lateralization of cognitive functions: the visual half-field task...

Lateralization of Cognitive Functions: The Visual Half-Field

Task Revisited

Ark Verma

Promotor: Prof. Dr. Marc Brysbaert

Proefschrift ingediend tot het behalen van de academische graad

van Doctor in de Psychologie

2014

Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited

Something I owe to the soil that grew

More to the life that fed

But most to Allah who gave me two

Separate sides to my head.

I would go without shirts or shoes,

Friends, tobacco or bread

Sooner than for an instant lose

Either side of my head.

Kim (1901)

--By Rudyard Kipling


Table of Contents

Acknowledgment i

Chapter 1: Introduction 3

Mythology of Lateralization 3

From mythology to science: a brief history

Of Investigations into Hemispheric Asymmetry 6

Methods Investigating Hemispheric Asymmetry

WADA Test 11

Behavioral Methods Investigating Hemispheric Asymmetry 13

EEG & MEG Methods 21

Hemodynamic Neuroimaging Methods 25

Evidence of Hemispheric Specialization

from Clinical Studies 28

from Split-Brain Patients 30

from Neurologically Intact Individuals 33

Structural & Functional Indices of Hemispheric Asymmetry 35

Structural Asymmetry between the Hemispheres 37

Functional Asymmetry in Visuospatial Processing 42

Motivations for the Current Thesis 48

Outline of the Current Thesis 50

References 52

Chapter 2: A right visual field advantage for tool recognition

in the visual half-field paradigm 79


Introduction 82

Method 92

Results 96

Discussion 98

References 103

Chapter 3: Avalidated set of tool pictures with matched objects and

non-objects for laterality research 109

Introduction 111

Method 120

Results 125

Discussion 130

References 133

Appendix 139

Chapter 4: Symmetry detection in Typically and Atypically

Speech Lateralized Individuals: AVisual Half-field Study 153

Introduction 156

Experiment 1 163

Method 164

Results 168

Discussion 169

Experiment 2 171

Method 172

Results 172

Discussion 173

Experiment 3 174

Method 177

Results 177

Discussion 179

General Discussion 180

Conclusion 183

References 184

Chapter 5: Evidence for Right Hemisphere Superiority in Figure Matching

& Judging Negative Emotions from Facial Expressions 195

Introduction 197

Experiment 1 203

Method 203

Results 205

Discussion 207

Experiment 2 207

Method 207

Results 210


Discussion 212

Experiment 3 212

Method 213

Results 215

Discussion 217

General Discussion 219

References 222

Chapter 6: General Discussion 230

The Visual Half-Field Paradigm: Conclusions 244

References 246

Nederlandse Samenvatting 249

Referenties 255

Acknowledgments

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Acknowledgments

Now, that four years of an academic journey culminate into this doctoral thesis, which I hereby

present before you, it is most befitting that I gratefully thank and acknowledge all those without

whom this would never have been possible.

First of all, I would like to thank my supervisor Prof. Dr. Marc Brysbaert, for his

unwavering support and guidance throughout these years without which this thesis could not

have been completed. I can vividly remember every instance you encouraged me to push harder

and take one more step, to reach this day. As an immigrant doctoral candidate, coming from

India to Gent, Belgium, there were certainly moments when I ran into difficult times, but I must

thank you for the enormous patience and compassion with which you would always persuade me

back on track and spur me into action, to understand and conduct quality research. Besides the

immense knowledge and your vast experience, you have always been an example to aspire for,

with the amount of hard work and dedication that you put into research and also with the passion

that still drives your every endeavor. I will certainly always keep it as a goal to reach out for in

the future years of my academic career.

I would like to thank Lise Van der Haegen, for your help in conducting the experiments

listed in Chapter 3, and also later, in writing of the manuscript. I would always remember you as

a very hard working colleague who would always have answers to my queries and who would

always be ready to help me out while I was still learning the ways to function in the university

and conduct research.

I would also like to express my heartfelt appreciation and gratitude towards Emmanuel

Keuleers, my senior colleague and officemate. You have been one of the closest friends I have


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made during my stay here, in Belgium. You have been my host to this beautiful country and

made me aware of its intricacies, its systems and thought processes. Besides, I will always be

indebted for your efforts in helping me settle down here for these four years, in many ways. At

this moment, I can remember the various rides you took me along to, right from the supermarkets

to restaurants, to those lovely walks in the nature and an introduction to mushroom-picking. I can

also recall the many discussions we have had on a broad range of topics from academics to

politics to philosophy, also some in which I tried to rub off my passion for cricket unto you and

also where we shared our unique styles of cooking, wherein you introduced me to European

cuisine (and helped me appreciate it, sans the extra salt and spices!!!). I am sure these moments

will stay etched in my memory forever and will keep reminding me of the good times I shared

with you.

I would like to thank Prof. Dr. Guy Vingerhoets, Prof. Dr. Wim Fias and Prof. Dr.

Wouter Duyck, who constituted my doctoral guidance committee, for their valuable inputs that

went a long way in enhancing the research presented in this thesis. I would like to thank them for

always taking out time to be present in annual meetings and their enthusiastic comments that

would often help me improve upon my experiments and provide a direction to the thesis.

I would like to thank members of my research group Qing, Wim, Maaike, Michael and

Pawel who have always been kind and helpful towards me. Also, I would like to thank Evelyne

Lagrou for her help in finalizing the thesis for publication.

I would also like to thank the academic and technical staff in the Department of

Experimental Psychology, where I conducted my work. I would especially like to thank Lies,

Linde & Christophe for being very helpful throughout these four years.

Acknowledgments

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Also, I would like to thank a host of undergraduate students, who participated in my

experiments. I can recall having enjoyed answering your questions about my research and my

experiences as a researcher in UGent. This work owes a lot to your patience and co-operation.

Apart from those at the university, there are many people I need to thank, who shared this

dream of obtaining a PhD with me and contributed in their own unique ways to bring it to a

reality.

I would like to thank Ms. Priyanka Srivastava and Ms. Monika Lohani who convinced

me for applying for a PhD, in the first place and helped me take the very first steps in this

direction. My teachers, Dr. Bhoomika R. Kar and Prof. Narayanan Srinivasan, for their constant

support and encouragement, even though it has been years since I left the Centre of Behavioral

and Cognitive Sciences, University of Allahabad.

I would then like to thank my parents, Mr. Akhilesh Kumar and Mrs. Rajkumari

Srivastava for being the constant source of strength and belief which held me together and

inspired me to carry on. I would also like to mention my siblings, Sagar Verma and Tripti

Verma who always shared my responsibilities and encouraged me in every way. I would like to

thank my parents-in-law Dr. Santosh Khare and Mrs. Vandana Khare, who have always believed

in me and encouraged me in my endeavors, and also my sisters-in-law Shraddha Khare and

Gaurisha Khare who have been so supportive and encouraging.

I have been fortunate to have had some wonderful friends throughout my life and these

years of PhD were no exception. I would like to acknowledge the amazing friendships that

developed and blossomed during my stay in Gent and also those that remained in India; as they


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have always shared my feelings and helped me get through the different phases of this

memorable journey.

Finally, I would like to thank the most prominent of these friendships, that which I shared

with my wife, Vatsala Khare, who has always stood by me through thick and thin and

encouraged me by creating a protected home around me, which never let me feel too homesick

and always proved to be a nest which was always there to return to. I value your many sacrifices

and love with which you have supported me, to bring this journey to a successful closure in form

of this thesis.

Chapter 1| Introduction

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Chapter 1: Introduction


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Chapter 1: Introduction

That the human brain consists of two hemispheres, i.e. the left and the right half, has evoked

pervasive fascination for over centuries now, both in the academic & popular discussions.

However, the mythology and symbolism associated with left & right dates back to ancient times,

long before organized scientific investigation took over the mantle to understand the

complementary and interdependent functioning of the two cerebral hemispheres.

In order to put contemporary laterality research in perspective, I will first revisit the

mythological avenues that first brought the notions of left and right into the domain of human

curiosity. Then, I will examine the historical evolution of research on cerebral lateralization from

split brain patients to neurologically intact individuals. I will then review the different methods

employed by scientists to investigate the functions of the two hemispheres. Finally, I will discuss

the evidence regarding structural and functional asymmetry in the human brain and evidence for

lateralized processing in the visual and auditory processing domains. At the end, I will

summarize the evidence, and point out the motivations for the work undertaken in the current

thesis.

Mythology of Lateralization

The dichotomized notion of hemispheric function possibly emanates from long standing

beliefs about duality: left & right or good & evil that have transcended human thought across

continents & cultures. In his review of myths associated with laterality, Corballis (1980) recounts

that such beliefs have been around for ages and have exerted enormous influence on religion,

philosophy, literature and scientific thought.


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Different cultures have held surprisingly similar beliefs about the left and right, from the

Maori civilization of New Zealand to the Isis cult of Egypt and also in ancient Israel (Bradshaw

& Nettleton, 1983, Corballis, 1980). Hertz (1909) documented the left-right symbolism in the

Maori culture, from New Zealand. For the Maori people, the right side of the body was

considered the sacred side, associated with the Gods, with the virtues of strength and life; the left

side, on the other hand was considered to be associated with demons, profanity, weakness &

death. The Maori expression tama tane or “the male side”, also refers to the right, and is

associated with strength, virility, the east, and creative force; the expression tama wahine or “the

female side” is associated with opposite of these virtues (Best, 1901, 1905). Similarly, In the

Pythagorean tradition of ancient Greece, the right side was associated with one, odd numbers, the

light, the straight, the good and the male; while the left corresponded to the many, the even

numbers, the dark, the crooked, the evil & the female. Such a bias towards the “right-male”

prototype may be characteristic of many patriarchal societies; and it sometimes gets reversed in

case of matriarchal societies. For example, the Isis cult of ancient Egypt preferred Isis (a female

Goddess) over Osiris (the male God), mother over son, night over day and also the Isis

procession was led by the image of a left hand.

Interestingly, the bias towards the right side in this dichotomy is also present in the Bible,

as pointed out by Corballis (1980), as in Matthew 25:33-41; 41:

And He will set the sheep upon His right hand and the goats upon His left. Then shall the King

say to those upon His right, “Come, ye blessed of my father, and inherit the Kingdom prepared

for you from the beginning of the world.”…Then shall He also say to those on the left, “Depart

from me, ye accursed, into everlasting fire prepared for the Devil and His angels.”


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Another example of the same can be derived from Hindu mythology, where the words for

right and left are dakshina & vama respectively , whereas dakshina is considered to be

straightforward, honest, amiable, compliant and submissive, vama is symbolized as contrary,

reverse, crooked & opposite. Also, vama is considered to be the side of females, often regarded

as the source of maya (illusion) and root of all evils.

Such polarized beliefs about the left and right were mostly pinned to the phenomenon of

handedness and might have stemmed from the fact that one of the two patterns of handedness

outnumbers the other by a large margin. As the left handed people were so few, they were often

regarded as anomalous and thown away as a stigma. Indeed, it has been pointed out that the

incidence of left handedness has been only about 10% for around 50 centuries (Coren & Porac,

1977), while right handedness appears to be a dominant pattern for even the Australopithecus,

which are said to use their right-hand to attack their victim with stones (Dart, 1949).

Initially, the cause of handedness was also attributed to other bodily asymmetries, for

instance, the rightward displacement of liver by Sir Francis Bacon (Corballis, 1980) or early

warfare (for a review see Wile, 1934). It is now accepted that the asymmetry of handedness has

its roots in the asymmetry of the brain, and that the left hemisphere of the brain is the dominant

hemisphere for the majority of people, which accounts for the high numbers of right-handed

people.

The current state of knowledge about the cerebral hemispheres has developed over a

period of time, gradually taking into account developments from phrenology to

neuropsychology, and evidence from split brain patients, epileptic patients, patients who suffered

from various manifestations of cortical atrophy and also a large number of studies done on


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neurologically intact individuals. In the next section we will briefly review the course of this

development.

From Mythology to Science: A Brief History of Investigations into

Hemispheric Asymmetry

Investigations into the functional asymmetry of the two hemispheres have closely

evolved together with the more general investigations of the localization of mental functions in

the brain. Accordingly, Anne Harrington (1995) in her review on the history of laterality research

remarks, “many of the fundamental assumptions – the unquestioned truths – that provide the tacit

grounding for modern laterality research have their source in an early nineteenth-century

approach to visualizing mind-brain relations called localization theory” (p.3). This new approach

that sought to break down the various attributes of mind into smaller building blocks based in the

brain still forms the basic principle in neuroscience.

When, in 1865, Paul Broca, the French physician, declared that speech was controlled by

the left hemisphere of the brain; he broke major ground in the field of neuroscience in general &

laterality research in particular. However, steps in the said direction had been taken long before

this moment (for a detailed review, see Harris (1999)).

Franz Joseph Gall, the Austrian anatomist and physician had developed his theory of

phrenology or organology by examining the skulls of people with “very one-sided talents” i.e. a

severe lack or abundance of certain abilities or “faculties”. Gall theorized about 27 faculties or

talents of the human mind divided into two groups as intellectual and moral, which were situated

in the brain; the intellectual in the anterior portions and the moral/passions in the posterior part

of the brain. In many ways, hence, Gall was one of the pioneers of cerebral localization along


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with few others like Thomas Willis (1681/1965), Georgius (Jirf) Prochaska (1784), and Emanuel

Swedenborg (1740-1741). Gall’s attempts at establishing phrenology as a credible theory

postulating cerebral localization of mental abilities, was met with mixed response from his

contemporaries; while he was opposed by critics as Thomas Sewall (1837) & Marie Jean Pierre

Flourens (1824, 1846) there was also supporting evidence produced by Jean Baptiste Bouillaud

(1825, 1839-1840), Jacques Etienne Belhomme (1848) in France and Samuel Jackson (1828),

Henry Dickson (1830), and Daniel Drake (1834) in America.

However, hemispheric specialization was not the main concern of Gall; he and his

contemporary Marie Francois Xavier Bichat (1805/1809) in their observations of the human

brain concluded that “all parts of the brain resemble each other on every side”, and Bichat

declared the law of symmetry which goes as “two parts essentially alike in their structure,

cannot be different in their mode of acting” (Harris (1999), translation by T. Watkins, pp. 8, 14).

As Gall, being a prominent physician of the era, also endorsed this view, structural & functional

symmetry became the dominant perspectives and contrary evidence presented by Felix Vicq

d’Azyr (1786), Joseph Francois Magendie (1827) & Bouillaud (1825) was never accredited.

It was not until Paul Broca, a French physician, encountered his first aphasic patient, M.

Leborgne, popularly known as “Tan”, as all he could articulate was “tan, tan, tan” that concrete

evidence for cerebral localization of speech began to surface. On posthumous examination of

Leborgne’s brain, Broca (1861a, 1861b, and 1861c) found extensive softening throughout the

left frontal lobe, more specifically in F3, the third convolution, corresponding to the triangular

and opercular parts of the inferior frontal gyrus. Similar areas of the brain were implicated in his

next aphasic patient named M. Lelong (Broca, 1861b). Even though cautious at first, with more

and more evidence indicating that the pattern of cerebral atrophy was focused on the left side of


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the brain, Broca finally declared in 1865 that speech could be lateralized in the left hemisphere;

though he was certain that “this does not allow us to say that the left hemisphere is the exclusive

seat of the general faculty of language” (Broca 1865, as quoted in Harris (1999)). Broca’s work

with aphasic patients, who were later known as patients of “Broca’s aphasia” or “motor

aphasia”, established the role of the left hemisphere in language production. Later, evidence

indicated the involvement of the left hemisphere in language comprehension as well.

Evidence regarding the role of the left hemisphere in language comprehension came from

cases of sensory aphasia. Early reports came from the German physician Johann Gesner (1769-

1776) and in an interesting self-report by the Montpellier physician Jacques Lordat (1843).

While Gesner described a patient with fluent but meaningless speech; Lordat reported that since

the age of 52, he had become “incapable of understanding sounds that I heard quickly enough to

grasp their meaning” (translated by J. Hubert, quoted in Riese 1954, p. 237). However, the cause

of such symptoms could not be clearly identified, as even though there were hints of the

involvement of posterior left hemisphere lesions, there was not enough data or theory to support

such claims.

Carl Wernicke (1874), a student of Theodore Meynert, provided useful data and theory to

explain these symptoms, in his doctoral dissertation, Der Aphasische Symtomencomlex [ On the

Aphasia Symptom Complex]. He described the case of a 59-year old, Suzanne Adam, who could

“comprehend absolutely nothing which was said to her”. Wernicke applied Meynert’s

neuroanatomical approach (Meynert 1866, 1872) to the study of aphasia and brought fresh

insights & revelations to the role of left hemisphere in language functions. Meynert’s approach

had three important highlights; firstly, it proposed that the anterior parts of the brain were

involved in motor functions, while the posterior parts of the brain were responsible for sensory


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functions; secondly, it simplified the tangle of white matter tracts and distinguished them as: the

ascending & descending pathways (cortical-subcortical connections), association pathways

(intrahemispheric connections), and the commissural pathways (interhemispheric pathways);

finally Meynert (1866) described the case of a 23-year old man, with paraphasic speech and

inability to understand. Autopsy of the patient revealed an infarct in the parietal operculum and

posterior insula, which led Meynert to conclude that, “its (Sylvian fissure) posterior part

contains the auditory cortex” where “’sound-images’ are formed”.

On the basis of these, Wernicke proposed that movements for articulation of speech were

stored in the Broca’s area while the traces of the sounds of words were stored in the posterior

regions, later known as “Wernicke’s Area”. Consequently, lesions in these posterior parts were

supposed to lead to loss of language comprehension ability, which came to be known as

Wernicke’s aphasia. Hence, the contribution of the left hemisphere in language comprehension

was confirmed.

Another major step, which set the ball rolling for decades of research on hemispheric

specialization, was the work by a British neurologist, John Hughlings- Jackson. In 1874, citing

clinical evidence, Hughlings-Jackson attributed the “recognition of objects, places, persons, &

c.” to the right hemisphere; thereby proposing that the right cerebral hemisphere might be

specialized for processing visuo-spatial information. Hughlings-Jackson, presented more

evidence for the special role of right hemisphere in spatial processing while treating a 59-year

old patient, Eliza T in 1876, who suffered from symptoms of visual disorientation, spatial

localization, in dressing herself etc.; later her autopsy revealed a “large gliomatus tumor” in the

temporo-occipital region of the right hemisphere. Importantly, Hughlings Jackson also provided

evidence for the contribution of the right hemisphere in production of emotional utterances; he


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noted that under strong emotion, speechless patients (i.e. suffering from left hemisphere

damage/aphasia) could utter oaths or “automatic phrases”. Similar evidence had earlier been

observed by Broca (1861a) also, as “Tan” could utter a curse when angry; hence indicating the

ability of emotional expression was not damaged. Another important contribution in this regard

was made by Jules Luys (1879, 1881), who described the differences between patients suffering

from left-hemisphere lesions &right hemisphere lesions respectively; and pointed out that while

“… right hemiplegics are more or less apathetic …silent, passive and stricken with hebetudes

(dullness/lethargy); left emotional hemiplegics are … afflicted with an abnormal

impressionability. They respond, (…) in a limping voice, broken up by a kind of sobbing… (at

other times) they are boisterous and loquacious, their face is congested…eyes sparkle”.

Such case descriptions coupled with other evidence established the right hemisphere

specialization for emotion; and promoted the right hemisphere as the irrational, emotional

hemisphere. Luys’ (1879, 1881) work was instrumental in developing related research in this

domain.

In light of these groundbreaking studies by the end of the 19th

century, it became evident

that not only the functions of the mind could be localized to the tangible brain; there were also

differences in the way these functions would be organized in the left and right halves of the

brain. This knowledge spurred decades of research into the asymmetries of the structure &

function of the brain. In the next section, I will survey the various methods that have been used

by researchers to investigate hemispheric asymmetries for various cognitive functions, such as

word recognition, face processing etc. The methods too, have evolved during the course of time,


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from the earliest, the WADA test till the recent hemodynamic methods as fMRI. Likewise, they

have changed the field’s approach and perception of the asymmetries in human behavior.

Methods Investigating Hemispheric Asymmetry of Cognitive Function

Intracarotid Amobarbital Test (WADA Test)

The intracarotid amobarbital testing procedure was first developed by Japanese-Canadian

epileptologist Juhn Atsushi Wada (1949), as a method to determine cerebral dominance for

language functions, prior to surgical sectioning of the brains of epileptic patients. Over the

decades, it has been modified to diagnose memory functions and predict the vulnerability to

amnesia (Milner, 1962). More recently, the WADA test has been used to evaluate lateralized

distribution of language and memory functions. Also, a variety of modern neuro-imaging

findings have been validated and correlated with WADA test measurements.

Basically, the WADA procedure involves injection of an anesthetic agent like sodium

amobarbital into the internal carotid artery via a catheter. The anesthesia effectively blocks or

shuts down the functions of the hemisphere where the drug is injected; and hence makes testing

of the functions partaken by the said hemisphere by virtue of deficiency or absence. The

anesthetic injection is usually presented for baseline testing for language and memory functions,

for comparisons with post-injection performance.

Usually after the injection of the anesthetic to the dominant hemisphere global aphasia

sets in, lasting for a few minutes; on resumption the speech is typically characterized by

paraphasic errors and perseverations; while in case of the non-dominant hemisphere, the patients

can still have relatively unaffected speech though other functions may be affected. Along with


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the determination of speech related functions and language dominance, the WADA test has also

been used to test for the lateralization of memory functions (Dodrill & Ojemann, 1997).

Off late, findings from various new methods have been correlated with those of the

WADA test. Lehericy et al. (2000) compared the indices of frontal and temporal language

language dominance obtained from the fMRI and the WADA tests and concluded that while

there was congruence between the two methods where the frontal lobes were concerned there

was less coincidence of measures for the temporal lobes. Other studies also compared language

lateralization measures obtained from fMRI and the WADA tests and found high correlation

between the two (Binder et al., 1996; Desmond et al., 1995).

Despite its usefulness in diagnostic information about cognitive functions (particularly

language and memory) seated in the brain, the WADA test has certain limitations. For instance,

it has been suggested that the documented predictive value of the WADA test is suboptimal

(Ojemann and Kelley, 2002). For instance, the cerebral amytal test is found to be only partially

predictive of post operative verbal memory deficits when measured via neuropsychological tests

(Dodrill and Ojemann, 1997). Further, the WADA test involves up to 0.7% risk of carotid artery

dissection (Lodenkemper et al., 2002). Other related risks include those of cerebral infarction,

arterial spasms and transient femoral neuropathy. As the WADA test is an invasive method, it is

less suitable for testing with normal participants. Apart from these methodological considerations

also affect the WADA test studies. For instance, the procedure for the WADA test is non-

standardized across testing centers (Rausch et al., 1993) and evidence regarding failure of

anesthetization with amobarbital in patients taking antiepileptic drugs has been reported

(Bookheimer et al., 2005).


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Finally, the WADA test does not allow further localization of language functions in each

hemisphere, as it is strictly a test of language lateralization; thus limiting its overall scope. As a

result recently, researchers have looked for noninvasive alternatives to the WADA test, such as

the near infrared spectroscopy method (Watanabe et al. 1998).

Behavioral Methods Investigating Hemispheric Asymmetries

The Dichotic Listening Method

The Dichotic Listening method, i.e. simultaneous presentation of same/different sounds

to the left and right ear respectively, was first introduced by Broadbent (1956), when he

presented digits from 0-9 to test different aspects of attention. As an experimental paradigm it

developed throughout the 1960s with a view to study functional cerebral lateralization (Kimura,

1967, Hugdahl, 2011).

Behavioral studies testing of lateralization for speech related functions employ the

dichotic listening technique (for detailed reviews see Hugdahl, 1995, 2003). Here, two different

auditory stimuli are presented at the same time, one in each ear (Kimura, 1967), and the subject

is asked to report the item heard first, or to discriminate between the two heard items, depending

on the requirements of the experimenter. Typically better recall from the right ear is termed as

right ear advantage and is attributed to the fact the contralateral projections are stronger and may

block those from ipsilateral connections (Kimura, 1967; Bryden, 1988). Importantly,

hemispheric advantages in processing have been manifested through ear advantages for the kind

of stimuli being processed; for e.g. right ear advantages for verbal stimuli and left ear advantages

for some nonverbal/emotional stimuli have been observed. Accordingly, different verbal and

non-verbal variants of the paradigm have been used over the years (Bryden, 1988; Hugdahl,


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1995, 2003). One of the most widely used paradigms has been the presentation of consonant-

vowel pairs, made up of six stop-consonants: /b/, /d/, /g/, /p/, /t/, & /k/, known as the C-V

syllables paradigm (Hugdahl, 2011). The major findings coming from the DL paradigm have

been that, participants with left-hemispheric dominance for language are found to be faster and

more accurate in reporting verbal items presented in the right ear, dubbed as the right ear

advantage (REA; Kimura, 1961; Studdert-Kennedy & Shankweiler, 1970) and conversely they

exhibit a left ear advantage for tasks involving the recognition of musical or environmental

sounds (Boucher & Bryden, 1997; Brancucci & San Martini, 1999, 2003; Brancucci et al. 2005;

Brancucci et al., 2008). Anatomically, the paradigm is based on the fact that monaural input to

each ear is represented in both cerebral hemispheres with an advantage for contralateral over

ipsilateral pathways (Fujiki et al., 2002). However when different stimuli are presented

simultaneously (i.e. dichotically) to the two ears, interactions between auditory pathways make

the situation more complex. Two major theories have been offered in this regard, the “structural

theory” (Kimura, 1967) postulates that the during the DL setup the contralateral auditory

pathway suppresses the ipsilateral pathway; hence auditory stimuli presented to the left ear are

processed first by the right cerebral hemisphere and vice-a-versa. Alternatively, the “the

attentional theory” has proposed that ear advantages are a result of priming, i.e. attending to a

particular type of stimuli and not due to the anatomical properties of the auditory system. Recent

evidence however, indicates support for the interplay of both structural and attentional factors

(Hugdahl et al., 2000; Jäncke et al., 2003; Thomsen et al., 2004).

Hugdahl (2011) presents evidence for a reasonably high reliability and validity of the DL

paradigm. For instance, while an early study reported a high reliability for the DL paradigm of

0.90 (Speaks, Niccum & Carney, 1982); more recent accounts as Voyers & Rodgers (2002) have


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also reported a high level of test-retest reliability. Several efforts regarding validating the

findings of the DL method as the right ear advantage (REA), have been successful using modern

neuroimaging methods, such as PET (Hugdahl et al., 1999) and fMRI (e.g. Van den Noort,

Specht, Rimol, Ersland, & Hugdahl, 2008; Van der Haegen, Westerhausen, Hugdahl, &

Brysbaert, 2013), and electrophysiology measures, such as EEG (Brancucci et al., 2005), and

MEG (Brancucci et al., 2004).

The DL paradigm has an appeal beyond the basic function of determining language

lateralization. DL as a paradigm has been used to investigate emotional processing in

individuals. Some of the earliest works presented emotionally intoned sentences (sentences in

angry, happy or sad voices) compared with monotone sentences and found a left ear advantage

(LEA) for the processing the emotional content of the sentences and a right ear advantage (REA)

for the verbal content (Ley & Bryden, 1982; Shipley-Brown et al., 1988). LEA for emotional

prosody has also been reported for nonsense words spoken in happy, sad, angry or fearful

prosody (McNeely & Netley, 1998). More recent experiments (Techentin & Voyer, 2007;

Techentin, Voyer & Klein, 2009) presented emotional valent stimuli in congruent or incongruent

intonation (for e.g. happy message with sad intonation) and found a stronger LEA for

incongruent target detection; indicating that an incongruent emotional tone can enhance the

emotional information of the content.

Further, the DL task has been instrumental in uncovering patterns of unusual

lateralization associated with psychopathology. In his review, Bruder (1983) presented evidence

that schizophrenic and depressed patients, showed smaller ear asymmetries on a dichotic

listening task and thus reduced lateralization when they were more ill as compared to when they

were faring better with the disease. More recently, Ocklenburg, Westerahausen, Hirnstein &


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Hugdahl (2013) conducted a meta-analysis and compared schizophrenic and normal participants

and found that schizophrenic patients showed weaker cerebral lateralization for language as

compared to the normal individuals. Finally, the DL paradigm has also helped to establish that

auditory verbal hallucinations in patients with schizophrenia are a result of aberrant speech

lateralization coupled with failure to focus attention (Hugdahl et al., 2012).

All in all, we can say that the DL paradigm has been a useful method to investigate not

only cerebral lateralization of language, but also other cognitive functions that are related with

auditory processing.

In the next section I will talk about the visual half-field method (VHF method) for

investigating the functional asymmetry between the two cerebral hemispheres.

The Visual Half-Field Method

One of the most popular methods of investigat ing the lateralization of cognitive

functions at the behavioral level has been the visual half-field method (Hunter & Brysbaert,

2008) along with the dichotic listening method.

The VHF task involves tachistoscopic presentation of stimuli in the left or the right

parafovea, and measurement of the participants’ speed and accuracy as a function of the

presentation location. The task is based on the logic that information displayed in the right visual

half-field (RVF) is initially projected to and processed by the left hemisphere while the

information presented to the left visual half-field is initially handled by the right hemisphere.

Exploiting this basic anatomical principle of the human visual system, researchers predicted that

people with left hemispheric language dominance should show a RVF advantage in a VHF task


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using verbal stimuli while the reverse should be true for participants with right hemispheric

language dominance.

The Visual Half-field method has been extensively used for research on the lateralization

of various cognitive functions over the last few decades. As a method the visual half-field

method places minimal demands on the experimenter, as it can be set up easily with the help of a

computer, a microphone and a button box (or keyboard) (Hunter & Brysbaert, 2008).

In one of the earliest studies, Mishkin & Forgays (1952) presented words unilaterally to

the left or the right of fixation to investigate visual hemifield asymmetries in visual word

recognition and found a right hemifield advantage. In a later study, Hines, Satz & Clementino

(1973) found better recall for digit sequences presented in the right visual half-field for right

handers. Apart from measuring effects for processing of verbal tasks, Ornstein, Johnstone,

Herron & Swencionis (1980) reported higher right hemisphere engagement in visuo-spatial tasks

with the exception of mental rotation.

Using the visual half-field paradigm in combination with ERPs, Kayser et al. (1997)

demonstrated right hemispheric specialization for processing pictures with negative valence.

Michimata (1997) showed a significant right hemisphere/left visual field advantage in judging

for coordinate spatial relations. Earlier, Laeng & Peeters (1995) had shown left and right

hemisphere advantages for categorical and coordinate judgment tasks respectively. Nagae &

Moscovitch (2002) showed that the recall of emotional words was more dependent on the right

cerebral hemisphere as compared to the left cerebral hemisphere. Wilkinson & Halligan (2002)

showed that the right hemisphere is faster and more accurate than the left hemisphere in judging

pre-bisected lines, in a perceptual landmark task. Koivisto & Revonsuo (2003) showed that the


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right hemisphere is more adept at gauging the overall shape of objects from memory while the

left hemisphere is adept at matching whether the parts of objects match with memory

representations. In a different area, Coulson & Williams (2005) used the visual half-field method

in combination with ERPs and found evidence for right hemisphere involvement in joke

comprehension.

Despite churning up numerous findings regarding the lateralization of a wide array of

cognitive functions at the behavioral level over the last three decades, there have been doubts

about the reliability and validity of the findings that came from visual half-field research.

Hunter & Brysbaert (2008) reviewed the problems associated with the method and

recommended a series of steps to strengthen the paradigm. For instance, Voyer (1998) pointed

out that the reliability of VHF tasks was only 0.56 for verbal tasks and 0.28 for non-verbal tasks.

