Where was I touched? – An investigation of tactile localization

and skin-based maps

Jack Brooks

Doctor of Philosophy

Neuroscience Research Australia

School of Medical Sciences, Faculty of Medicine

University of New South Wales

November 2017 ii Preface

The coding of the position of touch on the skin and of the size and shape of the body are both fundamental for interacting with our surrounds. The aim of this thesis was to learn more about the mechanisms of tactile localization and to characterize the principles by which skin-based representations of the body update. It is commonly accepted that skin-based representations of the body are generated from the statistics of touch and other inputs. My studies required skin stimulation customised to account for inter-individual differences in touch sensitivity and forearm shape. Within the constraints of these methodological challenges, the central questions of this thesis were addressed by performing multiple behavioural experiments. In my first study, I tested how touch intensity and history influence touch localization. The study showed that reducing touch intensity increases the variability of pointing responses to touch and results in spatial biases to the middle of the recent history of touch. Thus, I showed that when uncertain about perceived touch location, a strategy is used that minimises localization errors over time. This error minimisation mechanism stabilises our perception of events on the skin and their sensory features. Next, I investigated uncertainty in a motion stimulus by fragmenting it. Studies in vision suggest that missing sensory inputs are filled-in from the surrounds, while previous tactile studies suggest fragmented motion could influence skin-based representations. In my second study, I used a motion stimulus which instantly skipped a spatial gap on the forearm, as if the skin surface had been rearranged. As expected I observed mislocalization toward the spatial gap, consistent with changes to receptive fields of neurons corresponding to the skipped patch. The results of my third study were discordant with expectations about the perceived extent of fragmented motion. However, I identified a novel judgment-dependent perceived shortening of a tactile motion stimulus. My final study found that this judgment contingent effect was accompanied by a perceived shortening of the forearm. Future studies might further explore this linkage between skin-based and higher-order representations of the limbs. The findings from this thesis may be clinically relevant for correcting disordered representations.

iii Contents

Commitment to open science ...... ix

Originality statement ...... x

Copyright statement ...... xi

Authenticity statement ...... xi

Acknowledgements ...... xii

Publications from this thesis ...... xiii

Selected presentations from this thesis ...... xiv

Selected other publications during this candidature ...... xv

Abbreviations ...... xvii

Chapter 1: General Introduction ...... 1

1.1 Overview ...... 1

1.2 Touch localization ...... 2

1.2.1 Body representations ...... 4

1.2.2 Touch detection and localization ...... 6

1.2.3 Touch localization: Acuity is better than predicted ...... 8

1.2.4 Uncertainty about touch location ...... 9

1.2.5 Localization tasks ...... 12

1.2.6 Localization in external space ...... 12

1.2.7 Tactile extent ...... 14

1.2.8 Extent reporting methods ...... 17

iv 1.3 Contextual influences on touch localization ...... 19

1.3.1 Filling-in: Vision ...... 19

1.3.2 Filling-in: Skin-based maps ...... 22

1.3.3 Filling-in: On the body...... 24

1.3.4 Spatiotemporal context modulates localization ...... 25

1.3.5 The spatiotemporal conditions of the CRE ...... 26

1.3.6 Saltation: Models ...... 28

1.3.7 Saltation: Neural mechanisms ...... 29

1.4 Tactile perception of objects and the body ...... 31

1.4.1 Perceptual binding ...... 31

1.4.2 Binding: Occluded objects ...... 32

1.4.3 Space gives to time: The abridging effect ...... 34

1.4.4 Cortical reorganization...... 35

1.4.5 Organizing somatosensation: Analysing the statistics of touch to the skin

...... 36

1.4.6 Summary ...... 37

1.5 Aims of the present studies ...... 38

Chapter 2: Perceived Position of Touch on the Skin ...... 40

2.1 Summary ...... 40

2.2 Introduction ...... 41

2.3 Materials and methods ...... 44

2.4 Results ...... 50

2.4.1 Experiment 1: Stimulus distribution centred on forearm ...... 50

v 2.4.2 Experiment 2: Localization of Strong and Super strong stimuli ...... 51

2.4.3 Experiment 3: Stimulus distribution offset from middle of forearm ...... 52

2.5 Discussion ...... 55

Chapter 3: Artificial Tactile Scotoma ...... 59

3.1 Summary ...... 59

3.2 Introduction ...... 60

3.3 Materials and methods ...... 64

3.4 Results ...... 71

3.4.1 Preliminary Experiment 1: Effect of nearby pressure on localization ..... 71

3.4.2 Preliminary Experiment 2: Intensity adaptation ...... 72

3.4.3 Experiment 1: Artificial tactile scotoma ...... 73

3.5 Discussion ...... 78

Chapter 4: Tactile Motion Extent ...... 85

4.1 Summary ...... 85

4.2 Introduction ...... 86

4.3 Materials and general methods ...... 89

4.4 Experimental studies ...... 92

4.4.1 Experiment 1: Perceived extent of fragmented tactile motion ...... 92

4.5 Control experiments ...... 97

4.5.1 Control experiment 1a: Extent Judgment with Duration of Continuous

Brushing Matched to that of the Spatial Gap stimulus ...... 97

4.5.2 Control experiment 1b: Continuous brushing tactile extent ...... 99

4.5.3 Control experiment 1c: Low speed ...... 100

vi 4.5.4 Control experiment 1d: Non-adapting display ...... 101

4.5.5 Control experiment 2a: Imagined line matching ...... 103

4.5.6 Control experiment 2b: 25-cm block line matching ...... 103

4.5.7 Control experiment 2c: Judging length from sound ...... 104

4.5.8 Control experiment 3: Effect of repeated stimulus presentation without

repeated judgments of extent ...... 107

4.6 Discussion ...... 109

Chapter 5: Body Metrics ...... 112

5.1 Summary ...... 112

5.2 Introduction ...... 113

5.3 Materials and methods ...... 116

5.4 Experimental studies ...... 117

5.4.1 Preliminary experiment 1: Effect of tactile motion on perceived forearm

length ...... 117

5.4.2 Preliminary experiment 2: Intermingled judgments of tactile motion

extent and forearm length ...... 119

5.4.3 Experiment 1: Perceived extent of forearm length: Effect of response

dependent tactile motion path shrinkage ...... 121

5.5 Discussion ...... 123

Chapter 6: General Discussion ...... 126

6.1 Touch localization ...... 127

6.2 Tactile motion perception ...... 129

6.3 Structural representations ...... 132

vii 6.4 Limitations and methodological recommendations ...... 133

6.5 Clinical implications ...... 136

6.6 Conclusion ...... 138

Appendix A: Variable error – effect of drift ...... 139

Appendix B: Development of the wrap-around brush...... 140

References ...... 142

viii Commitment to open science

I intend to make the experimental findings and interpretations in this thesis freely available to other scientists, clinicians, educators, students, and anyone curious about the sense of touch. Instead of being locked away in this thesis, I will attempt to make these findings freely, immediately, and permanently available online to anyone by publishing them on preprint servers and in open access journals. It is my hope that this will make the experimental process more transparent and help the community understand the importance of science.

ix Originality statement

‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’

Jack Brooks

08 September 2017

x Copyright statement

‘I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the

350 word abstract of my thesis in Dissertation Abstract International (this is applicable to doctoral theses only). I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation.'

Jack Brooks

08 September 2017

Authenticity statement

‘I certify that the Library deposit digital copy is a direct equivalent of the final officially approved version of my thesis. No emendation of content has occurred and if there are any minor variations in formatting, they are the result of the conversion to digital format.’

Jack Brooks

08 September 2017

xi Acknowledgements

Thanks to all who participated in the experiments of this thesis. Although the majority of the data collected made it into the thesis, there were many hours spent in the lab tweaking and testing the set-up on people or piloting the studies herein that did not make the cut.

Thanks to my supervisors, Janet and Tatjana, for their input in experiment design, and detailed feedback on statistical analysis and writing style. For technical help, kind thanks go to Wai- Kit Tsang, Kaz Kazim, Hilary Carter, and Dave Menardo. Thanks to my office mates for their support.

Thanks to my housemates, there have been a few of you, given I’ve lived in almost a dozen places over the course of the thesis. In particular to DC and Jon, who I still play snooker with to this day.

Thanks to the running crew, in particular Ken Green, Jeremy Roff, Brad Milosevic, Jeff Hunt, and more recently Stu Paveley, Jonathon Fletcher, and John Walker.

Thanks to the following editors for taking a chance on me: Guy Nolch, Jef Akst, David Shaw, Andrew Katsis, and Lauren Davis. For helping me to hone my editing skills, thanks to John Ball, Lihan Chen, Michelle Jones, and Swetamber Das. Thanks also go to collaborators and co- authors for their constructive discussions: Uwe Proske, Lizzie Nguyen, Simon Green, Martin Heroux, Annie Butler, Jared Medina, Roman Liepelt, Gavin Buckingham, Anne Thaler, and Jorg Trojan. Thanks also to Dean Buonomano, Tobias Heed, Stuart Derbyshire, Roger Cholewiak, and Vebjorn Ekroll for sharing their knowledge and expertise.

Thanks to my family for their support, and especially my parents for getting me interested in science and supporting my education.

Finally, thanks to my partner Jen, for inspiring me every day, showing me how to take a pragmatic approach to problem solving, and being there for me throughout the thesis.

xii Publications from this thesis

Manuscripts in preparation

Brooks J, Seizova-Cajic T & Taylor JL. Touch intensity and distribution modulate perceived position on the skin. Journal of Neurophysiology. (Chapter 2)

Brooks J, Seizova-Cajic T & Taylor JL. A tactile artificial scotoma produces filling-in and stimulus- specific localization bias. Journal of Neurophysiology. (Chapter 3)

Brooks J, Seizova-Cajic T & Taylor JL. A response dependent path shrinkage of tactile motion also modulates perceived limb length. (Chapter 4/5)

xiii Selected presentations from this thesis

Brooks J, Seizova-Cajic T & Taylor JL. (2016) Tactile history influences perceived location of touch stimuli. Physiology Society Meeting, Dublin, Ireland.

Brooks J, Seizova-Cajic T & Taylor JL. (2016) Body representations of the limbs. Departmental seminar for the University of Leuven Faculty of Psychology and Educational Sciences, Leuven,

Belgium.

Brooks J, Seizova-Cajic T & Taylor JL. (2016) Making touch maps. Departmental seminar for the

University of Munster Institute of Psychology, Munster, Germany.

Brooks J, Seizova-Cajic T & Taylor JL. (2015) Motion across a tactile scotoma shifts perceived position. Meeting of the Australasian Experimental Psychology Society, Sydney, Australia.

Brooks J, Seizova-Cajic T & Taylor JL. (2015) Intensity and distribution of tactile stimuli modulate their perceived position. University of Western Sydney Sensory Symposium, Sydney, Australia.

Brooks J, Taylor JL & Seizova-Cajic T. (2014) Motion induced localization bias in touch.

University of Western Sydney Sensory Symposium, Sydney, Australia.

xiv Selected other publications during this candidature

Peer-reviewed

Brooks J & Trojan J. (2017) The Cutaneous Rabbit Effect: Phenomenology and saltation.

Scholarpedia (Accepted)

Brooks J, Nicholas J & Robertson J. (2017) Task dependence of odor discrimination: Choosing between speed and accuracy. Journal of Neurophysiology. (In Press)

Brooks J. (2017) Tactile spatiotemporal perception is dependent on preparatory alpha rhythms in the parieto-occipital lobe. Journal of Neuroscience. 37(39), 9350-9352.

Brooks J & Thaler A. (2017) The sensorimotor system minimizes prediction error for object lifting when the object's weight is uncertain. Journal of Neurophysiology 118(2), 649-51.

Brooks J & Medina J. (2017) Perceived location of touch. Scholarpedia 12(4), 42285.

Nguyen EHL, Taylor JL, Brooks J & Seizova-Cajic T (2016) Velocity of motion across the skin influences perception of tactile location. Journal of Neurophysiology 115(2), 674-84.

Brooks J, Allen TJ & Proske U (2013) The senses of force and heaviness at the human elbow joint.

Experimental Brain Research 226(4), 617-29.

Feature articles (non-refereed)

Brooks J. (2017) Senses of Self BrainWorld June.

Brooks J & Liepelt R. (2017) The Mind-Body Connection: Understanding Body Ownership and

Agency. The Scientist May, 40-46.

Brooks J. (2017) How We Sense Time. Australasian Science May, 25-27.

Brooks J. (2017) The gravity-defying mind. Lateral Magazine February.

xv Brooks J. (2017) What We Can Learn from Pickpockets. Australasian Science January, 23-25.

xvi Abbreviations

ANOVA Analysis of Variance

CE Constant Error

CI Confidence Interval

CRE Cutaneous Rabbit Effect

ISI Inter-stimulus Interval

MT Middle Temporal Area

RF Receptive Field

S1 Primary Somatosensory Cortex

SD Standard Deviation

SOA Stimulus Onset Asynchrony

SEM Standard Error of the Mean

VE Variable Error

The above abbreviations and acronyms are all redefined at first use within the thesis.

xvii Chapter 1

Chapter 1: General Introduction

1.1 Overview

This chapter summarises our knowledge about the localization of touch, contextual influences on touch perception, and how body metrics are represented. It also outlines the knowledge gaps in in this field that are addressed by this thesis, as well as the aims and hypotheses of the subsequent experimental chapters.

