QO QO1 QO2 IQOH R R 7 11

Figure 11 Y N V Q0 QO1 QO2 IQOV L N 3 6


Figure 13 Y N V Q0 QO1 QO2 IQOV N R 6 8

Figure 14 Y N Q0 QO1 QO2 QO3 QO4 R R 8 10



Figure 17 Y N Q0 QO1 QO2 QO3 QO4 L L 4 5

Figure 18 Y N H QO QO1 QO2 IQOH L L 1 5

Figure 19 Y N V Q0 QO1 QO2 IQOV N R 6 10




Figure 23 Y N V H HV L N 1 6


Figure 25 Y N Q0 QO1 QO2 QO3 QO4 L R 4 9


Figure 27 Y N V Q0 QO1 QO2 IQOV L N 4 6




Appendices 303

Ska (1990) Scores Berman and Noble (1995) Scores

QO Line Error Score /60 Line1 QO1 Left Hemi-space Line2 QO2 Right Hemi-space Line3 QO3 Line4 QO4 Benton (1978) Line5 V Global Score /30 Line6 H Line7 VH Line8 IQO Line9

IQOV Line10 IQOH Line11 Legend QO Intraqadrant oblique error - an error between lines from the same quadrant. QO1 An oblique confused with another oblique different by only one spacing of 18

degrees QO2 An oblique confused with another oblique different by two or three spacings of 18

degrees QO3 Both Oblique lines displaced by one or two spacings in the same direction

respecting the initial spacing QO4 Both oblique lines displaced without maintaining the initial spacing V A vertical error involving an incorrect identification of the vertical line numbered

6 H A horizontal error involving an incorrect identification of the horizontal lines

numbered 1 or 11 VH A vertical and horizontal error involving the simultaneous incorrect identification

of the vertical and one horizontal line IQO Intraquadrant oblique errors involving the displacement of one line from quadrant

to another quadrant IQOV Combined oblique interquadrant and vertical error involving the incorrect answer

in combination (V + IQO) IQOH Combined oblique interquadrant and horizontal error involving the incorrect

answer in combination (H + IQO) L Left hemi-space error R Right hemi-space error N Neutral position F Spatial error that relates to line closest to centre of object

(proximal errors)

M spatial error that relates to line in the middle of object B Spatial error that relates to line furthest from centre of object (distal

errors)

Note * Participants scores are entered into the second and third columns (Line1 and Line 2). If the answer is incorrect this indicated by circling N in the third column. The researcher then indicates what type of error with respect to spacing by circling one of the error types in the 4th column (type of line error). Whether error occurred in the left or right hemi-space and the line numbers are indicated by circling the appropriate answers in the remaining columns. The number of circled responses collated in the table at the bottom of the score sheet.

Appendices

Appendix E. Benton Judgment of Line Orientation (BJLO) Performance Scores in Participants with Schizophrenia and Healthy Controls by A1 Allele of the DRD2 Receptor Gene.

Schizophrenia

A1 (n=6) A2 (n=12)

M SD M SD χ2 p

Benton (30) 19.0 7.9 19.7 4.9 15 .182

Berman (60) 45.2 11.9 47.1 8.7 18 .158

Left hemifield 6.5 6.1 5.7 2.9 15 .059

Right hemifield 8.2 5.7 6.9 4.9 12.375 .336

Line1 0.7 1.6 0.0 0.0 2.118 .146

Line 2 1.2 1.6 1.0 1.7 3.15 .533

Line 3 1.7 1.9 1.9 1.3 3.15 .533

Line 4 1.7 1.4 2.2 0.9 6.171 .187

Line 5 0.8 1.2 0.5 0.5 2.25 .325

Line 6 0.2 0.4 0.2 0.6 2.531 .282

Line 7 1.7 1.6 0.5 1.0 3.886 .422

Line 8 2.3 1.5 3.1 2.2 6 .423

Line 9 2.0 1.7 2.2 1.6 8.625 .125

Line 10 2.0 1.7 1.0 2.0 13.95 .016*

Line 11 0.7 1.2 0.3 0.5 2.163 .339

QO1 5.5 3.4 7.2 2.4 12.75 .174

QO2 1.0 1.3 0.8 1.5 2.932 .569

QO3 2.0 2.4 1.1 1.4 5.571 .35

QO4 1.5 1.5 0.7 2.0 8.25 .083

V 0.0 0.0 0.0 0.0 0

H 0.5 0.8 0.2 0.4 2.143 .343

VH 0.0 0.0 0.0 0.0 0

IQO 0.2 0.4 0.6 2.0 2.531 .282

IQOV 0.0 0.0 0.2 0.6 0.529 .467

IQOH 0.3 0.8 0.0 0.0 2.118 .146

Appendices 305

Controls

A1 (n=8) A2 (n=12)