Moreover, the VHF advantages correlated only at 0.26 with the ear advantages (indexed in a

dichotic listening task) for the same participants. Attempts at revalidating findings from the VHF

experiments with more recent methods like functional transcranial doppler sonography (fTCD)

have also not always yielded encouraging findings. Krach, Chen & Hartje (2006) measured

hemispheric differences in blood flow in a word generation task, also they sought to compare the

laterality indices (LIs) obtained from a VHF experiment to those obtained from fTCD. They

found that the individual VHF differences did not correlate with the LIs based on fTCD in the

word generation task measured during the VHF task (r=0.18, n=58).

Overall there has been criticism about the validity of behavioral tasks for the

measurement of the laterality of language and other functions, for instance Heron (1957) argued

that VHF differences were caused by attentional biases towards either visual field and not due to


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hemispheric specialization. Hunter & Brysbaert (2008) observed that these criticisms were

probably due to many of the earlier tasks being suboptimal. Further, they predicted that some of

the low correlations reported were possibly due to bad testing rather than to the fact that VHF

differences are not fit for assessment of cerebral lateralization. Hunter & Brysbaert (2008)

recommended several steps to design a good VHF task:

Having a considerable number of trials.

Using matched stimulus sets to be presented across visual half-fields.

Using bilateral stimulus presentation (also recommended by Boles (1990)).

Using clearly visible stimuli.

Using adequate fixation control at the beginning of a trial.

Also testing left-handed participants to increase the range of LIs.

Possibly validating against an fMRI study.

They used the recommendations to design VHF picture naming and word naming tasks

respectively; and compared LIs obtained from RT (reaction time) patterns in these tasks to the

LIs obtained in the same individuals during a mental word generation task in the fMRI scanner.

A direct link was established between the findings of the two behavioral tasks and the fMRI task;

as participants with a clear RVF advantage in the picture and word naming tasks were shown to

be left hemisphere dominant in the scanner, while the ones with a clear LVF advanatge turned

out to be right hemisphere dominant. The authors concluded that a well designed visual half field

task can be used to assess language lateralization reliably. A further validation was provided by

Van der Haegen, Cai, Seurinck & Brysbaert (2011) who used the same tasks and tested a large

sample of 250 left handers and again compared the obtained LIs with those obtained in the fMRI

scanner; and found that none of the left handed participants who showed clear right visual field


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(RVF) advantages in the VHF word and picture naming was found to have bilateral or right

hemisphere dominance in the scanner, while 80% of those participants with a consistent LVF

advantage for both picture naming and word naming showed right hemisphere language

dominance in the scanner. Such a finding can be taken to make a strong case for using VHF tasks

for assessing cerebral lateralization of not only language related functions but also for other

cognitive functions as well, if the tasks are well designed or designed in accordance with the

recommendations of Hunter & Brysbaert (2008).

Using the VHF method has advantages over choosing neuroimaging techniques like,

fMRI, PET, fTCD etc. right at the onset of a new hypothesis. As mentioned earlier, setting up a

VHF task is cheap and easy, both in terms of resources and also the knowhow to handle the data

afterwards; while on the other hand each fMRI scan can cost up to a few hundred Euros, and

sophisticated technical knowledge about data gathering and analysis is required. This makes it

practically difficult to test new hypotheses directly using these techniques, or for that matter

testing hypothesis on a large sample of participants. Further, it might be beneficial first to test

new hypothesis on a behavioral level and later take the same for testing with a scanner.

Recent developments in visual half-field research, particularly, the new and improved

version of the paradigm offered by Hunter & Brysbaert (2008) has created exciting opportunities.

The paradigm needs to be tested for its performance with a variety of cognitive functions; there

are possibly two ways in which this can be done, firstly we need to design experiments that test

the pre-established notions of lateralization about various cognitive functions; and secondly to

test whether the paradigm can demonstrate complementary patterns of lateralization for the

participants that are typically and atypically lateralized for speech.


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Electro-encephalographic (EEG) and Magneto-encephalographic (MEG)

Methods

Electroencephalography and Magneto-encephalography are two closely related methods

that gauge brain functions and cerebral activity by reading variations in the electric fields and

magnetic fields over the cortex respectively.

The EEG instrumentation consists of a set of scalp electrodes coupled to a high

impedance amplifier and a digital data acquisition system. The system is capable of recording

data from 2 to 512 EEG electrodes placed over the scalp. First developed by Hans Berger in the

1920s (Berger, 1929) this method can record brain activity with high temporal resolution.

MEG (magnetoencephalography) is a comparatively younger method developed by

physicist David Cohen (Cohen, 1972). The MEG is a more sophisticate technique, requiring the

set up of expensive superconducting quantum interference devices (SQUIDs)- based

magnetometers housed in a magnetically shielded room; recording from upto 512 MEG sensors

with high temporal resolution.

Both techniques have a high temporal resolution and are capable of recording very fast

brain events of a duration of 1 ms or even less. Such a capacity allows the investigation of

transient neural activity indexed in event related potentials (ERPs) or magnetic fields (ERFs)

which are brain responses related to the presentation of a stimulus, detectable with the averaging

technique employed in data analysis (Celesia & Brigell, 1992).

While the EEG and MEG methods are both based on neuro-physiological and

electromagnetic processes, there are differences between them too. MEG as a method is much

costlier to use than EEG; though MEG signals are free from possible artifacts that might affect


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EEG signals. Also MEG signals are less distorted by the resistance of the skull and the scalp

tissue. Further, as the decay of magnetic fields over distance over the scalp is more pronounced

than electric fields, MEG signals are more sensitive to superficial brain activity. These set of

differences together make it easier to interpret data form MEG signals. However, there are some

advantages of using EEG over MEG too, as for instance with the EEG electrodes being placed

directly over the subjects scalp head movements are easily taken into account than in MEG.

The use of EEG and MEG also has the advantage of high temporal resolution over

hemodynamic neuroimaging methods like fMRI (functional magnetic reasonance imaging) and

PET (positron imaging tomography), both of which have a low temporal resolution.

With these special characteristics, the EEG and MEG methods can be ideal to gauge the

temporal asymmetry between the two hemispheres. For example: given its adeptness at handling

verbal material, the left hemisphere may respond with shorter latencies than the right hemisphere

in a task that uses verbal stimuli. Employing techniques as the visual half-field method (Hunter

& Brysbaert, 2008) or the dichotic listening paradigm (DL, Tervaniemi & Hugdahl, 2003) it is

possible to present stimuli in a lateralized fashion and observe differences in speed/accuracy of

the two hemispheres in terms of responses; the differences assumed to reflect the relative skill of

a particular hemisphere with respect to the stimuli being processed. While there are many ways

in which hemispheric asymmetries in function can manifest, in terms of differences in activations

or response latencies, laterality indices may serve well to illustrate the brain’s hemispheric

specialization for a given task pertaining to specific stimuli. In EEG/MEG studies, laterality

indices can be computed on ERP/ERF amplitudes and from frequency data (Brancucci, 2010).

EEG/MEG measures of hemispheric asymmetries have been found to be considerably stable over

time, within one subject (Brancucci, 2010).


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The EEG/MEG methods have been successful at uncovering various behavioral

asymmetries in humans, especially in the auditory domain. EEG/MEG has been used to

investigate lateralization of language related functions, mainly due to their high temporal

resolutions which affords a distinct advantage over the hemodynamic methods. Several findings

can be cited to illustrate the usefulness of these methods. The magnetic mismatch negativity

(mMMN; a cortical response to infrequent stimuli in a series) to language stimuli has been

shown lateralized to the left hemisphere in right-handed subjects for vowels (Naatanen et al.,

1997), fricative sounds (Lipski & Mathiak, 2007), syllables (Shtyrov et al., 2000), and words

(Pulvermuller, 2001). Similarly, a MEG study showed that while in the right hemisphere, the

mMMN elicited by an infrequent chord change was stronger than an mMMN elicited by a

phoneme change; the mMMN strength for a chord versus phoneme change did not differ

significantly; indicating at the specialization and sensitivity of the right hemisphere for musical

sounds (Tervaniemi, et al., 1999). Several specifically language related EEG/MEG components

have also been identified and reported over the last decade or so, having different temporal and

spatial characteristics. The N400 component has been found to index sematic processes, and is

elicited in terms of bilateral centroparietal negativity after the onset of a semantically anomalous

word in a particular context (Kutas & Hillyard, 1980). It is thought to be generated at the anterior

part of left inferior frontal lobe (Nobre & McCarthy, 1995). Syntactic processes on the other

hand, have been found to be indexed in either a left anterior negativity between 150-200ms for

phase structure violations (Friedrici et al., 1993) or between 300-500ms for morphosyntactic

violations between lexical elements (Coulson et al., 1998) or finally in a late bilateral

centroparietal positivity around 600ms, the P-600 (Osterhout & Holcomb, 1992). EEG/MEG as

methods, have also been compared with the traditional WADA test (Wada & Rasmussen, 1960)


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and fMRI (Kamada et al., 2007; Steinbeis & Koelsch, 2008) to demonstrate that they can be

reliably used as tools for the determination of language dominance. In the same vein, Ressel et

al. (2006) developed a tool to investigate hemispheric dominance and temporal aspects of

cortical linguistic processing based on a verb generation task and a vowel identification task

respectively. While the verb generation task elicited left lateralization in frontal brain regions;

the vowel identification task yielded significant left lateralization in posterior language regions.

Apart from their obvious utility in studies dealing with language and related functions,

EEG/MEG have been useful in various frontal lobe asymmetries which index affective and

cognitive well being of individuals. For instance, Fox & Davidson (1986) found that babies

exhibited greater left frontal EEG when confronted with sucrose (pleasant taste) compared to

water (neutral taste) or citric acid (unpleasant taste). Similarly, Kline et al., (2000) reported that

elderly women showed greater relative left frontal activity in response to a pleasant odor as

compared to a neutral or unpleasant odor. On a different note, frontal activity asymmetries

indexed via electromagnetic activity have also been linked to depression and related affective

disorders. For instance, individuals with a history of depression have been found to demonstrate

a pattern of asymmetrical resting EEG activity over the frontal cortex that is different from never

depressed persons (Allen et al., 2004).

Finally, EEG/MEG methods are being used in combination with other techniques like the

TMS (transcranial magnetic simulation; Thut & Minussi, 2009), fMRI (Kircher et al., 2004) and

the ultra low field (ULF) MRI signal methods to devise more advanced methods of investigating

brain functioning with increasing precision as far as both temporal and spatial resolutions are

concerned.


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While the EEG/MEG methodologies have been hailed for their good temporal resolution,

hemodynamic imaging methods have been useful in determining the areas in the brain involved

in specific cognitive functions. Emergence of hemodynamic brain imaging techniques like

positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have

given a whole new impetus to uncovering different functional networks in the brain and

hemispheric specialization (Frackowiak, Friston, Frith, Dolan, & Mazziotta, 1997). In the next

section, I will review important evidence for hemispheric specialization discovered using

hemodynamic imaging methods.

Hemodynamic Neuroimaging Methods

Functional brain imaging techniques as PET & fMRI have been extensively used in the

study of functional brain asymmetries for over a few decades (Toga & Thompson, 2003). With

different tracer compounds PET technique can map the rates of regional blood flow, and even

oxygen and water to different brain areas. Similarly, the fMRI technique can monitor blood flow

in real time during cognitive tasks. The blood flow varies as a function of brain activity and is

useful for identifying cortical areas involved in tasks for e.g. reading, speaking or visual search

etc. Later, statistical mapping techniques are used to compare activation in different brain areas

(Friston, 2003) within and between the two hemispheres.

Functional brain imaging studies have not only been useful in uncovering functional

brain asymmetries, they have also been useful in establishing structural asymmetries of the brain

(Hugdahl, 2011). For instance, in a voxel based morphometric analysis of the interaction for

handedness, sex and structural asymmetry, Good et al. (2001) found significant asymmetry of

cerebral grey and white matter in the temporal, occipital and frontal lobes including Heschl’s

gyrus and planum temporale regions; males demonstrated significantly more leftward asymmetry


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in Heschl’s gyrus and planum temporale compared to females. Similarly, Pujol et al. (2012)

found significant white matter asymmetry in language-related regions of the brain, in their

volumetric magnetic resonance imaging study of 100 healthy right-handed participants. At the

same time they found a rightward asymmetry for a temporo-parieto-occipital region. Also,

Greve, Van der Haegen, Cai, Stufflebeam, Sabuncu, Fischl, & Brysbaert (2013) used the surface

based analyses technique of fMRI data and demonstrated differences in cortical surface areas in

the superior temporal gyrus (STG) and fusiform gyrus between 34 left hemisphere language

dominant and 21 right hemisphere language dominant individuals.

Further, according to Hugdahl (2000) the introduction of hemodynamic brain imaging

methods, such as PET and fMRI have brought a new impetus to the research on the

specialization of the two cerebral hemispheres. For instance, Pujol, Deues, Losilla & Capdevila

(1999) demonstrated in a sample of 50 right and 50 left handed participants, that while 96% of

the right handed participants showed left hemispheric lateralization of language only 76% of the

left handed participants showed left hemispheric lateralization for language. Similar findings

were reported by Knecht et al. (2000) for healthy subjects, by Holland et al. (2001) and

Szaflarski et al. (2012) for children, with indications that this left hemispheric specialization

increases with age. fMRI has been useful in studying asymmetry for other cognitive functions as

well. With respect to emotion, for instance, Canli, Desmond, Zhao, Glover & Gabrieli (1998)

demonstrated left hemispheric lateralization for positively valenced pictures, and right

hemispheric lateralization for negative pictures. Wildgruber et al. (2004) demonstrated

predominantly right hemisphere activation for comprehending affective prosody. Further,

Virginia et al. (2000) used fMRI in combination with data from lesion studies and compared


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hemispheric preference for visuospatial tasks; they found a major role for the parietal areas of the

right hemisphere in visuo-spatial tasks.

Hence, there is plenty of evidence for the multifaceted use of direct neuroimaging in

investigating brain function in general and hemispheric specialization in particular. However,

running a neuroimaging study is not all that easy and hassle free. Right from setting up a

specialized lab with sophisticated instrumentation to the task of handling the complex data; the

technology of neuroimaging requires huge investment, and therefore, is still limited in its

availability to the wider research community. It is indeed expensive to collect data for several

kinds of studies, which is perhaps reflected in the small numbers of participants in most

neuroimaging studies. For a fast growing field of research like that of hemispheric specialization,

with more and more new hypotheses being generated this might present a handicap. Precisely for

this reason it is important to keep the traditional behavioral methods alive and running. It might

indeed be economical to design robust experiments with the behavioral counterparts like the

visual half-field method and the dichotic listening paradigm, before proceeding to test the

participants with methods such as PET, fMRI etc. Nevertheless, the neuroimaging methods

provide us with direct spatial localization of the cortical areas involved in different cognitive

functions and therefore are very important and indispensable for laterality research.

In the last section, I briefly reviewed some of the methods that have been used by

researchers to investigate into the functional asymmetries of the brain. Using these different

methods over the past many decades, researchers have documented evidences for hemispheric

specialization for various cognitive functions. In the next sections, I will review some of the

evidence that has been drawn from clinical studies of brain damaged patients, i.e. patients with

lesions in parts of their brain, split brain patients i.e. patients whose corpus callosum (bunch of


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neural fibers connecting the two hemispheres) has been severed, and also from neurologically

intact and healthy individuals.

Evidence of hemispheric specialization: from Clinical Studies

Clinical studies of patients suffering from brain lesions are quite informative for

researchers studying questions about the relationship between mental functions & neural

substrates. Not only the fact that lesions in the brain cause disturbance of normal cognitive

functioning, illustrating the relationship between brain & behavior, lesions in the brain have also

been the most dramatic demonstrations of cerebral asymmetry, in that lesions in the left

hemisphere regions of the brain lead to a loss of verbal functions while lesions to the right

hemisphere lead to the loss of non-verbal functions like visuo-spatial processing, emotion

processing etc. For instance: Bryden, Hecaen & DeAgostini (1983) reviewed 130 right-handed

patients with cerebral lesions and found that while 51% (36/70) of the patients with left

hemisphere lesions had aphasia in comparison to only 8% (5/60) with right hemisphere lesions;

52% (31/60) patients with right hemisphere lesions had problems with spatial cognition (e.g.

spatial agnosia, spatial dysgraphia, loss of topographical memory) in comparison to only 23%

(16/70) with left hemisphere lesions.

Different disorders resulting from brain lesions have indicated the importance of the

lesioned brain areas with regards to the affected mental function. Some of the examples are:

Broca’s Aphasia: Patients suffering from lesions to the posterior portion of the third, or

inferior, frontal gyrus anterior to the primary motor area in the left hemisphere of the brain;

typically produce telegraphic or agrammatic speech, omitting articles function words, such as

articles or prepositions.


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Wernicke’s Aphasia: Lesions to the posterior portion of the superior temporal gyrus, i.e.

the first temporal gyrus on the parietal-temporal junction of the left hemisphere lead to a disorder

commonly referred to as Wernicke’s aphasia. Patients typically produce fluent, effortless

utterances though consisting of meaningless jargon, “syntactically and prosodically well formed,

but irrelevant and empty of content”.

Prosopagnosia: This is a disorder of face recognition wherein a person fails to recognize

faces. According to Benton (1980) this deficiency can exist for recognizing familiar faces,

caused by mostly right hemisphere lesions; and for discriminating between unfamiliar faces,

which could be due to partly bilateral but majorly right hemisphere lesions. Lesions leading to

prosopagnosia may involve the parieto-occipital regions bilaterally, though unilateral damage to

the posterior portions of the right hemisphere is also sufficient to disrupt facial recognition

capacities.

Apart from clinical studies of manifested disorders, studies making use of methods like

WADA & ECT (electro-convulsive therapy) also provided researchers with valuable insights.

The Wada test developed by Wada (1949) involved inducing hemispheric inactivity by injecting

barbiturate sodium amytal in the ipsi-lateral carotid arteries. While the target cerebral

hemisphere is rendered inactive, the researchers can test for the more or less severely affected

cognitive functions and evaluate the relative involvement of the two hemispheres. ECT

originally used for treating patients with severe depression also provided means for the

determination of language dominance, as unilateral ECT treatments caused temporary dysphasia

in the patients.


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However, Bradshaw & Nettleton (1983) have pointed out that although clinical studies

have provided high volumes of information about brain functioning, the findings are beset by

several problems of interpretation. While on one hand the clinicians have little control over the

extent & influence of the lesions in their patients; it is a harder task to locate the specific cause of

specific cognitive symptoms. Moreover, individual differences between patient’s prior

experiences, such as age, education, motivation etc. make it difficult to build theories which can

be easily generalized to the rest of the population.

In the next section, I will present converging evidence obtained from the study of split-brain

patients.

Evidence of Hemispheric Specialization: from Split-brain patients

There have been various speculations about how the two cerebral hemispheres function.

Interestingly, the brain has even been visualized as a “double organ” (Holland, 1852). Certain

theories proposed that each cerebral hemisphere could be assumed to be a perfect organic whole

capable of functioning alone as an organ of thought, or that the two cerebral hemispheres, if left

alone might develop differently & independently (Zangwill, 1976).

While it was initially thought impossible to examine the functioning of each cerebral

hemisphere in isolation, commissurotomy operations performed with patients having epileptic

seizures, opened the isolated hemispheric functioning to empirical investigation. The corpus

callosum and anterior commissures connect the two cerebral hemispheres and co-ordinate the

functioning of the two hemispheres. In some patients with epilepsy these connecting fibres were

surgically severed to control the spread of epileptic seizures. Such an arrangement makes it

possible to examine the functioning of the two hemispheres in isolation. As the left & right


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hemispheres are disconnected and cannot communicate with each other, researchers used a

variety of ingenious methods to test their functioning, with regards to specific cognitive

functions, termed as positive competence of each hemisphere (Zaidel, 1983).

R.W. Sperry received a Nobel Prize in 1981, for his pioneering work with the

hemispherectomy patients of P.J. Vogel & J.E. Bogen. In his early work during the 1960s,

Sperry demonstrated the basic effect of splitting the two hemispheres; where the left hemisphere

was shown to dominate verbal functions. Later, from around 1968 to 1972 Sperry demonstrated

the complementary abilities of the right hemisphere in terms of nonverbal, visuospatial tasks.

Finally, Sperry also contributed to the development of new testing procedures, for instance,

chimeric stimulation and Zaidel’s scleral contact lens techniques (Bradshaw & Nettleton, 1983).

In order to test patients with commissurotomy operations for cognitive functions, it is

necessary to present information to only the targeted hemisphere, and elicit the relevant response

from only that hemisphere (see Efron, 1990) for a detailed discussion.

The human nervous system is arranged in such a way that sensory information from each

half of the body, projects directly only to the contralateral hemisphere and then via the corpus

callosum to the ipsilateral hemisphere. More specifically, tactile information presented to the

right limbs is first projected to and processed by the left hemisphere. Similarly, visual

information from the left or the right hemifields is also processed by the contralateral cerebral

hemisphere. Using this anatomical arrangement of the nervous system, testing techniques present

information to only one of the hemispheres and evaluate its adeptness at processing different

stimuli. The resulting findings have elucidated patterns of hemispheric superiority in different


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functions, establishing the roles of the left & right hemispheres in verbal & nonverbal (visuo-

spatial) information processing.

Patients who have undergone commissurutomy can verbally report words or pictures

flashed to the RVF or objects touched by the right hand; while they can’t verbally report these

stimuli if they are flashed to the LVF or touched by the left hand. The right hemisphere takes to

reporting or identifying stimuli by pointing or producing a selection response involving the left

hand. Further, while the right hand stays better in writing, the left hand may demonstrate better

capabilities in drawing, copying, block construction and other tasks involving processing spatial

relations.

While it may be useful to study the positive competences of each hemisphere in isolation,

there are some limitations to the data provided by these patients (e.g. Whitaker & Ojemann,

1977). Most of these patients have had long periods of abnormal neural functioning & epileptic

seizures; and this may have influenced the functioning of the hemispheres in unverifiable ways,

even though Hellige (1993) remarks that this might be a strong point of hemispherectomy studies

as uniform findings in spite of individual differences among patients make it more impressive.

For reasons pointed out at the end of each of the two earlier sections, research into

hemispherical asymmetries of the normal, neurologically intact human brain becomes

indispensable. Indeed, research with normal and healthy individuals’ forms a large chunk of the

studies that have looked into the lateralization of cognitive functions. In the next section, I

review evidences from normal individuals.


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Evidence of Hemispheric Specialization: from Neurologically intact

individuals

While several methodological considerations come in the way of interpreting &

integrating data from the clinical & hemispherectomy studies into the mainstream theories, the

neurologically intact brain has its own set of problems for researchers. In normal subjects,

although one can be sure of morbidity and surgical trauma being absent, the interaction between

the hemispheres is not entirely controlled. The commissures between the two hemispheres are

functioning normally and may be operating in both facilitatory & inhibitory ways to mediate the

transfer of sensory, perceptual, or mnemonic information between the two hemispheres

(Bradshaw and Nettleton, 1983).

Therefore, even though researchers may adopt similar ways for stimuli presentation and

testing participants, e.g. lateralized (unilateral/bilateral) presentation of visual or auditory

information through tachistoscopic or dichotic procedures, dependent measures like reaction

time differences or ear advantages may vary because of a wide variety of possible confounds.

I will now briefly mention a few examples of such differences observed in visual and

auditory modalities; where differences between visual fields or ears have indexed superiority of

either hemisphere in information processing.

RVF superiority has been reported for laterally presented single-letter stimuli, with

accuracy of recall being the dependent variable (Bryden, 1965, 1966; Bryden & Rainey, 1963);

and also for reaction time measure in letters of various languages e.g. for English letters (Geffen,

Bradhsaw & Wallace, 1971) or for Hebrew letters (Carmon, Nachshon, Isseroff, & Kleiner,


P. | 34

1972). A RVF advantage has also been found in terms of reaction time and recall accuracy for

unilaterally and even bilaterally presented words (Bradshaw, Nettleton & Taylor, 1981).

Conversely, LVF superiority has been documented for a variety of nonverbal tests such

as: lightness discrimination (Davidoff, 1975), color discrimination (Davidoff, 1976; Hannay,

1979; Pennal, 1977), dot detection (Davidoff, 1977; Umilta, Salmaso, Bagnara, & Simion, 1979),

and dot localization (Bryden, 1976). Further, LVF advantage for accuracy has also been

documented with photographed faces (Hillard, 1973) and even cartoon line drawing (Ley &

Bryden, 1979); along with reaction time advantages for photographs (Rhodes & Woodling,

1989) and schematic drawings (Patterson & Bradshaw, 1975).

Auditory studies testing for lateralization have been carried out using the dichotic

listening procedure; where right or left ear advantages indicate the dominance for left or right

hemisphere respectively. Typically, a standard dichotic listening procedure involves presenting

participants with two different auditory stimuli (often speech syllables), to the different ears

using headphones. Efficiency of processing these stimuli is measured and the difference between

the two ears is termed as an ‘ear advantage’. A right – ear advantage (REA) with dichotically

presented digits was reported by Kimura (1961). Further, a REA was also reported with words

(Dirks, 1964), nonsense sounds (Curry, 1967), and speech played backwards (Kimura & Folb,

1968), and with consonant-vowel syllables (Shankweiler & Studdert-Kennedy, 1967).

Left-ear advantages (LEAs) were reported for sound stimuli preferentially processed by

the right hemisphere, e.g. melodies (Kimura, 1964; Spree, Spellacy, and Reid, 1970; Goodglass

& Calderon, 1977), musical chords (Gordon, 1970), synthetic musical tones (Cutting & Rosner,


P.| 35

1974), piano tones (Sidtis & Bryden, 1978), and environmental sounds e.g. dish-washing,

phones ringing, dogs barking, clocks ticking etc. (Knox & Kimura, 1970).

Up till now, I have reviewed the growth of the discipline of lateralization research from

being a mythology to a scientific endeavor. I have demonstrated that through the use of a variety

of methods of investigation, researchers have documented many evidences for hemispheric

specialization for cognitive functions. However, this review was largely limited to the research in

20th century.

In the next section, I will review some recent findings related to structural and functional

symmetries between the two cerebral hemispheres.

Structural and Functional Indices of Hemispheric Asymmetry: Recent

Findings

Years of laterality research using many different methods, have furnished evidence of

functional specialization between the two hemispheres of the brain. However, finding a common

underlying principle to explain the vast variety of behavioral asymmetries observed in humans

has been a significant challenge to theorists and researchers alike (Hugdahl, 2000).

Consequently, numerous efforts have been put in to identify a basic principle which may

govern the lateralized organization of cognitive functions in the brain. A number of dichotomies

have been offered as possible factors; for instance, the processing of global vs. local visual

patterns, whereas the left hemisphere is deemed specialized for processing local elements, the

right hemisphere is proposed to be adept at processing global elements (Robertson, 1986).

Another principle proposed is the ability to make categorical vs. coordinate judgments, where

the left hemisphere is specialized for categorical judgments and right hemisphere for coordinate


P. | 36

judgments (Kosslyn, 1987). A third principle that has been offered is the processing of low

spatial frequency vs. high spatial frequency, where the right hemisphere has been found adept at

processing low spatial processing and the left hemisphere being involved in better processing of

higher spatial processing (Sergent, 1983; Ivry & Robertson, 1998).

Unfortunately, none of these principles have been able to account for the majority of

findings and produce consistent empirical evidence over the years. Accordingly, Hellige (1993)

states that, “the quest for a fundamental dimension of hemispheric asymmetry has been

unsuccessful” (p.58).

However, Hugdahl (2000) puts forward the language-visuospatial judgment as a basic

dichotomy that governs the lateralization of cognitive functions in the brain. Hugdahl (2000)

proposes that while the left-right distinction is an important anatomical principle of the brain’s

organization, it must be related to a fundamental principle of functional organization i.e.

language and visuospatial judgment, two capacities which have played an important role during

the course of human evolution. Further, he proposes that the lateralized functional organization

of the brain may be a consequence of the evolutionary pressure on the hemispheres towards

specialization for these functions. More specifically, it has been proposed that language and

related functions maybe lateralized to left hemisphere, while functions involving visuospatial

processing and others maybe lateralized to the right hemisphere; due to crowding (Lansdell,

1969, Teuber, 1974). Recent research with atypically lateralized individuals seems to support

these preliminary hypotheses, where it is reported that when language faculty is lateralized to the

right hemisphere, other functions get reversed to the left hemisphere (see Cai et al., 2013, Verma,

van der Haegen & Brysbaert, 2013).


P.| 37

Indeed, no processes other than verbal & visuospatial functions have produced consistent

empirical differences between the two hemispheres since Sperry’s first findings (Sperry, 1974).

With this foreground to the contemporary opinion about lateralization, I will now review

some recent research into structural and functional asymmetries of the brain that lays the

foundation for the current thesis.

Structural Asymmetry between the two Hemispheres

Marie-Francois Xavier Bichat, in his “law of physiological symmetry” proposed that two

structures i.e. the left and the right hemispheres, that look exactly alike should function alike as

well. However, it turns out that neither the two hemispheres look exactly alike, nor that they

function in identical ways (Amunts, 2010).

A detailed review of morphological asymmetries in the brain has been given by Amunts

(2010). She points out that the structural indices of the human brain include: a) macroscopic

features as the volume, shape and size of sulci, gyri and cerebral lobes; b) microstructural

features as the number and density of nerve cells in a brain region, size, volume, surface and

cortical thickness of cytoarchitectonic areas including cellular indices (cell characteristics as:

number of spines, degree of arborization of dendrites and axons) and c) molecular aspects of

brain organization and gene expression.

Further, it is also pointed out that while the macroscopic features and molecular features

can be studied by both in vivo (imaging techniques as MRI, CT, and PET) and in vitro methods

(autopsy, immunohistochemistry etc.), the microstructural features may only be studied via in

vitro methods. While in vitro methods have proved useful in posthumous examination of brain


P. | 38

atrophies, in vivo methods have worked well together with behavioral tests, along with

functional imaging experiments thus being able to observe the brain in action (Amunts, 2010).

Using these methods, researchers have identified numerous instances of structural

asymmetries in the brain at these three levels. Now, I will discuss some of these observed

asymmetries in the structure of the brain and their implications for cognitive function.

The Perisylvian Region: Language and the Auditory Functions

Three main regions of the brain have been put forward as key to the linguistic and

auditory functions of the brain. They are: the primary auditory cortex, the Heschl gyrus, and the

superior temporal gyrus; all three of which lie around the sylvian fissure.

The Sylvian Fissure

The left part of the sylvian fissure has been reported to be longer and more horizontal

than the right part (Eberstaller, 1890; Cunningham, 1892; Jancke & Steinmetz, 2004); with

indication that such a difference already exists at early stages of ontogeny (Le May & Culebras,

1972).

Further, it has been reported that men with consistent right hand preference had longer

left/horizontal segments in the sylvian fissure as compared to men without this preference

(Witelson & Kigar, 1992). Moreover, Hellige et al. (1998) have associated the length of the right

hemispheric sylvian fissure with error rates for detecting briefly presented consonant-vowel-

consonant trigrams.

Hechl Gyrus and Primary Auditory Cortex


P.| 39

The Heschl gyrus with the primary auditory cortex has been reported to be larger in the

left hemisphere than in the right hemisphere, as a result of larger amounts of white matter

underlying the gyrus (Rademacher et al., 1993; Penhune et al., 1996).

The Planum Temporale and Superior Temporal Gyrus

The planum temporale region is located posterior to the Heschl gyrus within the auditory

cortex and continues to the lateral surface of the superior temporal gyrus; it is typically

associated with the Wernicke’s area. The planum temporale region has been reported to be larger

in the left hemisphere in a range of studies (Pfeifer, 1911; von Economo and Horn, 1930;

Geschwind and Lewistky, 1968; Steinmetz, 1996 and Shapleske et al., 1999).