The thesis investigates tactile spatial perception using psychophysical methods, where a participant reports on what they “felt” in response to a stimulus. Participants in these studies reported phenomenological experience by comment or drawing, perceived touch location by pointing, and perceived distance using a visual line-matching task. There is limited literature on tactile localization and skin-based representations (maps) of the body, as stimulation of the skin is difficult to engineer. Given there is much more behavioural literature on mechanisms of visual localization, which can inform tactile spatial perception, I will refer to this literature when necessary.

The first section of this chapter introduces the complexities of localizing touch on the skin.

In it, I discuss the neural activity that reflects touch location in body co-ordinates. The second section of this chapter discusses contextual influences on touch localization, especially when the touch is bordered by a skin region devoid of sensory input. The final section explores the processes that lead to a unifying experience of the body.

1 Chapter 1

1.2 Touch localization

Swatting a fly on your arm, reaching to scratch an itch, or pointing to “where it hurts” on your body are all everyday actions that we take for granted. These movements all rely on an orderly mental representation of the size and shape of the body (Gibson, 1966; Proske & Gandevia, 2009). Of particular importance is the surface of the body, the site of our sense of touch and the boundary between us and our environment. Touch sense can code the identity, shape, temperature, and other features of an object in contact with the skin, all at a high spatial resolution (Vallbo & Johansson,

1984). Touch is a complex sense as it not only provides information about an object in contact with the skin, but also provides information about the body. Consequently, impaired sense of touch is debilitating, given that it is critical for movement and interaction with our environment (Birznieks et al., 2016; Collins et al., 2005; Robles-De-La-Torre, 2006). Whilst we can perceive the various features of touch such as texture, temperature, and pain, these sensations are not functionally useful without being coded in space. This section of the chapter focuses on the processes that map touch into co-ordinates so that we can act upon it.

Touch perception and localization start when mechanical depression of the skin activates cutaneous receptors. Receptors in the skin that are responsive to pressure—known as cutaneous mechanoreceptors—have been classed into four categories for the glabrous (non-hairy) skin (Vallbo

& Johansson, 1984) and at least seven categories for the hairy skin (Vallbo et al., 1995; Vallbo et al., 1993). This demarcation of receptor type is based on how fast the receptor adapts to a sustained stimulus and how sensitive they are to pressure (Johnson, 2001). The receptive field for a given receptor is the region of skin over which it will respond to its stimulus. Although receptive fields of cutaneous receptors are small (Johansson & Vallbo, 1979), they contain substantial overlap, so the sensation that emerges from a single touch is a consequence of the pooling of information from multiple receptors (Saal & Bensmaia, 2014). It is this convergence of sensory inputs and our top- down interpretations of them that allow us a unified experience of touch.

2 Chapter 1

Further integration of touch inputs eventually leads to a spatially organized map of the body. Initially, information from touch receptors, in conjunction with proprioceptors from the muscle and joints, is relayed via afferent neurons to the dorsal horn in the spinal cord. The receptive field on the skin of a single spinal nerve is referred to as a dermatome. As there is substantial overlap of dermatomes, additional processing is necessary before the first functional map of the body emerges. The signal then traverses the ipsilateral dorsal column of the spinal cord and at the medulla these neurons cross to the contralateral side. The pathway then continues via the midbrain; importantly, at this point, the first functional map of the body arises in the superior colliculus (Groh

& Sparks, 1996). The signal is then sent through the thalamus to the primary somatosensory cortex

(S1). Penfield and Boldrey (1937) showed in their seminal work that the body is topologically1 represented in S1 (Overduin & Servos, 2004; Wall & Dubner, 1972), much like how the retina provides a map of visual space. S1 has complete skin-based maps of the body in areas 1 and 3b

(Kaas et al., 1979).

Behaviourally relevant regions of the body typically take up more space in S1 (Sur et al.,

1980). The uneven allocation of cortical space presents a challenge for perceiving the spatial metrics of the body as the distance between two points in the S1 maps varies by location on the body. Psychophysical studies suggest that this results in distorted perception, for instance of the length and width of the hand (Longo & Haggard, 2011), but not to the degree expected from cortical differences (Sur et al., 1980; Taylor-Clarke et al., 2004). This discrepancy seems to necessitate additional processing, including remapping into visual space (Eads et al., 2015; Taylor-

Clarke et al., 2004) and accounting for the physical size of the body parts (Linkenauger et al.,

2015), to translate this distorted S1 signal into veridical co-ordinates regarding the location on the skin (Medina & Coslett, 2016). Beyond S1, tactile information, especially from areas 3b and 1, is processed in ‘what’ and ‘where’ pathways (Reed et al., 2005). The ‘what’ pathways project to the

1 Whilst the S1 map is also topographical (it provides a representation of a 3D surface), the topological

(preservation of relative locations across space) properties of the map are most relevant to this thesis.

3 Chapter 1

secondary somatosensory cortex, for processes such as object identification (Dijkerman & De Haan,

2007), while the ‘where’ pathways project to the posterior parietal cortex, a site of multisensory integration and action planning (Mountcastle et al., 1975). Therefore, a touch is represented in spatial co-ordinates in the superior colliculus, S1, and higher-order areas of the brain.

1.2.1 Body representations

Notably, Head and Holmes (1911) proposed that the our conscious bodily experience takes place within the brain2, an idea which has since been extended by others to our perceptual, conceptual, and social selves (De Vignemont, 2010; Gallagher, 2006; Longo & Haggard, 2010). Body representation is a concept which is difficult to define, and different authors assign it different meanings (Poliakoff, 2010). A widely held view is that neural activity in the somatosensory cortex and other brain regions reflects the size and shape of the body. Although it is unclear exactly how this neural activity represents the body, one possibility is that the brain draws upon the neural activity necessary for the task rather than having many representations (for more on this point see

Berlucchi & Aglioti, 2010; Carman, 1999; Fourneret & Jeannerod, 1998; Kammers et al., 2009).

This neural activity could simple reflect a stimuli's location within a task relevant reference frame— the place within which it is situated (for detailed definition see Pick, 1981)—rather than requiring a discrete representation. If there are direct representations of the body, it is unclear how many there are (De Vignemont, 2007), especially given that a stimulus can be represented in multiple reference frames simultaneously (Avillac et al., 2005; Duhamel et al., 1997). Either way, spatial information about the body is necessary for providing the body metrics for movement planning, separating self and other, and enabling the assignment of multisensory stimuli to a single physical event. In the case of touch localization, the body representation is used to represent the touch in bodily spatial co-ordinates which are relevant to the task.

2 Although most English texts credit the idea to Head and Holmes it was earlier proposed by others

(Bonnier, 1905; Pillmann, 2003)

4 Chapter 1

A phenomenon you may have experienced which suggests there are representations of body metrics is your awareness of the perceived increase in the size of the lips after anaesthesia at the dentist (Gandevia & Phegan, 1999). Other distortions of the body that are consistent with body representations are the existence of phantom limbs in amputees when there is no limb there

(Brugger et al., 2000; Ramachandran & Hirstein, 1998) or changes to the perception of the body due to damage to somatosensory areas (Schwoebel & Coslett, 2005). Another line of evidence is that damage to S1 does not result in total loss of the localization of touch sensation on the skin corresponding to the damaged region (Birznieks et al., 2016; Rapp et al., 2002). This suggests that although touch location is represented in somatosensory areas, it must to some degree be represented elsewhere otherwise damage to a represented location would lead to that location becoming a patch of numbness. As the body is constantly in a state of flux, body representations need to update rapidly and accurately for action (Dijkerman & De Haan, 2007; Proske & Gandevia,

2012). This need is exemplified by the finding that motor skills are impaired when body representations lag changes in growth (Dominici et al., 2009). Multiple other studies have presented evidence for the existence of tactile spatial representations using behavioural changes with postural modifications, tool-use and ownership illusions, as well as evidence from lesion studies (Cardinali et al., 2009; De Vignemont et al., 2005; Medina & Coslett, 2010; Pavani et al., 2000; Schaefer et al., 2008; Yamamoto & Kitazawa, 2001). Together these studies show that although neural activity represents the body in some way, it is unclear how this is achieved.

Clearly, these spatial representations of the body are important for touch localization.

Nevertheless, there is little known about the mechanisms that maintain reliable touch localization

(Kolasinski et al., 2016), especially when one is uncertain about touch location as highlighted by

Medina and Coslett (2016). Such a situation could arise if other stimuli act as distractors or if a weak touch is used. In these cases, environmental or neural noise could make the touch difficult to detect and localize.

5 Chapter 1

1.2.2 Touch detection and localization

All the studies in this thesis use touch stimuli that are consciously perceived, however certain studies suggest that localization is not dependent on conscious detection (Paillard et al., 1983) or even that conscious detection is dependent on localization (Kitazawa, 2002). In the past, these hypotheses have been assessed in case studies of patients with somatosensory cortex damage. There are numerous cases of such patients presenting with numb-touch, the apparent ability to report the location of a touch on the skin that was not consciously detected (Paillard et al., 1983; Rossetti et al., 1995; Volpe et al., 1979).

Parallel models

Paillard et al. (1983) reported the first known case of numb-touch in a patient with damage to the left occipital lobe resulting in numerous sensory deficits on the right side of her body. At the time of testing the patient was unable to feel touch applied to her right hand. Experimenters presented touch on her right hand to which the patient pointed with the other hand. Pointing responses that were within 20 mm of the target location were considered correct localizations. The patient achieved an accuracy of 26% even though she did not feel the touch. In contrast, a healthy control subject achieved over 90% accuracy with a touch stimulus that they consciously detected. Thereby, it appeared that the patient could report the location of touch with a degree of accuracy higher than expected given no awareness of the touch, but substantially cruder than normal acuity. The patient captured the essence of numb-touch with her comment, "But, I don't understand that. You put something there; I do not feel anything and yet I got there with my finger. How does that happen?"

If detection and localization are parallel processes there should also be cases of detection without localization. Paillard (1999) presented a case of tactile atopognosia, in which the patient could readily detect touch but was only crudely accurate when pointing to where they felt it on their hand. Several other cases of this dissociation have been presented (Anema et al., 2009; Halligan et al., 1995; Rapp et al., 2002). An alternative to numb-touch is that even though these patients may not be able to point to the touch on the arm, they might be able to accurately point to it on an image

6 Chapter 1

of the arm or vice-versa as observed in one case study (Anema et al., 2009). This finding suggests a dissociation of the conscious representation of the body used for perception, the body image, and the unconscious representation used for action, the body schema. Given there are many other action-perception dissociations in the literature (Goodale, 2014), this is a plausible explanation for numb-touch. If this explanation is correct, we could expect that healthy individuals would not show a dissociation of touch awareness and localization.

Serial model

In all documented cases of numb-touch the methods used to evaluate detection and localization were prone to methodological bias (Medina & Coslett, 2016). First, as Harris et al. (2004) point out, when setting the stimulus intensity for localization testing, many case studies have used the unsuitable yes-no detection task, in which the participant states whether or not they felt the touch.

As participants may adopt a conservative decision criterion for declaring ‘yes’, it is difficult to know whether they did in fact detect the stimulus on some of the occasions they report not detecting it (Campion et al. 1983). Second, Brooks and Medina (2017) point out that localization has often been measured using a pointing task in which localization is only deemed correct if the pointing response falls within an arbitrarily specified distance of the target.

The favourable solution to these two problems is to use a forced choice task for detection

(and localization) in which the participant must declare in which of two intervals (places) the touch occurred. Harris et al. (2006) used such a two-alternative forced choice task in healthy individuals and found that localization was dependent on detection. Other studies have found an analogous result, using transcranial magnetic stimulation over the parietal cortex in healthy individuals (Porro et al., 2007; Seyal et al., 1997). These observations refute the existence of parallel processing of detection and localization, numb-touch, and also the hypothesis that conscious detection is dependent on localization (Kitazawa, 2002). Hence, in healthy individuals touch localization is best explained by a serial model in which it is dependent on conscious awareness of the touch.

7 Chapter 1

1.2.3 Touch localization: Acuity is better than predicted

Initially, researchers believed that the limit to the accuracy of touch localization was set by the density of sensory innervation. On the fingertip, the most studied body part on this topic, the two- point discrimination was measured as 2 mm (Dallenbach, 1932; Weinstein, 1968). That is, two points separated by less than 2 mm were indistinguishable from a single point. This could be viewed as limited by a labelled-line model, where activation of a receptor invokes sensation at the position specified by that receptor, due to the neuroanatomical connection from the periphery to the cortex. However, in nature, touch location always arises from multiple neurons, as receptive fields have overlap and skin mechanics distribute contact forces. The signal arising from multiple neurons improves touch acuity beyond that which is expected for a single neuron (Koerber et al., 1993;

Loomis, 1979; Nicolelis et al., 1998). In a notable study, Loomis (1979) found evidence in a variation of the two-point discrimination task, using a stimulus that activated more neurons, that the limit was actually ten-fold lower at 0.2 mm, a tactile hyperacuity comparable to that observed in vision (Westheimer, 1975). Later, others used more robust methods and found similar values that matched afferent recordings (Wheat et al., 1995). Although the density of innervation in the periphery sets a hard limit to tactile spatial acuity, as a result of further processing localization in humans is better than predicted from a simple model of sampling limits.