M SD M SD χ2 p

Benton (30) 25.8 2.2 24.8 2.7 4.722 .787

Berman (60) 55.6 2.1 54.0 3.2 12.708 .176

Left hemifield 1.8 1.2 2.8 1.7 7.778 .169

Right hemifield 2.8 1.5 3.3 2.3 3.681 .72

Line 1 0.0 0.0 0.0 0.0

Line 2 0.1 0.4 0.3 0.5 1.111 .292

Line 3 0.8 0.9 0.7 0.8 0.278 .87

Line 4 0.6 0.7 1.4 1.1 3.274 .351

Line 5 0.3 0.5 0.3 0.5 0 1

Line 6 0.0 0.0 0.0 0.0

Line 7 0.3 0.5 0.3 0.5 0 1

Line 8 1.1 1.4 2.1 1.4 6.954 .224

Line 9 0.8 0.7 0.9 0.9 1.711 .425

Line 10 0.4 0.5 0.1 0.3 2.552 .11

Line 11 0.1 0.4 0.1 0.3 0.093 .761

QO1 3.6 2.8 4.3 2.5 13.056 .11

QO2 0.5 1.4 0.0 0.0 1.579 .209

QO3 0.1 0.4 0.6 0.8 2.292 .318

QO4 0.0 0.0 0.2 0.4 1.481 .224

V 0.0 0.0 0.0 0.0

H 0.0 0.0 0.0 0.0

VH 0.0 0.0 0.0 0.0

IQO 0.0 0.0 0.1 0.3 0.702 .402

IQOV 0.0 0.0 0.0 0.0

IQOH 0.0 0.0 0.0 0.0

Appendices

All Subjects

A1 (n=14) A2 (n=24)

M SD M SD χ2 p

Benton (30) 22.9 6.2 22.3 4.7 15.939 .386

Berman (60) 51.1 9.2 50.5 7.3 28.686 .071

Left hemifield 3.8 4.6 4.2 2.8 15.652 .11

Right hemifield 5.1 4.6 5.1 4.2 8.705 .795

Line 1 0.3 1.1 0.0 0.0 1.761 .185

Line 2 0.6 1.2 0.7 1.3 3.906 .419

Line 3 1.1 1.4 1.3 1.2 2.276 .685

Line 4 1.1 1.1 1.8 1.1 5 .287

Line 5 0.5 0.9 0.4 0.5 1.925 .382

Line 6 0.1 0.3 0.1 0.4 2.306 .316

Line 7 0.9 1.3 0.4 0.8 2.533 .639

Line 8 1.6 1.5 2.6 1.8 4.429 .619

Line 9 1.3 1.3 1.5 1.4 5.149 .398

Line 10 1.1 1.4 0.5 1.4 14.583 .012*

Line 11 0.4 0.8 0.2 0.4 1.771 .413

QO1 4.4 3.1 5.8 2.8 22.385 .022*

QO2 0.7 1.3 0.4 1.1 4.553 .505

QO3 0.9 1.8 0.4 1.4 6.873 .23

QO4 0.6 1.2 0.0 0.0 6.126 .19

V 0.0 0.0 0.0 0.0

H 0.2 0.6 0.1 0.3 1.765 .414

VH 0.0 0.0 0.0 0.0

IQO 0.1 0.3 0.3 1.4 0.734 .693

IQOV 0.0 0.0 0.1 0.4 0.599 .439

IQOH 0.1 0.5 0.0 0.0 1.761 .185

karen heslop thesis 2012.final - qut eprintseprints.qut.edu.au/59610/1/karen_heslop_thesis.pdfthe...

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