Further, the leftward asymmetry of the planum temporale region has been linked to

measures of functional asymmetry such as handedness and auditory lateralization (Steinmetz et

al., 1995; Steinmetz, 1996). Also, increased asymmetry in the planum temporale has been

associated with better abilities to process musical information; higher asymmetry was reported in

musicians than non musicians and controls (Schlaug et al., 1999) and in people with perfect pitch

than those without perfect pitch (Keenan et al., 2001). Reduced asymmetry on the other hand has

been reported for schizophrenics (Chance et al., 2008).

Broca’s Region

Brodmann’s areas 44 and 45 comprise the key regions of the Broca’s area, and occupy the pars

opercularis and pars triangularis, respectively (Amunts, 2010). The volume of the left area 44

was reported to be larger than the area in the right hemisphere in a two post-mortem studies

(Galaburda, 1980; Amunts, 1999). Also, both areas, 44 and 45, were found asymmetrical with

respect to the laminar distribution of cell bodies (Amunts and Zilles, 2001). Further, the total


P. | 40

number of neurons in area 44 were found to be more in the left side, no statistically significant

difference in the number of neurons could be ascertained for area 45 (Uylings et al., 2006).

Finally, studies have reported that such interhemispheric differences in the cytoarchitecture of

these areas could be found as early as 1 year old infants, it also increased with age (Amunts et

al., 2003).

These differences in the left and right sides of area 44 and 45 have also been linked to

functional features of the brain, for instance, interhemispheric differences in the structure of area

44 is associated with the development of adult like syntactic process, whereas those in area 45

are associated with the development of semantic processing abilities.

Somatosensory and Motor Areas

Hemispheric differences in structure has also been found in several components of the

motor and sensory systems of the human brain, for e.g. caudate nucleus (Watkins et al., 2001),

the cerebellum (Snyder et al., 1995) and the sensory and motor cortices. Also, interhemispheric

asymmetry in structure has been reported for the central sulcus (Davatzikos and Bryan, 2002;

Cykowski et al., 2008) and even though the results are not unequivocal (Amunts, 2010) a

correlation between the depth of the central sulcus and age has been claimed (Cykowski et al.,

2008).

Finally, in vivo morphometry studies of right handed male professional keyboard players

have revealed less asymmetry in the central sulcus than matched controls (Amunts et al., 1997).


P.| 41

The Limbic System

Components of the limbic system mainly implicated with affective and memory functions

have also been reported to demonstrate structural asymmetry. The limbic system includes the

hippocampus, the cingulated gyrus, the amygdale and the habenula.

A number of studies have reported asymmetry in terms of volume and surface of the

hippocampus; for e.g. rightward asymmetry was found in MRI data of 61 healthy volunteers (Li

et al., 2007). Also, rightward asymmetry in hippocampal and amygdalar volume has been

reported (Niemann et al., 2000; Szabo et al., 2001). Further, hippocampal asymmetry has been

shown to decrease with age (Shi et al., 2007).

Significant leftward asymmetry in the thickness of the anterior segment and significant

leftward asymmetry in the surface area of the posterior segment of the cingulated cortex was

reported in a MRI study of 68 healthy subjects and a group of patients with schizophrenia (Wang

et al., 2007).

Brain Areas Involved in Visuospatial Processing

Hasnain et al. (2006) analyzed spatial covariance between human occipital sulci and

other visual areas through retinotopic mapping and found stronger sulcus-function covariance in

the left occipital lobe than the right occipital lobe and suggested that the degree of hemispheric

lateralization is reflected in the strength of correspondence between cortical surface anatomy and

function. Volumetric analyses in a sample of postmortem fetal brains in the Yakovlev Collection

showed that male striate-extrastriate cortices were more asymmetrical than female brains (de

Lacoste et al., 1991).


P. | 42

Brodmann areas 39 and 40 form the parietal cortex and also play a role in the visual

processing in te brain; however claims of rightward asymmetry in terms of volume (Caspers et

al., 2008) have not be backed by other studies (Jancke et al., 1994; Eidelberg & Galaburda,

1984).

Over all, we can say that there is enough evidence for structural asymmetry in the brain.

The degree of asymmetries in structure, has been found to be differ with respect to brain region,

handedness, gender and disease (Amunts, 2010). Also, some of these asymmetries develop

during early stages of ontogeny and interact with age. Finally, it can be concluded that

anatomical symmetry of the brain interacts with the lateralization of cognitive function (Amunts,

2010).

Functional asymmetry in Visuospatial Processing between the Hemispheres

Functional asymmetry refers to the difference in the ability of the two hemispheres at

performing different cognitive functions. As most of the cognitive functions are mediated by

sensory modalities of vision and audition, asymmetries in visual and auditory processing can

serve as windows for better understanding asymmetries in cognition.

Given that my thesis explores lateralization of cognitive functions, mainly through the

visual modality; I will limit the discussion to asymmetries in visual processing.

Hemispheric asymmetries in visual processing exist not only in humans but in other

vertebrate species and primates as well (Hellige, 1996; Rogers and Andrew, 2002; Hopkins,

2007). Given such a pattern, speculations have been made that humans inherited such an

asymmetry during the course of evolution from their ancestors (Hellige, Laeng, & Michimata,

2010).


P.| 43

The nature of hemispheric asymmetry in processing visual information, however, has

been deemed “subtle” and “complementary” across species (Rogers & Andrew, 2002; Hopkins,

2007). More specifically, while both the hemispheres can process all aspects of visual

information to a reasonable extent, they exhibit complementary specializations for e.g. right

hemisphere is deemed dominant for “diffuse or global attention, spatial analysis and no

involvement in control of response” and the left hemisphere is supposed to be dominant for

“focused attention, processing of local cues and control of response” (Rogers and Andrew, 2002;

Hopkins, 2007).

Now, I will briefly examine the various asymmetries in visual processing observed in

humans.

Categorical and Coordinate Spatial Relations

Two most important functions of the visual system is to provide us the information about

“where” and “what” i.e. location and identification of things in the surroundings (Schneider,

1967; Ingle, 2002). Mishkin, Ungerleider & Macko (1983) identify two “cortical visual systems”

i.e. a ventral visual steam that mediates identification and a dorsal stream that mediates location

of objects in the space around us. It is known that both of these streams are duplicated in each of

the two cerebral hemispheres, though it is proposed that the hemispheres are concerned with

qualitatively different aspects of the “where” and “what”.

I will begin with reviewing findings of hemispheric asymmetry in processing the “where”

or the location processing visual systems.

Kosslyn (1987, 2006) distinguishes between “coordinate” and “categorical”

spatial relations between objects that are used by the visual system to compute the location of


P. | 44

objects. Coordinate relations between objects occur within a”metric space” and allow the

perception and expression of distances between objects quantitavely (for e.g. two objects are x

meters apart). Categorical relations, on the other hand express qualitative spatial relations

between objects, and “categorize” space to describe objects as “above”, “below”, “alongside”,

“behind”, “between” or “inside” each other (Pinker, 2007).

Several studies have documented evidence that for the majority of population,

typically right handed, the left hemisphere is adept at processing categorical relations while the

right hemisphere is better at processing coordinate spatial relations (Hellige, 1995; Laeng,

Chabris, & Kosslyn, 2003).

Early evidence in this direction was provided by visual half field studies wher

participants were found to be faster and more accurate in judging coordinate relations when

presented in the left visual half-field and judging categorical relations when presented with such

stimuli in the right visual half-field (Hellige & Michimata, 1989). A range of simple geometrical

figures to more naturalistic figures have been used as stimuli to ask participants to produce such

judgments (Lange, Peters, & McCabe,1998; Roth & Hellige, 1998; and van der Ham, van Wezel,

Oleksiak, & Postma, 2007; Laeng & Peters,1995). However, the visual half field differences in

RTs (reaction times) have been found to be rather volatile (Hellige,& Cumberland,2001) and

small. A meta analysis by Laeng, Chabris & Kosslyn (2003) showed that the left hemisphere is

about 8 ms faster for making categorical judgments and the right hemispheres is just about 14ms

faster for making coordinate judgments, respectively; though these differences were highly

significant (combined Z value = 6.93, p < 0.0001).


P.| 45

Another source of evidence comes from clinical studies. For instance, Laeng (1994)

demonstrated that left hemisphere damaged patients were worse at noticing changes in

categorical relations while they did much better at noticing coordinate relations between stimulus

objects; and right hemisphere damaged patients were much better at noticing categorical

relations but fared badly when asked to judge coordinate relations between stimulus objects.

Similar evidence was also provided in a recent clinical study (Palermo, Bureca, Matano and

Guariglia, 2008).

While there it has been a little difficult to find consistent neuroimaging evidence for these

findings (see Amunts, 2010 for a detailed discussion); some recent studies (Slotnick, Moo,

Tesoro, & Hart, 2001; Trojano, Conson, Maffei, & Grossi, 2006) have used the repetitive

transcranial magnetic stimulation (rTMS) method to support the earlies proposition of left

hemisphere role in categorical relations processing and right hemisphere role in coordinate

relations processing.

Spatial Frequency Processing

Sergent (1983) proposed that the left and the right hemispheres of the brain are more

efficient at processing information carried by channels tuned to the high and low spatial

frequencies respectively. A number of studies have demonstrated evidence that supported this

hypothesis by using spatial frequency filtered stimuli (Jonsson, & Hellige 1986; Michimata &

Hellige, 1987) and sinusoidal gratings (Kitterle, Hellige, & Christman, 1990, 1992).

Further, it has been proposed that the hemispheric differences regarding the processing of

categorical and coordinate spatial relations may be linked to the asymmetry in processing spatial

frequencies (Kosslyn et al. ,1992); and the testing of this hypothesis by Okubo & Michimata


P. | 46

(2002, 2004) has supported the hypothesis. It can therefore be concluded that spatial frequency

processing mediates computation of spatial relations, and hemispheric asymmetry in the former

is reflected in the latter.

We have discussed the hemispheric asymmetries in processing the “where” aspect of

visual processing; now we turn to the “what” question.

Global-Local Processing

Answering questions about “what” an object is, involves processing information about its

composition. Often, an object can be described as having global (larger, holistic) structure that

may be composed in turn by many local (smaller) structures (Navon, 1977). It has been proposed

that while the left hemisphere is better at processing information about these local constituents

the right hemisphere is better at processing information about the larger structure (Sergent, 1983;

Fink, Halligan, Marshall, Frith, Frackowiak, & Dolan. 1996, 1997; and Yamaguchi, Yamagata,

& Kobayashi, 2000).

Evidence supporting this hypothesis has been provided by clinical studies which show

that damage to the left versus the right superior temporal gyrus disrupts local versus global

processing (Ivry, & Robertson, 1998). Also, visual half-field studies have shown a typical RVF-

LH advantage for identifying local patterns and a LVF-RH advantage for identifying global

patterns (Hubner, 1998; Hubner & Studer, 2009; Hopkins, 1997). Neuroimaging studies have

also supported the hypothesis, though the evidence from these studies has been variable (Sasaki,

Hadjikhani, Fischl, Liu, Marrett, Dale & Tootell, 2000; Han, Weaver, Murray, Kang, Yund, &

Woods, 2002 and Amunts, 2010).


P.| 47

Finally, visual processing asymmetries for global-local processing have been linked to

asymmetries in processing spatial processing, i.e. global processing has been proposed to be

mediated by relatively low spatial frequencies while local processing has been proposed to be

mediated by relatively high spatial frequencies (Hellige, 1993, 1995; Amunts, 2010). In line with

these proposals, spatial filtering has been shown to influence the pattern of hemispheric

asymmetry in global-local processing accordingly (Hughes, Fendrich, & Reuter-Lorenz, 1990;

Han et al., 2002; Yoshida, Yoshino, Takahashi, & Nomura, 2007).

Object Discrimination

The hemispheric asymmetry in processing spatial relationships has also been linked to

object discrimination; wherein, a left hemisphere advantage has been proposed for between

category discrimination and a right hemisphere advantage has been proposed for within catgory

discrimination (Amunts, 2010). Several studies have provided supporting evidence for this

hypothesis (Laeng, Zarrinpar, & Kosslyn, 2003; Laeng, Carlesimo, Calta-girone, & Miceli,

2002).

Saneyoshi et al. (2006) conducted a fMRI study and demonstrated relatively greater left

hemisphere contributions to between category object discrimination and relatively greater right

hemisphere contribution to within category object recognition, respectively. Further, Saneyoshi

& Michimata (2009) have also conducted a behavioral visual half-field study, showing a RVF-

LH advantage in RTs (reaction times) for a categorical discrimination task and a LVF-RH

advantage for a coordinate task, using novel objects called ‘geons’ as stimuli.


P. | 48

Face Recognition

As with object discrimination, another basic visual asymmetry in processing global

versus local features mediates a processing asymmetry that has been documented for face

recognition. Cooper & Wojan (2000) pointed out that face identification involves processing

configural, metric or coordinate relations between face-parts (eyes, nose, lips etc.) whereas just

differentiating faces from other classes of stimuli involves categorical processing. Consequently,

it has been proposed that the left and right hemispheres play qualitatively different roles in face

processing (Amunts, 2010). Rossion, Dricot, Devolder, Bodart, Crommelinck, de Gelder and

Zoontjes (2000) used positron emission tomography (PET) in a whole and part based face-

matching tasks and showed greater right fusiform face area during the whole condition and

greater activation in the left FFA during the part condition.

All in all, we have seen that several asymmetries in the processing of visual information

have been reported. It can also be said that asymmetries in processing some fundamental

channels of information (for e.g. spatial frequency) may mediate hemispheric asymmetries in

processing categorical-coordinate spatial relations, global-local processing etc.

I have, now reviewed the methods of investigation, the evidences & also the markers that

have established the functional asymmetries between the two hemispheres of the brain. I will

now introduce my own studies in the next section.

Motivations for the current thesis

Research into the lateralization of cognitive functions has travelled a long way from

being a source of mythical stigmatization of the left handed individuals to being a major topic of

investigation in the empirical fields of neuroscience, neuropsychology, cognitive psychology and


P.| 49

many other related areas. I have surveyed the many methods that have been used to investigate

the laterality of cognitive functions and the functioning of the two cerebral hemispheres. I have

also summarized the evidence for the lateralization of a variety of cognitive functions from

multiple sources.

While there has been plenty of research into the functional specialization of both the

hemispheres, the major body of work leans heavily towards the language-related and other left

hemispheric functions. There are several reasons for this, one of them probably being, as

Hugdahl (2000) remarked, that the language-related functions have consistently given stable

findings over the years. Research with nonverbal stimuli and paradigms has not always produced

consistent results (Whitehouse, Badcock, Goen & Bishop, 2009). Another observation is that for

the development of laterality research, more and more new research needs to be done with the

behavioral methods as an initial point and later supplemented with the sophisticated

neuroimaging techniques available today. Indeed, a lot of work with the Dichotic Listening task

is being done in the lab of Kenneth Hugdahl, who has used the DL paradigm in a variety of areas

in cognitive psychology, clinical psychology, neuroscience etc. In our lab major work has been

done with the visual half-field task as far as lateralization of language is concerned, in both

typically and atypically lateralized populations (Van der Haegen et al., 2011, 2012).

I undertook the task of further validating and testing the version of the visual half-field

task proposed by Hunter & Brysbaert (2008), with respect to cognitive functions other than

language. The idea was to test the task with at least one other left hemispheric and one or more

right hemispheric cognitive function. If possible I would also validate the same task with left-

handed atypically lateralized individuals. Eventually, I was successful in testing the task with

tool recognition (chapters 2 & 3) as a left hemisphere function. I was also able to test the VHF


P. | 50

task with 3 different right hemisphere functions; symmetry detection (chapter 4), figure

comparison & facial emotion perception (chapter 5). I was able to test the symmetry detection

task with a group of atypically lateralized left handed individuals, provided by my colleague Lise

Van der Haegen (Van der Haegen et al., 2011).

Outline of the present thesis

In Chapter 2, I present work with the tool-recognition task, which was pre-established as a left

hemisphere lateralized function. The VHF task used could successfully replicate the RVF/left

hemisphere advantage for tool recognition.

In Chapter 3, I further standardized the stimuli used in the tool recognition and object

recognition tasks and replicated & even enhanced the RVF/left hemisphere advantage for tool-

recognition through our VHF paradigm.

In Chapter 4, I took a right hemisphere lateralized cognitive function of symmetry detection. I

additionally checked whether symmetry detection is lateralized in a complementary fashion in a

sample of atypically lateralized individuals. I found the expected LVF/right hemisphere

advantage for symmetry detection in the typically lateralized right handed and left handed

individuals. I also found an indication for the reversed RVF/left hemisphere lateralization for

symmetry detection in the group of left handed atypically lateralized individuals.

In Chapter 5, I present experiments with figure comparison and facial emotion perception.

While a left visual half-field/right hemisphere lateralization for figure comparison could be

ascertained, the experiments with facial emotion perception served to illuminate a more complex

picture than a straightforward right hemisphere lateralization for all emotions. Additionally, in


P.| 51

the data of the three experiments I investigated for the possible validation of the polarity coding

hypotheses. I found that participants were overall faster for index finger-yes responses.

Finally, in Chapter 6, I will look back at all the studies put together and try to arrive at a

conclusion about the efficacy of the particular VHF paradigm as a viable task to study

lateralization of cognitive functions in general, and right hemisphere functions in particular.

Further, I will also speculate at future research using the VHF task.


P. | 52

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Chapter 2|A right visual field advantage for tool recognition

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Chapter 2: A right visual field advantage for tool

recognition in the visual half field paradigm


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Chapter 2: A right visual field advantage for tool recognition in the

visual half-field paradigm

Neuropsychological and brain imaging studies have shown that the identification and use

of tools mainly involve areas of the left hemisphere. We investigate whether this dominance can

be observed in a behavioral visual half-field (VHF) task as well. To make sure that the VHF

effect was due to laterality and not due to attentional bias, we made use of two tasks: tool

recognition and object recognition. On the basis of the existing literature, we predicted a right

visual field (RVF) advantage for tool recognition, but not for object recognition. Twenty right-

handed participants made judgments about whether one of two bilaterally presented stimuli was

an object/non-object or a tool/non-tool. No VHF/hemisphere advantage was found for object

recognition, whereas a significant RVF/left hemisphere advantage was observed for tool

recognition. These findings show that VHF tasks can be used as a valid laterality measure of tool

recognition.

Introduction

The use and manufacturing of tools are typical human skills, going back to prehistoric times

(Ambrose, 2001); although primates can also be taught to manipulate existing objects in order to

achieve goals. Neuropsychological and brain imaging research have indicated that tool

knowledge in humans not only

This Chapter has been published as Verma, A., & Brysbaert, M. (2011). A right visual field advantage for tool

recognition in the visual half-field paradigm. Neuropsychologia, 49, 2342-2348.


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involves dedicated brain regions but also that these areas are lateralized to the language dominant

(usually the left) hemisphere (Lewis, 2006).

Tool knowledge involves two types of information: (i) knowledge about tools and their

functions, and (ii) the motor skills needed to manipulate tools. Evidence from patients with brain

damage suggests that these two types of information are controlled by different brain areas, as

there is a double dissociation between both functions (Buxbaum, Schwartz, & Carew, 1997;

Buxbaum, Vermonti, & Schwartz, 2000). Patients suffering from ideational apraxia have

problems with the knowledge of tools and their use, whereas patients with ideomotor apraxia are

particularly deficient in the effective manipulation of tools.

Randerath, Goldenberg, Spijkers, Li, and Hermsdorfer (2010) examined 42 patients and

18 healthy controls on tool grasping and typical use of tools. They found that patients with

impaired tool use had a large area of overlap in the left supramarginal gyrus, whereas patients

with erroneous grasping had lesion overlap in the left inferior frontal gyrus and the left angular

gyrus. Goldenberg and Spatt (2009) examined 38 patients with brain damage and compared

appropriate tool use (both for common tools and new tools) and functional associations to tools

(i.e., knowing which recipients are appropriate for a tool and which other tool could be used for

the same purpose). These authors too observed that parietal lesions involving the left

supramarginal gyrus impaired tool use (both common and novel), whereas left frontal lesions

affected tool use and tool knowledge (as assessed by the test for functional associations). Osiurak

et al. (2009) compared 21 left brain damaged, 11 right brain damaged and 41 healthy controls on

experimental tests assessing the conventional use of objects, conceptual knowledge about object

function, pantomime of object use, recognition of object utilization gestures, and unusual use of


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objects. They found that left brain damage patients had more difficulties on the unusual use of

objects than controls or right brain damaged patients.

Brain imaging has also been used to investigate and localize the various components of

tool use. The most frequently used task involves asking participants to pantomime specific tool

operations and to compare these movements to repetitive limb movements (Choi et al., 2001), to

other meaningful hand gestures (Fridman et al., 2006), or to meaningless hand movements

(Fridman et al., 2006; Grezes & Decety, 2001a; Johnson Frey, Newman Norlund, & Grafton,

2005; Moll et al., 2000). Technological limitations often prevent the investigation of real tool

use. Therefore, researchers usually work with imagined operations, asking participants to engage

in mental simulations of tool use; the assumption being that the brain activity during simulation

corresponds to that of the actual operation.

Another frequently used paradigm in the functional neuroimaging literature involves

showing participants pictures of tools vs. pictures of humans, animals, houses, faces, or even

scrambled images, and measuring the differences in brain activity (Beauchamp, Lee, Haxby &

Martin, 2002; Chao, Haxby & Martin, 1999; Chao & Martin, 2000; Creem Regehr & Lee, 2005).

Kallenbach, Brett, and Patterson (2003) argued that the best comparison is tools vs. other

manmade objects, such as houses, because otherwise it is difficult to determine whether the

observed differences in brain activity are tool specific or caused by processing differences

between man-made things and naturally occurring organisms (humans, animals). Other

neuroimaging studies have involved naming tools vs. animals (Chao et al., 1999), or naming

tools vs. actions (Rumiati et al., 2004).


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In line with the neuropsychological evidence, two sets of left-hemisphere brain areas

have been identified in functional neuroimaging: Those related to the identification of tools, and

those related to the motor skills required for tool manipulation. As far as the identification of

tools is concerned, three cortical areas have been identified. They are: the left ventral pre-central

gyrus in the frontal lobe (ventral Premotor Cortex, VPMCx), the left Intraparietal Sulcus (IPS) in

the posterior parietal cortex, and the posterior middle temporal gyrus (PMTG) either on the left

or bilaterally (Beauchamp et al., 2002; Chao & Martin, 2000; Martin, Wiggs, Ungerleider &

Haxby, 1996; Perani et al., 1999). PMTG was particularly involved in a study by Chao et al.

(1999), who compared the perception of tools to that of houses, suggesting that the activity in

this area could be associated with the manipulability of the object (tools vs. houses). Chao and

Martin (2000) showed additional activation of the left VPMCx and the left IPS for the naming of

manipulable tools vs. houses. The left VPMCx has also been shown active during the

pantomiming of tool use, imagining motor actions, observation of movement; hence leading to

the proposal that it stores movement representations and relevant motor information for tool use

(Buccino et al., 2001; Decety et al., 1994; Grafton, Fagg, Woods & Arbib, 1996; Moll et al.,

2000). The left IPS activity has been linked to the retrieval of tool specific grasping movements

(Grezes & Decety, 2001a). Lesion data also suggest that this area is responsible for finger

movement coordination associated with grasping and manipulating objects (Binkofski et al.,

1998).

With respect to the motor skills required for tool manipulation, Frey (2008) combined the

results from apraxia studies and neuroimaging studies, and concluded that retrieval and planning

of these skills involves a network of cortical areas in the left hemisphere, situated in the parietal,

prefrontal, and posterior temporal cortices. Surprisingly, the left hemisphere dominance was also


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observed when the actions were performed with the left hand (Moll et al., 2000). The

involvement of parietal and frontal brain areas in tool related motor responses can be understood

in the light of a proposal made by Heilman, Rothi, and Valenstein (1982). According to this

proposal, parietal sites store representations of skills whereas the frontal sites take part in the

retrieval of the skills during performance. Activation of the left PPC (posterior parietal cortex)

during pantomiming and imagery corroborates the proposal.

In summary, it can be concluded that tool use, as a behavior that is specially advanced

and sophisticated in humans compared to other species (see Boesch and Boesch (1990) for

chimpanzees, and Hunt and Gray (2004) for crows), involves various components that are

lateralized to the left hemisphere.

Interestingly, to our knowledge no one has yet investigated whether the left lateralization

of tool knowledge can also be confirmed in a behavioral study. Neuroimaging techniques, such

as fMRI, are good methods to establish the lateralization of cognitive functions. However, they

also tend to be rather resource intensive, meaning that they are less suited for research on large

groups or for pilot testing. Before the introduction of functional neuroimaging, barely two

decades ago, the common practice was to test the laterality of cognitive functions with

behavioral methods, such as visual half field (VHF) experiments for visual stimuli and dichotic

listening tasks for auditory stimuli (Bradshaw & Nettleton, 1983; Bryden, 1982). So, for tool

identification researchers would have used a VHF experiment and gauged the laterality of the

function by comparing the performance of right handers to stimuli presented in the left visual

field (LVF) with stimuli presented in the right visual field (RVF).


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The VHF technique rests on assumption that a visual stimulus can be processed

more efficiently if it is projected directly to the specialized hemisphere than if it is initially sent

to the nonspecialized hemisphere. Due to the crossing of nasal fibers in the optic chiasm, stimuli

in RVF are projected directly to the left hemisphere, whereas stimuli in LVF are projected to the

right hemisphere. Therefore, the expectation is that tool identification would be better in RVF

than in LVF, given the left hemisphere dominance for this function.

The reason why researchers in tool use may not have thought of the VHF task is that it

has been criticized as a good measure of laterality in the past decades. For instance, Voyer

(1998) showed that the laterality index on the basis of a VHF task has a low reliability (r = 0.56

for verbal tasks and r = 0.28 for nonverbal tasks). Another problem is that VHF tasks usually

reveal some 30% LVF advantage for verbal stimuli in right handers, although it is well

established that right hemisphere dominance in these people is below 5% (Knecht et al., 2000).

Furthermore, there is a low correlation between the laterality estimates of the same participants

based on a VHF task and those based on a dichotic listening task (Kim, 1997). All these findings

have questioned the usefulness of the VHF task and suggested that task related variables may be

more important in the outcome than the fact that the two VHFs have direct access to different

hemispheres.

Hunter and Brysbaert (2008) recently reviewed the task variables that may play a role in

VHF asymmetries and made eight recommendations for the proper implementation of a VHF

experiment. First, because of the low reliability of the VHF asymmetries, experimenters must

present a reasonably large number of trials to the participants. How many depends on the

conclusions one wants to draw from the study. If the goal is to make an individual assessment of

the participants, then more trials will be required than when the goal is to draw conclusions on


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the basis of the grouped data. Second, the stimuli in LVF and RVF must be matched. Otherwise,

the VHF asymmetry may be influenced by the stimuli presented in both VHFs. Third; bilateral

presentation is to be preferred. In this technique, two stimuli are presented simultaneously in

LVF and RVF and a central arrow indicates to which stimulus the participant must respond. This

procedure creates competition between the left and the right hemisphere and also seems to be

better to counteract attentional biases to LVF or RVF (e.g., as a result of the reading direction).

Fourth, the stimuli must be clearly visible, despite the fact that stimulus presentation is limited in

the VHF paradigm (because the participants must not be able to make eye movements to the

stimulus). Fifth, some fixation control must be exerted, to make sure that the stimulus is

presented in the intended hemisphere. If fixation control entirely depends on instructions, there is

no way to exclude participants who fail to follow the instructions. Sixth, the task must be a valid

measure of the function one wants to assess (e.g., a naming task must be used if the experimenter

wants to measure the laterality of speech). Seventh, the stimuli must be optimized to exclude

confounds (i.e., the stimuli should be carefully selected to minimize irrelevant effects due to

factors such as stimulus clarity, stimulus roundedness, stimulus orientation, and so on). And

finally, low correlations are to be expected if the range of participants is limited. The main

outcome of a VHF task (or any other laterality task) is to determine whether a person is left or

right dominant, not whether there are consistent differences in the degree of left dominance.

So, if only left hemisphere dominant participants are tested (who all show the expected

RVF advantage), one is bound to find low reliability data and low correlations with other tasks

(because the differences in RVF advantage between the participants are largely due to noise). If

one wants to test the validity of a VHFtask, one must compare left dominant with right dominant

participants and check whether the VHF asymmetries of both groups are indeed reversed.


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Using these criteria, Hunter and Brysbaert (2008) were able to show that a word naming

VHF task with short word stimuli is a valid measure of speech dominance, as assessed with

fMRI and functional transcranial Doppler sonography. In the present study, we investigate

whether a good VHF task is also able to reveal the left hemisphere dominance for tool

recognition. To further make sure that the VHF asymmetry for tool recognition is related to the

task and not to a general attention bias towards RVF (e.g., because of the left–right reading

direction of the participants), we additionally presented a task, object recognition, for which no

RVF advantage is expected. According to some authors no consistent VHF asymmetries are

expected for object recognition (for a review, see Biederman & Cooper, 1991). Others have

reported a tendency towards a LVF advantage, in particular when the objects are presented in a

non canonical view (McAuliffe & Knowlton, 2001).


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Objects

Non-Objects

Figure 1: Examples of stimuli used in the Object Recognition Experiment


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(A)

(B)

Figure 2: Examples of stimuli used in the tool recognition experiment. (A) Tools & (B) Non-

Tools.


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Method

Participants

The participants were 20 students from Ghent University. There were 14 females and 6

males; all participants were right-handed with a mean laterality index of 73.9 on the Edinburgh

Handedness Inventory. The experiment took 1.5 h in total. Participants were paid 12€.

Stimuli

For the object recognition task, we took line-drawings of 40 objects and 40 non-objects

from the Line Drawing Library developed at the Laboratory of Experimental Psychology,

University of Leuven, Belgium (van Diepen & De Graef, 1994). The objects included in the list

were those encountered in daily life, such as ball, clock, cup, etc. The non-objects were

unnamable, made up images that matched the objects in general shape. The upper panel of Fig. 1

shows three examples of objects used and the lower panel shows three examples of non-objects

used in the object recognition task.

For the tool recognition task, we used line drawings of 30 tools and 30 non-tools from the

IPNP Pictures database (Snodgrass & Vanderwart, 1980). The tools were familiar in daily life,

such as hammer, saw, screwdriver etc. The objects included familiar objects, such as bottle,

candle, shoe, etc. Care was taken to ensure that the tool and non-tool pictures were perceptually

similar (which imposed a strong limitation on the number of pictures that could be used), so that

the tools on average did not have a different shape from the other objects (tools in general tend to

be elongated and are often drawn with the right slant typical for right-hand use). The upper panel

of Fig. 2 shows three examples of tools used and the lower panel shows three examples of non

tools used as control objects.


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It was not possible to use the same pictures for object/non-object and tool/non-tool tasks,

because the Leuven database did not contain enough pictures of tools, whereas the IPNP

database did not include pictures of non-objects. This was a limitation, but not a real problem

because both tasks were run in separate blocks, and we did not expect carry over effects from

one type of drawing to the other. All pictures were sized to 150 × 150 pixels.

Procedure

Participants started by completing the Edinburgh Handedness inventory. They were then

seated in front of a 17” computer screen at a distance of 80 cm. Before the start of each

experiment the participants were familiarized with the pictures that would be presented, by

giving a tachistoscopic presentation of the stimuli (with the same presentation duration as in the

real experiment).

The sequence of presentations was as follows. First there was a blank screen for 1000 ms.