The philosopher Hermann Lotze (1852) introduced the idea that the location of any sensory stimulus is given by its local sign. That is, its location is in some way reflected in neural activity, which Hermann von Helmholtz suggested could be learnt from experience (Von Helmholtz &

Southall, 2005), as the brain cannot simply look at our anatomy. As labelled-lines models cannot explain the local sign, one possibility is that it is defined by signals from multiple neurons. For instance the tactile hyperacuity discussed above could manifest from the relative levels of activation of different receptive fields being used to pinpoint location to a greater resolution than if receptive fields gave binary on-off outputs (Duncan & Boynton, 2007; Loomis & Collins, 1978). Touch acuity can also be improved by sampling the touch stimulus for longer—temporal integration—to allow for the accumulation of sensory evidence relating to the contact location (Steenbergen et al.,

8 Chapter 1

2014). Wheat et al. (1995) point out that this is only the case if signal-to-noise ratio is increased.

Therefore, models of touch localization should consider the convergence of signals from multiple neurons.

1.2.4 Uncertainty about touch location

For a consciously detected touch, the somatosensory system faces another problem, maintaining stable spatiotemporal perception when there is substantial environmental and neural noise. In spatial and temporal domains, touch perception is not always stable, especially for weak or transiently presented touch stimuli (Schweizer, 2000; Tong et al., 2016). A single touch stimulus is subject to systematic temporal bias as conscious awareness of touch on the body lags the stimulus, due to the time taken for the signal to travel to the brain and be processed (Kopinska & Harris, 2004). A touch to the foot takes as much as 50 ms longer than a touch to the hand to reach the brain (Macefield et al., 1989). If the brain is to accurately represent tactile events in time it must account for this neural latency. Behavioural studies show that simultaneous touch applied to the hand and the foot is perceived as occurring at the hand first (Harrar & Harris, 2005), but not by as much as predicted from neural latencies (Bergenheim et al., 1996; Halliday & Mingay, 1964). Such a bias goes away if one’s hand touches one’s foot, as the touches are perceptually bound and perceived as simultaneous

(Von Békésy, 1963). Although the temporal perception of touch is imperfect, it is more precise than the spatial domain(Goldreich, 2007).

The localization of a single touch can be altered when there is uncertainty about its location.

In early studies of touch perception, Maximilian von Frey used horse hairs to measure touch detection thresholds, as he noticed that beyond the bending force of the hair there was a plateau in the force applied to the skin (Bell-Krotoski, 1990). These filaments were further developed, enabling experimenters to accurately and reliably apply a range of forces using different stiffness filaments (Semmes et al., 1960; Weinstein, 1962). Experimenters have observed increased localization variability for weak mechanical stimuli (Hamburger, 1980; Ponzo, 1911), while others concluded intensity and localization are independent (Franz, 1916; Pritchard, 1931). Further, with uncertainty, systematic shifts in localization have been observed (Denny-Brown et al., 1952;

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Halligan et al., 1995; Schweizer, 2000), with no unifying explanation given for the origin of these biases. Critically, Steenbergen et al. (2014) tested localization, in fifteen participants, of electro- cutaneous stimuli on the forearm at seven different locations. The localization task was to point to the perceived position of the touch on a photograph of the arm overlaid on a graphics tablet (which blocked the view of their arm). They modulated the stimulus intensity by changing the number of pulses presented (1, 3, or 7). The study found that the weaker stimuli were localized with more variability and were biased toward the middle of the forearm. The authors suggest that the bias is toward a default position on the arm when there is uncertainty about the touch location. Hence, evidence suggests weak touch is localized with more variability and with a contractive bias toward the middle of the limb.

Studying individuals with damage to certain brain regions may help to further elucidate the mechanisms of these spatial biases. Stroke patients with damage to somatosensory regions often exhibit increased localization variability (Connell et al., 2008; Semmes et al., 1960). Paillard et al.

(1983) noted in the individual with damage to left occipital lobe described above (1.2.2) that the pattern of localization errors on the right hand was toward the middle of the hand. However, often this patient did not feel the touch, so we cannot be certain if this represented a smaller and distorted representation of the hand or simply a response bias (e.g. similar to Anstis, 2003). In a recent study, the localization abilities of two stroke patients with somatosensory damage were tested with touch stimuli that they always detected (Medina & Rapp, 2014). The patients tended to localize the touches as closer to the middle of the hand than their physical locations, as also observed in other patients (Birznieks et al., 2016; Rossetti et al., 1995). This contraction bias may relate to these patients having less cortical area dedicated to processing of the touch stimuli, resulting in uncertainty about the touch location.

Whilst the bias toward the middle of the limb in the previously mentioned studies could represent a bias toward a default position (when uncertain of stimulus location), this solution corresponds with other potential error minimization mechanisms. As noted by Weber (1834) the joints of the body could act as anchor points to which localization is biased toward. Consistent with

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this notion, Cholewiak and Collins (2003) found that when vibro-tactile stimuli on the forearm are located near the elbow they are mislocalized toward it (and similarly at the wrist). When the task is changed, such that participants must report when a touch moving along the arm is at the elbow, participants report it arriving there 2-3 cm before it touches the elbow (Brugger & Meier, 2015).

However, the directions of these biases are not in agreement with the finding of Steenbergen et al.

(2014). Such a bias to the middle of the forearm bears a resemblance to the categorical response bias described by Huttenlocher et al. (1991), whereby targets are shifted towards the middle of the response space when uncertain about the judgment. In the case where the touch is applied to the forearm, the elbow and the wrist might act as boundaries of the response space, such that the bias is toward the space in between them. Whilst exactly how this might unfold across the entire forearm is unclear, it appears that the joints of the body act as special landmarks in spatial perception.

Another hypothesis is that the contraction biases arise through Bayesian inference when uncertain about the perceived location of touch. Bayesian models posit that the current sensory input and the prior sensory input can be combined to optimise the accuracy of perception (Wolpert

& Ghahramani, 2005). For instance, in conditions of uncertainty about the tactile location, one could defer to prior experience to improve the likelihood that perception is correct. This optimisation is achieved by flexibly weighting the influence of the current and prior inputs depending on their signal quality. There is strong evidence for the use of Bayesian inference in this manner from animal studies (Basso & Wurtz, 1997) and, more recently, from behavioural studies

(Chalk et al., 2010; Fischer & Whitney, 2014). If a Bayesian model is adhered to, we could expect that the perceived location of a weak stimulus would be biased toward the prior history.

Alternatively, touch localization might not be served by a Bayesian model, with some arguing that Bayesian models do not adequately explain perception (Bowers & Davis, 2012). An alternative to Bayesian inference is that constant weighting is given to both current and prior inputs regardless of the uncertainty of each input. The constant weighting explanation is unlikely as it is inconsistent with the finding by Steenbergen et al. (2014) that weak stimuli lead to a greater bias than strong stimuli. Another alternative is a simple adaptive learning model, where the linkage

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between the actual response and the correct response to a stimulus updates with successive trials.

This model also does not explain the result of Steenbergen et al. (2014) as in their experiment participants did not receive feedback on accuracy. Nevertheless, it remains unknown in touch if a

Bayesian-like hypothesis is correct, and if so, how much of the history of sensory input is relevant.

The studies described in Chapter 2 of this thesis address these knowledge gaps in the role of the recent spatial history of touch in touch localization.

1.2.5 Localization tasks

Touch localization has been reported using a variety of methods. Yes-no and forced choice methods

(Flach & Haggard, 2006; Whitsel et al., 1986) can be useful for identification tasks (e.g. “Which finger was touched?”) or when the chance level needs to be controlled (as in numb-touch). Yet, these methods only capture absolute position with crude precision. Others have used temporal order judgment tasks in which two stimuli are presented and the participant must judge which was presented first (Heed & Azañón, 2014). These can have a fine resolution, but can only be interpreted as an indirect measure of touch localization. Another method is to have the participant point to where they felt the touch. Pointing is a continuous and sensitive measure (Trojan et al.,

2010) and has the added benefit of being a natural movement. Therefore, studies in this thesis that use localization have used the method of pointing. It is important to note that when pointing is used to localize touch, external (or at least limb-based) reference frames regarding the position of the touch in external space are also called upon (Badde & Heed, 2016; Taylor & McCloskey, 1988).

This thesis must therefore also consider tactile representation in external space.

1.2.6 Localization in external space

If touch is indeed localized in external space, a veridical skin-based representation (see 1.2.1) of the body must be integrated with other information such as skin stretch and limb and body movement.

Within a skin-based representation the signalled location of a touch (e.g. on the hand) is unchanged regardless of the limb position in external space. In 1709, Berkeley put forward the notion that a visual 2D representation of 3D space could be used to predict the tactile consequences of the interaction with the environment. These external representations (not necessarily visual) signal the

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touch in regards to the position of the limb and the body. Critically, in localization tasks such as the pointing task, participants need to know touch location in a reference frame that accounts for its position on the skin and the relative positions of the limbs (Fig. 1.1). The spatial co-ordinates of these reference frames can have different centres, which are usually what is most behaviourally relevant for the task (Alsmith et al., 2017; Batista et al., 1999; Colby, 1998; Harrar & Harris, 2009).

A touch that is represented in such a reference frame could be denoted as x, in relation to the centre of the reference frame y. Higher-order processes could transform touch location into these behaviourally relevant co-ordinates by integrating multiple bodily representations. Candidate regions for this integration include S1, which is subject to modulation by other sensory inputs

(Schaefer et al., 2007; Schaefer et al., 2009), the secondary somatosensory cortex (Burton, 1986;

Fitzgerald et al., 2006), and other higher-order brain regions (Van Boven et al., 2005). Whilst uncertainty remains about the integration of body representations into behaviourally relevant reference frames for perception and action (Badde & Heed, 2016), there are many models for how these reference frames are integrated (Badde & Heed, 2016; Heed & Azañón, 2014).

These models of spatial remapping into external co-ordinates typically describe serial or parallel processes. Cross-modal cueing tasks can be used to test these hypotheses. In such tasks, an irrelevant stimulus (e.g. visual) that is represented in a different spatial reference frame from the target stimulus directs attention to a location. Azañón and Soto-Faraco (2008) used a crossed-arm paradigm in conjunction with a tactile stimulus which was cued by a visual stimulus. Crossed arms were used so that skin-based and external reference frames signal conflicting locations. For short intervals between the stimuli of around 100 ms, the cueing effect was maximal when the touch was on the opposite hand to the visual cue. At longer intervals between the stimuli, the cueing effect was maximal when the cue and stimulus were at the same location. A credible explanation is that touch is represented in a skin-based (somatotopic) reference frame first, and in an external reference frame second. This serial remapping hypothesis is consistent with many other findings (Shore et al.,

2005; Yamamoto & Kitazawa, 2001), but could also be explained by other serial models (Heed &

Azañón, 2014). Unlike these serial models, Brandes and Heed (2015) propose that the reference

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frames are concurrently available (parallel processing) but that the weighting of their integration varies with time. How this would work conceptually, however, is unclear. Regardless of the contention about the mechanisms by which reference frames are integrated, it is clear that they are integrated so that touch is represented in a behaviourally relevant reference frame.

Figure 1.1. A flowchart depicting the process of localizing touch in external space. A touch stimulus in the periphery activates touch receptors, which transmit the signal via the spinal nerves to the somatosensory cortex, where conscious awareness of the touch and its location in skin-based co-ordinates arises. Integration of this signal with other sensory inputs using higher-order processes brings the touch location into external spatial co-ordinates.

1.2.7 Tactile extent

The perceived distance a touch stimulus spans or the distance between two touch stimuli, known as tactile extent, has been the subject of many studies (for a review see, Green, 1982). Just like tactile localization, extent perception varies by body site. Weber (1834) found that the necessary

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separation for two stimuli to be individuated, known as the two-point discrimination threshold, varies across the body (see also Mancini et al., 2014). This observation could arise because regions of the body that are more densely innervated with cutaneous receptors have smaller receptive fields and take up more cortical space (Cody et al., 2008; Sur et al., 1980). On the forearm, the two-point discrimination threshold is typically 2-4 cm (Friedline, 1918; Gibson & Craig, 2005; Mancini et al.,

2014). The studies in this thesis require judgments of substantially longer extents (10-30 cm), which cannot be explored using the two-point discrimination task due to ceiling effects. In addition, the processing and perception of longer extents might rely upon other mechanisms including higher- order representations.

In the tactile domain, Longo and Haggard (2011) proposed the counting model of perceived tactile extent. The counting model states that extent perception arises by counting the number of cortical receptive fields that fall within an extent defined by two touches. The key evidence for this model is that perceived extent varies by the allocation of cortical space. A well-known example of this is that an extent on the hand is perceived as longer than an extent on the forearm (Weber,

1834). This spatial bias arises as the hand is more densely innervated than the forearm and therefore a given extent crosses the receptive fields of a greater number of neurons (Cholewiak, 1999) because the separation between receptive fields is roughly a constant of receptive field size (Sur et al., 1980). In the same vein, studies have found that extents applied across the hand (Longo &

Haggard, 2011) or forearm (Green, 1982; Wong et al., 1974) are judged as longer than those applied parallel to the long axis of the limb. This result is again attributable to receptive field variations, because they span greater distances along the forearm than across it (Cody et al., 2008; Powell &

Mountcastle, 1959). Interestingly, it seems that the magnitude of the above biases is much less than predicted from the regional differences in receptive field size and density (Taylor-Clarke et al.,

2004), or from a simple model of cortical distance (i.e. the correspondence between cortical distance and physical distance). It is thought that higher-order body representations correct the distorted S1 map (Medina & Coslett, 2010), much like corrective processes for cortical

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magnification in vision. Therefore, it seems that perception of tactile extent stems from some variation of a counting model which partially accounts for receptive field size and density.