This was followed by a fixation cross (sized 1◦ of visual angle) in the center of the screen for

300 ms. The fixation cross was then replaced by a slide which included an ARROW of 1◦ of

visual angle in the center pointing to the left or to the right, together with a picture in LVF and a

picture in RVF (extending from 3◦ to 7◦). The duration of the slide was 200 ms. Research by

Walker and McSorley (2006) indicated that participants are not able to initiate an eye movement

within 200 ms when they first have to pay attention to a stimulus at the fixation location. The

pictures in LVF and RVF could depict an object or a non-object in the object recognition task,

and a tool or a non-tool in the tool recognition task. The participants were instructed to direct

their attention to the picture to which the arrow pointed, and to ignore the other picture. If the

picture was an object (or a tool) they had to press with their left and right index fingers


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simultaneously; if the picture represented a non-object (or non-tool) they had to press with their

left and right middle fingers. Responses were registered with an external four button box,

connected to the USB port of the computer. We used bimanual responses to avoid the stimulus–

response compatibility effect (i.e., the fact that responses with the right hand are faster to stimuli

in RVF than LVF, whereas the reverse is true for responses with the left hand). Reaction times

were calculated based on the first key press registered.

Eight types of trials were defined, depending on the VHF the participant had to attend to

(LVF or RVF), whether this VHF contained a picture of an object/tool or non-object/non-tool,

and whether the opposite VHF contained a picture of the same category (e.g., tool–tool) or of the

other category (e.g., tool–nontool). This ensured that over trials the same information was

presented in LVF and RVF.

Each task (object decision, tool decision) started with a practice session of 48 trials,

before the main experimental block was administered. The experimental block was divided into

2 parts having 240 trials each. There was a break of 2–3 min between the two parts. The object

recognition task always preceded the tool recognition task, to avoid participants from recoding

stimuli of the object recognition task as tools. Reaction times of the correct responses and

accuracies were the dependent variables.


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Table 1: Showing comparative RT (percentage error) analysis for the two tasks.

Fig 3: Showing significant RVF facilitation for tools, while no such facilitation is seen for

objects.

LVF RVF

Object Recognition YES NO YES NO

Compatible Distractor 430 (17.5%) 460 (10.8%) 420 (17.6%) 470 (9.7%)

Incompatible Distractor 414 (18.1%) 487 (12.9%) 417 (18.9%) 503 (12.9%)

Tool Recognition

Compatible Distractor 469 (17.5%) 467 (12.1%) 456 (16.2%) 460 (10.7%)

Incompatible Distractor 485 (21.2%) 508 (15.1%) 458 (18.7%) 484 (14.4%)


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Results

First, we compared the two tasks with a 2 ×2 × 2 ×2 omnibus ANOVA, containing

task (object/tool), VHF (LVF/RVF), response (yes/no), and compatibility of the distracter picture

(compatible/ incompatible) as independent variables (Table 1). Distracter compatibility refers to

the arrangement of the pictures in the two visual half fields: A compatible condition is a

condition, in which the pictures of both visual half fields belong to the same category (tool, non-

tool, object, non-object), whereas an incompatible condition refers to a situation in which the

pictures of the visual half fields belong to opposite categories. For the RT data, this resulted in a

significant main effect of task type (object recognition = 451 ms, tool recognition = 474 ms; F

(1, 19) = 5.117, p < 0.05), response type (yes = 444 ms, no = 481 ms; F (1, 19) = 17.589, p <

0.001), and distracter compatibility (compatible = 455 ms, incompatible = 470 ms; F (1, 19) =

43.303, p <0.001). The main effect of VHF was not significant (LVF = 465 ms, RVF = 459 ms;

F (1, 19) = 5.117, p = 0.22).

Most importantly, as predicted, there was a significant interaction between task and VHF

(F (1, 19) = 10.231, p < 0.001), which is shown in Fig. 3. VHF was also involved in a significant

three-way interaction with Task and distracter compatibility (F (1, 19) = 7.685, p < 0.05). The

interpretation of both effects will be clearer when we have a look at the individual tasks.

Finally, there was a significant interaction between response type and distracter

compatibility (F (1, 19) = 24.415, p < 0.001). The compatibility effect was only observed for the

noresponses (t (19) = 56.35, p < 0.001). There was no difference between compatible and

incompatible trials in the yes trials (t (19) = 0.576, p = 0.97). The same omnibus 2 ×2 × 2 × 2

ANOVA on the percentages of error only revealed significant main effects of response type (Yes


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= 18.2, no = 12.4; F (1, 19) = 8.622, p < 0.01) and distracter compatibility (compatible = 14.1,

incompatible = 16.6; F (1, 19) = 12.528, p < 0.01).

We ran separate 2 × 2 × 2 ANOVAs for the two different tasks, to separately

understand the effects of the three variables (visual half field, response type, and distracter

compatibility). For the RTs in the object recognition task, there was no significant effect of

Visual Field (F (1, 19) = 0.616, n.s.), but there were significant effects of response type (F (1,

19) = 33.700, p < 0.01) and distracter compatibility (F (1, 19) = 8.998, p < 0.01). In addition,

there were significant interactions between VHF and Response type (F (1, 19) = 4.510, p < 0.05)

and between response type and distracter compatibility (F (1, 19) = 36.172, p < 0.01). The latter

has been discussed in the omnibus analysis; the former is new and is due to the fact that no

responses were 13 ms faster in LVF than RVF (t (19) = 3.379, p > 0.05), whereas RTs were 3 ms

faster in RVF than LVF for yes responses (t (19) = 0.868, p > 0.05). The 2 × 2 × 2 ANOVA on

the percentages of errors only revealed significant main effects of Response type (F (1, 19) =

15.338, p < 0.01) and distracter compatibility (F (1, 19) = 4.916, p < 0.05). The three- way

interaction was not significant (F (1, 19) = 0.262, p > 0.05).

The 2 ×2 ×2 ANOVA of the RTs in the tool recognition task returned the predicted

effect of VHF (F (1, 19) = 8.477, p < 0.01) with faster responses in RVF (465 ms) than in LVF

(483 ms). There was no significant difference between response types (F (1, 19) = 1.88, p >

0.05), but participants were faster in distracter compatible trials than in distracter incompatible

trials (F (1, 19) = 30.448, p < 0.01). VHF was further involved in a significant interaction with

distracter compatibility (F (1, 19) = 4.848, p < 0.05), because the RVF advantage was smaller

with compatible distracters (10 ms) than with incompatible distracters (25 ms). Finally, as in all


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the previous analyses there was a significant interaction between Response type and distracter

compatibility (F (1, 19) = 7.478, p < 0.05). The three-way interaction was not significant (F (1,

19) = 0.019, p > 0.05). The same ANOVA on the percentages of error only revealed a significant

main effect of Compatibility (F (1, 19) = 12.564, p < 0.05). The effects of VHF and response

type failed to reach significance in this analysis (VHF: F (1, 19) = 2.445, p > 0.05; response

type: F (1, 19) = 3.534, p > 0.05).

As the participants were significantly faster on the object/non-object decision task than

on the tool/non-tool decision task (object recognition = 451 ms, tool recognition = 474 ms; F (1,

19) = 5.117, p < 0.05); we further checked whether task difficulty played a role in the LVF

advantage obtained in the tool/non-tool decision task. The reaction times of each participant in

the tool/non-tool decision task were split into a faster and a slower half and were analyzed with

the same 2 × 2 × 2 ANOVA having VHF, response (yes/no) and compatibility as factors. The

analyses revealed that the VHF advantage was the same in the fast half of the trials (RVF = 365

ms, LVF = 382 ms; F (1, 19) = 18.910, p < 0.01) as in the slow half (RVF = 563 ms, LVF = 581

ms; F (1, 19) = 5.114, p < 0.05). The same analysis for the object recognition task revealed that

the VHF asymmetry was absent both in the fast trials (LVF = 352 ms, RVF = 356 ms) and in the

slow trials (LVF = 543 ms, RVF = 548 ms). Given this pattern of results, it is unlikely that task

difficulty was involved in the LVF advantage for tool recognition.

Discussion

In this article we examined whether we could find evidence for left hemisphere

lateralization of tool recognition with the use of a behavioral VHF experiment. As reviewed in

the Introduction, left hemisphere lateralization of tool knowledge has been well established on


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the basis of neuropsychological and brain imaging data (Frey, 2008; Frey, Funnel, Gerry and

Gazzaniga, 2005; Goldenberg & Spatt, 2009; JohnsonFrey, 2004; Kallenbach et al., 2003; Lewis,

2006; Osiurak et al., 2009; Randerath et al., 2010). Showing a similar effect in a VHF task would

not only make a new lateralized function available for behavioral research with healthy

participants; it would also provide a further validation of the VHF task, which has been

questioned.

Our results showed that the expected RVF advantage for tool recognition is observed, if a

basic protocol is used to make sure that participants perform the task under optimal conditions.

In addition, the same advantage was not observed in a very similar task (object recognition) for

which no VHF asymmetry was expected (Biederman & Cooper, 1991). These findings support

Hunter and Brysbaert’s (2008) conclusion that the VHF paradigm is a valid paradigm when used

properly and that researchers can make use of the VHF task to examine the laterality of cognitive

visual functions.

The finding of no VHF asymmetry in the object recognition task is further interesting,

because it deviates from the object naming task, which induces a RVF/left hemisphere advantage

similar to word naming (Hunter & Brysbaert, 2008). In object naming, however, a small set of 5

pictures is shown repeatedly and participants have to name the picture as fast as possible. In this

task, the bottleneck is not to identify the picture but to pronounce the correct name (which is a

left hemisphere function). The difference between the object naming task and the object

recognition task clearly shows the importance of carefully selecting the proper VHF task for the

function one wants to study.


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The finding of no VHF difference in the object naming task is in line with the existing

literature (Biederman & Cooper, 1991). In one of the more recent studies, McAuliffe and

Knowlton (2001) reported a small (8 ms) LVF/RH advantage by manipulating SOA and object

orientation. As we did not change object orientation or manipulate SOA, we did not expect to

trigger differences in perceptual processing between the hemispheres. At the same time, we saw

some evidence for a LVF advantage on the no responses, against no VHF difference for the yes

responses, leading to a significant interaction between VHF and response type in the object

recognition task. It is not clear whether much attention should be given to this finding until we

know more about its robustness. Possible reasons why right handed participants may find it

easier to give no responses to stimuli in LVF could be related to right hemisphere superiority at

processing non familiar shapes or to the fact that participants spontaneously tend to associate no

responses with “left” and yes responses with “right” (Nuerk, Iversen, & Willmes, 2004).

The fact that we found different results for tool/non-tool decisions and object–non-object

decision further confirms that tools form a special category of objects strongly related to specific

movements (Grafton, Fadiga, Arbib, & Rizzolatti, 1997). Most of the tools in our stimuli pool

(razor, axe, hammer) belonged to the class of manipulable objects, which are associated with

discrete activations in left posterior parietal cortex. Tools (as a class of manipulable objects)

encourage automatic engagement of mechanisms involved in the planning of grasping and

reaching movements, activating the left pre-motor cortex during naming/observation (Frey,

2008). It has been proposed that tools when viewed can be processed not only for identity but

also for how they can be used as opposed to other classes of objects (Creem Regehr & Lee,

2005). This proposal hints to the fact that viewing pictures of tools in comparison to objects is

more likely to trigger activations in the brain regions responsible for simulating motor actions


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closely associated with them even when the actions are not overtly performed (Tucker & Ellis,

1998). As these regions largely lie in the left hemisphere (Frey, 2008) a clear left

hemisphere/right visual field advantage is a logical expectation, which was confirmed by our

results.

A slight complication is that the tool recognition VHF task contains 8 types of trials,

rather than the two conditions of neuroimaging studies. The participants not only respond to

tools in LVF and RVF, but in addition they have to respond to stimuli that evoke a no response,

and they are confronted with compatible or incompatible distracters. Both variables have

significant effects: Participants are faster on yes trials than on no trials, and they are faster on

trials with compatible distracters than on trials with incompatible distracters. Luckily, these

variables do not interact with the RVF advantage to such an extent that they wipe out the main

effect of VHF. In addition, later experiments can zoom in on the effects due to the distracter, to

get a clearer image of the inter-hemispheric dynamics in the tool recognition task. Given that the

distracters influence the processing of the targets, there is crosstalk involved, the origin of which

will be interesting to flesh out (see, e.g., Ratinckx & Brysbaert, 2002, for a similar study in

number processing).

All in all, the present study replicates earlier evidence for the left hemisphere

lateralization of tool use by finding a clear RVF advantage of 17 ms for tool recognition. This is

an important step towards establishing valid behavioral estimates of cerebral asymmetry. The

visual half field task as operationalized here is a viable means to assess the laterality of cognitive

functions, the more so because participants only showed the RVF advantage for the tool

recognition task and not for the object recognition task, where no VHF asymmetry was

predicted. The ease with which VHF studies can be run means that this is a more versatile


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technique to examine the details of tool lateralization. Above, we discussed the possibility to

investigate the inter-hemispheric dynamics. Other topics to address are the extent to which the

effect depends on the type of tools (e.g., manipulable or not), and whether the VHF advantage is

fundamental enough to be observed in a tool/nonobject decision task, or whether in that case

tools are processed like other objects. Further questions are how tool use is lateralized in left-

handed individuals, how important the orientation of the tool is (e.g., typical for left or right hand

use) and whether this interacts with the handedness of the participant. Finally, studies with

atypically lateralized individuals can be expected to yield interesting results, as it would be

fascinating to investigate whether tool representations follow language representations and shift

to the right hemisphere in right dominant individuals. The present study calls for a greater

exchange between behavioral and neuroimaging research by providing a behavioral paradigm

that can be used both as a precursor to brain research and in combination with brain research

(e.g., to see to what extent brain activity differs when the stimulus is presented in LVF or RVF).


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basis of pantomiming the use of visually presented objects. NeuroImage, 21, 1224–1231.

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Chapter 3|A validated set of tool pictures with matched objects and non-objects

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Chapter 3: A validated set of tool pictures with

matched objects and non-objects for laterality

research


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Chapter 3: A validated set of tool pictures with matched objects and

non-objects for laterality research

Neuropsychological and neuroimaging research has established that knowledge related

to tool use and tool recognition is lateralized to the left cerebral hemisphere. Recently,

behavioral studies with the visual half field technique have confirmed the lateralization (Verma

& Brysbaert, 2011; Garcea, Almeida & Mahon, 2012). A limitation of this research was that

different sets of stimuli had to be used for the comparison of tools to other objects, and objects to

non-objects. Therefore, we developed a new set of stimuli containing matched triplets of tools,

other objects, and non-objects. With the new stimulus set we successfully replicated the findings

of no visual field advantage for objects in an object recognition task, combined with a significant

right visual field advantage for tools in a tool recognition task. The set of stimuli is available as

supplementary materials to this article.

Introduction

Manufacturing and using tools have been considered important milestones in the

evolution of the human brain and date back at least 2.5 million years (Ambrose, 2001).

Although tool use has been considered as a typically human skill (Oakley, 1956), there is

evidence that many species ranging from birds (Lefebvre, Nicolakakis, & Boire, 2002) to

elephants (Hart, Hart, McCoy & Sarath, 2001), crows (Hunt, 1996), orangutans (van

This chapter has been accepted for publication as Verma, A., & Brysbaert, M. (in press). A validated set of tool

pictures with matched objects and non-objects for laterality research. Laterality.


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Schaik, Ancrenaz, Borgen, Galdikas, Knott, Singleton, Suzuki, Utami & Merill, 2003), capuchin

monkeys (Westergaard and Fragaszy, 1987), dolphins (Krutzen, Mann, Heithaus, Connor, Beider

& Sherwin, 2005) and chimpanzees (Boesch and Boesch, 1990) engage in various forms of tool

use.

Several definitions have been offered to differentiate “tools” from other objects and “tool

use” from other types of behavior. For example: an early definition of tool use offered by Jane

Goodall describes tool use as, “the use of an external object as a functional extension of the

mouth or beak, hand or claw, in the attainment of an immediate goal” (van Lawick-Goodall,

1970, page 195). Alcock (1972, page 464) defines tool use as “the manipulation of an inanimate

object, not internally manufactured, with the effect of improving an animal’s efficiency in

altering the form or position of some separate object”. Finally, Beck (1980, page 10) defines tool

use as “the external employment of an unattached environmental object to alter more efficiently

the form, position or condition of another object, another organism, or the user itself when the

user holds or carries the tool during or just prior to use and is responsible for the proper and

effective orientation of the tool”. However, Preston (1998) observes that various definitions of

tool use basically attempt to formalize for scientific purposes a “folk category” of tool use which

underwrites the definitions of “tools” found in dictionaries, and hence are simply ‘inadequate’.

Indeed, many examples of animal and human behavior can be cited that may not be covered

within these definitions.

To paraphrase the various possible definitions of tools and tool use that differ in their

scope and usefulness (read Preston, (1998) & Amant & Horton, (2008) for a detailed discussion),

a “tool” has to be an “external”, “inanimate” object employed by a user for a “goal-directed”

action. For the purpose of the current study we followed a definition of tools proposed by Frey


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(2007), who defines “tools as manipulable objects that are used to transform an actor’s motor

output into predictable mechanical actions in order to attain specific goals”. Accordingly, all

objects presented as tools in our study were man-made, hand manipulable and had typical and

well-established uses. For example: a hammer is typically associated with driving nails. Hence,

in the current study the tools are defined in “typical” contexts so that we can interpret the

consequent findings in a constrained frame of reference and avoid ambiguity.

Even though a variety of species have been reported to be engaged in tool use, the

understanding and use of tools in humans goes far beyond the animal skills. Evidence indicates

that humans possess specialized neuronal mechanisms allowing them to understand the

functional properties of tools, both simple and complex (Frey, 2007). Not only does the human

brain have dedicated regions for tool use, these regions are lateralized to the left hemisphere,

which is also the dominant hemisphere for language and related functions (Lewis, 2006, Frey

2004). Indeed, a lot of evidence from clinical studies indicates a major role of the left hemisphere

of the brain in accessing and processing the knowledge of tools and tool use. For instance,

Hermsdorfer, Li, Randerath, Goldenberg & Johanssen (2012) found that patients with left

hemisphere stroke exhibited reduced hand rotation at the bowl and the plate in pantomiming as

well as actual use. Randerath, Goldenberg, Spijkers, Li & Hermsdorfer (2010) found a large area

of lesion overlap was found in the left supramarginal gyrus of patients with impaired tool use

whereas lesion overlap in the left inferior frontal gyrus and left angular gyrus for patients who

were impaired in tool grasping. Also, Goldenberg & Spatt (2009) observed that parietal lesions

involving the left supramarginal gyrus impaired tool use (both common and new) and left frontal

lesions affected tool use and tool knowledge. Further, Osiurak et al. (2009) found that left brain

damaged patients had more difficulties on the unusual use of objects when compared to healthy


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controls or right brain damaged patients. Finally, Goldenberg, Hermsdorfer, Glindemann,

Rorden, and Karnath (2007) examined 44 patients with left sided cerebrovascular accidents, and

found that lesions in the inferior frontal gyrus and adjacent portions of the insula and precentral

gyrus led to defective pantomiming ability.

Adding to the evidence from clinical studies, a large number of neuroimaging studies also

demonstrate greater involvement of left hemisphere areas in tasks related to tool knowledge and

use.

Typically, in neuroimaging research, participants are asked to pantomime specific tool

operations, and the brain activity related to these movements is compared with that of repetitive

limb movements (Choi, Na, Kang, Lee, Lee & Na, 2001), meaningful hand gestures or

meaningless hand movements (Fridman, Immisch, Hanakawa, Bohlhalter, Waldvogel, Kansaku,

Wheaton, Wu, and Hallett, 2006; Grezes & Decety, 2001). Other researchers present participants

with pictures of tools vs. pictures of humans, animals, houses, faces, or even scrambled images,

and measure the differences in brain activity (Beauchamp, Haxby & Martin, 2002; Chao, Haxby

& Martin, 1999; Chao & Martin, 2000). It has been suggested that for such comparisons it is best

to compare tools to other man-made objects, such as houses, because otherwise it is difficult to

be sure that the observed differences in brain activity are specific to tool use or could be due to

other categorical differences, such as that between man-made objects and natural, animate

organisms (Kallebach, Brett, & Patterson, 2003).

Using a variety of tasks and paradigms, neuroimaging research has uncovered a range of

left hemispheric cortical areas important for tool knowledge and tool-use behavior. For instance,

the left ventral pre-central gyrus in the frontal lobe (ventral Premotor cortex, VPMCx), the left


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Intraparietal sulcus (IPS) in the posterior parietal cortex, and the posterior middle temporal gyrus

(PMTG) either in the left hemisphere alone or bilaterally (Beauchamp et al. 2002; Chao &

Martin, 2000; Perani, Schnur, Tettamanti, Gorno Tempini, Cappa, and Fazio,. 1999) have been

linked to tool-identification. Johnson-Frey, Newman-Norlund & Grafton (2005) reported that

sites in the left inferior frontal, inferior parietal and posterior temporal cortices are involved in

planning tool use regardless of the hand used. Finally, Kroliczak & Frey (2009) provided

evidence that the left intraparietal sulcus, supramarginal gyrus, caudal superior parietal lobule

and dorsal pre-motor cortices, are engaged in planning both transitive and intransitive actions.

While multiple accounts implicate the left hemisphere superiority in tool- related

behavior, some evidence for right hemisphere contribution in tool processing has also been

reported (Frey, 2008). Specifically, Hamilton & Grafton (2008) reported that right inferior

parietal and right inferior frontal cortices area encode physical outcomes of actions in the real

world. In a similar vein, Hartmann, Goldenberg, Daumuller & Hermsdorfer (2005) reported that

right brain damaged patients had problems in keeping track of multiple step action sequences,

which might be vital for tool-use behavior. Further, while Frey (2008) demonstrates activations

in the left posterior parietal (pPar), dorsal and ventral premotor cortices along with middle

frontal gyrus and frontal and posterior temporal cortices during tool use pantomimes; he also

reports relatively smaller activations in the homologous right hemisphere sites. Also, left handed

patients have been found to show signs of apraxia following right hemisphere lesions also

(Valenstein & Heilman, 1979; Dobatao, Baron, Barriga, Pareja, Vela & Sanchez Del Rio, 2001).

Finally, left handed participants have also been reported to show greater recruitment of right

parietal, frontal and temporal cortices than right handed participants while listening to the sounds


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made by hand-held tools versus the sounds made by animals, reflecting a possible automatic

activation of praxis representations lateralized to the right hemisphere (Lewis, 2006).

Together, findings from clinical and neuroimaging research indicate that knowledge and

skills related to tools, are represented in functionally specialized networks distributed mainly but

not exclusively over the left hemisphere (Frey, 2004). Frey (2004) postulates two major

networks i.e. the conceptual network that represents tool knowledge and consists of areas

displaying activation during semantic tasks and the skill network which consists of areas

activated during retrieval of tool related skills. Major areas represented in the conceptual network

include the left and right fusiform gyri, the left middle temporal and superior temporal gyrus, the

left ventral premotor cortices, Brodmann’s Areas 44/45 (Broca’s area) and the left medial Frontal

Gyrus. The conceptual network mediates tool observation, tool naming, action word generation

and observing action goals. The skill network comprises of Brodmann’s Areas 7, 39, 40, left

medial and anterior inferior parietal sulcii, left dorsal premotor cortices and left medial frontal

gyrus. The skill network accomplishes skill representation/retrieval, reaching, grasping and

manipulation related activities (for a detailed description of the two networks, see Frey 2004).

Tool-use behavior is accomplished by coordinated functioning of the smaller modules of these

two networks, which carry out specific component functions (Frey, 2004).

To examine whether the lateralization of tool-use skills is affected by handedness, Frey,

Funnell, Gerry and Gazzaniga (2005) examined the relationship between hand dominance and

tool use skills by comparing a right-handed male and a left-handed female callosotomy patient

and found a left hemisphere advantage for pantomiming actions associated with familiar tool-

objects and pictures in both patients. Later, Frey (2008) concluded that tool-use behavior in

majority of humans is lateralized to the left hemisphere, regardless of handedness.


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Although tool-use lateralization appears to be unrelated to handedness, tool-use related

behavior appears to be co-lateralized along with the linguistic capabilities of individuals.

Recently, Vingerhoets, Alderweireldt, Vandemaele, Cai, Van der Haegen, Brysbaert, and Achten

(2013) compared a group of typically lateralized individuals with left hemisphere speech

dominance, to a group of atypically lateralized individuals with right hemisphere speech

dominance (as assessed with fMRI) and found that the brain areas involved in tool pantomiming

were lateralized to the same hemisphere as language production, regardless of handedness.

Additional proof was provided by Uomini & Meyer (2013), who demonstrated with fTCD that

acheulean stone tool production and cued word generation caused almost identical cerebral blood

flow lateralization in their participants; and concluded that stone tool making and language are

served by common neural substrates.

Co-lateralization of tool-making or tool-use along with the linguistic capabilities of

humans has been viewed as a significant clue to the co-evolution of both these behaviors in

humans (Frey, 2008). Several authors (Corballis, 2009; Corballis, 2010; Corballis, Badzakova-

Trajkov & Haberling, 2012; Stout & Chaminade, 2012) have explored hypotheses that propose

that language evolved as a result of advances in manual praxis. More recently, it has been

proposed that the human brain is endowed with a system of mirror neurons for observing and

matching actions, which might be homologous to the macaque mirror neuron system (Rizollatti,

2005; Rizzollatti, Fogasi & Gallese, 2001). Further, it has been argued that this mirror system

has aided the evolution of manual gestures (for e.g. grasping) into meaningful communicative

symbols (akin to modern day sign-language) and later into full fledged language articulated

using the vocal tracts in humans (Rizzollatti & Arbib, 1998; Arbib, 2002; Corballis, 2009, 2010).

Researchers have also linked the incidence of population level right-handedness in humans and


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primates to the evolving culture of tool use that posed demands of manual dexterity both in tool

production and manipulation (Corballis, 2009; Steele & Uomini, 2009). However, some authors

are still looking for alternative explanations for the shared neural substrates of tool and language

functions and even their proximity on the evolutionary time-scale (Stout & Chaminade, 2012).

Finally, the mirror system hypothesis and its implications for co-evolution of language along

with tool-use has been a topic of much speculation in the recent years and provides ample reason

for researchers to engage with research both on tool-use and language. Apart from a vast array of

clinical and neuroimaging research the hemispheric dominance for tool use has also been

examined in behavioral studies. Verma & Brysbaert (2011) used the visual half-field (VHF)

paradigm, in which stimuli are presented to the left and to the right of the fixation point and

participants have to respond to the stimuli. The authors found that while there was no visual field

difference for object recognition, a significant right visual field (RVF) advantage was observed

for tools in the tool recognition task, in line with the left hemisphere dominance for tool

processing. Garcea, Almeida & Mahon (2012) used a lateralized masked priming paradigm to

test for a visual half field asymmetry in tool processing. Using tools and animals as target stimuli

and identical or scrambled versions of the targets as primes, they reported that there was a RVF

advantage in priming effects for tool targets but not for animal targets.

Verma and Brysbaert (2011) argued that the strongest evidence for laterality of tool use

in VHF studies is obtained when a tool recognition task is combined with an object recognition

task. The prediction then is that a RVF advantage will be observed for tool recognition, together

with no VHF advantage for object recognition. This pattern of results rules out the possibility

that the RVF advantage for tool recognition is confounded by an uncontrolled variable (e.g., in

the display of stimuli, in the participants’ attention allocation, or in the fixation of the central


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stimulus). A problem for the approach, however, was that it was impossible to find matched

pictures of tools, non-tool objects and non-objects from the same database. As a result, Verma &

Brysbaert (2011) had to compare pictures of tools vs. non-object tools from one source with

pictures of objects vs. non-objects from another source. A similar problem was present in

Garcea, Almedia, and Mahon (2012), who compared different sets of animals and tools as

stimulus categories. Research would be more straightforward if the same pictures could be used

in all comparisons, both as targets and primes.

To have access to better stimulus materials, we decided to compile a new set of stimuli,

which contains matched triplets of tools, non-tool objects, and non-objects, so that research can

examine object and tool recognition in the same study with the same materials. To test the

validity of the new stimulus set, we tried to replicate the findings of our previous study (Verma

& Brysbaert, 2011). As in that study, we make use of two experiments. First, an Object

Recognition VHF experiment will be run, in which participants are presented with pictures of

objects and non-objects in the left and right visual half-field. The participants have to decide

whether the designated picture displays an object or a non-object using bi-manual responses.

Second, a Tool Recognition VHF experiment will be run, in which the same pictures of objects

are presented with pictures of tools and participants have to decide whether the indicated picture

represents a tool or not. The object recognition experiment acts as a control experiment for the

tool recognition experiment. If no visual field difference is observed for the objects in the first

experiment and a significant RVF advantage for the tools in the tool recognition experiment,

then we can safely assume that the VHF advantage is due to tool-specific brain activity and not

to a confounded variable.


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Method

Participants

A group of 39 undergraduate students from Ghent University took part in both the object

decision experiment and the tool decision experiment. They were all right handed and had

normal or corrected to normal vision. The study in total took slightly over one hour and

participants were paid 12€.

Stimuli

We had three types of stimuli drawn by an artist: pictures of objects, non-objects, and

tools. We explained that it was important to have perceptually similar items that were

comparable in terms of overall shape, contour, luminance, and so on. All stimuli were digitally

generated and were similar to the line drawings of the IPNP pictures database (Snodgrass &

Vanderwart, 1980). The object pictures consisted of line-drawings of familiar objects, such as:

book, boot, maize, asparagus, carrot, palm etc. The tool pictures consisted of line-drawings of

familiar hand-manipulable tools like: knife, hammer, comb, pliers, etc. The non-object pictures

were made in such a way that they would match a pairing of an object and a tool in overall

shape, size, etc. Specifically, all figures were sized 150 x 150 pixels and presented as bitmap

images. The figures extended 3 degrees of visual angle. Figure 1 shows three examples of each

category.


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Objects

Non-Objects

Tools

Figure 1: Showing examples of Objects (Non-tools), Non-Objects and Tools. While Objects

and Non-Objects were used in Experiment 1, Objects and Tools were used in Experiment

2.


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In all, we managed to have 38 triplets of matched pictures representing an object, a tool

and a non-object (see the Appendix). All pictures were sized 150 x 150 pixels. To make sure that

our stimuli were perceived by the participants in the way we intended them, we ran two rating

studies using 6-point Likert scales: the Object Rating Scale (ORS) and the Tool Rating Scale

(TRS). In the ORS, 20 participants rated the ‘objectness’ of the object and non-object stimuli.

For each stimulus they indicated how certain they were that the stimulus represented an object;

with 1 = least certain and 6 = most certain. In the TRS, 20 new participants rated the ‘toolness’

of the tool and object stimuli, indicating with a rating from 1 to 6 how certain they were that the

stimulus in question represented a tool (1 = least certain, 6 = most certain).

Figure 2 shows the results of the rating studies. In the Object Rating Scale, 36 of the 38

non-object stimuli, scored between 1 to 3 points, while 2 scored marginally between 3 and 3.5,

indicating that all non-object stimuli were perceived as non-objects by the participants.

Furthermore, all of the 38 object stimuli scored between 4 to 6 points, indicating that they were

easily distinguishable from the non-objects. In the Tool Rating Scale, 34 out of the 38 non-tool

objects scored between 1 to 3 points, 4 objects scored between 3 and 3.5. On the other hand 30 of

the 38 tool objects scored between 4 to 6 points, while four objects scored between 3 and 4, and

four less than 3. The four pictures with tool scores lower than 3 were all musical instruments,

namely a guitar, saxophone, harp, and pipe. The 4 other objects which were not clearly

categorized were cigarettes, zipper, kettle and wristwatch. All scores can be found in the

Appendix.

We decided to use all stimuli in the validation study, so that we had data about all of

them. Of course, researchers are free to omit the less clear ones if they want to run a study

without ambiguous stimuli.


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(A) Object Rating Scale (B) Tool Rating Scale

Figure 2: Mean ratings of the pictures on the Object Rating Scale (ORS) and the Tool

Rating Scale (TRS). In the object rating scale: a score of 1-3 corresponds to non-objects

and a score of 3-6 corresponds to an object. In the tool rating scale: a score of 1-3

corresponds to an object and a score of 3-6 corresponds to a tool. See the Appendix for the

rating values of the individual stimuli.

0

1

2

3

4

5

6

Non-Objects Objects

ORS Score

0

1

2

3

4

5

6

Objects Tools

TRS Score


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Procedure

Participants were seated in front of a 17” computer screen at a distance of 80 cm. At this

distance, the pictures subtended a visual angle of 4 degrees and were presented laterally between

3-7 degrees from the fixation location. Before the start of each experiment the participants were

familiarized with the pictures that would be presented. They were given a tachistoscopic

presentation of the stimuli (with similar presentation times as in the real experiment) and asked

to name the pictures. They were corrected if needed.

For the first experiment, the pictures of the objects and the non-objects were used and

participants had to decide whether one of the two bilaterally presented stimuli was an object or a

non-object. For the second experiment, the same pictures of the objects were combined with

those of the tools, and the participants had to decide whether one of the two bilaterally presented

stimuli was a tool or not.

On each trial participants were first presented with a blank screen for 1000 ms, followed

by a fixation cross (sized 1 degree of visual angle) at the center of the screen for 300 ms. The

fixation cross was replaced by a display which had a centrally presented arrow (sized 1 degree of

visual angle) pointing to the left or to the right, along with two pictures, one in the left visual

field (LVF) and one in RVF. The duration of the display was 200 ms, based on the research of

Walker & McSorley (2006) showing that participants are unable to initiate an eye movement

within 200 ms if they have to attend to a stimulus at the fixation location (the central arrow in

our case). The stimuli presented in LVF and RVF could represent an object or a non-object (in

Experiment 1), or a tool or a non-tool (in Experiment 2). The stimuli in the VHFs could belong

to the same category (compatible) or a different category (incompatible). Participants were

instructed to attend to the stimulus in the VHF to which the central arrow pointed, and to decide


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whether it represented an object/non-object (Experiment 1) or a tool/non-tool (Experiment 2). In

case the stimulus represented an object (Experiment 1) or a tool (Experiment 2), the participant

had to press two buttons with the index fingers of both hands; otherwise they had to press

buttons with the middle fingers of both hands. We used bi-manual responses to avoid a stimulus-

response compatibility effect (i.e., responses by the right hand are faster to stimuli in RVF and

vice-a-versa). Reaction Times and Accuracy were calculated based on the first key-press

registered. Reaction time measurement started from stimulus offset, like in Verma and Brysbaert

(2011). This means that 200 ms must be added to get the total processing time.

Depending on the VHF of stimulus presentation (LVF or RVF), the stimulus (object/non-

object, tool/non-tool), and whether the stimulus in the contra-lateral visual field was from the

same category (compatible vs. incompatible), eight types of trials could be formed. There were

80 instances of each type in each experiment, giving 640 trials in all. All participants started with

the object vs. non-object decision task, and ended with the tool vs. non-tool task.

Results

The findings of the two experiments are summarized in Figures 3 and 4.

We ran a 2 x 2 x 2 x 2 omnibus ANOVA to compare the two tasks, having Task (Object

recognition vs. Tool recognition), VHF (LVF vs. RVF), Response (yes vs. no), and

Compatibility of the distractor in the opposite VHF (from the same vs. different category) as

repeated measures. For the RT data, we obtained significant main effects of VHF (LVF=412.7

ms vs. RVF=406.7 ms; F (1, 38) = 10.09, p<0.01), Response (Yes= 385.7 vs. No=433.7, F (1,

38) = 123.75, p<0.01), and Compatibility (Incompatible= 419.8 vs. Compatible= 399.6, F (1, 38)


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= 85.57, p<0.01). The main effect of Task was not significant (Object Recognition = 405.1 vs.

Tool Recognition = 414.3, F (1, 28) = 0.24, p>0.05).

Significant interaction effects were: Task x VHF (F (1, 38)= 27.33, p<0.01); Task x

Response (F (1, 38)= 5.87, p<0.05); VHF x Response (F (1, 38)= 11.74, p<0.01); Task x VHF x

Compatibility (F (1,38)= 4.96, p<0.05); Response x Compatibility (F (1,38)= 91.93, p<0.01) and

Task x Response x Compatibility (F (1, 38)= 30.33, p<0.01).

We also calculated the same omnibus ANOVA on percentage accuracy. This revealed

significant a main effect of Compatibility (Incompatible = 87.3% correct vs. Compatible =

89.9%, F (1, 38) = 50.86, p<0.01). The effect of Task was close to significance (Object

Recognition = 89.9 vs. Tool Recognition = 87.2, F (1, 38) = 4.03, p = 0.052). The significant

interaction effects were: Task x VHF (F (1, 38) = 4.57, p<0.05), VHF x Compatibility (F (1, 38)

= 6.09, p<0.05) and Response x Compatibility (F (1, 38) = 16.30, p<0.01). The interpretation of

these effects will be clearer when we have a look at the ANOVAs for the two tasks separately.


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Figure 3: The results from the object recognition task, showing the lack of a clear VHF

difference (except for the significant LVF advantage for non-objects in the RTs). Left

panel: RT data; right panel: Percentage Acuuracy (P.A.) %.

Figure 4: The results from the tool recognition task, showing the robust RVF advantage in

the presence of a very similar performance level as in the object recognition task. Left

panel: RT data; right panel: Percentage Accuracy (P.A.) %.

350

375

400

425

450

475

500

LVF RVF

RTs

Objects

Non-Objects

75

80

85

90

95

LVF RVF

P.A. (%)

Objects

Non-Objects

350

375

400

425

450

475

500

LVF RVF

RTs Tools

Non-Tools

75

80

85

90

95

LVF RVF

P.A.s (%)

Tools

Non-Tools


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We ran a 2 x 2 x 2 ANOVA for each task, i.e. Object Recognition and Tool Recognition,

to understand the effects of VHF, Response and Compatibility better. In the Object Recognition

task, the 2 x 2 x 2 ANOVA on RTs revealed a significant main effect of Response (Yes i.e.

Objects= 376.7 ms vs. No i.e. Non-objects = 433.6) and Compatibility (Incompatible = 415.9 vs.

Compatible = 394.4). The main effect of VHF was not significant (LVF = 403.4 vs. RVF =

406.8, F (1, 38) = 1.88, p >0.05). The significant interactions were VHF x Response (F (1, 38) =

5.44, p<0.05) and Response x Compatibility (F (1, 38) = 110.07, p<0.01). The interaction

between VHF and Response seems to be driven mainly by the no responses (for non-objects):

There was no significant difference in RTs between LVF and RVF for objects (LVF = 377.2 vs.

RVF = 376.2, F(1, 38) = F(1, 38) = 0.088, p>0.05 ) while there was a significant LVF advantage

in RTs for non-objects (LVF = 429.6, RVF = 437.5, F(1, 38) = 9.13, p<0.01). The interaction

between response x compatibility was also mainly driven by the effect of compatibility for non-

objects; non-objects seemed to become particularly salient in case of compatible information

across the visual fields and elicit faster RTs as compared to when stimuli in the two visual fields

were from different categories (Incompatible = 456.2, Compatible = 410.9, F (1, 38) = 130.96,

p<0.01). For the Accuracy data, the 2 x 2 x 2 ANOVA revealed a significant main effect of

compatibility (Incompatible = 88.7, Compatible = 91.2, F (1, 38) = 20.11, p<0.01). The

interaction effects of VHF x Compatibility (F (1, 38) = 4.23, p<0.05) and Response x

Compatibility (F (1, 38) = 14.48, p<0.01) were significant, indicating that overall participants

were more accurate in cases where information across the two visual fields belonged to the same

category. The three way interaction between VHF, Response and Compatibility was not

significant (F (1, 38) = 0.147, p>0.05).


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In the Tool Recognition task, the 2 x 2 x 2 ANOVA for RTs revealed significant main

effects of VHF (LVF = 421.9 ms, RVF = 406.6 ms, (F (1, 38) = 32.74, p< 0.01), Response (yes =

394.8, no = 433.8, F (1, 38) = 53.27, p<0.01) and Compatibility (Incompatible = 423.7,

Compatible = 404.8, F (1, 38) = 58.32, p<0.01). The significant interaction effects were VHF x

Compatibility (F (1, 38) = 5.65, p<0.05) and Response x Compatibility (F (1, 38) = 21.79,

p<0.01). The interaction between VHF and Response failed to reach significance (F (1, 38) =

2.57, p>0.05). In the tool recognition task, participants responded significantly faster to pictures

of tools presented in RVF than in LVF (LVF = 404.6, RVF = 384.9, F (1, 38) = 20.05, p<0.01).

Also participants responded significantly faster to tools in the compatible condition than in the

incompatible condition (incompatible = 399.5, compatible = 390.1, F (1, 38) = 8.51, p<0.01). For

the non-tool objects, participants were also significantly faster in RVF (LVF = 439.2, RVF =

428.4, F (1, 38) = 11.43, p<0.01); also similar to the tools, non-tool objects were responded to

significantly faster in the compatible condition (incompatible = 448.1, compatible = 419.5, F (1,

38) = 78.08, p <0.01). For the Accuracy data, the 2 x 2 x 2 ANOVA revealed significant main

effects of VHF (LVF = 86.7, RVF = 87.8, F (1, 38) = 4.26, p<0.05) and compatibility

(incompatible = 85.8, compatible = 88.6, F (1, 38) = 30.36, p<0.01).

To be sure that the inclusion of the 8 tool stimuli, which did not score above 4 in the Tool

Rating Scale, did not distort the findings; we reanalyzed the data from the tool recognition study

excluding these stimuli. Fortunately, the results did not change at all. There was again a main

effect of VHF (LVF= 420.9 ms vs. RVF = 406.1 ms), F (1, 38) = 35.30, p<.01, Response (yes =

393.2 ms vs. no = 433.8 ms), F (1,38) = 53.48, p <.01, and Compatibility (compatibility = 403.6

ms vs. incompatibility = 423.4 ms), F (1,38) = 60.24. The interaction between VHF x

Compatibility, F (1, 38) = 7.15, p < 0.05 (p= 0.011) and between Response x Compatibility was


P. | 130

also again significant, F (1, 38) = 21.53, p < 0.01. Finally, the VHF advantage for tools did not

change either (LVF = 412.3 ms vs. RVF = 385.3 ms), F (1, 38) = 25.24, p < 0.01. As the initial

analysis already excluded the incorrect trials; the exclusion of the stimuli did not affect the

percentage accuracy pattern.

All in all, the addition of the less clear stimuli did not make a difference in the pattern of

results; and probably they can be kept included in the stimuli pool.

Discussion

To improve research on tool recognition (in particular, laterality research), we developed

a set of pictures in which tools, non-tool objects, and non-objects were made as similar as

possible (see Figure 1 for examples; see the Appendix for a list of all the picture names; see the

supplementary materials for files of the pictures). To validate the new stimulus materials, we

used them in the two experiments described by Verma and Brysbaert (2011): An object and a

tool recognition experiment. On the basis of our previous results (and in line with the existing

literature), we expected no VHF difference for the object-recognition experiments, whereas a

significant RVF advantage was predicted for the tool recognition experiment.

We indeed obtained a very robust interaction between Task (object recognition vs. tool

recognition) and VHF. The results of the Object Recognition experiment pointed to equal

performance in LVF and RVF for responses to objects, combined with an 8 ms LVF advantage

for responses to non-objects. The latter was also observed in Verma and Brysbaert (2011) and is

not contradictory to the expectations. Non-objects are by definition unnamable, and arguably the

participants resort to a spatial analysis for rejecting these stimuli as existing objects. Because


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spatial analysis predominantly relies on the right hemisphere, especially in the case of right

handers (Vogel, Bowers & Vogel, 2003), a LVF advantage is not surprising.

More importantly, we replicated the predicted RVF advantage for tool recognition. This

was true for the yes-responses to tools (20 ms RVF advantage) and for the no-responses to the

non-tool objects (11 ms RVF advantage). In Verma & Brysbaert (2011) the differences were

respectively 17 ms and 3ms. The RVF advantage becomes even larger if the analysis is limited to

the incompatible trials, when the distractor in the opposite VFH was not from the same category

as the target. Then the difference increases to 26 ms for the tools and to 15 ms for the non-tool

objects.

Also interesting is the finding that overall response times and accuracies were very

similar in both tasks (RT ≈ 410 ms, % correct ≈ 89%). This makes it easier to interpret the

interaction (Loftus, 1978) and is much better than in Verma & Brysbaert (2011), where the

object recognition task (451 ms) was significantly faster than the tool recognition task (474 ms)

and also more accurate (85.2 % vs. 84.2% correct). This illustrates the importance of using the

same, controlled stimuli in both tasks.

To encourage more researchers to investigate tool and object recognition, we make the

new set of stimuli available as supplementary materials. The main omission of the Snodgrass &

Vanderwart (1980) stimulus bank is that it does not have pictures of non-objects. This makes it

impossible for researchers to run object vs. non-object discrimination tasks on these stimuli. In

addition, we found it hard to compile enough well-matched stimulus pairs of tools and non-tool

objects with this stimulus bank. Other pictures databases (e.g., van Diepen & De Graaf, 1994) do

contain pictures of non-objects, but have a shortage of tool pictures. Because the drawing style of


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both datasets is different, it is impossible to combine a picture from one set with that of another

set, without introducing all types of low-level visual confounds (e.g., the thickness of the lines or

the level of texture in the picture). Now, we have a set of stimulus materials addressing these

concerns. This should encourage further research into tool use and the lateralization of the skills

involved.


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Appendix: Triplets of stimuli: objects, non-objects and tools, together with

mean ratings in the Object Recognition Scale (ORS) and the Tool Recognition

Scale (TRS).

Triplet 1

Maize Non Object 1 Broom

(ORS = 5.65 ; TRS = 1.1) (ORS = 2.15) (TRS = 5.35 )

Triplet 2

Fence Non Object 2 Comb

(ORS = 5.5; TRS = 2.15) (ORS = 3.55) (TRS = 5.0)

Triplet 3

Log Non Object 3 Rolling Pin

(ORS = 5.85; TRS = 1.65) (ORS = 1.65) (TRS = 5.3)


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Triplet 4

Airplane Non Object 4 Anchor

(ORS = 5.89; TRS = 2.5) (ORS = 1.57) (TRS = 4.55)

Triplet 5

Ship Non Object 5 Iron

(ORS = 5.84; TRS = 2.1) (ORS = 1.84) (TRS = 5.35)

Triplet 6

Curtain Non Object 6 Harp

(ORS = 6.0; TRS = 1.55) (ORS = 1.31) (TRS = 2.6)


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Triplet 7

Finger Non Object 7 Pistol

(ORS = 5.89; TRS = 3.05) (ORS = 1.52) (TRS = 4.35)

Triplet 8

Pear Non Object 8 Guitar

(ORS = 5.94; TRS = 1.2) (ORS = 1.84) (TRS = 2.75)

Triplet 9

Lamp Non Object 9 Hand-drill

(ORS = 5.89; TRS = 2.0) (ORS = 1.94) (TRS = 5.9)


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Triplet 10

Chocolate Non Object 10 Sharpener

(ORS = 5.42; TRS = 1.25) (ORS = 2.36) (TRS = 5.4)

Triplet 11

Pumpkin Non Object 11 Kettle

(ORS = 5.73; TRS = 1.2) (ORS = 1.36) (TRS = 3.7)

Triplet 12

Bouquet Non Object 12 Pipe

(ORS = 5.73; TRS = 1.1) (ORS = 1.68) (TRS = 3.2)


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Triplet 13

Mushroom Non Object 13 Umbrella

(ORS = 5.84; TRS = 1.15) (ORS = 2.0) (TRS = 4.2)

Triplet 14

Band-aid Non Object 14 Wristwatch

(ORS = 5.65; TRS = 3.35) (ORS = 1.63) (TRS = 3.55)

Triplet 15

Flower Non Object 15 Razor

(ORS = 5.89; TRS = 1.1) (ORS = 1.1) (TRS = 5.2)


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Triplet 16

Twig Non Object 16 Zipper

(ORS = 5.84; TRS = 1.7) (ORS = 1.26) (TRS = 3.4)

Triplet 17

Shoe Non Object 17 Wrench

(ORS = 5.94; TRS = 2.15) (ORS = 1.52) (TRS = 6.0)

Triplet 18

Carrot Non Object 18 Toothbrush

(ORS = 5.68; TRS = 1.05) (ORS = 1.78) (TRS = 5.2)


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Triplet 19

Sausage Non Object 19 Stethoscope

(ORS = 4.73; TRS = 1.1) (ORS = 1.52) (TRS = 5.2)

Triplet 20

Candle Non Object 20 Spoon

(ORS = 5.84; TRS = 3.15) (ORS = 2.26) (TRS = 5.25)

Triplet 21

Boot Non Object 21 Shovel

(ORS = 5.57; TRS = 2.3) (ORS = 1.78) (TRS = 5.6)


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Triplet 22

Pillar Non Object 22 Screwdriver

(ORS = 5.68; TRS = 1.9) (ORS = 1.68) (TRS = 5.9)

Triplet 23

Bottle-gourd Non Object 23 Saxophone

(ORS = 4.0; TRS = 1.1) (ORS = 1.63) (TRS = 3.0)

Triplet 24

Incline Non Object 24 Saw

(ORS = 5.26; TRS = 3.4) (ORS = 2.04) (TRS = 6.0)


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Triplet 25

Pamphlet Non Object 25 Ruler

(ORS = 5.68; TRS = 2.9) (ORS = 2.52) (TRS = 5.0)

Triplet 26

Spring-onion Non Object 26 Pliers

(ORS = 5.52; TRS = 1.15) (ORS = 2.05) (TRS = 5.9)

Triplet 27

Sunflower Non Object 27 Pan

(ORS = 5.63; TRS = 1.1) (ORS = 1.89) (TRS = 4.65)


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Triplet 28

Asparagus Non Object 28 Pen

(ORS = 5.47; TRS = 1.04) (ORS = 1.31) (TRS = 5.05)

Triplet 29

Palm Non Object 29 Mop

(ORS = 5.73; TRS = 1.15) (ORS = 2.52) (TRS = 5.6)

Triplet 30

Feather Non Object 30 Knife

(ORS = 5.78; TRS = 2.6) (ORS = 1.94) (TRS = 5.8)


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Triplet 31

Bone Non Object 31 Hammer

(ORS = 5.78; TRS = 1.65) (ORS = 1.89) (TRS = 6.0)

Triplet 32

Ice-cream Non Object 32 Funnell

(ORS = 5.94; TRS = 1.1) (ORS = 1.42) (TRS = 5.2)

Triplet 33

Cactus Non Object 33 Fork

(ORS = 5.73; TRS = 1.1) (ORS = 1.63) (TRS = 5.35)


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Triplet 34

Book Non Object 34 Dustpan

(ORS 6.0; TRS = 1.85) (ORS = 2.21) (TRS = 5.35)

Triplet 35

Celery Non Object 35 Paint-brush

(ORS = 5.42; TRS = 1.15) (ORS = 3.31) (TRS = 5.7)

Triplet 36

Flag Non Object 36 Axe

(ORS = 5.73; TRS = 2.35) (ORS = 2.73) (TRS = 5.85)


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Triplet 37

Beans Non Object 37 Needle

(ORS = 5.73; TRS = 1.15) (ORS = 3.21) (TRS =4.85)

Triplet 38

Chimney Non Object 38 Cigarettes

(ORS = 5.89; TRS = 1.9) (ORS = 1.42) (TRS = 1.55)


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Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals

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Chapter 4: Symmetry Detection in Typically and

Atypically Speech Lateralized Individuals: A Visual

Half-field Study


P. | 154


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Chapter 4: Symmetry Detection in Typically and Atypically Speech

Lateralized Individuals: A Visual Half-field Study

Visuospatial functions are typically lateralized to the right cerebral hemisphere, giving

rise to a left visual field advantage in visual half-field tasks. In a first study we investigated

whether this is also true for symmetry detection off fixation. Twenty right-handed participants

with left hemisphere speech dominance took part in a visual half-field experiment requiring them

to judge the symmetry of 2-dimensional figures made by joining rectangles in symmetrical or

asymmetrical ways. As expected, a significant left visual field advantage was observed for the

symmetrical figures. In a second study, we replicated the study with 37 left-handed participants

and left hemisphere speech dominance. We again found a left visual field advantage. Finally, in

a third study, we included 17 participants with known right hemisphere dominance for speech

(speech dominance had been identified with fMRI in an earlier study; Van der Haegen et al,

2011). Around half of these individuals showed a reversed pattern, i.e. a right visual half-field

advantage for symmetric figures while the other half replicated the left visual-field advantage.

These findings suggest that symmetry detection is indeed a cognitive function lateralized to the

right hemisphere for the majority of the population. The data of the participants with atypical

speech dominance are more in line with the idea that language and visuospatial functions are

lateralized in opposite brain hemispheres than with the idea that different functions lateralize

independently, although there seems to be more variability in this group.

This chapter has been published as Verma, A., van der Haegen, L., & Brysbaert, M. (2013). Symmetry detection in

typically and atypically lateralized individuals: a visual half field study. Neuropsychologia, 51, 2611-2619.


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Introduction

The brain is divided in a left and a right half. Decades of research have shown through a variety

of methods that a number of cognitive functions are unequally represented in both hemispheres.

Asymmetries have been documented in both structure and functioning. For instance, the planum

temporale region of the brain has been found to be larger in the left than in the right hemisphere

(for recent reviews, see Amunts, 2010; Greve, Van der Haegen, Cai, Stufflebeam, Sabuncu,

Fischl, & Brysbaert, in press). In most people language is lateralized to the left hemisphere. This

hemisphere has also been reported to be superior in processing local elements, while the right

hemisphere has been reported to be specialized in processing global elements (Bradshaw &

Nettleton, 1981). Along the same lines it has been pointed out that the left hemisphere is good at

categorical decisions whereas the right hemisphere is relatively better at coordinate decisions

(Kosslyn, 1987). Finally, the two hemispheres are supposed to be differentially adept at

processing spatial frequency; the left hemisphere has an advantage for processing higher spatial

frequencies, whereas the right hemisphere would be better at processing low spatial frequencies

(Sergent, 1983).

Several fundamental principles (e.g., analytic vs. holistic) have been proposed to

understand the asymmetries of the two hemispheres (both structural and functional), but these

have not been very successful (Hellige, 1993). Hugdahl (2000) observed that of all dichotomies

put forward none has produced more consistent findings than the traditional distinction between

language functions in the left hemisphere and a range of visuospatial functions in the right

hemisphere. He argued that the functional asymmetry of the brain is the result of evolutionary

pressure towards specialization for behaviors unique to the evolution of modern man. The

emergence of language capabilities is one of the most plausible candidates to serve as a


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fundamental force for a functional division of the brain into a right and left half. Another facility

of humans that can serve this function is the ability to represent the 3-dimensional environment

as a visuospatial map. While the ability and need to communicate symbolically may have led to

the evolution of the left hemisphere as specialized in language and related functions, the right

hemisphere specialization could be due to the fact that orientation in space required rapid

identification of objects and their relations. Hence, according to Hugdahl (2000) the language-

left hemisphere and the visuospatial right hemisphere dichotomy is the guiding principle to

understand brain asymmetries in human cognitive performance.

While many studies have documented the left hemisphere dominance for language

processing, comparatively little behavioral research has been dedicated to the functions of the

right hemisphere. Most of these studies were done with the visual half-field (VHF) task. In this

task stimuli are presented in the left and right parafovea, and more efficient processing in the left

visual field (LVF) than in the right visual field (RVF) is interpreted as evidence for right brain

laterality. Bryden (1982) pointed out that on the basis of this evidence the right hemisphere is

likely to be better able to handle a variety of cognitive functions, such as spatial abilities

(Benton, Hannay & Varney, 1975), face recognition (Geffen, Bradshaw & Wallace, 1971), and

emotional expression (Ley & Bryden, 1981). The specialization for spatial abilities was attested

by LVF advantages for lightness discrimination (Davidoff, 1975), color perception (Hannay,

1979; Pennal, 1977), dot detection (Davidoff, 1977; Umilta, Salmaso, Bagnara, & Simion, 1979),

dot localization (Bryden, 1976), perception of line orientation (Atkinson & Egeth, 1973),

stereopsis (Carmon & Bechtoldt, 1969), and depth perception (Kimura & Durnford, 1974).

Music perception was another function ascribed to the right hemisphere (e.g., Gates &

Bradshaw, 1977) and Hughdahl (2000) further pointed to the critical involvement of the right


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parietal cortex in the allocation of attention, as exemplified by hemineglect after damage to this

region (but not to the left homologue). It must be noted, however, that most of these studies

reflect lateralization in relative terms. While many visual field advantages have been

corroborated by later neuro-imaging studies, it is often the case that the tasks evoke bilateral

activation, with one hemisphere being more active than the other.

The initial findings with the VHF task and other related behavioral paradigms (such as

dichotic listening) have since been replicated and extended with the use of neuroscientific

methods like fMRI, PET, MEG, etc. Shulman, Pope, Astafiev, McAvoy, Snyder, & Corbetta

(2010) used fMRI to measure hemispheric asymmetries during shifts of spatial attention evoked

by a peripheral cue stimulus and during target detection at the cued location. They found right

hemisphere dominant activity at the temporoparietal junction during the shifting of spatial

attention. During later target detection they also observed a more wide-spread right hemisphere

dominant activity in the frontal, parietal and temporal cortices. Yovel, Tambini, & Brandman

(2008) and Hemond, Kanwisher, & Op de Beeck (2007) correlated the much documented LVF

advantage for face detection with fMRI-measured brain activity, and argued that it was related to

a processing asymmetry in the fusiform gyrus (FFA). Also based on fMRI data, Mashal, Faust,

Tendler, & Jung-Beeman (2008) claimed that the right hemisphere plays a major role in solving

semantic ambiguities and in processing non-salient meanings of idiomatic expressions. In a

related domain, Marinkovic, Baldwin, Courtney, Witzel, Dale, & Halgren, E. (2011) on the basis

of MEG data proposed that activations stemming from the right prefrontal cortex play a vital role

in joke appreciation and consequently in humor understanding. Other evidence for right

hemispheric specialization was obtained by Klosterman, Loui, & Shimamura (2009), who


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examined retrieval of agrammatical musical sequences (i.e. non-verbalizable sequences of tones)

and found that particularly the right posterior parietal cortex (PPC) was involved.

In the present research, we examined whether symmetry detection is another right

hemisphere dominant task. Symmetry refers to the property of a visual object where in two

(ormore) parts of the object are separated by an imaginary axis and related to each other.

Symmetry can be of various types. Mirror symmetry refers to situations where the two half

planes obtained by dividing the object/display along an in visible central axis are mirror images

of each other. Cases where the central axis is vertical manifest vertical symmetry, those where

the central axis is horizontal manifest horizontal symmetry, and when the axis is diagonal the

pattern reflects diagonal symmetry. Rotational symmetry is found when the rotation of a pattern

aligns with the original pattern. Because symmetry perception is particularly efficient when the

symmetry axis coincides with the vertical midline (Herbert & Humphreys, 1996), a further

distinction is made between symme-try at fixation (when the stimulus is in the center of the

visual field) and symmetry off fixation (when the stimulus is in parafoveal vision).

Symmetry is everywhere in the visual world and thus it is no surprise that biological

vision systems are endowed with adaptive strategies for perceiving and utilizing this property

(Wagemans, 1995). Pigeons can discriminate and classify shapes on the basis of symmetry

(Delius & Nowak, 1982) and experiments with human infants have provided evidence for

aninnate preference of symmetric patterns (Bornstein, Ferdinandsen, & Gross, 1981). Symme-

try is also easily detected in random dot configurations presented for less than 150ms

(Barlow&Reeves, 1979). This is particularly true for the detection of vertical symmetry at

fixation (Royer, 1981).


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Symmetry is used in various other visuospatial functions as well. Koffka (1935) noted

that it was a helpful cue for figure- ground segregation, which was empirically confirmed for

vertical mirror symmetry by Machilsen, Pauwels, and Wagemans (2009). Marr (1982) proposed

that symmetry is an important non- accidental feature for determining the principal axis of a

shape, prior to deriving an object centered description relative to this axis. Bayliss and Driver

(1994) suggested that memory representations of objects involved in formation about their

symmetry. Finally, studies have shown superior recognition for faces in case of symmetric facial

features; hence demonstrating the importance of symmetry in face perception (Little & Jones,

2006; Rhodes, Peters, Lee, Morrone, & Burr, 2005; Troje & Bulthoff, 1997).

Because of the importance of symmetry detection, authors have speculated about whether

it could be a basic, preattentive feature used for image segmentation, just like orientation,

brightness, color, or movement. Kootstra, de Boer, & Schomaker (2011), for instance, found that

when participants were viewing complex photographic images, their early fixations

predominantly were on highly symmetrical areas of the image. The authors further showed that a

computational model of eye guidance, including symmetry information to predict eye-

movements, outperformed the existing models based on contrast features. On the other hand,

Gurnsey, Herbert, & Kenemy (1998) reported evidence that the detection of vertical bilateral

symmetry embedded in random noise is poor unless the axis of symmetry is at the point of

fixation, and they argued that symmetry does not play a role in image segmentation until an

object has been fixated. This message was recently repeated by Roddy and Gurnsey (2011), who

showed that symmetrical stimuli in parafoveal vision are subject to interference from other

stimuli (crowding) and on the basis of this finding argued that symmetry is not special to the

early visual system (see Olivers & van der Helm,1998, for a similar argument).


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Whatever the exact status of symmetry detection in human perception (preattentive or

not), no author denies its importance for visuospatial cognition.Consequently we hypothesized

that it was likely to bea right-hemisphere function and to give rise to a significant LVF advantage

in a VHF task. Examination of the literature revealed some hints to such an effect. As far as we

could ascertain, four studies have provided evidence for right lateralization of symmetry

detection.

In a study by Corballis & Roldan (1974), participants were presented with lateralized

tachistoscopic dot patterns and had to tell whether these were symmetrical around the vertical

axis or not. It was found that the yes-responses were 11ms faster in LVF than RVF, suggesting

different abilities for processing symmetry in the two hemispheres. Brysbaert (1994) examined

the effects of lateral preferences (handedness, footedness, eye and ear preference) on VHF

asymmetries and used symmetry detection as one of the tasks. He reported a small but significant

LVF advantage for the task. More recently, Wilkinson & Halligan (2002) examined stimulus

bisection in LVF and RVF (i.e., the so-called landmark task) and reported that stimulus

symmetry contributed to the performance in LVF but not in RVF. From this finding they

concluded that “the detection of visual symmetry is preferentially lateralized to the right

hemisphere” (p. 1045). These findings were confirmed in a later fMRI study (Wilkinson &

Halligan, 2003) when it was found that the presence/absence of symmetry corresponded to

activity in the right anterior cingulate gyrus, an area associated with a variety of higher level

attentional functions. The superior perception of line bisection in LVF was associated with

activation in the right superior temporal gyrus.

However, other studies failed to find evidence for right hemisphere superiority in

symmetry perception. Herbert & Humphrey (1996), for instance, examined whether the quick


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perception of vertical symmetry at fixation could be due to interhemispheric comparison and

indeed found that the detection of vertical symmetry at fixation was anomalous in two persons

born without corpus callosum, but relatively normal for presentation off fixation. More

importantly for the present purpose, they did not report a significant advantage for stimuli

presented in LVF.