Recently, Longo (2017) proposed that the processes which correct for distortions from the counting model take place in the posterior parietal cortex. This hypothesis seems consistent with evidence showing that changes in perceived tactile extent arise from the integration of touch with other sensory inputs. More specifically, modulations of tactile extent have been described for tactile-visual (Longo & Sadibolova, 2013; Taylor-Clarke et al., 2004), tactile-auditory (Tajadura-

Jiménez et al., 2017; Tajadura-Jimenez et al., 2012), and tactile-proprioceptive (De Vignemont et al., 2005) interactions. In line with the above proposal of Longo, these illusory body distortions are met with neural activity in the parietal cortex (e.g. Ehrsson et al., 2005).

Measures of tactile extent are also relevant to higher-order representations that segment the body into its many parts. The observation that perceived tactile extent is larger when it the extent stimuli crosses a joint suggests that the joints have special significance in segmenting the body (De

Vignemont et al., 2005). At the S1 level, the receptive fields are somewhat partitioned by limb or body part (e.g. finger, Sur et al., 1980) and likely organised by sensory experience (Braun et al.,

2000b). However, within S1, correct segmentation of the body is not always maintained, as shown by referred sensations to other limbs resulting from cortical reorganisation after amputation

(Ramachandran & Hirstein, 1998). Beyond S1, it is likely that a structural representation emerges that faithfully segments the body into its parts (Gallagher, 2006). The existence of such a representation could explain the apparent paradox observed in conditions such as finger agnosia (or somatoparaphrenia) in which primary sensation remains even though the limb is not recognised

(Kinsbourne & Warrington, 1962).

Confirming spatial distortions of the body that have been measured with localization methods by using perceived extent is an important step for the field. For instance, one tactile- proprioceptive illusion in which the forearm is perceived to shorten, as measured by pointing to the index finger (Longo et al., 2009), has been found by others to result from a perceived position shift

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of the whole forearm (Bellan et al., 2016). Importantly, and in contrast to localization judgments, extent judgments are unchanged by perceived position shifts of the limb or body. Although extent judgments have this advantage, they might also have the disadvantage of the spreading of attention which increases uncertainty or of missing local changes in perception. Even so, explicit measures of extent are required to verify observations using implicit measures of extent such as localization, which may introduce potential methodological biases.

1.2.8 Extent reporting methods

Studies investigating the mechanisms of perceived tactile extent have used different reporting methods (Cholewiak, 1999; Green, 1982). As mentioned previously, the two-point discrimination task has limited range due to a ceiling effect at longer extents. At longer extents, one method is to use implicit extent measures, such as the line bisection task (Longo & Lourenco, 2007) or localization of tactile stimuli or landmarks (Cardinali et al., 2009; Longo et al., 2009). Others have used the segmented space method in which one indicates on a segmented drawing of the limb where they perceived the touch (Whitsel et al., 1986). Whilst these methods are simple to implement, they are all subject to bias from making successive localization judgments (Medina & Duckett, 2017).

A simple method for longer extents, which has been used to measure perceived limb length, is to use templates (Gandevia & Phegan, 1999; Longo & Haggard, 2010) or images (Longo &

Haggard, 2012). While this is a quick method, it has cognitive contributions, for example, the bias of participants selecting the image that looks normal can result in differences from line matching tasks. Recent studies have also used comparison procedures in which two extents are applied to separate body parts and the participant must judge which one is longer (De Vignemont et al., 2005;

Taylor-Clarke et al., 2004). As the experiments of this thesis use longer extents (25-30 cm), there are no body sites with adequate acuity or which can accommodate a stimulus without crossing joints, so the comparison procedure was not used. A line-matching task was instead used for perceived extent.

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Overall, this section has shown that touch localization is dependent on both bottom-up and top-down processes; from wiring in the periphery to inferences based on prior experience of the self. Assigning a touch a location in spatial co-ordinates is a complex process, which begins by distinguishing the signal arising from touch to the skin from environmental noise. Ultimately, our touch localization ability is guided by conscious processes which represent touch location in the spatial co-ordinates of the body. Importantly, I have identified a knowledge gap in mechanisms of localization when uncertain. It was also noted that as localization by pointing is used in this thesis, external representations of touch must be considered. Beyond the spatial biases tested using localization, judgments of extent are necessary to confirm results and extend knowledge about body representations. The next section of this thesis considers how spatial touch perception is challenged in the natural environment by the spatiotemporal context.

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1.3 Contextual influences on touch localization

The previous section described the localization of simple touch stimulus configurations, but in the natural setting the somatosensory system is often faced with the challenge of making sense of touch from incomplete information. This section discusses these situations, whereby other sensory inputs—the context—can guide localization. There are multiple mechanisms by which the brain uses the context to make inferences about missing sensory input to the skin. Particularly important are the spatial and temporal order of events, which are typically tightly coupled to one another, often as a result of movement. Although spatiotemporal sequences of tactile input can arise from movement of a limb across another surface, or movement of an object across the limb, this thesis focuses on the latter.

In perception, there is often a need to estimate the properties of a partly occluded object or of a sensory region which is devoid of input. Such sensory estimation is referred to as filling-in or completion, and has been extensively researched in visual perception, which I discuss briefly here before reviewing tactile filling-in. One of the earliest examples of visual filling-in comes from the

1600s, where King Charles is recorded as having used his blind spot to perceptually decapitate people before execution. While a variety of definitions for filling-in have been provided, this thesis will use the definition given by Komatsu (2006, p. 220) “a perceptual phenomenon in which a visual attribute such as colour, brightness, texture or motion is perceived in a region of the visual field even though such an attribute exists only in the surround”. The surround for the physiological blind spot, where the optic nerve leaves the eye, is the region surrounding the void as well as the matching visual region from the other eye (Fiorani et al., 1992). Filling-in processes use and interpret information from the surrounds of a missing sensory input to best estimate the stimuli within the missing area.

1.3.1 Filling-in: Vision

In vision, filling-in not only occurs for the physiological blind spot, but also for other areas where input may be missing either through injury or experimental manipulation. The time-course of

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filling-in is highly dependent on the level at which the sensory input is missing and how long it has been missing. For the physiological blind spot, which is present from birth, two bars positioned on either side are filled-in almost instantly such that a long single bar is reported (Ramachandran,

1992a). This observation shows that the visual system has learnt to rapidly account for this lack of sensory input. A region devoid of sensory input, a scotoma, typically takes a few seconds to fill-in regardless of whether it is pre-existing or created using a visual illusion (De Weerd et al., 1995;

Paradiso & Nakayama, 1991; Ramachandran & Gregory, 1991). Such an artificial scotoma3 can be created by blocking a small region of the visual field and stimulating the surround with uniform static stimuli (Martinez-Conde et al., 2004; Troxler, 1804). Ramachandran and Gregory (1991) found that using dynamic surround stimulation strengthens the perception of filling-in of an artificial scotoma. The filling-in of different features or qualia occurs over different time-courses.

For instance some have demonstrated that colour fills in before texture (Ramachandran, 1992b).

Thus, when it comes to visual scotomas the strength and time-course of filling-in is dependent on the age of the scotoma and the stimuli in its surround.

Interestingly, Kapadia et al. (1994) showed that the perceived position of a visual stimulus placed on the edge of an artificial visual scotoma (peri-scotomatous) is shifted toward the middle of the scotoma (Kapadia et al., 1994). The mechanism for the shift in perceived location could come about via multiple mechanisms, but is likely explained by local mechanisms as targets further away from the scotoma (exo-scotomatous) were unaffected. Within minutes, the receptive fields of neurons corresponding to an artificial scotoma experience a five-fold increase in size (Pettet &

Gilbert, 1992) as depicted in Figure 1.2. Others have found evidence that receptive field size is unchanged, but instead the neurons increase their sensitivity within the region to which they are already responsive (DeAngelis et al., 1995; Ohzawa et al., 1985). In theory, this adaptive mechanism operates so that we remain sensitive to changes in contrast. In line with these

3 Anecdotally, an analogous scotoma can be experienced on the body by covering a patch of skin of the arm and placing it under a running shower or hair dryer.

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observations of receptive field changes, Kapadia et al. (1994) propose that the shift in localization could be a result of neurons with receptive fields constrained to the scotoma area now responding to stimuli that are situated adjacent to the scotoma. This shift could also be compounded by neurons with receptive fields outside of the scotoma adapting to the conditioning stimulus such that they are now smaller and/or less responsive (Schwartz et al., 2007b). However, I do not know of a study that measured receptive field changes inside and outside of an artificial scotoma and localization within the same experiment.

In the somatosensory system, adaptation also results in decreased receptive field size

(Tommerdahl et al., 2002) and circumstances that could be considered analogous to a scotoma, such as limb amputation or anaesthesia, also produce increases in receptive field size (Weiss et al., 2004;

Weiss et al., 2000). On the hand, Weiss et al. (2004) demonstrated that anaesthesia of one finger caused increased localization errors to that finger when an adjacent finger is touched. These mislocalizations were caused by cortical receptive field expansion corresponding to the anaesthetized finger, verified by magnetoencephalography. A surprising aspect of anaesthesia is that while the perceived size of the anaesthetized thumb increases by ~70% (Gandevia & Phegan,

1999), the perceived size of an object held between the anaesthetized thumb and fingers only increases by 30% (Berryman et al., 2006). Consequently, findings with anaesthesia on the finger might differ when only the skin-space is considered, as in the artificial tactile scotoma generated in

Chapter 3 of this thesis.

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Figure 1.2. Schematic showing a potential mechanism for the compressive position shifts of an artificial scotoma induced by surround motion. A. A stimulus (solid line) results in activation of two neurons which faithfully signal the touch location (dotted line). B. If an artificial scotoma is created by providing stimulation in the surround of the occluder, the receptive fields for the neurons underneath the occluder expand. Note that Kapadia et al. (1994) predicted that the receptive fields shape would be conserved, here I have depicted it only enlarging in the direction of the scotoma stimulation. The touch now activates three neurons, and is signalled to lie within the scotoma.

1.3.2 Filling-in: Skin-based maps

The flat surface of the skin and its receptors share a likeness to that of the retina, but there is less available evidence of how filling-in processes unfold on the body. Two stimuli, presented simultaneously and brought close enough together on a continuous skin patch are perceived as one, at a location in between the two stimulus positions. Von Békésy (1959) found that if dynamic vibro- tactile stimulation is used the illusory position displacement is observed for larger spatial separations. The perceived location could be shifted by adjusting the relative intensity of each vibrator. This tactile funnelling illusion was subsequently observed by others (Chen et al., 2003) for up to three stimulus locations (Gardner & Spencer, 1972). Neural activity corresponding to the illusory location is found in somatosensory cortex in monkeys (Chen et al., 2003; Chen et al.,

2007). Despite being similar to visual filling-in, the tactile funnelling illusion critically differs as there is a perceived position shift of the stimuli.

In contrast, thermal inputs to the skin do satisfy Komatsu’s definition of filling-in. If the index, middle, and ring fingers are touching objects, the temperature of the objects the index and ring fingers are touching modulate the perceived temperature of the middle object (Green, 1977).

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Interestingly, this thermal referral is only observed if the middle finger is contacting an object. It appears that such temperature filling-in is contingent on mechanical input to the gap. The illusion was also found to work for touch on the forearm, suggesting it can arise within the skin space. In another experiment the spatial and somatotopic distance between the stimulus locations was varied.

The study showed that thermal referral was strongest when the locations were nearby in somatotopic space, confirming that it unfolds in somatotopic rather than external co-ordinates (Ho et al., 2010). Therefore, suggesting it is not simply a case of grouping the sensations as originating from a single external object which has a uniform temperature.

Classic filling-in hypotheses predict that the temperature referral is a result of filling-in processes using the surrounds as a blueprint for the unknown. However, the findings of Ho et al.

(2011) provide strong evidence that this is not the case, based on their experiment using intensity judgments. In the uniform control condition each finger received the same temperature. In the critical thermal referral condition, they found that the apparent thermal intensity in the middle finger increased from control whereas that in the outer fingers decreased. They propose that the referral of this thermal sensation to the middle finger seems to occur from summation and averaging of the total thermal input (Ho et al., 2011). Ho et al. (2011) propose that these results are highly consistent with the “feature mixing” variant of filling-in, also observed in vision (Geldard, 1976;

Hsieh & Tse, 2009), which is subtly different from the active-spreading and feature-tagging hypotheses of filling-in (De Weerd et al., 1995; Pessoa & De Weerd, 2003). Feature-tagging models of filling-in, suggest that the filling-in is simply a copy of the surrounds. Feature-tagging would have resulted in no change in the perceived temperature of the surrounds. The active-spreading hypothesis suggests that sensory input from the surround slowly spreads into the void, but does not make any prediction that the surround sensation altered. The feature-mixing model of thermal referral was supported by a comparable finding using purely thermal stimuli (Cataldo et al., 2016).

Therefore, it seems that thermal referral results from averaging the temperature in the surrounds and distributing it across the stimulated space. These studies have shown that the features of a touch

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stimulus can be referred to other locations on the skin, the extent of which depends on the specific configuration used.

1.3.3 Filling-in: On the body

On the body, filling-in is also observed between limbs or body parts. MacKay (1967) illustrates that a bottle grasped in the hand feels like a continuous surface and “not … holes in the bottle where the spaces are between my fingers”. Such filling-in is also dependent on how we typically map the relative positions of body parts, which could be to a default posture (Bromage & Melzack, 1974;

Romano et al., 2017). A classic example of filling-in on the body is the Aristotle illusion, in which a pen held between two crossed fingers (such that the pen touches the sides of the fingers that do not usually touch each other) is typically perceived as two objects (Benedetti, 1985). When the illusion is reversed by touching the far sides of the each finger (i.e. the sides that touch each other if the fingers were not crossed) only a single object is perceived (Bufalari et al., 2014). Therefore, although we can use tactile-proprioceptive integration to infer object shape, it is susceptible to bias arising from experience within a constrained range of limb positions.