Neuroscientific methods also point to a strong bilateral brain activation in symmetry

detection tasks. In an fMRI study, Tyler et al. (2005) presented observers with symmetric and

random dot patterns. The symmetric configurations were found to selectively activate a region in

the dorsolateral occipital cortex (DLO) and activity did not differ significantly between

hemispheres. Sasaki et al. (2005) also reported that symmetrical patterns (both of dots and lines)

activated the extrastriate visual cortex in human and non-human primates (areas V3A, V4, V7

and LO); they did not observe hemispheric differences either (at least none were reported in the

ms). Finally, Cattaneo et al. (2011) used TMS to investigate the neural correlates of symmetry

perception. As expected, they found that pulses to DLP affected symmetry detection, whereas

pulses to V1/V2 did not have an adverse effect. Importantly for the present discussion, no

hemispheric differences were reported (in one analysis there even was a tendency towards left-

hemisphere dominance). For the correct interpretation of the neuroscientific findings it is

important to keep in mind that they all involved large stimuli (up to 20 degree of visual angle)

extending into both VHFs. As illustrated by Herbert & Humphrey (1996), particularly for

vertical symmetry there is a likely difference between symmetry perception at fixation and

symmetry detection off fixation, with strong interhemispheric interactions in the former case.

In the present study, we first examined whether we could replicate the LVF advantage for

parafoveal symmetry detection in right-handed participants, as reported in the four studies


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discussed above. One reason why other researchers may have failed to find the effect is that not

all VHF studies adhere to good methodological standards (Hunter & Brysbaert, 2008). In

particular, it has been found that VHF asymmetries are much more stable and consistent when

independent information is presented simultaneously in LVF and RVF and participants have to

respond to the stimulus indicated by a central arrow. Because of the bilateral presentation, the

influence of attention capture by the stimulus onset is reduced. In addition, the simultaneous

arrival of information in the two hemispheres gives the dominant hemisphere more chances to

outperform the non-dominant hemisphere. Also, the central arrow forces the participant to pay

attention to the fixation location before stimulus onset. Therefore, we first wanted to see whether

the LVF advantage for parafoveal symmetry detection can be replicated under suitable

methodological conditions (Experiment 1). To further extend the results, the same experiment

was tested in a group of left-handed subjects with typical left hemispheric speech lateralization

(Experiment 2). Their lateralization was assessed with two VHF naming tasks and in some cases

confirmed with an fMRI silent word generation task, comparing left and right hemisphere

activity in Broca’s area (see Hunter & Brysbaert, 2008; Van der Haegen, Cai, Seurinck &

Brysbaert, 2011, for further details). Finally, left-handers with known atypical right speech

lateralization took part in the VHF task (Experiment 3). This allowed us to test whether the

lateralizations of speech and symmetry detection are statistically independent or whether there is

a bias to have both functions separated (see Cai, Van der Haegen, & Brysbaert, 2013, for a recent

review of this literature).

Experiment 1

Research about symmetry detection has been done with very different stimulus materials

ranging from simple dot patterns to polygons and complex art displays (Carmody, Nodine &


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Locher, 1977; Locher & Nodine, 1989; Locher & Wagemans, 1993; Donnely, Humphreys, &

Riddoch, 1991). Here, we chose to use symmetric and asymmetric arrangements of rectangles,

because these stimuli were used in previous studies suggesting a right-hemisphere advantage for

symmetry detection (Brysbaert, 1994; Wilkinson & Halligan, 2002, 2003).

Method

Participants

Participants were 20 right-handed students from Ghent University. Handedness was

assessed with a Dutch translation of the Edinburg Handedness Inventory (Oldfield, 1971). A

questionnaire about eye preference, ear preference, and footedness was also administered (Porac

& Coren, 1981). Participants were asked to use a number between -3 and -1 to indicate their

degree of left side preference and between +1 and +3 to indicate their degree of right side

preference (Brysbaert, 1994). Miles’ (1930) test of eye-dominance was also administered to the

participants. Finally, all participants had been diagnosed as left lateralized for speech production

in an earlier fMRI study by Van der Haegen et al. (2011).

Stimuli

The stimuli were figures made in black lines against a white background. They were

made by joining three horizontal rectangles, one above another giving rise to a symmetric or an

asymmetric arrangement (Figure 1). There were 60 different symmetric and 60 different

asymmetric stimuli. They were up to 4° wide and 2° high.


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Symmetric Shapes

Asymmetric Shapes

Figure 1: Two examples of the symmetric and the asymmetric shapes used as stimuli in the

experiments. All stimuli were made by joining three horizontal rectangles that could differ

in length.


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Procedure

Participants were seated in front of a 17 in. computer screen at a distance of 80 cm.

Before the start of each session, they were familiarized with the stimuli, by giving them a central

tachistoscopic presentation of the various stimuli on the computer screen.

Stimulus presentation followed the VHF protocol outlined by Hunter and Brysbaert

(2008). A trial started with the presentation of a blank screen for 1000 ms. Then a fixation cross

(sized 1degree of visual angle) appeared at the centre of the screen for 300 ms. Participants were

instructed to focus on the cross when it appeared. The cross was followed by a slide with two

stimulus figures presented left and right at a distance of 3 degree from the fixation location, and a

centrally presented arrow (sized1degree of visual angle). The arrow could point towards LVF or

RVF and participants had to respond to the stimulus at the side indicated. Because stimulus

presentation was bilateral and participants had to process the central arrow, the stimuli could be

presented for 200 ms without running the risk of fast saccades to one of them (Walker &

McSorley, 2006). The stimuli appearing in LVF or RVF could be symmetric or asymmetric. For

symmetric stimuli participants had to press buttons with their left and right index fingers

simultaneously; for asymmetric stimuli they had to press with the left and right middle fingers.

___________________________________________________________________________

1 In other experiments we sometimes present stimuli of both the compatible and the incompatible type in the

distractor VHF (e.g., Hunter & Brysbaert, 2008). We did not do so here, because it would have required us to make

the experiment longer if we wanted to have a decent number of observations in all conditions. Based on pilot testing

we also had the fear that bilateral symmetry presentation might be too salient (i.e., would elicit particularly fast

responses). As the participants were instructed to constantly fixate at the center of the screen and to respond as

rapidly as possible to the indicated stimulus, we did not have the impression that they were able to make use of any

redundancy in the distractor stimulus, an impression that seems to be borne out by the findings.


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Bimanual responses were used to avoid the stimulus-response compatibility effect (i.e.thefactthat

responses with the right hand are faster to stimuli in RVF while responses with the left hand are

faster to stimuli in LVF).

There were four types of trials depending on the direction of the central arrow and

whether or not the target stimulus was symmetric or asymmetric. The four types were Left

Symmetric (central arrow pointing towards LVF, symmetric figure presented in LVF), Left

Asymmetric (central arrow pointing towards LVF, asymmetric figure in LVF), Right

Symmetric (central arrow pointing towards RVF, symmetric figure in RVF), and Right

Asymmetric (central arrow pointing towards RVF, asymmetric figure in RVF). The stimulus in

the non-target VHF was always incompatible with the target stimulus (i.e., if asymmetric figure

had to be attended to, the distractor stimulus was of the asymmetric type). The specific stimuli

(out of the 60 possibilities) were randomly selected by the experiment presentation software.The

experiment was preceded by 40 practice trials, while the main block contained 160trials (40 trials

of each type). As there were 120 stimuli and 200 trials each involving 2 randomly drawn stimuli,

some trials contained a stimulus in LVF or RVF that had been shown before. Stimulus repetition

does not affect the VHF asymmetry in Hunter and Brysbaert (2008) protocol, not even with word

stimuli (e.g., Van der Haegen et al., 2011). As a matter of fact, Hunter and Brysbaert (2008)

recommend the repetition of stimuli over VHFs, as this ensures that the stimulus materials

presented in LVF and RVF are matched. In the present studies there were no indications either

that the asymmetry was different in the first half of the experiment than in the last half.


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Results

Separate 2 X 2 analyses of variance (ANOVAs) were run on the reaction times (RT) of

the correct trials and the percentages of errors (PE). The factors were VHF (left and right) and

Stimulus Type (Symmetric and Asymmetric). For the RT data, this resulted in a significant main

effect of VHF (LVF = 484 ms, RVF = 522 ms; F (1, 19) = 12.859, p < 0.01). Also, a significant

main effect of Stimulus Type was observed (Symmetric = 485ms, Asymmetric = 521ms; F (1,

19) = 20.299, p < 0.01). The interaction of VHF and Stimulus Type was not significant, F (1, 19)

= 1.748, p = 0.202; although there was a trend towards a larger LVF advantage for symmetric

figures than for asymmetric figures on the basis of the mean scores. For symmetric figures, the

LVF advantage was 55ms while for asymmetric figures the advantage was only 23 ms. In all,

16 out of the 20 right-handed participants showed the left-visual field advantage for symmetric

figures, while only 12 participants showed the advantage for asymmetric figures.

For the error data, the main effect of VHF was significant, (LVF=13.7%, RVF=19.3%; F

(1, 19) =14.129, p<0.01). There was no significant effect of Stimulus Type, but the interaction

between VHF and Stimulus Type was significant (F (1,19) = 8.058, p<0.05), because the LVF

advantage was larger for symmetric than asymmetric pictures. In terms of errors 18/20

participants showed an LVF advantage for symmetric figures, while only 8 participants showed

the LVF advantage for asymmetric figures.

The fact that a high number of participants show the difference is reassuring as it confirms that

the LVF advantage is not due to a small number of participants with very large asymmetries.

Also the fact that the advantage is larger for symmetric figures than for asymmetric figures

provides support for our speculation that the advantage can be attributed specifically to


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symmetry detection and is not due to the visual properties of the 2-d shapes we used as stimuli.

The data are shown in Figure 2.

We also checked for any kind of practice effects for the symmetric and asymmetric

stimuli by comparing the first and second halves of each of the four conditions, but did not find

any statistically significant difference, neither in terms of RT nor accuracy.

Discussion

In the first experiment we sought to investigate whether we could replicate the LVF advantage

for symmetry detection reported in a few studies primarily aimed at other variables (the influence

of lateral preferences on VHF asymmetries; Brysbaert, 1994; and the contribution of stimulus

symmetry to performance on the landmark task; Wilkinson & Halligan, 2002). In both RTs and

PEs, our hypothesis of right hemisphere dominance was confirmed for right-handers with known

left hemisphere speech dominance. The effect was larger for symmetric stimuli than for

asymmetric stimuli, a finding that is often reported in yes/no-decision tasks. Indeed, in many

lexical decision experiments the robust RVF advantage is only observed for words and not for

non-words (Howell & Bryden, 1987; Laine & Koivisto, 1998; Measso & Zaidel, 1990; Mohr et

al. 1994; Nieto et al. 1999). In the next experiment we investigate what happens in left-handers

with typical left hemispheric language lateralization.


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Figure 2: A LVF advantage for symmetry detection in right-handers (left panel: RT; right

panel: PE). The VHF asymmetry is clearer for symmetric pictures (responses) than for

asymmetric pictures (responses), in line with the observation in lexical decision that the

VHF asymmetry is clearer for yes-responses to words than for the slower no-responses to

non-words. Error bars indicate the 95% confidence intervals and are based on the error

terms of the VHF * Stimulus type ANOVA (Masson & Loftus, 2003).

400

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Experiment 2

Now that we have shown an LVF advantage for most right-handers with confirmed left

hemispheric speech lateralization when taking strict methodological considerations into account,

the next step is to evaluate the robustness of this effect. In general, more variability of functional

brain organization has been found in left-handers (Bradshaw & Nettleton, 1981), making them a

suitable group to test the reproducibility of the LVF advantage observed in Experiment 1. Part of

the variability in left-handers is due to the fact that they more often have atypical speech

dominance. It is estimated that 20-25% of the left-handers have atypical dominance (Knecht et

al., 2000), against only 1-5% of the right-handers. In addition, it might be expected that left-

handed participants with left speech dominance show more variability in the laterality scores of

various functions than right-handers. In genetic models of hand preference, left-handedness is

thought to be the result of a gene generating random laterality preferences (e.g., McManus,

1985). This may lead to more cross-lateralization of functions (such as speech production and

symmetry detection) in left-handers than in right-handers.

In Experiment 2, we first tested the VHF asymmetry for symmetry detection in a rather

large group of left-handers, who were comparable to the participants of Experiment 1 in terms of

left hemisphere language functioning. In Experiment 3, we looked at a smaller group with known

right hemisphere speech dominance, to see what consequences a specialization shift from the left

to the right inferior frontal gyrus has for the brain functions underlying symmetry detection.


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Method

Participants

Participants were 37 left-handed participants from Ghent University. The group originally

consisted of 19 individuals who had been confirmed as left hemisphere speech dominant with

fMRI (for more details, see Van der Haegen et al., 2011). Because the findings with the original

group were somewhat ambiguous (a clear trend, but no significance), we nearly doubled the

group to maximize the power of the study1. We were unable to scan the additional individuals,

but they were selected on the basis of a VHF word and picture naming task. All had a clear RVF

naming advantage of more than 20 ms in one of the tasks, and no LVF advantage in the other

task. Based on the results of Hunter & Brysbaert (2008) and Van der Haegen et al. (2011), we

can be confident that this approach reduced the chances of including an atypically lateralized

participant to almost zero. The 37 left-handers were given the same test as in Experiment 1 and

were paid for participating in the experiment.

Stimuli and Procedure

The stimuli and the procedure were exactly the same as in Experiment 1.

Results

We ran a 2 x 2 ANOVA with VHF (2 levels: LVF, RVF) and Stimulus type (2 levels:

Symmetric, Asymmetric) as factors. For the reaction time (RT) data, the ANOVA yielded neither

a significant main effect of VHF nor Stimulus type. However, the interaction effect was

significant (F (1, 36) = 16.28, p < 0.01). For the percentage error data, there was no significant

main effect of VHF or Stimulus type either. Again, the interaction was significant (F (1,36) =

1 The authors thank an anonymous reviewer for this suggestion.


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10.75, p<0.01). One-way ANOVAs indicated that the VHF effect was significant for the

symmetric stimuli (RT: LVF = 519 ms, RVF = 553 ms, F (1, 36) = 13.34, p<0.01; PE: LVF =

18.5%, RVF = 26.5%, F (1, 36) = 15.42, p < 0.01) and for the asymmetric stimuli. However, for

the latter, the direction was opposite with evidence of a RVF advantage, which was significant

for RT (LVF = 562 ms, RVF = 546 ms; F (1, 36) = 5.29, p < 0.05), but not for PE (LVF =

21.6%, RVF = 17.7%; F (1, 36) = 2.93, p=.095).

When we looked at the individual data, we saw that 29/37 (78.4%) of the participants

showed the LVF advantage for the symmetric stimuli in terms of RTs, and 28/37 (75.7%) in

terms of accuracy. For the asymmetric stimuli, 25/37 (67.5%) of the participants had the opposite

RVF advantage in RTs, and 23/37 (62.1%) in terms of accuracy.

Discussion

In line with the right-handed group of Experiment 1, the left dominant left-handers of

Experiment 2 had a clear LVF advantage for symmetric stimuli, although the size of the advange

(RT = 34 ms, PE = 8.0%) tended to be smaller than in Experiment 1 (RT = 55 ms, PE = 13.7%).

At the same time, there was evidence for more distributed processing in left-handers than in

right-handers, as we observed some evidence for a RVF advantage in the processing of

asymmetric stimuli (Figure 3).

In terms of individual differences, there were few indications that the LVF advantage for

symmetric stimuli was less stable in left-handers than in right-handers, as the percentage of

participants showing the effects was remarkable similar for RT (16/20 or 80% in right-handers

vs. 29/37 or 78.4% in left-handers). For accuracy there was a trend towards less consistency in


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left-handers (18/20 or 90% of the right-handers vs. 28/37 or 75.7% of the left-handers made

fewer errors in the LVF condition).

Experiment 3

In a final experiment, we addressed the question whether different functions lateralize

independently or whether atypical speech dominance creates atypical laterality for visuospatial

functions as well. The first view says that verbal and visuospatial abilities are independent

functions and, therefore, lateralize separately. This possibility was first raised by Bryden,

Hecaen, & DeAgostini (1983) who reported that “an analysis of the concurrent incidence of

aphasia and spatial disorder in 270 patients with unilateral brain damage suggests that the two

functions are statistically independent” (p. 249). Although aphasia was more frequent after left

hemisphere damage and spatial disorders after right hemisphere damage, the incidence of

combined disorders was not less than predicted on the basis of statistical independence. From

this finding Bryden et al. (1983) concluded that the complementary specialization of the

hemispheres is not causal in nature and that atypical laterality of one function has no implication

for the other. Similar suggestions were made by Kosslyn (1987), Whitehouse & Bishop (2009),

Badzakova-Trajkov, Häberling, Roberts, & Corballis (2010), and Pinel & Dehaene (2010).


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Panel A: Left Dominant (typically lateralized) participants

Panel B: Right Dominant (atypically lateralized) participants

Figure 3: VHF asymmetries of left-handers as a function of language dominance. Panel A

shows the performance of the left hemisphere dominant (typically lateralized) participants

(left: RT; right: PE). Panel B shows the performance of the right hemisphere dominant

(atypically lateralized) participants. For the symmetric figures, there is a clear interaction

between VHF and cerebral dominance (a LVF advantage for the typically lateralized

participants and a trend towards RVF advantage for the atypically lateralized

participants). Contrary to the findings of the participants with language and motor control

in the same hemisphere, the left-handed participants with LH language control tended to

show an opposite VHF advantage for the asymmetric figures than the symmetric figures

(top panel). Error bars indicate the 95% confidence intervals and are based on the error

terms of the VHF * Stimulus type ANOVA (Masson & Loftus, 2003).

400

450

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RTs

(ms)

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The alternative view says that atypical laterality of language will result in reversed

laterality for other functions. Such a result can be expected on the basis of the cognitive

crowding hypothesis (Lansdell, 1969; Levy, 1969; Teuber, 1974). According to this hypothesis,

visuospatial abilities cannot fully develop in the language hemisphere and are “crowded out” to

the other brain half. Supporting evidence for this theory was recently reported by Cai, Van der

Haegen & Brysbaert (2013) who ran an fMRI study on a visuospatial attention task (the

landmark task) with the same participants as in the present study. In the landmark task brain

activity was compared between an experimental condition, in which participants had to judge

whether a vertically displayed line bisected a horizontal line in the middle, and a control

condition, in which participants had to indicate whether the vertical line touched the horizontal

line. The landmark task is known to activate a dorsal fronto-parietal pathway in the right

hemisphere. Cai et al. (2013) found that their data were almost completely in line with the

crowding hypothesis: Whereas 15 of 16 participants with LH speech dominance showed the

expected RH asymmetry, all 13 participants with RH speech had a reversed LH laterality in the

landmark task. The authors argued that the complementarity pattern had been obscured in

previous studies, because inadequate comparison conditions had been used and/or the reliability

of the measures had not been ascertained, so that measurement noise could have been mistaken

for independence of cognitive functions.

Given the findings of Cai et al. (2013), it would be interesting to know whether their

results can be replicated with the present symmetry task. The predictions are straightforward.

According to the cognitive crowding hypothesis, we should observe a reversed RVF advantage

for symmetric stimuli in participants with right hemisphere language dominance. In contrast,

according to the statistical independence hypothesis, atypical lateralization of language should


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have no influence on the laterality of symmetry detection and, hence, participants with right

speech dominance should show the same LVF advantage for symmetric stimuli. Seventeen left-

handers with known atypical RH dominance (Van der Haegen et al., 2011) took part in the

symmetry detection task. Given the data of Experiment 2, this is a rather small sample. However,

it is the best we could achieve, given the difficulty to find participants with atypical brain

asymmetry.

Method

Participants

Participants were 17 left-handed participants from Ghent University who were recruited

from the study by Van der Haegen et al. (2011). They were all identified as being clearly

atypically right lateralized for speech by the fMRI study. Participants were paid for their

participation.

Stimuli and Procedure

The stimuli and the procedure were exactly the same as in Experiments 1 and 2.

Results

The data are shown in the lower part of Figure 3. As in Experiment 2, we performed 2 x 2

ANOVAs on the RTs en PEs with VHF (2) and Stimulus type (2) as factors. There was no

significant main effect of VHF, neither for RT (LVF = 578 ms, RVF = 562 ms; F (1, 16) = 1.59,

p=.22), nor for PE (LVF = 19.2%, RVF = 16.6%; F (1, 16) = 2.24, p=.15). The main effect of

stimulus type was significant for RT (symmetric = 554 ms, asymmetric = 586 ms; F (1, 16) =

7.56, p<0.05), but not for PE (symmetric = 18.3%, asymmetric = 17.4%; F(1,16) = .09, p=.76).

Although the interaction between VHF and Stimulus type was not significant (RT: F(1,16) = .05,


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p=.81, PE: F(1,16) = .37, p=.55), we ran one-way anova for the symmetric and asymmetric

stimuli separately, given their central roles in our prediction. For symmetric figures, there was a

RVF advantage of 19 ms and 4.7%, but this failed to reach significance both in RT (LVF = 563

ms, RVF = 544 ms; F (1,16) = .852, p=.370) and PE (LVF = 20.7%, RVF = 16.0 %; F (1,16) =

1.415, p=0.252). For the asymmetric figures, a similar but even smaller trend to RVF advantage

was found, which was far from significant, both in RT (LVF = 592 ms, RVF = 579 ms, F (1,16)

= .699, p=.416) and PE (LVF = 17.7%, RVF = 17.1% ; F(1,16) = .034, p= 0.857).

In terms of individual scores, for the symmetric stimuli in the reaction time (RT) data

only 8 out of 17 participants had the RVF advantage predicted by the crowding hypothesis while

9 participants showed a LVF advantage. For the percentage of errors, 9 out of 17 participants

had a RVF advantage while the other 8 participants showed a LVF advantage. For the

asymmetric stimuli, in terms of reaction times 9 out of 17 participants displayed the RVF

advantage for RT and 8 out of 17 participants for PE.

To further test the relationship between speech dominance and laterality of symmetry

detection, we correlated the VHF differences in RT obtained in the present experiment with the

participants’ speech laterality indices, as reported by Van der Haegen et al. (2011). These

laterality indices were based on the difference in brain activity in Broca’s area between the left

and the right hemisphere (measured with fMRI) while the participants were silently generating

words starting with a target letter (see Van der Haegen et al., 2011, for further details about the

task and the calculation of the laterality index). This analysis was limited to the 19 left-handed

participants of Experiment 2 and the 17 left-handed participants of Experiment 3, who took part

in the earlier fMRI study, as the speech laterality index could not be calculated for the 18

additional participants of Experiment 2 and we wanted to avoid a confound with handedness


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(therefore excluding the right-handed participants from Experiment 1). There was a positive

correlation of r = .299 (N = 36, p= .076) for symmetric figures (indicating that participants with a

strong LH dominance for language showed a larger LVF advantage for symmetry detection)

while only a correlation of 0.144 (N = 36, p = 0.403) was found for asymmetric figures.

Discussion

Experiment 3 revealed a trend towards a RVF advantage for parafoveal symmetry detection in

participants with atypical right hemispheric speech dominance. This finding is more in line with

the predictions of the cognitive crowding hypothesis than the statistical independence hypothesis,

which would have been confirmed if the participants with atypical speech dominance had shown

a LVF advantage as well. This suggests that the consequences of atypical speech laterality go

beyond language-related functions. Cai et al. (2013) reached the same conclusion on the basis of

the landmark task. At the same time, it must be acknowledged that there was much more

variability among the participants with atypical speech dominance, because the RVF advantage

was found in only half of the sample. As a result, the RVF advantage was not statistically

significant. So, although the data point against the statistical independence hypothesis, they do

not point against a view of more variability in participants with atypical speech dominance.

Further of interest is the observation that the VHF advantage was the same for symmetric

and asymmetric figures, in line with the results of Experiment 1 and opposite to those of

Experiment 2. A possible interpretation could be that the left-handed LH dominant participants

of Experiment 2 had their control centers for speech and dominant hand in opposite hemispheres,

whereas for all other participants these centers were in the same hemisphere (either LH or RH).


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Future studies with larger samples of atypically lateralized subjects are needed to confirm

the explorative findings of Experiment 3. In conjunction with the correlational analysis of the

lateralization indices and VHF differences, these data do give a first indication that symmetry

detection lateralizes to the language non-dominant hemisphere.

General discussion

In this paper we addressed two questions:

a) Whether symmetry detection is a right hemisphere function resulting in a LVF advantage

in a VHF-paradigm.

b) Whether the VHF advantage differs in people with typical and atypical language

dominance.

For the first question we sought to replicate a pattern we discerned in the literature (Corballis

& Roldan, 1974; Brysbaert, 1994; Wilkinson & Halligan, 2002, 2003) but which had mainly

been investigated as a secondary phenomenon. Given that symmetry detection is a fast-acting

visual function and given that most visuospatial functions are lateralized to the right in the

majority of people, we hypothesized that we should observe a robust LVF advantage in a

properly run VHF task (Hunter & Brysbaert, 2008). We indeed were able to do so (Experiments

1 and 2). For the correct interpretation of this finding it is important to keep in mind that the

symmetry detection we studied consisted of symmetry outside the fixation location. As discussed

in the introduction, there is evidence that symmetry detection at fixation may be based on other

processes (Herbert & Humphrey, 1996) with bilateral involvement of the extrastriate dorsolateral

occipital cortex (Cattaneo et al., 2011; Sasaki et al., 2005; Tyler et al., 2005).


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We used Hugdahl’s (2000) distinction between language and visuospatial functions as the

basis of our prediction. However, we do not want to exclude the possibility that the finding is in

line with other hypotheses of brain asymmetry as well. One of these hypotheses is the spatial

frequency hypothesis (Sergent, 1983; De Valois & De Valois, 1988; Kosslyn, Chabris, Marsolek

& Koenig, 1992). According to this hypothesis, the right hemisphere is specialized in processing

low spatial frequencies, whereas the left hemisphere is better at processing high spatial

frequencies. Our data are in line with this hypothesis if we assume that the symmetry decision in

our task was based on low spatial frequency information. Indeed, some early theories postulated

that symmetry detection largely depended on low level spatial grouping (Barlow & Reeves,

1979; Julesz, 1979). However, more recent models of symmetry perception no longer assume a

dominance of low-frequency information but include filters of different frequencies and

orientations, which are used flexibly as a function of stimulus complexity (Dakin & Hess, 1997;

Poirier & Wilson, 2010).

Another hypothesis of hemispheric specialization is that the right hemisphere may be

specialized in identifying the global forms of stimuli, whereas the left hemisphere would be more

specialized at processing details (Lamb, Robertson, & Knight, 1989, 1990). Our data are in line

with this view if we can assume that the symmetry perception for our stimuli was based on the

global form of the stimulus. There indeed seem to be two particularly informative regions of

information for symmetry perception: one around the symmetry axis and one consisting of the

stimulus outline (Wenderoth, 1995).

The two alternative views illustrate that the division between language processing vs.

visuospatial processing need not be the only distinction explaining the right hemisphere

dominance for symmetry detection in the stimuli we used. An intriguing possibility of the


P. | 182

alternative views is that different types of stimuli may induce different hemispheric superiorities

(and VHF advantages) for more complex figures or figures with asymmetries in the details. This

could also explain why not all studies have found a LVF-advantage for symmetry perception,

which is an attractive option for future research.

The second question addressed in this paper is what consequences atypical language

laterality has for the lateralization of other functions. This is still a much under-investigated issue

in brain research. At first, researchers assumed complementarity of the brain hemispheres with a

causal role of speech laterality. Lateralization of speech implied that all language-related

functions were localized in the same hemisphere, and that other functions, in particular

visuospatial functions, were forced to the other hemisphere. An example of this view is the

cognitive crowding hypothesis (Lansdell, 1969; Levy, 1969; Teuber, 1974), discussed in the

Introduction (see also Plaut & Behrmann, 2011, for a recent computational implementation of

this view).

The complementarity view was questioned by Bryden et al. (1983), who observed a higher

incidence of combined language and spatial disorders after unilateral brain damage than

predicted. In their view, the pattern of results was more in line with a statistical independence

interpretation, according to which there is bias to left lateralization of language and a bias to

right lateralization of visuospatial functions, but no cross-talk between both biases. Such an

interpretation was in line with the modularity model of the brain that became dominant in the

1980s (Fodor, 1983). According to this model, the brain consisted of several independent

(encapsulated) modules functioning autonomously. The idea was taken up by several laterality

researchers (e.g., Kosslyn, 1987; Brysbaert, 1994) and is still used as a framework for the

interpretation of brain imaging data (Badzakova-Trajkov, Häberling, Roberts, & Corballis, 2010;


P.| 183

Pinel & Dehaene, 2010). Surprisingly, when it was investigated in the largest group of people

with atypical speech dominance examined thus far, the statistical independence idea failed to

predict the findings (Cai et al., 2013). As a matter of fact, the findings were almost completely

in line with the complementarity view (only one exception on a total of 29 participants tested).

Our data (Experiment 3) are also more in favor of the complementarity view than the

statistical independence view. Whereas right-handed and left-handed participants with LH

speech dominance showed a LVF advantage of 30 ms and more (Experiments 1 and 2), left

handed participants with RH dominance showed a reverse RVF advantage of some 20 ms

(Experiment 3). According to the statistical independence hypothesis, atypical lateralization of

language should have had no influence on the laterality of symmetry detection and, hence, all

groups should have shown the same LVF advantage for symmetry detection. At the same time,

there was quite some variability in the data of the RH dominant participants, preventing the RVF

advantage from being significant. Therefore, it is safer to consider Experiment 3 as a pilot

experiment to be backed up and extended by future investigations.

Conclusion

In the present study, we set out to determine whether symmetry detection off fixation is a

cognitive function lateralized to the right hemisphere, like the other visuospatial functions. For

this purpose we chose a behavioral VHF task along the lines recommended by Hunter &

Brysbaert (2008). In two experiments we found a clear LVF advantage for the detection of

symmetrical figures in LH speech dominant participants. In the last experiment we observed a

trend towards a reversed RVF advantage for participants with RH speech dominance. These

findings are in line with the proposal that visuospatial functions lateralize to the brain half

opposite to the hemisphere involved in language processing (Hugdahl, 2000).


P. | 184

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Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions

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Chapter 5: Evidence for Right Hemisphere

Superiority in Figure Matching & Judging Negative

Emotions from Facial Expressions


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Chapter 5: Evidence for Right Hemisphere Superiority in Figure

Matching & Judging Negative Emotions from Facial Expressions

While there has been plenty of research investigating the lateralization of left-hemisphere

cognitive functions, limited research has been conducted on right hemisphere functions. In this

study, we investigated the lateralization of figure comparison using our VHF paradigm and also

sought to compare existing theories of facial emotion recognition i.e. right hemisphere

hypothesis& the valence hypothesis, respectively. We were able to replicate a significant

LVF/right hemisphere advantage for figure comparison. The results for the facial emotion

recognition experiments were not conclusive, though indications favored the right hemisphere

hypothesis. Finally, we were able to discern that participants are faster for responding to ‘yes’

responses with their index fingers; in the experiments using our HF-paradigm.

Introduction

For several decades, functional asymmetries between the two cerebral hemispheres have

been the focal point of laterality research. Asymmetries have been reported for both structure and

function of the two hemispheres (for a review on structural asymmetry see Amunts, 2010; for a

review on functional asymmetries, see Hugdahl & Westerhausen, 2010).

Several of the observed asymmetries in behavior have been viewed together as

dichotomies of function between the two hemispheres of the brain. Common examples are:

language versus visuospatial functions (Davidson & Hugdahl, 1995), local versus global

processing (Bradshaw & Nettleton, 1981), categorical versus co-ordinate decisions (Kosslyn,

1987) and processing of high versus low spatial frequencies (Sergent, 1983). Hugdahl (2000)


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points out that of all these dichotomies, only the language versus visuo-spatial processing

dichotomy has given the most consistent account of experimental results over time.

While there has been a large body of research involving language/verbal material

supporting left/dominant hemisphere superiority, studies of cerebral laterality with visuo-spatial

measures have been less numerous (Gur et al., 2000; Unterrainer et al., 2000 & Kimura, 2004).