In our natural environment, touch often involves motion. For two objects moving along adjacent fingers, their relative movement directions determine if they are perceived as one or two objects. Synchronous movements are perceived as one object, whereas asynchronous are perceived as two objects (Kitada et al., 2003; see also Ohka et al., 2010). This perception is likely achieved by perceptually binding the objects as one and filling-in the space between them. Experiments using fMRI reveal that this filling-in observed for the synchronous movements is associated with increased activity in parietal areas (Kitada et al., 2003) as well as temporal, frontal, and cerebellar areas (Peelen et al., 2010). In a surprising result, if the stimuli in the Aristotle illusion are replaced with motion stimuli (moving along the long axis of the finger) the illusion is abolished (Craig,

2003), perhaps through a similar binding process. These filling-in processes for dynamic stimulation, are consistent with Gestalt grouping principles, which strive to provide the simplest and most likely solution to the sensory input (Todorovic, 2007). Thus, on the body, filling-in is observed for static, thermal, and motion stimuli.

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1.3.4 Spatiotemporal context modulates localization

Although filling-in has typically been described as a process where information from the surrounds can be used to fill a void in sensory input, it could equally be thought of as a position bias, wherein touch on the outside of the void is localized inside the void. Thus, the spatiotemporal context, other touches at different locations or times, within which a touch is presented can influence how its position is coded. The Cutaneous Rabbit Effect described in this section demonstrates such spatiotemporal contextual effects, which lead to position shifts into the untouched space, and therefore are directly relevant to touch localization. Interestingly, early studies of tactile spatiotemporal perception borrowed methods used in acoustics, in which it was noted that two stimuli occurring close together in time interfered with one another (Sherrick, 1960; Verrillo, 1965).

Frank Geldard and Carl Sherrick first described the Cutaneous Rabbit Effect (CRE) in their seminal study in 1972 (Geldard & Sherrick, 1972). In this version of the illusion five rapid taps were applied to the wrist, then the middle of the forearm, and then the elbow. Remarkably, the taps were perceived uniformly along the arm at locations in between the stimulus locations. The CRE is often studied using simpler stimulus configurations such as the utterly reduced rabbit, in which two spatially separated taps are given with a short temporal interval (Geldard, 1975). The main phenomenological property of all versions of the CRE is discrete tapping sensations in between the stimulated locations. Thereby, in the CRE the localization of one stimulus is influenced by its spatiotemporal context, which can be stimuli that occur before or after it at other locations.

Geldard and colleagues noticed that the perceptual patterns arising from the stimuli were dependent on their spatiotemporal properties. For instance, the hops were perceived as further apart if fewer taps were given, and closer together if more taps were given. The compressive position shift of the stimuli in the CRE is often referred to as saltation (Geldard, 1975), inspired by the latin saltare – to jump. For two taps with equal stimulus length and intensity, the stimulus given first is perceived as shifted toward the second stimulus. Geldard called these taps the “attractee” and the

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“attractant” (Geldard, 1975). The position of the attractant can also shift under certain circumstances, but to a lesser degree than the attractee (Trojan et al., 2010). Although, the

Cutaneous Rabbit effect is briefly reviewed here, a great resource is available at http://tactileresearch.org/pucclabs/pagePCRPIndex.html detailing many of the initial studies of the

Geldard lab.

1.3.5 The spatiotemporal conditions of the CRE

The cutaneous rabbit illusion only occurs for a specific set of stimulus conditions. First, there must be localization variability, which can be modulated by varying the stimulus intensity and its presentation time. Weaker stimuli intensities result in larger compressive shifts (Tong et al., 2016).

Second, the effect only occurs for certain spatial and temporal intervals, which are interdependent.

Rabbit-like hops at locations that do not coincide with the stimulated locations seem to occur for inter-stimulus distances of up to 30 cm (Geldard, 1982). The spatial limits over which the CRE is observed may depend on the acuity of the region, as proposed by Geldard (1982), however to my knowledge no-one has tested this hypothesis. If the spatial distance is sufficiently reduced the two stimuli will be perceived in the same location, but only if the temporal gap is also short (Boldt et al.,

2014). It is not just the spatial interval on the skin surface but rather the stimuli separation in external space that dictates if the CRE is perceived. For example, the CRE is observed for a stimulus applied to each arm when the arms are close together, but it is not observed if the arms are held far apart (Eimer et al., 2005). Therefore, the spatial constraints of saltation (compressive position shift) are apparently set in an external reference frame.

The temporal limits of saltation are also well defined. Most studies report the temporal intervals as the stimulus onset asynchrony (SOA) and inter-stimulus interval (ISI). The SOA refers to the time between the onset of the first stimulus and the onset of the second stimulus, whereas the

ISI is the time between the end of the first stimulus and the onset of the second stimulus. As the stimulus duration in these studies, when reported, is typically ~10 ms (Flach & Haggard, 2006;

Tong et al., 2016), in practice the SOA and ISI are interchangeable. Therefore, these will be referred to under the term temporal interval. Starting at long temporal intervals (~1 s), the perceived

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spacing between touch stimuli seems close to veridical. As these time intervals are reduced the stimuli at the first stimulus location begin to drift toward the second stimulus location (and vice- versa), however the point at which this occurs is subject to high inter-individual variability. As the temporal interval is further reduced, the amount of compressive position shift increases (Flach &

Haggard, 2006; Trojan et al., 2010). Geldard proposed that a point is reached where the stimuli are perceived as co-incident in location. This point, might also reflect the limits of direction detection or temporal order judgment (van Wassenhove, 2009), depending on the reporting method used.

Importantly, the majority of studies are in agreement that greater compressive bias is observed as the temporal interval is decreased.

Although the extent of the compressive position shift in the CRE is determined by the spatiotemporal configuration, the position shift of the whole element pattern is subject to attentional modulation. The evidence for this comes from the study of Kilgard and Merzenich (1995) in which a tactile stimulus given well before the CRE was used to cue attention at either the attractee or attractant location. They found that the position shift was toward the cued location, and that this cueing did not influence the overall compression bias. Similar findings regarding attention were made by Flach and Haggard (2006). A problem with these findings is pointed out by Trojan et al.

(2010), who observed at intervals of up to at least 1 s, that the cueing might be captured by the CRE rather than merely effecting attention. Even so, robust cueing effects on spatial touch perception have been observed in other situations (Cohen et al., 2005; Röder et al., 2002) suggesting some degree of attention dependent mislocalization.

The perceptual experience arising from the spatiotemporal configuration used in the CRE can vary depending on instruction and the previous experience of the participant. At some temporal intervals, particularly around 200 ms, when the participant attends to particular perceptual properties, the touch stimuli are indistinguishable from continuous motion on the skin, so called apparent motion (Sherrick, 1968). It is interesting to note that apparent motion critically differs from the CRE, in that it requires filling-in of sensation that does not exist, in contrast to the CRE which only involves a position shift. This attention-based shift in perceptual set has been observed

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in similar spatiotemporal configurations in other tactile (Carter et al., 2008) or visual-tactile situations (Asai & Kanayama, 2012).

1.3.6 Saltation: Models

Numerous attempts have been made to explain the position shifts observed in the CRE. In order to explain the models, two similar spatiotemporal effects must first be introduced, the Tau and Kappa effects. The Tau effect is demonstrated using at least three stimuli (A,B,C), with the perceived distances (A-B, B-C) between three constantly spaced stimuli depending on the relative temporal interval between each pair (Helson, 1930), such that a longer spatial distance is perceived for the taps that have a greater temporal interval and vice versa. The Kappa effect is the time analogue of the Tau effect, subjective time between stimuli is biased by relative inter-stimulus distance (Cohen et al., 1953). These effects differ from the CRE as they rely on relative spacings and cannot be reduced to a two-tap situation. Hence, any hypotheses that suggest this spatial distortion is simply dependent on the relative spacing of the stimuli, in time and in space, cannot explain the CRE.

Collyer (1976) proposed that the compressive effect of saltation is caused by the bias to perceived velocity4 constancy (i.e. smooth motion). Whereby in a multi-tap sequence taps separated by longer time intervals are perceived as further apart and taps separated by shorter time intervals are perceived closer together, as if the stimulus was moving at one steady velocity. This hypothesis cannot explain the shortening observed for two-tap sequences. Flach and Haggard (2006) proposed that the location of the second stimulus in a two-tap sequence is weighted more heavily than the first, a consequence of tactile memory decay (Harris et al., 2002). However, this fails to explain effects observed in multi-tap sequences.

Wiemer et al. (2000) proposed that the compressive effects of the CRE could arise from a probabilistic assumption that skin locations that are stimulated frequently close together in time must be located close together in space. The downfall of this model is that it predicts spatial dilation

4 Velocity and speed are used interchangeably within the thesis.

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at longer temporal intervals (i.e. that locations stimulated further apart in time are located further away). This dilation is only observed at small spatial intervals (Boldt et al., 2014), but not at large ones (Trojan et al., 2010). On the contrary, if continuous motion is used, such as by Langford et al.

(1973) or Whitsel et al. (1986) expansion is observed at slower speeds (which are equivalent to longer temporal intervals). So, whilst the Wiemer model may not explain the rather contrived situation of the CRE, it performs well for ecological stimuli. One reason for this difference could be that continuous motion and the CRE have different profiles of local and global motion.

Most CRE configurations can be explained if the probabilistic model of Wiemer is combined with one that accounts for mechanisms that reduce localization errors when the location of a stimulus is uncertain. Goldreich (2007) propose a Bayesian model in which we have an expectation for slow moving stimuli on the skin, which is deferred to when we are uncertain about touch location, as in the conditions of the CRE. Thus, when a two-tap CRE is given with short temporal interval, the stimuli are judged to be near each other because a slow-moving stimulus could not move far in the short interval. Likewise, at longer temporal intervals, stimuli moving at a low speed will have moved further and will be judged further apart. To illustrate, the predictions of the Bayesian model (Goldreich & Tong, 2013) can be simulated for numerous spatiotemporal configurations online (http://psych.mcmaster.ca/goldreichlab/LL/Leaping_Lagomorphs.html).The model seems to explain the compressive shifts of the CRE regardless of whether they are measured by point localization or tactile extent judgment (Tong et al., 2016). Although the Bayesian model is generally accepted to account for most of the localization features of spatiotemporal configurations using discrete stimuli, some of its assumptions await experimental verification.

1.3.7 Saltation: Neural mechanisms

The neural mechanisms that lead to the compressive effects observed in the Cutaneous Rabbit

Effect are contentious. The CRE is not simply a result of mechanical transduction as its compressive shifts are observed for electro-cutaneous stimuli (Geldard, 1975), as well as heat and pain stimuli (Trojan et al., 2006). Geldard initially proposed that the illusory location is represented in primary somatosensory cortex, based on his observation that the CRE did not cross the body

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midline and is therefore restricted to one hemisphere (Geldard, 1982). However, others later found the CRE does cross the midline (Trojan et al., 2010) and can move between limbs (Eimer et al.,

2005; Miyazaki et al., 2010). Unfortunately, the only study that has investigated the neural activity corresponding to the illusory location, was inconclusive, and methodologically unsound

(Blankenburg et al., 2006). The study found activity in primary somatosensory cortex in the illusory condition which was similar to that of real stimulation of that location. However, the study only used a coarse yes-no detection method to compare the phenomenology of the illusory and control conditions, which were designed to produce identical perceived touch location. Based on other work, the perception in these two conditions may have been rather different, because the experience of touch at the illusory location in the CRE is substantially less than when there is actually a touch at that location (Cholewiak & Collins, 2000). Studies producing illusory location similar to in the

CRE have found the location is represented in SI (Bufalari et al., 2014; Chen et al., 2003) and parietal cortex (Peelen et al., 2010), amongst other areas (Takahashi & Kitazawa, 2017). Currently, it remains unclear where and how the illusory location in the CRE is represented within the brain.

Collectively, the studies described in this section show that touch localization is modulated by context as demonstrated in the Cutaneous Rabbit Effect and its related spatiotemporal illusions.

The resulting position shifts are subject to the spatial and temporal properties of touch stimuli, the relation of these properties, and top-down influences such as attention. Although these mechanisms are mostly well characterised, they have only been demonstrated for relatively simplistic stimulus patterns.

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1.4 Tactile perception of objects and the body

One component of the Cutaneous Rabbit Effect which was not discussed in the previous section is the aspect of it that relates to object identity. Also not discussed was how touch informs one not just about objects in contact with the skin, but also about the body itself. This section discusses how spatiotemporal perception is influenced by the processes which assign object identity, the velocity of motion, and expectations from past experience. The final parts of the section briefly summarise how persistent tactile stimulation can influence perception of the body.

1.4.1 Perceptual binding

By its original definition, the CRE gives rise to the perception of a single object hopping along the arm. However, as pointed out by Shore et al. (1998) the source of the CRE could also be perceived as arising from separate objects. It is unknown whether this feature of the CRE and other related spatiotemporal illusions is critical to the spatial biases observed. For instance, Bayesian models assume that it is perceived as the same object. Visual studies of the same effect suggest it still occurs when the object changes colour (Geldard, 1976), but do not report if object identity persists.

As mentioned above, at some temporal intervals of the CRE the stimuli are perceived as apparent motion. As apparent motion is indistinguishable from continuous motion this would necessitate that one object is the source of the stimulus. Therefore, at least in some situations object identity is maintained over fragmented motion.

In vision, the ability to recognize motion when the sensory input is fragmented has likely developed by an evolutionary pressure to perceive a moving object, as it is more likely to present a threat. For example, if a venomous spider was crawling up one's arm, one would want to resolve it as a spider, and not a few harmless ants. The brain has a simple way of distinguishing moving objects. In the above example, a series of dots are moving in the same direction. The brain could treat them individually; however, this would be computationally costly. Instead, the brain uses

Gestalt principles of grouping and perceives the dots as part of a single moving object, a simpler

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and more efficient solution. Therefore, spatiotemporal perception is dependent on how stimuli are grouped (Todorovic, 2007; Wertheimer, 1923).

A variation of the Cutaneous Rabbit Effect, known as the Ternus effect provides evidence that the attribution of object identity is highly malleable (Harrar & Harris, 2007). In this effect, there are three stimulation positions. The tactile stimuli are displayed at the first two positions (1, 2) then after a short temporal interval at the second two positions (2,3). Depending on the temporal interval and the locus of attention, the percept is either group motion (both locations shifted across one position) or only motion of the outer stimulus (1 to 3). It is hypothesised that the perceived identity of the middle stimulus determines which of these percepts arises; group motion if it is perceived to shift one place or outer stimulus motion if it is perceived as stationary (Braddick,

1974). This attentional dependence of object identity is observed in similar spatiotemporal configurations (Carter et al., 2008). Further, these findings demonstrate that the malleability of object identity can influence perceived location of an object.

1.4.2 Binding: Occluded objects

In our everyday experience motion can be fragmented if the object of interest is occluded by another object at any point in its motion path. Visual experimenters noticed perceived object identity remained intact when a moving object disappeared from view behind another object

(occlusion) and reappeared at the other side of the occluding object before it was expected

(discussed in depth in Michotte, 1946; Wertheimer, 1923). These researchers defined the spatial and temporal ranges over which object identity and/or motion continuity were maintained. Various other studies tested how the occlusion influences what is perceived (for review see Nijhawan,

2002). Critically, studies have found than when a gap is introduced into the motion of a visual stimulus it is only noticed if it occurs within the first 200 ms of motion but not if it occurs later

(Hidaka et al., 2009; Kanai et al., 2007). It is likely that by 200 ms the global motion context has been set, such that when uncertain about the motion, it is interpolated across the gap. This prediction was borne out in a study in which the temporal order of two stimuli in a motion path defined by discrete stimuli was reversed. The later the local motion reversal occurred within the

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motion sequence, the more likely it was that it was unnoticed, as the global motion dominated over the local motion (Hidaka et al., 2009).

In the tactile domain, researchers have noted a similar phenomenon in the temporal percept of an input, whereby temporal gaps in a continuous vibro-tactile target go unnoticed. Strikingly, perceived continuity only occurred when the gaps were filled with vibro-tactile noise (Kitagawa et al., 2009). The authors propose that this is because the noise is greater than the signal from the target vibration, hence producing uncertainty. In these circumstances, it is plausible that the tactile vibration is present but masked by another stimulus. If there were no noise then one correctly perceives that the tactile vibration did not continue through the gap. Therefore, in this case the noise creates the possibility that the tactile vibration could have been continuous.

The classic tunnel effect has been given little attention in spatial touch perception. Essick et al. (1992) tested the effect on the face with gap sizes of 0.25 cm and 1 cm with before-and-after motion distances of 0.25 cm. Participants were asked to judge whether they felt two discrete successive motions, a single smooth motion, or simultaneous motion. Starting at low speeds participants typically experienced discrete sensations, then at moderate speeds smooth motion and at higher speeds they perceived simultaneous motion. Essick et al. (1992) also noted that the 1 cm gap required faster speeds than the 0.25cm for smooth motion perception, perhaps due to absolute temporal limits of binding temporally separated stimuli to the same object. This dependence of the perception of apparent motion on speed is similar to that observed with the use of discrete touch stimuli (Kirman, 1974; Sherrick & Rogers, 1966).

Following from this experiment, it was of interest to investigate if the perceived motion extent for a given speed was influenced by its fragmentation. Participants in a follow-up study received brushing stimuli on the face, either as a continuous 0.75 cm motion or the same motion with the middle 0.25 cm blocked from touching the skin (Essick et al., 1991). Participants were tested at ten velocities ranging from 0.5 to 64 cm/s. An increase in the speed from 10 cm/s to 50 cm/s resulted in approximately a halving in perceived distance in both conditions. That is,

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fragmenting the motion for a given speed did not influence the perceived extent. When these data were replotted with regards to the inter-stimulus interval of the endpoint of the first motion and the start-point of the second motion the spatial distortion were similar to that predicted from the

Cutaneous Rabbit Effect. Although, an analogous result would be obtained if they were replotted in regards to the total duration of the velocity stimulus, which in this case is a constant of gap duration.

Essick et al. (1991) noted the difference from their data to that obtained in the CRE, but did not test if changing the relative speeds adjacent to and across the gap could explain this difference.

1.4.3 Space gives to time: The abridging effect

Although, fragmented tactile motion has been subject to multiple studies most of these occurred over twenty years ago, and they did not vary the relative velocity of motion inside and outside the gap. In the tactile domain, my advisors Seizova-Cajic and Taylor (2014) recently found in a study with ten participants that the spatiotemporal properties of a motion gap have important consequences for how the space is perceived. They found that when a brush moved along the forearm at 15 cm/s then instantly skipped a 10-cm patch and continued at 15 cm/s that participants perceived spatially continuous smooth motion. This was consistent with the above findings for discontinuous motion (Essick et al., 1992), the notion that there is an optimal crossing time for apparent motion (Kolers, 1972), and demonstrate that these effects operate over much larger spatial areas. The single most striking observation of the study was that if the motion stopped immediately after the gap participants perceived a backwards position shift in comparison to baseline measures at that position. Therefore it was as if that space within the gap shrank, such that the two skin patches were stitched together or abridged. If space is uncertain, then the perceived position of the brush could be given by a velocity constancy model (Collyer, 1976). This was later confirmed using three different surround velocities, although the position shift was not as much as predicted from velocity constancy (Nguyen et al., 2016). Hence, the data might be best explained by a combination of velocity constancy and filling-in mechanisms. Motion neurons might be responsible for these changes in localization, given they have large receptive fields (Nishida & Johnston, 1999) which could extend across the gap. It is not known exactly how this neural mechanism operates for

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different speeds or which neurons serve this function. Seizova-Cajic and Taylor (2014) also observed that the degree of mislocalization increased with exposure to the stimulus. As the stimulus configuration simulates the condition of a rearranged skin surface, with more stimulation, could an illusion like this lead to persistent changes to the local sign? The study found that when baseline was remeasured upon cessation of stimulation, the effect had quickly dissipated, but with more exposure to stimulation the effect may have persisted.

1.4.4 Cortical reorganization

The primary somatosensory cortex, which as noted earlier has a map of the body, can reorganise in response to peripheral changes such as skin stimulation (Braun et al., 2000b) as well as cortical changes (Makin & Bensmaia, 2017; Medina & Rapp, 2014; Wang et al., 1995). This makes S1 an appropriate candidate for representing the body metrics which change as we grow. Animal studies suggest that receptive fields in the somatosensory cortex reorganize in response to amputation, nerve section, and other experimental interventions (Merzenich & Jenkins, 1993; Rosselet et al.,

2008). For example, removal of a digit results in an expansion of the S1 representations of the surrounding digits (Makin et al., 2015).

In humans, it is difficult to study how physical changes to the body affect body representations, but insight can be gained by observing amputees. It is common for amputees to perceive a limb that does not exist, a phantom limb. The exact source of the perceived phantom limb is contentious; proposals have included sensory information from the stump, or a pre-existing map of the body. A clue to the construction of these maps comes from the case of a patient born with just three fingers on one hand (McGeoch & Ramachandran, 2012). She correctly perceived just three fingers, but following an accident, amputation of the hand resulted in the perception of a complete phantom hand with five fingers. One hypothesis is that cross-referencing of information from the unaffected side aided the construction of additional phantom fingers (Giummarra et al.,

2007). Alternatively, an innate body representation could exist (Brugger et al., 2000), which is subject to updating based on the statistics of sensory input. These observations in amputees show that cortical representations of the body can reorganize.

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1.4.5 Organizing somatosensation: Analysing the statistics of touch to the skin

Similar cortical reorganization occurs through persistent skin stimulation. For instance, the size of the cortical representation of the fingers has been observed to scale with hours of practice in professional piano players (Ragert et al., 2004). Some studies have achieved similar reorganization by systematically and persistently stimulating the skin surface to mimic physical changes to the body (Braun et al., 2000b; Sterr et al., 1998). Early studies in macaques suggested that the spatiotemporal statistics of the stimulation dictate cortical reorganization of somatosensory areas.

Two locations persistently stimulated at the same time were represented closer together in the cortex, whereas if the locations were stimulated sequentially they were represented further apart

(Clark et al., 1988; Wang et al., 1995).

In humans, a similar observation was made using co-stimulation of the thumb and little finger for an hour a day for 20 days (Braun et al., 2000a). Conditioning resulted in these fingers’ S1 representations expanding toward each other. In addition, subjects were more likely to mislocalize touch of the thumb to the little finger, and vice-versa. Therefore, it seems that changes in the somatosensory cortex are mirrored with changes in perceived location. These changes to the cortical representation might arise by interpreting signals from receptors that are frequently activated at the same time as highly likely to be closely located (Detorakis & Rougier, 2014; Dinse & Merzenich,

2002; Wiemer et al., 2000). That is, the brain uses a temporal code to create space. This reorganization could occur in a Hebbian-like manner, whereby the association strengthens with subsequent co-stimulations (Hebb, 1949; Koenderink, 1990) or potentially through changes in excitability without changes in connectivity (Hegner et al., 2006). If Hebbian learning is adhered to, these representational changes arise could include experience dependent synaptic plasticity, arborisation, and functional sharpening of neuroanatomical connections (Buonomano & Merzenich,

1998; Detorakis & Rougier, 2012).

In another study, Craig (1993) gave participants persistent vibro-tactile stimulation on the forearm for a few weeks. The stimulation was typically 10-second bursts near the elbow, given every minute. A touch given to this area was typically reported as weak and diffuse. Such distorted

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primary sensation was accompanied by disordered localization, with some subjects even experiencing a single touch as being at more than one location. The mislocalizations spanned many centimetres and were highly robust, as even when subjects saw where the touch was applied they

“felt” it at a different location. When the vibration was removed, these mislocalizations were reduced but were still present at least four weeks after cessation of vibration. As in the previous study, the authors interpreted this result to have arisen from somatosensory reorganization, given that it took weeks of stimulation for mislocalization to occur and that the mislocalization persisted for weeks after vibration ceased.

Together, the above experimental interventions show that the brain is a self-organizing map which updates body representations using a probabilistic strategy (Kohonen, 1998). The binding of events that occur at different locations or at different times seems to be important for some features of motion perception, and also of cortical reorganization. It seems that binding, amongst other processes such as velocity constancy helps to make sense of moving stimuli.

1.4.6 Summary

From the periphery to the brain, touch localization on the skin is improved by the increasingly complex properties of receptive fields, the integration of this information with body representations, and top-down interpretations. The first section showed that touch localization is not simply set by receptor density or the cortical representations of the body. Further, the anatomical linkage between the periphery and the cortex is insufficient to produce stable spatial perception of touch, when considered in our natural environment. This was exemplified in the second section which showed that the localization of touch is modulated by predictive processes that use the spatiotemporal properties of the touch. Critically, this introductory chapter has highlighted knowledge gaps in localizing touch when uncertain, the perception of scotomas in touch, and spatial perception of moving touch. The psychophysical studies herein addressed these knowledge gaps.

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1.5 Aims of the present studies

This thesis seeks to unravel some of the mysteries surrounding touch localization and skin-based representations. This goal was examined in four main studies, each of which was informed from initial findings in pilot studies and supported by control studies. Specifically, the thesis seeks to address three main aims, detailed below.

Aim 1: Determine whether the recent history of stimulation affects tactile localization.

This aim is addressed in Chapter 2, where I set out to determine how the recent history of touch influences localization when uncertain about location (Medina & Coslett, 2016). In the critical experiment, I systematically modulated the intensity and spatial probability of touch on the forearm.

I hypothesised that weaker intensity touches would be mislocalized toward the average spatial location of the recent history of touch.

Aim 2: To measure if an artificial tactile scotoma results in change to tactile localization.

In Chapter 3, I investigated the tactile version of the visual artificial scotoma, in regards to its potential influence on touch localization. An artificial scotoma was created by inserting a spatial gap into tactile motion using the paradigm from my advisors study (Seizova-Cajic & Taylor, 2014) .

The localization of a touch stimulus given after the scotoma conditioning ceased was measured for locations bordering the scotoma and for those further away. I hypothesised that touch to the adjacent skin would be mislocalized, and that this bias would be towards the middle of the scotoma as a consequence of increased activation of its neurons through receptive field expansion or increased responsivity (Pettet & Gilbert, 1992).

Aim 3: To study perception of tactile motion extent and its potential contribution to representation of body metrics.

My advisors Seizova-Cajic and Taylor (2014) demonstrated that an artificial tactile scotoma produced a shortening of an implicit extent measure of the motion path. In Chapter 4, I

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hypothesised that an explicit measure of the motion path over fragmented motion provided by an artificial tactile scotoma would shorten. I further tested the effects of motion velocity and repeated judgments on perceived extent. A novel bias identified in these experiments was used to explore if spatiotemporal sensory information from the skin contributes to the representation of limb length

(Chapter 5).