One of the reasons for this could be that few tasks used in the visuo-spatial paradigms were

found to produce the same consistent and robust results as exhibited by the word- processing

paradigms, which yield reliable and replicable evidence for a left hemisphere advantage

(Whitehouse, Badcock, Groen & Bishop, 2009). Consequently, there has been a disparity in the

amount of research dedicated to the functions of the left compared to the right hemisphere. This

presents a case for encouraging more research with right hemisphere capabilities; and recently a

number of researchers have taken up the challenge.

Most of the early research about right hemisphere functions used the visual half field

paradigm, which makes use of the organization of the human visual system to judge the

adeptness of a particular hemisphere at a particular task by tachistoscopically presenting stimuli

to either the left or the right visual half-fields (LVF or RVF). Better performance on the stimuli

presented in the left visual field is taken as evidence for superior right hemisphere stimulus

processing and vice-a-versa.

With this paradigm the right hemisphere was found to be efficient at a variety of visual

and spatial processing tasks, such as: spatial abilities (Benton, Hannay & Varney, 1975), face

recognition (Geffen, Bradshaw & Wallace, 1971), identification of emotional expression (Ley, &

Bryden, 1979), lightness discrimination (Davidoff, 1975), color perception (Hannay, 1979), dot


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localization (Bryden, 1976), line orientation (Atkinson & Egeth, 1973) and depth perception

(Kimural & Durnford, 1971). Most of the time, however, the left visual field advantage was

small, suggesting that the right hemisphere superiority was not due to unilateral specialization

but due to relative degrees of lateralization.

In recent times, the use of neuroimaging technology has extended and validated the

earlier behavioral findings about right hemisphere functions. In fMRI studies, the right

hemisphere has additionally been found to mediate in spatial attention (Shulman, Pope, Astafiev,

McAvoy, Snyder & Corbetta 2010), solving semantic ambiguities (Mashal, Faust, Hendler &

Jung-Beeman, 2008), joke appreciation (Marinkovic, Baldwin, Cortney, Witzel, Dale, and

Haldgren, 2011), and even appreciating agrammatical musical sequences (Klostermann, Loui &

Shimamura, 2009). Others like Yovel, Tambini, & Brandman (2008) and Hemond, Kanwisher &

Op de Beeck (2007) found dedicated areas in the right hemisphere; specifically the fusiform

gyrus related to face processing.

In a TMS study, Battelli, Herpich, Tyler, Grossman & Agosta (2013) found evidence for

a major role of the right hemisphere in temporal aspects of attention. Also in a TMS study,

Hirnstein, Westerhausen & Hugdahl (2013) found a role for the right planum temporal (PT) in

stimulus selection and (stimulus driven) auditory attention. Finally, Bona, Herbert, Toneatto,

Silvanto & Cattaneo (2013) found evidence for right hemisphere specialization in symmetry

detection and grouping in an fMRI-guided TMS study.

All in all, with improvements in methodology there has been an array of findings in

recent times illuminating the various functions in which the right hemisphere takes the lead.


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In the current series of experiments we investigate whether the results with the visual

half-field paradigm become more convincing if we use our own visual half-field protocol

(Hunter & Brysbaert, 2008; Verma & Brysbaert, 2011; Verma, van der Haegen & Brysbaert,

2013). This protocol stresses the importance of bilateral stimulus presentation, bimanual

responses, the use of matched stimuli in the visual half-fields, and the need for a sufficiently

large number of trials to get stable results.

Using this paradigm we have demonstrated reliable right hemisphere superiority for

symmetry detection in typically lateralized right and left handed individuals, whereas indications

of reversed left hemisphere superiority for symmetry detection in atypically lateralized left

handed individuals were observed (Verma, et al., 2013). The results regarding symmetry

detection from the visual half-field paradigm have already been corroborated by similar findings

from a TMS study reported by Bona et al. (2013). Also, the same paradigm has been used

successfully for replicating twice the left hemisphere lateralization for tool recognition reported

in neuroimaging studies (Verma & Brysbaert, 2011, submitted). Hence, we had good hopes that

this particular visual half-field paradigm could return more consistent left visual field advantages

than reported in the past. We decided to concentrate on two right hemisphere functions, which

fall in the purview of visual processing, i.e. figure comparison and facial emotion perception.

Figure comparison involves asking participants to compare a black irregular polygon

presented in the target visual field (left or right) to a same or different polygon presented 200 ms

earlier in central vision. Participants have to indicate by means of a bimanual key press response

whether the comparison and target polygons match or not. Performance is measured in terms of

reaction times (RTs) and accuracy. This particular task has been used in a series of experiments

by (Hausmann and Gunturkun (1999, 2000) and is reported to reveal a robust left visual field


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advantage, hence indicating a right hemisphere involvement (Rode et al., 1995; Hausmann &

Gunturkun, 1999; Hausmann, Becker, Gather & Gunturkun, 2002). One likely reason for this is

that the polygons cannot be named easily and hence require visuo-spatial processing to be

compared.

The other right hemisphere function we have chosen to investigate involves judgment of

emotion from facial expressions. Recognizing emotions embedded in facial expressions, is a

specialized function that requires a fair degree of sophistication. At least two types of

information need to be accessed when interacting with faces, i.e. identity of the face & the

emotional expression on the face. Evidence indicates that these two information channels may be

handled by separable and independent subsystems (Bruce & Young, 1986; Young, McWeeny,

Hay & Ellis, 1986; Posamentier, & Abdi, 2003). It is known that the processes involved in the

identification of emotional expression from faces engage the right and the left hemispheres

differentially, though the exact role of the hemispheres is still a cause of considerable debate

(Adolphs, Jansari & Tranel, 2001; Najit, Bayer & Hausmann, 2013).

Two major theories have been put forward to explain the functional cerebral asymmetry

for perception of emotion from faces, namely the Right Hemisphere Hypothesis and the Valence

Specific Hypothesis (Adolphs, et al., 2001). The right hemisphere hypothesis proposes that all

emotions are processed preferentially by the right hemisphere whereas the valence specific

hypothesis postulates that the right hemisphere is specialized for processing negative emotions

(anger, fear, sadness & disgust) and the left hemisphere for processing positive emotions

(happiness, surprise) (Najit et al., 2013, Adoplhs, et al., 2001).


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A number of studies have used the VHF paradigm to evaluate the competing hypotheses

(Hugdahl, Iversen, Ness & Flaten, 1989; Hugdahl, Iversen & Johnsen, 1993; Van Strien & Van

Beek, 2000; Rodway, Wright & Hardie, 2003; Alves, Aznar-Casanova, & Fukusima, 2009;

Stafford & Bandaro, 2010; Jansari, Rodway & Gonclaves, 2011). Typically, such a study

involves presenting emotionally salient human or chimeric faces to either the left visual half field

or the right visual half field, or both; and participants are asked to identify, discriminate or match

the facial expression of the target stimuli (Najit, et al., 2013). Performances in the respective

visual fields are compared to assess the involvement of each hemisphere in emotion recognition

as a whole and also their efficiency in processing specific emotions.

Evidence has been reported for both the right hemisphere hypothesis (Borod, Cicero,

Obler, Welkowitz, Erhan, Santschi, Grunwald, Agosti & Whalen, 1998; Burt & Perrett, 1997)

and the valence specific hypothesis (Canli, 1999; Jansari, Tranel & Adolphs, 2000; Adolphs, et

al., 2001). Furthermore, the task has been used to compare the hemispheric asymmetry for facial

emotion perception in left and right-handed participants and reported evidence indicating that the

right hemisphere advantage in facial emotion perception is independent of handedness (van

Strien and van Beek, 2000). A recent study, which also reviewed the earlier literature on the

competing hypotheses, also failed to find conclusive evidence in favor of either the right

hemisphere or the valence specific hypothesis. Instead they reported a consistent right

hemisphere advantage for a subset of negative emotions only, i.e. anger, fear & sadness

suggesting a “negative valence model” (Najit et al., 2013).

In the first experiment of this study we asked participants to match a black irregular

polygon presented centrally to a polygon presented 200 milliseconds later in a target visual field


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(left or right) indicated by a central arrow. Going by the literature, we hypothesized a clear left

visual field/right hemisphere advantage for this task.

For facial emotion perception, we decided to compare instances of a positive emotion

(happiness) with two different instances of negative emotions (sadness & disgust) in separate

experiments. Accordingly, in the second experiment we compared the recognition of happy

versus sad faces and in the third experiment we compared the recognition of happy versus

disgusted faces. If the right hemisphere hypothesis holds, an overall left visual field/right

hemisphere advantage should be found across the two experiments on all types of emotional

faces; else a left visual field/right hemisphere advantage should be found for sad & disgusted

faces, while a right visual field/left hemisphere advantage should be found for the happy faces in

the two experiments.

Experiment 1: Figure Matching Experiment

Method

Apparatus

The experiment was carried out using a 17” CRT monitor placed at a distance of 80 cm

from the participant. The experiment was carried out using the presentation software E-Prime

2.0. A response box was used to register bi-manual key-press responses.

Participants

Forty-one right-handed undergraduate students from the Gent University participated in the

experiment. They were paid 15 € to participate in the session.


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Stimuli

The stimuli consisted of 80 filled black irregular polygons, having an unfixed number of

sides; sized at 150 x 150 pixels. These stimuli have also been used in earlier studies (Rode et al.,

1995; Hausmann & Gunturkun, 1999; Hausmann, Becker, Gather & Gunturkun, 2002). Some

examples are given in figure 1.

Figure 1: Examples of the irregular polygons used in Exp. 1. In total 80 different polygons

were used in the experiment so that they could not easily be learned.

Procedure

Before the start of the main session participants were familiarized with the stimuli used in

the experiment. A trial started with a blank screen presented for 1000ms; followed by a fixation

cross presented at the centre of the screen for 300ms. The fixation cross was replaced by a

polygon presented at the same location for 200ms. A slide with an arrow at the center and one

polygon on each side of the arrow was presented after that, again for 200ms. The arrow could

point either towards the LVF or the RVF and the participants were to respond to the visual field

pointed to by the arrow. The stimulus offset was replaced by a blank screen, as there was no

mask presented. Participants responded to the blank screen and decided whether the polygon


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presented at the indicated visual field matched the centrally presented polygon by pressing with

the index fingers of both hands on the response box; if not, they pressed with the middle fingers

of both hands. There were 8 types of trails keeping the 3 factors (VHF, Match, and

Compatibility) in mind. Compatible trials here refer to the cases where stimuli in both the visual

fields matched the central polygon; all other instances would be considered incompatible trials.

Overall, there were 60 instances of the 8 types of trials in mind; hence in total 480 trials divided

into two blocks and presented in two blocks. Reaction times and accuracy were measured.

Reaction time measurement began at stimulus offset, when the blank screen appeared; the upper

limit was set at 3000 ms.

Results

The results of the first experiment are shown in Table 1. For the RT analyses, only the

correct trials were included. We started with a 2 x 2 x 2 ANOVA keeping VHF (2; LVF, RVF),

Match (2, Matched, Unmatched) and Compatibility (Compatible, Incompatible) as factors. The

main effect of visual half field turned out to be insignificant, F (1, 40) = 0.97, p>.05. The main

effect of match, came out to be significant, F (1, 40) = 35.77, p< 0.01; indicating that the match

trials were faster (Match = 472 ms, Unmatch = 505ms). The main effect of compatibility was

also found to be significant, F (1, 40) = 12.17, p< 0.01; indicating that the trials on which

compatible i.e. similar information was presented to both the visual half fields were faster

(Compatible = 478ms, Incompatible = 498ms). The significant interactions were, VHF x Match,

F (1, 40) = 8.91, p < 0.01; VHF x Compatibilty, F (1, 40) = 13.21, p< 0.01 and Match x

Compatibilty, F (1, 40) = 12.42, p < 0.01. We also compared the reaction times for match trials

in the incompatible condition for the left and right visual half fields respectively, and found a


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significant left visual field advantage for match trials; F (1,40) = 4.00, p< 0.05; indicating that

match trials in the left visual field were faster (LVF = 467ms, vs. RVF = 484ms).

---------------------------------------------------------------------------------------------------------------------

Match Unmatch

LVF RVF LVF RVF

Compatible 472 (79%) 465 (76%) 503 (89%) 473 (77%)

Incompatible 467 (83%) 484 (80%) 522 (88%) 521 (88%)

--------------------------------------------------------------------------------------------------------------------

Table 1: The performance of participants in reaction times (and percentage accuracy) for

the different conditions. The difference in incompatible match trials over the left and right

visual fields of 17 ms was significant.

---------------------------------------------------------------------------------------------------------------------

For the data on percentage accuracy, we followed the same analysis scheme. We again

first performed the 2 x 2 x 2 ANOVA keeping VHf (2; lvf, rvf), Match (2; match, unmatch) and

Compatibility (2; compatible, incompatible) as factors. The Main effect of visual half field

turned out to be significant, F (1, 40) = 5.93, p < 0.05 (p = .019); indicating that the participants

were more accurate in the left visual field. Further, the main effect of Match, also came out to be

significant, F (1, 40) = 11.62, p< 0.01. Finally, the main effect of compatibility was found to be

significant as well, F (1, 40) = 6.95, p < 0.05 (p = 0.012). Significant interactions were, VHF x

Compatibility, F (1, 40) = 5.01, p<.05; and VHF x Match x Compatibility, F (1, 40) = 17.25,

p<.01.


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Discussion

Experiment 1 was set up to see whether our VHF paradigm (Hunter & Brysbaert, 2008;

Verma & Brysbaert, 2011; Verma, van der Haegen & Brysbaert, 2013) would give stronger

evidence for right hemisphere involvement in figure matching than the existing paradigms. The

results confirm the hypothesis of a left visual half-field/right hemisphere superiority (especially

for the accuracy data), but can hardly be called overly convincing. In particular, for the

compatible trials, there was a tendency for RVF advantage in RTs (but not in accuracy).

Remember than in these trials, the same pictures were presented in LVF and RVF and

participants had to respond to the picture indicated by the arrow. The clearest results were found

on the incompatible - match trials where two difference pictures were show and the picture to be

responded to, agreed with the previous comparison picture shown in central vision. We will

return to this condition in the General Discussion. First we present the data of the emotion

recognition experiments.

Experiment 2: Happy-Sad Facial Emotion Recognition

Method

Apparatus

The apparatus used in Experiment 1 was also used in this experiment.

Participants

The same participants, who participated in the earlier experiment, took part in this experiment.


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Stimuli

57 Happy & Sad faces of the same persons were used as stimuli; obtained from the Radboud

Faces Database (RaFD) (Langner, Dotsch, Bijlstra, Wigboldus, Hawk & Knippenberg, 2010).

All the faces were sized at 150 x 226 pixels. Figure 2 shows two examples.

Procedure

All the participants were familiarized with the faces stimuli before the start of the main

experimental session. A trial started with a blank screen for 1000ms, followed by a fixation cross

presented for 300ms. Later, a slide with an arrow presented at the center and a face stimulus on

both sides of the arrow, was presented for 200ms. The face stimuli on the two sides of the arrow

could be either happy or sad, or both happy or both sad. A difference with Experiment 1 was that

the identity of the faces differed in LVF and RVF, so that the same picture was not shown in

both VHFs. The central arrow could either point towards the LVF or the RVF and the

participants had to respond to the visual field indicated by the arrow. Participants were instructed

to decide whether the face stimulus in the target visual field was happy or sad. Participants

responded to a blank screen at the offset of the slide with the arrow and two face stimuli. The

blank screen stayed on till a maximum of 1500 ms or terminated as soon as the key press

response was made.


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Figure 2: Examples of happy and sad stimuli used in Experiment 2.


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To indicate a happy face, the participants were asked to press with the index fingers of

both hands; and to indicate a sad face, they were asked to press with the middle fingers of both

hands. Keeping the three factors in minds (VHF, Facial expression & Compatibility) there were

8 types of trials. The main experimental session consisted of 50 x 8 types of trials, leading to

overall 400 trials divided over two blocks presented to the participants with a gap of 3-4 minutes.

The main experimental session was preceded by a practice block which consisted of 40 trials.

Results

The results are shown in Table 2.

---------------------------------------------------------------------------------------------------------------------

Compatible Incompatible

LVF RVF LVF RVF

Happy 411 (85%) 418 (84 %) 415 (85%) 428 (85%)

Sad 449 (86%) 456 (85%) 463 (86%) 475 (84%)

----------------------------------------------------------------------------------------------------------------------------

Table 2: Depicting the performance of participants in reaction times (percentage accuracy)

in the Happy-Sad experiment

---------------------------------------------------------------------------------------------------------------------

The RT analysis was limited to the correct trials. In a 2 x 2 x 2 ANOVA with VHF (2;

lvf, rvf), Facial expression (2; happy, sad) and Compatibility (2; compatible, incompatible) as


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factors, the main effect of visual half-field was marginally significant, F (1, 40) = 3.24, p = .07;

hinting towards the finding that across all stimuli participants were slightly faster in the lvf than

in the rvf (lvf = 435 ms vs rvf = 444 ms). Another significant main effect was Face type, F (1,

40) =60.56, p< 0.01; indicating that participants were faster for happy faces than sad faces.

(Happy face = 418 ms vs. Sad face = 461 ms). Finally, the main effect of compatibility was also

found to be significant. F (1, 40) = 19.17, p< 0.01; indicating that participants were faster for

compatible trials (Compatible = 433 ms vs. Incompatible = 446 ms). None of the interaction

effects came out significant.

We also did separate ANOVAs for the happy and sad faces. For the happy faces, we did a

2 x 2 ANOVA keeping VHF (2; Lvf, rvf) and Compatibility (2; compatible, incompatible) as

factors. The main effects of visual half field and compatibility came out to be non-significant.

Also, the interaction between vhf x compatibility was found to be non significant.

For the sad faces, the same 2 x 2 ANOVA was performed keeping VHF (2; Lvf, rvf) and

Compatibility (2; compatible, incompatible) as factors. For the sad faces, the main effect of

visual half field was found to be insignificant. The main effect of compatibility was found to be

significant, F (1, 40) = 25.86, p< 0.01. The interaction between VHF x Compatibility did not

come out as significant.

For percentages of accuracy, we carried out an omnibus ANOVA, which had 3 factors

(VHF(2) X Face (2) X Compatibility(2). None of the main effects came out as significant. There

were no differences in terms of visual half-field (LVF= 85.9 pc vs. RVF = 85.1 pc); face type

(happy = 85.2 pc vs. sad = 85.8 pc) and even compatibility (incompatible = 85.6 pc vs.

compatible = 85.3 pc). None of the interactions between the three factors were significant.


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Discussion

The data from Experiment 2 again provide limited support for a right hemisphere

involvement in het perception of emotion on human faces. There was a next to significant LVF

advantage across the board, which was the same for happy and sad faces. This finding is in line

with the right hemisphere hypothesis, and against the valence specific hypothesis (sees the

introduction). More important (and disappointing) for us was the finding that the LVF advantage

turned out to be rather weak, making it difficult to introduce manipulations in the design and

examine the effects.

While preparing the stimulus materials for Experiment 2, it struck us that for most faces

the teeth were visible when the person was happy (see Figure 2). To investigate the impact of

this possible confound, we included a third experiment, in which the teeth were visible in the

conditions with both positive and negative emotions. This was possible by comparing happy

versus disgusted emotions (Figure 3). The face stimuli with disgusted facial expression are

comparable to the stimuli with happy facial expression, as the teeth are equally visible in both

the cases and the only difference is the facial expression. Furthermore, the disgusted expression

also serves as a good candidate to test the valence specific hypothesis because it is a “negative

valence” expression.

Experiment 3: Happy-Disgusted Facial Emotion Recognition

In Experiment 3, we compared the face stimuli with happy and disgusted facial

expressions.


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Method

Apparatus

The same apparatus that was used in the earlier experiments was used in this experiment.

Participants

The same participants, who took part in the earlier two experiments, participated in this

experiment too.

Stimuli

The 57 happy faces used in the earlier experiment were used in combination with faces of

the same persons bearing the disgusted expression obtained from the Radboud Faces Database

(RaFD) (Langner, Dotsch, Bijlstra, Wigboldus, Hawk & Knippenberg, 2010).

Procedure

All the participants were familiarized by the faces stimuli before the start of the main

experimental session. A trial started with a blank screen for 1000ms, followed by a fixation cross

presented for 300ms. Later, a slide with an arrow presented at the center and a face stimulus on

each side of the arrow, was presented for 200ms. The face stimuli on the two sides of the arrow

could be either happy or disgusted, or both happy or both disgusted. As in Experiment 2, the

faces were always from different persons. The central arrow could either point towards the LVF

or the RVF and the participants had to respond to the visual field indicated by the arrow.

Participants were instructed to decide whether the face stimulus in the target visual field was

happy or disgusted. Participants responded to a blank screen at the offset of the slide with the

arrow and two face stimuli. The blank screen stayed on till a maximum of 1500 ms or terminated

as soon as the key press response was made.


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Figure 3: The stimuli used in Experiment 3. When people show a disgusted face their teeth

are visible, just as when they are laughing. This allowed us to check whether the visibility

of the teeth was responsible for the data observed in Experiment 2.


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To indicate a disgusted face, the participants were asked to press with the index fingers of

both hands; and to indicate a happy face, they were asked to press with the middle fingers of

both hands. Keeping the three factors in minds (VHF, Face & Compatibility) there were 8 types

of trials. The main experimental session consisted of 50 x 8 types of trials, lead to overall 400

trials divided into two blocks presented to the participants with a gap of 3-4 minutes. The main

experimental session was preceded by a practice block which consisted of 40 trials.

Results

The main findings are shown in Table 3.

---------------------------------------------------------------------------------------------------------------------

Compatible Incompatible

LVF RVF LVF RVF

Happy 498(77%) 501 (77 %) 503 (74%) 513 (74%)

Disgusted 465 (81%) 478 (78%) 484 (78%) 500 (77%)

---------------------------------------------------------------------------------------------------------------------------

Table 3: The performance of the participants in reaction times (and percentage accuracy)

in the Happy-Disgusted experiment.

---------------------------------------------------------------------------------------------------------------------

The analyses of the RT data were limited to correct trials only. We began by a 2 x 2 x 2

ANOVA, with VHF (2; lvf, rvf), Facial expression (2; happy, disgusted) and Compatibility (2;

compatible, incompatible) as factors. In this ANOVA, the main effect of VHF did not turn out to

be significant, F (1, 40) = 2.74, p > 0.05. In contrast, the main effect of face type was significant,

F (1, 40) = 13.41, p < 0.01; indicating that the participants were faster for the disgusted faces


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(Happy = 504 ms vs. Disgusted = 482 ms). The other significant main effect was of

compatibility, F (1, 40) = 15.33, p < 0.01; indicating that the participants were faster for

compatible trials. The only other significant effect was the interaction between face x

compatibility, F (1, 40) = 5.87, p < 0.05, because the compatibility effect was larger for

disgusted faces than for happy faces.

For the sake of clarity, we also performed 2 x 2 ANOVAs with VHF (lvf, rvf)) and

compatibility (compatible, incompatible) as factors for the happy and disgusted faces separately.

For the disgusted faces, we found a next to significant effect of visual field F (1,40) = 3.23, p =

0.08; hinting at the fact that the participants were slightly faster in recognizing the disgusting

faces presented in the left visual field (lvf = 474 ms vs. rvf = 489 ms). The main effect of

compatibility was also found to be significant, F (1, 40) = 17.29, p < 0.01; indicating that the

participants were faster for compatible trials (compatible = 471ms vs. incompatible = 492 ms).

The interaction between vhf x compatibility was not significant.

For the happy faces, the main effect of Compatibility was, F (1, 40) = 4.49, p < 0.05;

indicating that the participants were faster on compatible trials (compatible = 500 ms vs.

incompatible = 508 ms). The main effect of VHF was not significant (LVF = 501 ms vs. RVF =

507 ms); also the interaction between VHF x Compatibility was not significant.

The analysis of percentage accuracy data followed the same scheme as that of the RTs. In

the omnibus ANOVA none of the main effects was significant; no differences were observed in

terms of VHF (LVF = 77.7 pc vs. RVF = 76.7 pc), Face (Happy = 75.9 pc vs. Disgusted = 78.6

pc) or Compatibility (incompatible = 76.0 pc vs. compatible = 78.5 pc). Given these null effect,

we do not report the separate analyses for the happy and disgusted faces.


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Discussion

There are two noteworthy findings in this experiment. The first is that we again find weak

evidence for a LVF advantage, in line with the right hemisphere hypothesis for emotional

processing. The findings are very similar to those of Experiment 2, making it unlikely that the

results of Experiment 2 were a confound of the visibility of the teeth in the happy conditions.

A second remarkable finding is that the responses to the happy faces in Experiment 3 are

slower than those to the disgusted faces, whereas in Experiment 2 they were faster than those to

the sad faces. This suggests that positive emotions are not always responded to faster than

negative emotions. As a matter of fact, it looks like the difference between the emotions may be

part of a larger pattern we can discern in our paradigm.

One of the features of our paradigm is that the participants have to make binary decisions.

These usually are yes-no decisions (tool vs. non-tool, object vs. non-object, symmetric vs. not,

similar or not). Throughout the experiments, we found that responses to the yes-trials were faster

than those to the no-trials. In addition, the VHF asymmetry was larger for the yes-trials than for

the no-trials.

What Experiments 2 and 3 suggest is that not so much the yes-no distinction is important,

but the distinction between responding with the digits vs. the middle fingers. There is a

considerable literature in experimental psychology about so-called markedness effects.

‘Markedness’ refers to a condition in which the response alternatives do not have equal strength,

but one is dominant over the other or is preferentially associated with one type of response than

with another. In numerical cognition, for instance, it has been noticed that even numbers are

faster responded to with the right hand, whereas the reverse is true for odd numbers. This is


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called the linguistic markedness association of response codes (MARC) effect (Willmes &

Iversen, 1995; Neurk, Iversen & Willmes, 2004; Cho & Proctor, 2007). Berch et al. (1999)

proposed that the MARC effect is due to “compatibility between the linguistically marked

adjectives ‘left’ and ‘odd’ and the unmarked adjectives ‘right’ and ‘even’” (p. 296).

Proctor and Cho (2006), in their polarity correspondence account, attributed the

markedness effects to a tendency participants have to translate response alternatives along a ‘+’

vs ‘-’ polarity dimension. In this view markedness can be considered as a form of polarity coding

(Cho & Proctor, 2007). Among the various tasks to which the polarity correspondence account

applies, we find up vs. down, right vs. left mapping, even vs. odd, above vs. below (Cho &

Proctor, 2003; Proctor, Wang & Wu, 2002; Weeks & Proctor, 1990). To this sequence we could

add: digits vs. middle fingers.

Indeed, when we look back upon the series of experiment run in this thesis, we always

find that the digit responses are faster than the middle-finger responses, and tend to show

stronger VHF asymmetries. What Experiments 2 and 3 suggest, is that the fingers indeed may

make the difference, rather than the allocation of responses to the fingers. Indeed, the positive

emotion happiness was responded to faster in Experiment 2 than the negative emotion sadness

but the negative emotion disgust was responded to faster in Experiment 3 than the positive

emotion happiness (the ideal test would, of course, be to compare the same emotions in both

experiments, assigned to the different fingers; unfortunately, there was no time any more to run

this pair of experiments).

To get an idea of the statistical robustness of the polarity effect in our paradigm, we ran a

combined analysis of the RT data for the three experiments put together, to compare the ‘digits’


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and the ‘middle-fingers’ responses. A similar, response type (2) x vhf (2) ANOVA was done.

The main effect of response type came out significant F (1, 40) = 72.54, p < 0.01; indicating that

over all three experiments “digits” responses were faster (digits = 463ms vs. middle-fingers =

500 ms). The main effect of visual half field was also significant, F (1, 40) = 4.59, p <0.05;

indicating an overall lvf/right hemisphere advantage ( lvf = 476 ms vs. rvf = 487 ms). The

interaction between response type x vhf did not come out significant, F (1, 40) = 2.31, p > 0.05;

but separate analyses indicated a significant lvf/right hemisphere advantage the “digits”

responses (matched, happy, and disgusted combined: lvf = 455 ms vs. rvf = 471 ms; F (1, 40) =

5.5, p < 0.05) and not for the “middle-fingers” responses (unmatched, sad, happy combined: lvf

= 496 ms vs. rvf = 503 ms; F (1, 40) = 1.66, p > 0.05).

General Discussion

In this study, we examined whether the VHF paradigm we have been developing in this

thesis (Hunter & Brysbaert, 2008; Verma & Brysbaert, 2011, Verma, Van der Haegen, &

Brysbaert, 2013) is better than the existing ones to uncover right hemisphere functions. To our

regret, this is not really the case. Whereas the findings with the paradigm are quite clear for left

visual field functions such as word and picture naming (Hunter & Brysbaert, 2008; Van der

Haegen, Cai, Seurinck, & Brysbaert, 2011) and tool recognition (Verma & Brysbaert, 2011,

submitted), the results for right hemisphere tasks seem to yield rather small LVF advantages that

struggle to exceed the threshold of statistical significance. This may be an indication of the fact

that right hemisphere functions are less lateralized than left hemisphere function, or it may be an

indication that we have not yet found the best tasks to study right hemisphere functions. In any

case, the findings of the present series of experiments suggest that our paradigm itself with

bilateral stimulus presentation, bimanual responses and a large number of trials is not enough to


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improve the situation. We were successful in finding a left visual field/right hemisphere

advantage for polygon matching, a finding that has been reported in earlier experiments (Rode et

al., 1995; Hausmann & Gunturkun, 1999; Hausmann, Becker, Gather & Gunturkun, 2002) and

for emotion recognition (Natale, Gur & Gur, 1983; Davidson, Ekman, Saron, Senulis & Friesen,

1990), but our data do not stand out as particularly convincing. As a result, although our data are

more in line with the right hemisphere hypothesis for emotion recognition than the valence

specific hypothesis, they are not more conclusive than those published before (Killgore &

Yergelun-Todd, 2007; Najit et al., 2013).

One element that has come out of the present series of experiments, though, is that the

assignment of responses to the fingers seems to be important. Responses assigned to the digit

fingers seem to be faster than responses assigned to the middle fingers, in line with Cho and

Proctor’s (2007) suggestion that positive responses are faster than negative responses. This will

be specifically the case when in addition the responses differ in polarity as well (e.g., same

responses tend to be seen as positive whereas different responses tend to be seen as negative),

but the results of Experiment 3 suggest that this is not a necessity. When the negative response

‘disgust’ was assigned to the digit fingers, participants responded faster to this emotion than to

happiness. Further parametric research is indicated to find out whether this enables some further

improvements for our paradigm, as it looks like VHF differences are stronger for response

alternatives assigned to the digit fingers than for response alternatives assigned to the middle

fingers.

The fact that the assignment of emotions to response alternatives has an effect on

response speed also puts some existing claims about emotion recognition into doubt. Earlier

studies (Kirita & Endo, 1995; Adolphs, Jansari & Tranel, 2001; and Leppanen & Hietanen,


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2003) have suggested an advantage for recognizing happy faces over neutral faces or other

emotional expressions. Our results suggest that this may be due to the correspondence with

response polarity rather than with the speed of emotion recognition. In addition, Experiment 2

made us aware that one has to be very careful with the visibility of the teeth as strong indicator

of happiness. One of the possible reasons for the happy face advantage in comparison with “sad”

faces could be that the visible teeth in the happy faces might be acting as a visual cue for the

participants and helping them discriminate the happy from the sad faces. Such a proposal finds

support in a study by Calvo, Nummenmaa & Avero (2010) who conclude that the happy face

recognition advantage might rely initially on featural properties. Kirita & Endo (1995) on the

other hand attribute the happy face advantage to spatial information in the happy faces, also

proposing that the human face recognition system might be selectively tuned for recognizing

face stimuli.