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Chapter 2: Perceived Position of Touch on the Skin

2.1 Summary

This chapter focuses on touch localization when uncertain. In healthy individuals, location uncertainty can occur if touch is given amongst noise or if the touch is weak or only briefly presented. Previously, Steenbergen et al. (2014) found that reducing the intensity of electro- cutaneous stimuli increases the variability of localization responses, in conjunction with erroneous localization toward the middle of the forearm. The first experiment tested if this occurs in a more natural setting using a mechanical touch stimulus that gives a distinct pressure sensation. Two different von Frey filaments (weak and strong intensities) were applied to the forearm at four locations. Participants pointed to the location where they perceived touch. Weaker stimuli were localized with more variability and were biased toward the middle of the forearm. A second similar experiment then compared localization of stimuli of strong and super strong intensities. No differences in localization were seen. Following these observations, another experiment was undertaken to determine if the bias was really toward the middle of the forearm or toward the prior touch history. Two stimulus distributions, each offset from the middle of the forearm, were used.

Compared to responses to strong stimuli, responses to weak stimuli within each distribution were biased toward the middle of that distribution (0.6 cm, F[1,15] = 15.96, p < .001). This strategy minimises localization errors when there is uncertainty about perceived location. Interestingly, there was an overall shift of the mean of responses to each distribution as a whole toward the middle of the arm, consistent with long-known tendencies to centre responses in stimulus space. These experiments show that touch localization is influenced differently by the recent history depending on its intensity.

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2.2 Introduction

Pointing to the location of touch on the skin seems like a simple task, but a closer look reveals a surprisingly complex process. As described in Chapter 1, activation of touch receptors leads to activity in S1, which is topologically ordered to represent the skin surface (Penfield & Boldrey,

1937). The relation between the skin surface and number of neurons representing the surface in S1 differs for different regions of the body, and correlates closely with the peripheral variations in density of innervation.

In tightly controlled conditions, the location where a single touch is perceived typically corresponds to the middle of the population response of the neurons in S1 (Chen et al., 2003; Chen et al., 2007). However, there is no simple correspondence between the stimulated skin location and the percept. For example, prolonged stimulation over many days on the forearm can change perceived location of touch, likely through cortical reorganisation (Craig, 1993). As demonstrated with the Cutaneous Rabbit Effect (Geldard & Sherrick, 1972), context also affects localization accuracy. In the CRE, multiple rapid taps at one location and then at another result in perception of taps along the skin between the two locations. Therefore, a touch to a particular skin location will not always be felt at that location.

Stimulus intensity also affects tactile localization. A weak stimulus is localized with greater variability than a strong stimulus. This was demonstrated with electro-cutaneous (Steenbergen et al., 2014) and mechanical (Hamburger, 1980) stimuli on the skin. This increase in variable error when stimulus intensity is decreased is likely a result of a reduction of the signal-to-noise ratio

(Wheat et al., 1995). In a study primarily designed to test the effect of touch intensity on spatial perception, Steenbergen et al. (2014) varied the intensity of electro-cutaneous stimuli by varying the number of pulses. Increasing the number of pulses results in increased firing of the same afferents, without activation of additional afferents (van der Heide et al., 2009). By contrast, when intensity of a more ecological mechanical stimulus is increased, there is greater indentation of the skin that results in a relatively linear increase in firing of already activated afferents (Vallbo & Johansson,

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1984), and also in the activation of other afferents, gradually decreasing the further they are from the stimulus (Knibestöl & Vallbo, 1980; Phillips & Johnson, 1981). Therefore, the electro- cutaneous stimulus is not coded in the same way as ecological touch.

The intensity of a stimulus can influence perception of its absolute location. In tactile perception, it was initially thought that localization of static stimuli was independent of stimulus strength (Franz, 1916; Pritchard, 1931), but Steenbergen and colleagues (2014) observed that the perceived locations of slightly above-threshold electro-cutaneous stimuli are shifted toward the middle of the forearm. This was observed in conjunction with an increased variable error of localization for weak stimuli suggesting their location was uncertain. The error toward the middle of the forearm for weak stimuli could be interpreted as evidence of a bias toward a default position on the forearm. In contrast, it could be a bias resulting from integrating the recent history of stimulation.

Two questions arise from the findings of Steenbergen et al. (2014). First, do the effects of stimulus intensity apply to mechanical touch stimuli as well as to electro-cutaneous stimuli? This is an interesting question as touch stimuli are ecologically more relevant. Second, did the observed bias gravitate toward the middle of the forearm, or rather toward the middle of the particular stimulus distribution that preceded the response?

To answer these questions, three experiments were devised. Localization was recorded from pointing responses to mechanical touch stimuli on the forearm. Experiment 1 tested whether, compared to strong stimuli, weaker touch stimuli are localized with more variability and if they were mislocalized toward the middle of the forearm. Results demonstrated that mechanical touch stimuli exhibit similar biases to those found by Steenbergen et al. (2014). Experiment 2 confirmed that the bias was a result of the increased localization variability for weak stimuli. Given the results of experiments 1 and 2, a third experiment was undertaken to test whether the bias was towards the middle of the forearm, or the middle of the prior stimulus distribution. The main hypothesis was that perceived touch location is a function of the sensory input from the current touch and other

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recent touches. This was tested using two different stimulus distributions on two different days to determine whether responses to weaker stimuli are biased toward the middle of the forearm or the recent history of touch stimuli.

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2.3 Materials and methods

Three experiments were performed, all of which used the same apparatus, method of stimulation, and method of reporting touch location. The apparatus and set-up is described first below, followed by details that are specific to each experiment.

2.31. Participants

Participants gave their written informed consent before taking part in the study. Twelve right- handed5 participants (6M, 6F), mean age 31 (range 23-46) took part in Experiment 1. Ten people

(9F, 1M), all right handed, mean age 34 (range 22-46) participated in Experiment 2. Sixteen participants (10M, 6F), 13 right handed, mean age 30 (range 22-40), undertook Experiment 3. The experiments were submitted to and approved by the ethics committee of the University of New

South Wales and conformed to all aspects of the Declaration of Helsinki (2008). Some participants were paid for their participation and some participants took part in more than one experiment.

2.3.2 Apparatus and set-up

Subjects sat with the ventral side of the left forearm rested on padding. Their left forearm was obscured from their view by a vertically positioned graphics tablet set parallel to the forearm (Fig

2.1A). The graphics tablet (Wacom, 18.2” x 12.0”) was used to record pointing response location.

Four cm long markings were drawn across the dorsal forearm at four (Experiment 1 and 2, Fig

2.1B) or six locations (Experiment 3, Fig 2.1C) with a whiteboard marker. Subjects had their eyes closed throughout both experiments.

5 Handedness in all experiments of the thesis was determined by asking the participant.

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2.3.3 Procedure

Touch detection threshold on the left forearm was measured using three sequential staircases

(Experiment 1 and 2) or two interleaved staircases (Experiment 3). Staircase methods are reported here using the recommendations of Garcı́a-Pérez (1998). For each trial, the experimenter manually applied a von Frey filament to the skin in one of two brief time intervals (~2-3 s), which the experimenter verbally cued as “first” and “second”. Subjects declared which interval they felt the touch in. Each staircase began by random selection of a filament between 0.008 and 2 grams based on expectations from piloting. An increment or decrement of one filament from the standard

Semmes-Weinstein scale was used for incorrect and correct responses respectively. Each staircase was terminated at three (Experiment 1 and 2) or five (Experiment 3) staircase reversals. Touch detection threshold was calculated as the mean of all reversals (Table 1 and 2).

Figure 2.1. Method of localization and depiction of target locations. A. Participants pointed to the perceived location of touch on the forearm by pressing a stylus into a graphics tablet. Between trials the hand returned to a reference point (grey square). B. Stimuli locations for Experiment 1 and 2. Each marking spanned 4cm in the transverse direction on the arm. The spacing was 4.5 cm for each of locations 1-2 and 3-4, and 11 cm for locations 2-3. C. Stimulus locations for Experiment 3. Six locations were used, the most proximal four on one day and the most distal four on the other day. The spacing between locations was 4 cm.

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Detection thresholds were used to calculate stimulus intensities for the localization task separately for each subject (see Table 1 and 2). In Experiment 1 Weak stimuli were one filament stronger than detection threshold. Strong stimuli were set as the nearest filament (rounded up) to the detection threshold multiplied by 100. Ideally, an even stronger stimulus intensity would be used, however this could have led to pain sensation which is known to be localized differently from tactile sensation (Steenbergen et al., 2012). In Experiment 2, Strong stimuli were set by determining the lowest intensity that could be correctly perceived in ten consecutive trials which was then multiplied by five and rounded up to the nearest available filament. Super strong stimuli were calculated as 25 times the strong intensity and then rounded up to the nearest available von Frey filament. In Experiment 3 Weak stimuli were set at the lowest intensity that could be correctly perceived in ten consecutive trials. Strong stimuli were set as the nearest filament (rounded up) to fifty times the Weak intensity. Threshold at the most proximal location was used for calculating intensities for stimuli applied at the two most proximal locations, and threshold at the most distal location (Experiment 1 and 2) or second to most distal location (Experiment 3) was used to calculate those for the two most distal locations.

Touch was applied with Weak and Strong stimuli at four locations in random order. Each location was a 4-cm long line drawn across the forearm and the experimenter applied the touch at any point on the line in order to avoid adaptation. In each block, there were ten trials of each combination of intensity and location, for a total of 80 trials. For each trial, the filament was applied to the arm. Subjects pointed to where they felt the touch, using a graphics tablet pen held in the right hand (Fig 2.1A). Participants moved the pen to the tablet surface and when it was felt to match the location of the touch on the left forearm, the participant clicked the pen button and its position was recorded. After pointing, the filament was removed. To avoid the accumulation of pointing errors the subject moved their right hand back to a reference position (Bock & Eckmiller, 1986). If the subject did not feel a touch, it was repeated. Each trial took ~6-7 s.

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Table 1. Touch detection thresholds and stimulus intensities for experiment 1 (n = 12).

Location 1 Location 4

Touch detection threshold (g) 0.05 (0.02-0.29) 0.03 (0.02-0.16)

Weak stimulus intensity (g) 0.09 (0.03-0.52) 0.04 (0.03-0.04)

Strong stimulus intensity (g) 4.56 (1.44- 1.62 (1.44-2.38)

29.10)

Group mean data (range).

Table 2. Touch detection thresholds and stimulus intensities for experiment 3 (n = 16).

Proximal distribution Distal distribution

1 3 1 3

Touch detection threshold 0.10 (0.02- 0.05 (0.02- 0.08 (0.01- 0.10 (0.02-

(g) 0.4) 0.2) 0.6) 0.8)

Weak stimulus intensity 0.51 (0.04- 0.33 (0.04- 0.40 (0.04- 0.41 (0.03-

(g) 1.44) 1.75) 1.44) 1.75)

Strong stimulus intensity 44.44 (4.10- 30.78 33.41 (4.10- 31.24 (2.38-

(g) 117.25) (4.10- 117.25) 117.25)

117.25)

Group mean data (range).

2.3.4 Experiment 1: Localization of Weak and Strong stimuli

The four locations were centred on the forearm. The two innermost locations were 11 cm apart and the outermost locations were 3.5 cm further out (Fig 2.1B). One localization block of 80 trials was completed.

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2.3.5 Experiment 2: Localization of Strong and Super strong stimuli

The locations used were the same as in Experiment 1. One localization block of 80 trials was completed.

2.3.6 Experiment 3: Localization of stimuli from different distributions

All subjects were naïve to the hypothesis of the experiment, however four subjects had previously taken part in Experiment 1. Testing was performed on two separate days. On each day, six locations were marked, 4 cm apart on the left forearm with the most proximal location ~3 cm from the elbow and the most distal ~3 cm from the wrist. The conditions were counterbalanced across days. Touch stimuli were applied at either the four most proximal markings (proximal distribution) or the four most distal markings (distal distribution; Fig 2.1C). This experiment used two localization blocks, a total of 160 trials, on each day.

2.3.7 Data analysis

Pointing data were converted from pixels to centimetres distance from the graphics tablet edge. In

Experiment 1 and 2 trials in which the subject indicated they had made a mistake were removed. In

Experiment 3 trials in which the stimulus was repeated were flagged. Outliers were defined as trials that fell further than two standard deviations away from the mean indicated location computed for each subject for each combination of location and stimulus intensity (3% of points in Experiment 1 and 2 and 4% in Experiment 3).

For Experiment 1 and 2 the outcome measures were (a) variable error (a measure of uncertainty about perceived location, see Appendix A), computed as the standard deviation of the ten responses made by a participant to localise each of the stimulus intensities at one location on the arm, and (b) the computed extent for the Inner (2,3) and Outer targets (1,4). The extent was computed as the distance between the perceived locations (e.g. 2 and 3, or 1 and 4). Variable error and computed extent were analysed with separate two-way repeated measures ANOVA with factors

Intensity and Location.

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Experiment 3 manipulated Distribution (Proximal, Distal), Block (First, Second), and

Location (1,2,3,4). Each participant had ten pointing responses for each combination of these factors. The main outcome measure in Experiment 3 was the displacement of the pointing responses to Weak stimuli compared to those to Strong stimuli (referred to as Δws) for the two locations which were common to each distribution. Experiment 3 used two separate analyses. The primary analysis used Δws for the locations which were common to each distribution and also separately for all locations. The secondary analysis used responses at all locations, for the Δws and separately for

Strong stimuli only. A bias of the response to Weak stimuli in the proximal direction results in a negative value and a bias of the response to Weak stimuli in the distal direction a positive value.