To conclude, we have re-affirmed the left visual field/right hemisphere advantage for

polygon matching and emotion recognition, but have not found that our VHF paradigm is better

for these functions than the existing VHF paradigms. At the same time, our results suggest that

response polarity may be an important factor in VHF tasks with binary responses.


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Chapter 6: General Discussion

Chapter 6|General Discussion

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Chapter 6: General Discussion

The main aim of the current thesis was to test the Visual Half-Field paradigm put forward by

Hunter & Brysbaert (2008), for investigating the lateralization of cognitive functions in general,

and the lateralization of non-verbal right hemisphere functions in particular. In the course of the

thesis, I was able to test one left hemisphere lateralized task (tool-recognition), and three right

hemisphere lateralized cognitive functions (symmetry detection, figure comparison and facial

emotion detection). I was also able to develop a standardized set of stimuli related to object and

tool recognition (i.e. pictures of objects, non-objects and tools) by replicating the earlier tool-

recognition study. Finally, I was able to test the lateralization of symmetry detection in a sample

of left-handed atypically lateralized individuals, and report indications of reverse lateralization

for symmetry detection in these atypically lateralized individuals.

In the next section, I will provide an overview of the studies undertaken during the thesis.

I will briefly discuss the purpose of each study and interpret the results and their significance in a

broader perspective. In the final section, I will attempt to draw conclusions on the basis of all

these studies put together and lay down directions for future research.

In chapter 2, I presented the first behavioral VHF-study investigating tool-recognition. In

a visual half-field paradigm, we presented tool-objects and non-tool objects, bilaterally, in a tool-

recognition experiment. The target visual field was cued by a centrally presented arrow, and

participants were asked to respond with ‘yes’ for a tool and ‘no’ for a non-tool. Bi-manual key-

press responses were elicited and reaction times and accuracy were measured. Also, to be sure

that the lateralization (VHF asymmetry) obtained for tools in comparison to non-tool objects

were not due to attentional biases; we conducted a separated object recognition experiment. In an


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identical experimental set up; participants were asked to respond ‘yes’ for objects (i.e. non-tools

in the tool-recognition experiment) and ‘no’ for non-objects. Whereas the laterality of tools has

been pre-established in a range of clinical and neuroimaging studies (Frey, 2008), no clear

lateralization has been proposed for object recognition (Biedermann & Cooper, 1991).

In accordance with our hypotheses, we did not find a VHF asymmetry for objects

in the object recognition experiment; but we found a significant RVF/left hemisphere advantage

for tools in the tool recognition experiment. These results were important for a number of

reasons. Firstly, as we were able to replicate the left hemispheric lateralization of tool

recognition in our behavioral visual half-field paradigm, it became clear that the visual half-field

paradigm is a valid paradigm to investigate the lateralization of cognitive functions. Secondly,

now a new left hemisphere lateralized function, i.e. tool recognition is made available for

researchers to experiment with. We have approached tool recognition in a standard recognition

paradigm. Future experiments can now go ahead and experiment with more specific nuances.

This is interesting for new researchers, as they can now use our behavioral paradigm as the point

of departure and then take the participants to the scanner (as in fMRI) with the same tasks. For

instance, an experiment could be designed presenting tools in orientations that could be left/right

hand manipulable and see if the behavioral VHF asymmetry towards the RVF still holds.

Further, the visual half-field paradigm itself can be used to investigate the laterality of various

other cognitive functions as well. As the VHF experimental set up performed as we predicted, it

also presents a case for being used as a precursor to fMRI experiments investigating the

lateralization of cognitive functions in general. Thirdly, that we did not find a VHF asymmetry

for object recognition which implies that the VHF paradigm is sensitive to subtle differences

between classes of stimuli.


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Although, we took care to follow the recommendations of Hunter & Brysbaert (2008)

while designing the object and tool recognition experiments; we had to accept a particular

problem when selecting the stimuli. We discovered that while there were stimulus banks with

pictures of objects available that could be used as tools and non-tools for the tool-recognition

experiment, it was difficult to find matching non-objects pictures for our object recognition

experiment. For this reason, we had to conduct the two experiments using stimuli from two

different databases, i.e. stimuli (objects and non-objects) for the object recognition experiment

were drawn from one database (van Diepen & De Graaf, 1994) and stimuli (tool objects and

non-tool objects) for the tool recognition experiment were drawn from another database

(Snodgrass & Vanderwart, 1980). To tackle this problem, we paid an artist to draw stimuli for us

which could be used in both experiments. The artist was commissioned to draw matched sets of

objects (non-tool objects), non-objects and tools. As these three categories of stimuli were made

by the same person, using the same resources and maintaining the same parameters, they were

now more comparable in image criteria (size, overall shape etc). We decide to standardize these

stimuli by replicating the earlier two experiments.

So, in chapter 3, we present a study that was undertaken primarily to standardize the

pictures of objects, non-objects and tools, in order to make such stimuli available to future

researchers. The basic idea was to replicate the object recognition and tool recognition

experiments with these new stimuli and see if the VHF asymmetry for tools could be replicated,

or even enhanced by the use of better stimuli. More importantly, the participants see the same

stimuli in both experiments, hence, the data from the two experiments were mutually more

comparable. The three categories of stimuli (i.e. the objects, non-objects and tool-objects) were

organized in triplets. Each triplet comprised of a single specimen from each of the three


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categories and care was taken that specimens in a triplet were matched on criteria such as size,

overall shape etc.

To start, we asked 20 participants to rate the object-non object stimuli on a 6-point likert

scale, i.e. Object Non-Object Rating Scale, for their object-ness. To our benefit, most of the

stimuli were rated as expected, i.e. stimuli made as objects were rated as objects and those made

as non-objects were rated as non-objects. Next we used a different 6-point likert scale, i.e. Tool

Non-tool Rating scale, wherein we asked participants to rate stimuli on their tool-ness. The

stimuli which were earlier rated as objects in the Object Non-Object Rating Scale were included

along with the stimuli which were made as tools. To guide participants, a basic definition of a

tool was provided in the instructions. For the most part objects constructed as tools were rated

high on tool-ness, while those rated low on tool-ness were included as non-tools in the

subsequent experiment.

We replicated the object recognition and tool recognition experiments, following

the same protocol as in the earlier study. In the object recognition experiment, we found no VHF

asymmetry for objects, but a significant LVF/right hemisphere advantage for non-objects. As,

non-objects are unnameable figures, it is probable that the participants used spatial analysis to

distinguish the non-objects from the objects; hence, the LVF/right hemisphere advantage for

non-objects was not surprising. In the tool recognition experiment we found the expected

significant RVF/left hemisphere advantage for tool recognition. The RVF advantage for tools

was even more enhanced as compared to the earlier study; it rose from 17ms (for the

incompatible condition) to 26ms (for the incompatible condition). Surprisingly, the same objects

that did not show a VHF asymmetry in the object recognition experiment showed a LVF

asymmetry in the tool recognition experiment. This inconsistent VHF asymmetry for objects is


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not surprising (Biedermann & Cooper, 1991). More importantly, the new pictures of objects,

non-objects and tools were correctly classified in the Likert scales, and in the object and tool

recognition experiments. These pictures have now been made available for use by the research

community interesting object or tool recognition on our lab website <

http://crr.ugent.be/archives/1594 >.

Having established in the earlier two studies, that the VHF paradigm works well for a left

lateralized cognitive function (i.e. tool recognition), I decided to test the paradigm for a cognitive

function lateralized to the right hemisphere. It has been asserted by Hugdahl (2000) that the

language-visuospatial dichotomy has produced the most consistent VHF asymmetries. Hence it

was decided to choose a visuospatial function for investigation, i.e. symmetry detection.

In chapter 4, I decided to investigate the lateralization of symmetry detection using our

VHF paradigm. Symmetry detection is an important visuospatial function that helps us make

sense of our visual world. For instance, it has been found to be important for figure ground

segregation and face recognition (Koffka, 1935; Little and Jones, 2006). While there was

behavioral evidence for a right hemisphere role in symmetry detection (Corballis & Roldan,

1974; Brysbaert, 1994), the neuroimaging evidence regarding the lateralization of symmetry

detection was not clear (Tyler, Baseler, Kontsevich, Likova, Wade, and Wandell, 2005;

Cattaneo, Mattavelli, Papagno, Herbert, and Silvanto, 2011).

We hypothesized that symmetry detection as a cognitive function is lateralized to the

right hemisphere, and would yield a LVF/right hemisphere advantage in our VHF paradigm. In

order to separate the effects of handedness on the VHF asymmetry for symmetry detection,

separate experiments were performed for right handed and left handed participants.


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To start with, a group of 20 right handed undergraduate students participated in the

symmetry detection experiment. These students were also expected to be typically lateralized for

speech dominance, i.e. left hemisphere dominant. The stimuli were formed of three rectangles

arranged on top of each other, in the form of a composite figure that could be symmetrical or

asymmetrical along the vertical axis. We used bilateral presentation and participants were asked

to respond ‘yes’ if they saw a symmetrical figure in the target visual field (cued by the central

arrow) and ‘no’ for an asymmetrical figure. Bimanual key-press responses were registered and

reaction times and accuracy were measured.

The data from the right handed participants confirmed our hypotheses. We observed a

significant main effect of visual half-field and stimulus type. A significant LVF/right hemisphere

advantage for symmetry detection was observed in 80% of the participants. The results provided

a clear indication of the right hemisphere lateralization of symmetry detection in typically

lateralized right handed individuals.

Next we investigated the lateralization of symmetry detection in left handed participants.

While a large percentage of left handed individuals are also typically lateralized for speech,

about 20-25% of left handed individuals are right hemisphere speech dominant (Knecht, Drager,

Deppe, Bobe, Lohmann, & Floel, 2000). Hence, the left handed participants were segregated into

typically and atypically lateralized groups; this was done by one of my colleagues, Lise Van der

Haegen in one of her earlier studies (Van der Haegen, et al., 2011) and the two groups

participated in the symmetry detection experiment separately.

In Experiment 2, 37 typically lateralized left handed individuals participated in the

symmetry detection experiment. In this experiment, we did not find main effects for either visual


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half field or stimulus type, instead, a significant interaction between vhf and stimulus type was

found. On a closer examination, we found that 29 out of 37, i.e. 78.4 % of the left handed

typically lateralized individuals showed a LVF/right hemisphere advantage for the symmetric

stimuli. Hence, even though the right hemisphere role in symmetry detection was clear, the

findings were not as strong as in the case of right handed participants.

In experiment 3, 17 left handed atypically lateralized participants took part in the

symmetry detection experiment. While the two earlier experiments had confirmed that symmetry

detection is lateralized to the right hemisphere in typically lateralized left speech dominant

individuals irrespective of their handedness, this experiment was expected to provide an insight

into the lateralization of symmetry detection in atypically lateralized individuals. In accordance

with the crowding hypothesis (Cai et al., 2013; Lansdell, 1969; Teuber, 1974) we hypothesized a

reversed lateralization of symmetry detection in these individuals, i.e. a RVF/left hemisphere

advantage was expected. The data from this experiment, however, were not very clear. Only

around 50 % of the participants i.e. 8 out of 17 for RTs and 9 out of 17 for percentage errors

showed the expected RVF/left hemisphere lateralization for symmetry detection, while the other

participants showed the signs of a LVF/right hemisphere advantage. It should be noted, however,

that the sample consists of a small number of atypically lateralized individuals. Research with a

larger sample may provide a clearer picture. We did not have access to more of the atypically

lateralized participants, and hence, it is still unclear whether symmetry detection may be

lateralized to the left hemisphere in atypically lateralized individuals.

However, the experiments presented in Chapter 4, are important for a range of reasons.

Firstly, it can be safely said that symmetry detection (off fixation) is lateralized to the right

hemisphere in typically lateralized individuals, irrespective of their handedness. Secondly, while


P.| 239

earlier studies had used stimuli like random dot stereograms (for e.g. Corballis & Roldan, 1974)

or investigated symmetry detection indirectly (Wilkinson & Halligan, 2002), the current study

established the lateralization of symmetry detection more directly, using more ecologically valid

stimuli (i.e. geometrical shapes). Thirdly, the first two experiments also provided evidence for

the fact that VHF asymmetries are better predicted by speech dominance than handedness; as,

both groups of typically speech lateralized individuals demonstrated a LVF/right hemisphere

advantage for symmetry detection. Finally, although the results of the third experiment were not

clear, they surely indicate that lateralization of various cognitive functions in the atypically

lateralized individuals needs to be investigated. Indeed, there is already evidence that certain

visuospatial functions may be lateralized to the opposite hemisphere as well (Cai et. al., 2013).

In light of this finding, more research needs to be done with atypically lateralized individuals.

Hunter & Brysbaert (2008) also indicated that one of the best ways to test the validity of a VHF

task was to test with right hemisphere dominant individuals. To this effect, we concede that we

were limited by the number of participants in Experiment 3. However, there were indications that

symmetry detection was lateralized to the left hemisphere in some participants in whom

language was lateralized to the right hemisphere. Hence, more research on symmetry detection

with a larger sample of atypically lateralized individuals might be required to ascertain whether

the lateralization of symmetry detection gets reversed.

We had by now tested the visual half-field paradigm for one left hemisphere and one

right hemisphere lateralized cognitive function, and found that the tasks in the paradigm perform

reasonably well. It was decided to investigate the lateralization of few other cognitive functions

which were assumed to be lateralized to the right hemisphere.


P. | 240

In Chapter 5, we decided to investigate the lateralization of figure comparison and facial

emotion detection. Figure comparison is a visuospatial task, wherein participants are asked to

compare a black irregular polygon presented in the target visual field (left or right, cued by a

central arrow) to a similar polygon presented centrally 200ms earlier. Participants were asked to

respond ‘yes’ if the target polygon matched the polygon presented earlier and ‘no’ if it did not.

Bimanual key-press responses were registered, and reaction times (RTs) and accuracy were

measured. The figure comparison task had been used in earlier studies and shown to reveal a

significant LVF/right hemisphere advantage (Rode et. al., 1995; Hausmann & Gunturkun, 1999,

2000). One of the reasons for the observed right hemisphere advantage could be that the

polygons were unnameable figures, and hence participants would have been more inclined to use

spatial analysis rather than a verbal strategy or remembering a name.

We decided to replicate the figure comparison task with our new VHF paradigm and test

whether the paradigm would yield a stronger LVF advantage than reported before. This would

give us information about the efficiency of our paradigm relative to that of previous paradigms.

As expected, we were able to find a significant LVF advantage in trials where the

participants were able to match the two polygons. While we did not observe a main effect of

visual half-field in RTs, we found a significant main effect for visual half-field in the percentage

accuracy data. Such a finding may be due to the fact that the overall effect was smaller for RTs,

but more clearly present for the accuracy data; something that had also been observed in earlier

studies. All in all, we were able to replicate the LVF/right hemisphere advantage for figure

comparison, but the data with our paradigm was not more convincing than the existing data.


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In a final task, we decided to put our VHF paradigm to a tougher test. Facial emotion

judgment is an important cognitive function which helps us operate in a social environment and

has been the subject of investigation for psychologists in general and laterality researchers in

particular. While it has been known that facial emotion detection engages both hemispheres

differentially, the exact role of the two hemispheres is still an issue of considerable debate (Najit

et al., 2013). Further, two major competing theories have been offered to explain the role of the

cerebral hemispheres in facial emotion detection, i.e. the right hemisphere hypothesis and the

valence hypothesis, respectively. While the former asserts that all emotions are detected by the

right hemisphere predominantly, the latter hypothesis proposes that the right hemisphere

specializes in detecting negative emotions and the left hemisphere of the brain specializes in

detecting negative emotions. Several studies have provided evidence in favor of and against both

theories, though none have been conclusive. Most notable of these is a recent study by Najit et al.

(2013) where they compared the two hypotheses directly and failed to find evidence for either of

them.

We decided to test the two theories of facial emotion judgment using our VHF paradigm.

For this reason we chose a positive emotion (happiness) and a negative emotion (sadness) and

presented participants with a simple emotion recognition task. Participants were presented with

either happy or sad faces, bilaterally, and were asked to respond ‘yes’ if they saw a happy target

face and ‘no’ if they saw a sad target face (indicated by an arrow). Bimanual responses were

registered and RTs and accuracy were measured. We found a marginally significant main effect

of visual half-field, indicating that participants were faster for judging both happy and sad faces

in the left visual half-field. The other major finding was that participants were faster for happy

faces. While the first finding may be taken as support for the right hemisphere hypothesis; the


P. | 242

effect was only marginally significant (p = 0.07) and separate analysis for happy and sad faces

failed to corroborate the fact that the participants were consistently faster for judging emotions in

the lvf/right hemisphere. On the other hand, we were intrigued by the observation that

participants were much faster at detecting the happy faces (p< 0.01). A possibility was that the

participants were using a visual cue (the teeth) to recognize happy faces over sad faces.

To control for the possible confound, we decided to contrast the happy faces with another

negative emotion. We chose to contrast the happy faces with disgusted faces, in which the teeth

were also displayed. Participants were again presented with a simple emotion recognition

experiment. They now had to respond ‘yes’ to disgusted faces and ‘no’ to happy faces. Having

ruled out the confounding variable of ‘teeth’ as visual cue, we hoped to get clearer results.

Unfortunately, again we failed to find a main effect of visual half-field. Interestingly,

participants were faster at responding to disgusted faces as compared to happy faces in this

experiment. The other notworthy finding was a close to significant LVF/right hemisphere

advantage for disgusted faces (p= 0.08). While this may be viewed as an indication for support to

the right hemisphere hypothesis, one must admit that this finding is far from conclusive.

All in all, the experiments with facial emotion detection using our VHF paradigm did not

present conclusive results. More specifically, we did not find evidence in favor of either of the

two competing hypotheses. However, one of the findings in the last experiment stands out; that

happy faces were responded to more slowly than the disgusted faces. This finding was important

for two reasons; firstly, it shows that positive emotions are not always responded to faster than

negative emotions and secondly, this finding seems to be indicative of a larger pattern inherent to

our VHF paradigm.


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According to the recommendations made by Hunter & Brysbaert (2008), in all

experiments under our VHF paradigm, participants have to make binary decisions (e.g. ‘yes’ for

happy and ‘no’ for sad etc). Importantly, it can be observed that the participants have been faster

for ‘yes’ responses for all experiments, throughout the thesis. Also, it can be observed that VHF

asymmetries have been larger for the ‘yes’ responses. These findings align with the so-called

marked-ness effects in binary responses, wherein it has been proposed that participants are faster

for one type of response alternative over the other (Willems & Iversen, 1995). This has also been

explained using the polarity coding hypothesis by Cho & Proctor (2007). In all the experiments

of the thesis, we have observed that participants responded more rapidly with their index fingers

for ‘yes’ responses.

To test the markedness effect, we combined the performance of the participants in the

three experiments of Chapter 5 and analyzed for a 2 x 2 ANOVA (Response Type, VHF). In line

with our expectations, participants were faster for responses with the index fingers. Also,

participants were significantly faster in the LVF/right hemisphere. Given the assumed right

hemispheric nature of the three tasks, this finding is not surprising.

The findings reported in the three experiments presented in Chapter 5, are interesting in

their own right. While we have been able to replicate the LVF advantage for figure comparison

and even partially for facial emotion detection; the findings are not entirely convincing. These

results may point towards two possibilities. One, the right hemisphere functions may not be so

strongly lateralized and hence it will always be difficult to find strong visual field advantages for

tasks investigating right hemisphere functions, Or secondly, the VHF task may not be strong

enough in itself to uncover the subtle visual field effects for right hemisphere functions. Given

the findings from Chapters 2, 3 and 4; I am more inclined to put away the second possibility.


P. | 244

While one can say that Chapters 2 and 3 basically investigated the same cognitive function, i.e.

tool recognition, known to be strongly left-lateralized, the findings from Chapter 4 must be taken

into account before dismissing the merits of the VHF paradigm for investigating the right

hemisphere function. Indeed, the VHF paradigm was able to uncover subtle visual half-field

advantage for symmetry detection. Also, it should be noted that a significant LVF advantage was

observed for non-objects in the object recognition experiment in chapter 3. Also, it has been

suggested that it is generally difficult to find consistent and robust effects for right hemisphere

functions (Whitehouse, Badcock, Green & Bishop, 2009). Unfortunately though, our VHF

paradigm failed to solve the debate on facial emotion detection. However, a new finding surfaced

during the analyses in Chapter 5. We discovered that polarity or markedness turned out to be an

important factor in our VHF paradigm. Over the experiments in the thesis, participants have been

faster for ‘yes’ responses with their ‘index fingers’, and VHF asymmetries have been clearer for

these responses. More research using the VHF paradigm may be desirable further to investigate

the impacts of polarity on visual half-field effects.

The Visual Half-Field Paradigm: Conclusions

Over the course of this thesis I have conducted many experiments using the visual half field

(VHF) paradigm proposed by Hunter & Brysbaert (2008). While the paradigm performed well as

far as the left lateralized function, i.e. tool recognition was concerned, the results with right

hemisphere lateralized functions were not completely convincing. However, we have been able

to set up a standard VHF paradigm which has a good chance of being successful if the protocol is

followed. Further, as more and more different cognitive functions are tested using the VHF

paradigm; we can expect more of its strengths and weaknesses to be discovered.


P.| 245

For future research, more right hemisphere functions need to be investigated using the

VHF paradigm. As pointed out, investigators may also want to investigate various factors like

response polarity, and see how they impact VHF asymmetries. One of the important aspects of

research into right hemisphere functionshas been the non-uniformity of stimuli used throughout

the various studies across laboratories. In our view, researchers using the VHF paradigm should

engage in the endeavor to develop and standardize stimuli which can be used for various kinds of

tasks, investigating lateralization of cognitive functions (an example could be developing a

standard set of stimuli for facial emotion recognition, global-local levels of processing etc.).

In the end, I would like to present the VHF paradigm as we have used it for use by the

larger research community beyond our lab, and encourage them to use the task for investigating

the lateralization of cognitive functions.


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Nederlandse Samenvatting

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Nederlandse samenvatting

Lateralisatie van cognitieve functies: Verder onderzoek met de

visuele halfveldtaak

Het belangrijkste doel van deze verhandeling was om de validiteit van het visuele halfveld

paradigma, zoals voorgesteld door Hunter en Brysbaert (2008), uit te testen voor onderzoek naar

de lateralisatie van cognitieve functies, in het bijzonder voor de lateralisatie van functies in de

niet-dominante hersenhemisfeer. Hiertoe werden de volgende taken gebruikt:

werktuigherkenning (linkse hersenhelft), symmetriedetectie, figuurvergelijking en detectie van

emoties op gezichten (alle drie rechterhemisfeertaken). Ik ben er verder in geslaagd om een

gestandaardiseerde stimulusset te ontwikkelen die beter onderzoek mogelijk maakt over de

lateralisatie van werktuigherkenning en objectherkenning. Hier toe werden gematchte sets van

werktuigen, andere voorwerpen en niet-objecten ontwikkeld. Een andere interessant aspect aan

mijn thesis is dat ik symmetriedetectie heb kunnen onderzoeken bij een groep van proefpersonen

met atypische taaldominantie. In deze groep vond ik aanwijzingen voor een omgekeerde

lateralisatie van symmetriedetectie in de linkerhemisfeer.

Hieronder bespreek ik de verschillende hoofdstukken wat meer in detail.

Hoofdstuk 1

Hoofdstuk 1 bevat een literatuurstudie over lateralisatie-onderzoek, met bijzondere aandacht

voor de functies die in de volgende hoofdstukken aan bod komen. Er wordt ook een overzicht

gegeven van de verschillende technieken die gebruikt worden bij lateralisatie-onderzoek. Hierbij

valt, zoals in veel andere gebieden van de neuropsychologie, een toenemend belang van


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hersenscanstudies op. Toch blijft gedragsmatig onderzoek belangrijk, omdat dit veel goedkoper

en flexibeler is. Hierbij is het wel belangrijk dat het onderzoek degelijk uitgevoerd wordt. Hunter

en Brysbaert (2008) wezen op de tekortkomingen van veel studies met de visuele halfveld (VHF;

visual halffield) taak en stelden een reeks van aanbevelingen op, waaraan VHF studies moeten

beantwoorden. De huidige verhandeling gaat na in hoeverre het toepassen van deze

aanbevelingen leidt tot duidelijkere resultaten met betrekking tot linkerhemisfeer en – vooral –

rechterhemisfeertaken.

Hoofdstuk 2

Een functie waarvan recent is komen vast te staan dat die gelateraliseerd is in de taaldominante

hemisfeer betreft het herkennen van werktuigen. Deze taak hebben we dan ook als eerste

gebruikt. De proefpersonen moesten beslissen of een aangeduide tekening naar een werktuig

(hamer, schroevendraaier, vork, …) verwees of niet. In navolging van Hunter en Brysbaert

(2008) werd tegelijk links en rechts een tekening aangeboden (bilaterale presentatie) en moest de

proefperson reageren op de tekening waar een centraal aangeboden pijl naar verwees. De

responsen waren bimanueel (met de wijsvingers of de mindervingers van beide handen), om een

effect van stimulus-responscompatibiliteit te vermijden. Deze proef leverde een duidelijk

voordeel van het rechtse visuele veld op bij rechtshandigen, zoals voorspeld op basis van de

linkerhemisfeerdominantie. De proefpersonen konden sneller aangeven of een tekening

aangeboden rechts van het fixatiepunt naar een voorwerp verwees dan een tekening aangeboden

links van het fixatiepunt. Om zeker te zijn dat het effect te wijten was aan lateralisatie van

werktuigherkenning en niet aan oninteressante neveneffecten, zoals de aandachtsverdeling, werd

een tweede proef afgenomen, waarin de proefpersonen moesten aanduiden of de figuur waarnaar


P. | 252

verwezen werden een bestaand object voorstelde dan wel een verzonnen niet-object. Zoals

verwacht, leverde deze proef geen voordeel van het rechtergezichtsveld op.

Hoofdstuk 3

Een ongemak bij het onderzoek uit hoofdstuk 2 was dat we moesten werken met verschillende

sets van voorwerpen in de studie over werktuigherkenning en voorwerpherkenning. De

werktuigen en bijbehorende voorwerpen kwamen uit de database van Snodgrass en Vanderwart,

1980). Deze database bevat enkel tekeningen van bestaande voorwerpen. Om tekeningen van

niet-voorwerpen te vinden, moesten we gebruik maken van een database uitgewerkt door van

Diepen en De Graaf (1994). Deze database bevat voorwerpen en gematchte niet-voorwerpen,

maar geen werktuigen. Jammer genoeg was de tekenstijl volledig verschillend, zodat we de twee

sets niet konden combineren. Omdat we de VHF-taak voor het herkennen van werktuigen op

punt wilden hebben voor verder onderzoek, hebben we een set van gematchte tekeningen van

werktuigen, andere voorwerpen en niet-voorwerpen laten ontwerpen, geïnspireerd op het

onderzoek in Hoofdstuk 2. Bovendien hebben we stimuli gevalideerd op basis van twee

beoordelingstaken (in hoeverre is dit een tekening van een werktuig, en in hoeverre is dit een

tekening van een bestaand voorwerp?). Toen we deze stimuli gebruikten, stelden we inderdaad

vast dat de data nog mooier werden. Vooreerst steeg het rechterveldvoordeel van 17 ms naar 26

ms. Bovendien waren de tijden in de voorwerpherkenningstaak en de werktuigherkenningstaak

nu aan elkaar gelijk (in Hoofdstuk 2 ging de voorwerpherkenningstaak sneller dan de

werktuigherkenningstaak). De nieuwe stimulusset, samen met de validatiestudies, worden

gepubliceerd en zullen beschikbaar zijn voor andere onderzoekers die rond werktuigherkenning

willen werken.


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Hoofdstuk 4

In Hoofdstuk 4 onderzocht ik een taak van de niet-dominante rechterhemisfeer. Uit een overzicht

van Hugdahl (2000) was gebleken dat het onderscheid tussen taalgerelateerde vs. visuospatiale

functies nog altijd het best de taakverdeling tussen de dominante en de niet-dominante

hersenhelft weergeeft. Daarom besloot ik gebruik te maken van een minder onderzochte

visuospatiale functie, namelijk symmetriedetectie. In een eerste proef werd aan rechtshandigen

gevraagd om aan te geven of de figuur waarnaar de centrale pijl verwees, symmetrisch was of

niet (volgens het paradigma van Hunter & Brysbaert, 2008). Dit leverde inderdaad een

significant voordeel in het linkse gezichtsveld op bij 80% van de proefpersonen. Nadien werd de

proef herhaald bij linkshandigen van wie op basis van voorgaand hersenscanonderzoek (Van der

haegen, et al., 2011) geweten was dat ze ofwel linksdominant waren voor spraakproductie ofwel

rechtsdominant. Bij de linksdominanten werd het voordeel van het linkse gezichtsveld herhaald,

maar het was iets kleiner dan bij de rechtshandigen. Bij de rechtsdominante linkshandigen was er

een duidelijke trend in de richting van een voordeel voor de rechtergezichtshelft, maar was er

ook evidentie voor veel meer individuele variabiliteit bij de proefpersonen. Dit lijkt erop te

wijzen dat atypische lateralisatie voor taalproductie tot op zekere hoogte gepaard gaat met

atypische lateralisatie van symmetriedetectie (zie ook Cai et al., 2013, voor een gelijksoortige

bevindingen met een andere visuospatiale taak).

Hoofdstuk 5

In Hoofdstuk 5 onderzocht ik de bruikbaarheid van het paradigma van Hunter en Brysbaert

(2008) voor twee andere taken van de rechterhemisfeer, die gewoonlijk geen al te duidelijke

resultaten geven in VHF studies: het vergelijken van moeilijk te benoemen veelhoeken en het

herkennen van emoties in gezichten. Bij het herkennen van moeilijk te benoemen veelhoeken


P. | 254

wordt een voordeel van het linkse visuele veld verwacht, want deze taak kan niet (of moeilijk) op

basis van taal verwezenlijkt worden. Hoewel de verschillen meestal in de verwachte richting

gaan, is het verschil tussen de linkse en de rechtse helft van het gezichtsveld echter altijd klein.

Ik ging na of het groter zou worden met ons paradigma. Jammer genoeg bleek dit niet het geval

te zijn: we vonden geen verschil in reactietijden, enkel een klein verschil bij procent herkend.

Een soortgelijke bevinding werd gedaan bij het herkennen van emoties op gezichten. Ook hier

was er enige evidentie voor een voordeel van de linkse gezichtshelft (de rechterhemisfeer), maar

het verschil was opnieuw niet meer overtuigend dan de bestaande bevindingen. Als dusdanig ben

ik dus op de grenzen van het paradigma gestoten: het maakt consistente verschillen duidelijker,

maar heeft weinig effect bij zeer kleine verschillen (misschien omdat de functies niet sterk

gelateraliseerd zijn).

Een onverwachte bevinding was dat sneller geantwoord werd op gelukkige gezichten wanneer

men met de wijsvingers op deze gezichten moest reageren dan wanneer men met de

middelvingers op deze gezichten moest reageren. Een heranalyse van alle studies in deze

verhandeling bevestigde dat responsen met de wijsvingers in elke proef tot de snelste reacties

leidden en ook tot de duidelijkste VHF verschillen. We brengen deze bevinding in verband met

het markedness effect, aangetoond bij binaire responsen. Het laat ons toe om de resultaten van

het paradigma van Hunter en Brysbaert (2008) beter te begrijpen.

Hoofdstuk 6

In Hoofdstuk 6 wordt een samenvatting gegeven van de bevindingen en de conclusies die uit

deze verhandeling kunnen getrokken worden. Dit hoofdstuk was de leidraad voor de huidige

Nederlandse samenvatting.


P.| 255

Referentie











analysis. Neuropsychologia, 49, 2879–2888.



Leuven.


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lateralization of cognitive functions: the visual half-field task...

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