Locations in each distribution were coded 1-4, ordered proximal to distal. The α was set at .05 for all statistical analyses.

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2.4 Results

2.4.1 Experiment 1: Stimulus distribution centred on forearm

Variable error

The variability of pointing responses around each location for the two stimulus intensities is shown in Figure 2.2. Variable error was computed for each participant as the standard deviation of their ten pointing responses and analysed using a two-way repeated measures ANOVA for Intensity (Weak,

Strong) and Location (1,2,3,4). The mean variable error for responses to Weak stimuli was 2.51 cm

(± 1.45) compared to 1.97 cm (± 0.82) for Strong stimuli. The two-way ANOVA showed that the main effect of Intensity was significant (F[1,11] = 5.18, p = .044). There was no main effect of location (F[3,33] = 0.91, p = .442, Greenhouse-Geisser corrected). The interaction of intensity and location was also non-significant (F(3,33) = 0.018, p = .997).

Figure 2.2. Localization responses from Experiment 1 to Weak and Strong touch stimuli (mean ± 95% CIs; n = 12). A. The variable error of responses to stimuli at four locations was higher for weak stimuli (p = .044). The diagram of the forearm shows the four target locations (1, 2, 3,4). B. The computed extent for the Inner (2,3) and Outer (1,4) locations. Computed extent was significantly shorter for responses to weak stimuli (p = .022). The horizontal dashed lines represent the distances between the inner locations (11 cm) and the outer locations (12 cm). * denotes significance.

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Computed extent

These distances were computed as the difference between Locations 2 and 3 (Inner), and the difference between 1 and 4 (Outer) shown in Figure 2.2. Computed extent was analysed using a two-way repeated measures ANOVA for Intensity and Location (Inner, Outer). The two-way

ANOVA showed that the main effect of Intensity was significant (F[1,11] = 7.1, p = .022), as was the effect of Location (F[1,11] = 198.4, p < .001). The interaction of intensity and location was significant (F[1.11] = 5.8, p = .034).

2.4.2 Experiment 2: Localization of Strong and Super strong stimuli

As shown in Figure 2.3 there was no difference between the conditions for computed extents of

Outer (p = .49) or Inner targets (p = .87) by stimulus intensity. Variable errors pooled across locations for Strong (13.2 ± 1.1 mm) and Super strong (14.4 ± 1.5 mm) stimuli were not different (p

= .29). Therefore, stimulus intensity only affects localization (variability and position) at weak stimulus intensities.

Figure 2.3. Plots showing extent computed from pointing responses for Strong and Super Strong stimulus intensities for Experiment 2 (n = 10). There was no difference in the localization of the two stimulus intensities (p = .29). A. Inner targets. B. Outer targets. The horizontal dotted lines indicate the physical distances between the touch locations.

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2.4.3 Experiment 3: Stimulus distribution offset from middle of forearm

Variable error

The variable error for responses to Weak stimuli (1.30 ± 0.07 cm) was larger than that to Strong stimuli (1.15 ± 0.07 cm). A three-way repeated measures ANOVA (Intensity, Block, and target

Location), showed a significant effect of intensity (F[1,15] = 12.2, p = .03), but no other main effects or interactions.

Proximal condition 1 2

Distal condition 1 2

Figure 2.4. The ∆ws, computed as the difference between localization responses to Weak and Strong stimuli, for the locations that were common to the distributions in Experiment 3 (mean ± 95% CIs; n = 16). Stimulus responses were significantly shifted toward the middle of the distribution they were presented within (p = .001). Responses were shifted proximally when targets were presented in the proximal distribution (white columns) and distally when they were presented in the distal distribution (grey columns). The diagrams of the forearm show the target locations (black bars) that appear in this figure, as well as those that do not (grey bars) The arrow shows that positive values are a bias in the distal direction (i.e toward the wrist). * denotes significance.

Targets common to both distributions

Responses to Weak stimuli were expressed relative to responses to Strong stimuli to derive ∆ws for the two targets common to each distribution (Fig 2.4). Two-way ANOVA was performed on ∆ws with the factors of Distribution (Proximal, Distal) and Location. The main effect of Distribution was highly significant (F[1,15] = 15.4, p = .001). Location was also significant (F[1,15] = 9.1, p = .009).

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The interaction was non-significant. This analysis showed that Weak stimuli are biased toward the middle of the distribution they are presented in.

Proximal condition 1 2 3 4

Distal condition 1 2 3 4

Figure 2.5. The computed ∆ws from localization responses for the two distributions in Experiment 3 (mean ±95% CIs; n = 16). There was a highly significant main effect of location (p < .001), suggesting that the outer locations were more shifted than the inner locations. *denotes significance. The diagrams of the forearm show the target locations (black bars) that appear in this figure.

All targets

Responses to Weak stimuli were expressed relative to responses to Strong stimuli for all targets (Fig

2.5). Two-way ANOVA was performed on ∆ws with the factors of Location (1,2,3,4), Block (1,2), and Distribution (Proximal, Distal). The main effect of Location was significant (F[3,45] = 19.54, p

< .001). There was no effect of Block (F[1,15] = 1.84, p = .20) or Distribution (F[1,15] = 0.19, p =

.67). No interaction was significant.

Responses to Strong stimuli

Responses to Strong stimuli were expressed relative to the target Locations (Fig 2.6). A two-way

ANOVA was performed on this constant error with the factors of Distribution (Proximal, Distal) and Block (1,2). The ANOVA showed a significant effect of Distribution (F[1,15] = 9.7, p = .007) with no effect of Block (F[1,15] = 1.1, p = .30) or interaction. The mean constant error for the proximal distribution was 0.75 cm and for the distal distribution it was -1.7 cm, a difference of 2.4

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(0.9-4.0) cm. This analysis showed that responses in the Proximal distribution were shifted distally and those in the Distal distribution were shifted proximally.

Proximal condition 1 2 3 4

Distal condition 1 2 3 4

Figure 2.6. The constant error of localization for responses to Strong Stimuli for the two distributions in Experiment 3 (mean ±95% CIs; n = 16). Constant error was computed as the difference between the response and the stimulus location. Responses were significantly shifted by distribution (p = .007). *denotes significance. The diagrams of the forearm show the target locations (black bars) that appear in this figure.

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2.5 Discussion

These experiments tested the influences of intensity and recent stimulation history in touch. These experiments have confirmed that reducing the intensity of mechanical touch stimuli increased the variable error of localization, as previously observed by others (Hamburger, 1980; Ponzo, 1911).

Furthermore, there was a constant error: Weak stimuli were mislocalized toward the middle of the forearm when it coincided with the middle of the stimulus distribution (Experiment 1). But in

Experiment 3, when Weak stimuli were shown in the context of a stimulus distribution situated distally or proximally to the middle of the forearm, they were not biased toward the middle of the forearm. Instead they exhibited a localization bias toward the middle of their respective distributions. Interestingly, a bias was also observed for Strong stimuli, in which the mean of responses was shifted toward the centre of the arm. These biases demonstrate that the spatial properties of the recent stimulation history influence the perceived location of the stimulus (Aim 1).

Importantly, our initial findings for variable error and localization error were similar to those with electro-cutaneous stimuli even though mechanical touch and electro-cutaneous stimuli are coded differently. The coded intensity of a touch stimulus is determined by how many afferents it stimulates and their rate of firing (Knibestöl & Vallbo, 1980; Vallbo & Johansson, 1984).

Increasing the number of pulses of electro-cutaneous stimuli results in increased firing of the same afferents, without activation of additional afferents (van der Heide et al., 2009). This kind of touch input is unlikely to arise naturally. Increases in both the number and rate of afferents firing are observed in conjunction with increased pressure applied to the skin (Vallbo & Johansson, 1984).

Although these two types of tactile stimuli are coded differently, they both show localization errors that are dependent on the uncertainty that comes with low stimulus intensity.

The contraction of responses to Weak stimuli is consistent with a general response bias described in other tasks when uncertain (Huttenlocher et al., 1991; Stevens & Greenbaum, 1966).

These compressive biases are away from the borders and toward the middle of the response space,

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which are the elbow and wrist in the experiments of this chapter (Green, 1982). However, this response bias could not explain the findings of Experiment 3.

It appears that the bias in our experiment was not simply one that averages all prior inputs, but rather one that makes use of the recent history of stimulation. The bias toward the centre of the distribution could also be caused by serial dependence, attention, or prior expectations. Our experiment could not differentiate between any of these possibilities. Serial dependence is a bias of the response to the current stimulus toward the immediately preceding stimulus; with further back stimuli having less influence (Fischer & Whitney, 2014). Observations consistent with serial dependence could be brought about by attending to the previous location, as attention is known to influence localization (Fortenbaugh & Robertson, 2011; O'Boyle et al., 2001). Prior expectations can be formed from a window of the recent history of stimuli (Chalk et al., 2010) and under these circumstances offer a similar solution to serial dependence. For our data, the bias was unaffected by

Block. That is, the bias was not increased by a longer exposure to the distribution. This suggests that the important window of prior exposure was relatively short. In our experiment the immediately preceding stimulus was more often than not (in ~75% of cases) in the direction toward the centre of the stimulus distribution so serial dependence or attentional cueing mechanisms are plausible.

A weak stimulus is likely encoded with substantial variability, as the signal it produces may be of comparable size to environmental noise. Yet, if the stimulus is applied many times, the neural response from each application, when averaged, should signal the same location as the physical stimulus (Gold & Shadlen, 2007; Goldreich & Tong, 2013). However, in everyday life, touch often needs to be localised rapidly or in conjunction with other distractors because there is not always time to accumulate complete sensory information. By incorporating the history, a percept closer to reality than relying purely on a single measurement can be produced. As the stimulus strength increases, the signal has less noise and is less influenced by a prior, accordingly it is appropriately localised near the actual location. The results of Experiment 2, which used two levels of strong

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stimuli, confirm that this was the case, as there was no difference between localization uncertainty and consequently of localization error.

Unexpectedly, Experiment 3 showed a shifted response to strong stimuli. In one study, the localization of well-above threshold touch stimuli by healthy participants was not biased by the recent history of stimulation, although localization by stroke patients was influenced (Medina &

Rapp, 2014). In contrast, Weak and Strong stimuli were presented in the same session, interleaved and saw responses shift distally for the proximal distribution and proximally for the distal distribution in Experiment 3. The response shift to Strong stimuli, as seen for the two separate stimulus distributions towards the centre of the arm, is analogous to effects seen when pointing to targets (Elithorn et al., 1953). The direction of the shift is consistent with the “stimulus centering bias”, a shift of the mean of responses toward the centre of the response space, known for judgments made under uncertainty (Stevens & Greenbaum, 1966). Biases of this kind could be optimal for statistics of the task that are not known (Bays & Wolpert, 2007), such as pointing under uncertainty (Tassinari et al., 2006). The shift of strong responses could relate to effects in external space, such as drifting of perceived limb position (Bellan et al., 2016; Wann & Ibrahim, 1992).

These possibilities were not further explored.

Whilst there was a shifted response to Strong stimuli, the perceived distance between them was veridical. It is not clear how the stimuli used in our experiments and the expectations built up from previous trials influence these results. Even though these experiments showed that under uncertainty touch location is biased toward the prior distribution it was not tested to which parameters this strategy was optimised (e.g. the mean or the mode of the prior distribution). For instance, because we explore the world with our hands, we are likely to receive more touch inputs at the hands than at the elbow. If the prior distribution of touch on the forearm is indeed skewed, the bias towards it will differ depending on if the mean or the mode is used. If it were to the mode then touch would be biased more toward the hand than if it were to the mean. Such experiments could confirm that the perceptual system does not merely utilise the average of the prior distribution regardless of the uncertainty of the sensory input so it is not just a long-term averaging strategy.

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Learning more about these localization mechanisms might be relevant to stroke patients with damage to somatosensory areas, who have been observed to localize touch on the hand towards the middle of the hand (Birznieks et al., 2016; Denny-Brown et al., 1952; Paillard et al.,

1983; Rapp et al., 2002; White et al., 2010). This effect could reflect greater spatial uncertainty than in healthy individuals. If the brain representation of the hand is reduced in size due to injury, reorganization such that the whole hand serviced by the remaining neurons may lead to poorer spatial resolution, more uncertainty about location and hence, localization biases. Clinical and behavioural findings need to be brought together to understand neuroanatomical differences between the neurologically intact and those with deficits that underlie body representations (Longo et al., 2015).

These experiments revealed two novel findings. First, spatial biases observed using mechanical touch stimuli are similar to those observed for electro-cutaneous stimuli. Second, multiple biases influence perceived tactile position. An important source of bias is the recent history of stimulation, which affects near-threshold stimuli when compared to supra-threshold stimuli. This compressive bias is one instance of those described in many modalities. Other biases also affect strong stimuli and are consistent with long-known tendencies to centre responses in stimulus space.

These findings have important implications for other clinical and psychophysical studies of touch, in which stimulus intensity should be controlled and reported.

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Chapter 3: Artificial Tactile Scotoma

3.1 Summary

We used motion to create a tactile stimulus analogous to an artificial scotoma in vision, a numb spot in the middle of the motion path. Here we ask if locations near the edges of this numb spot (peri- scotomatous targets) undergo illusory displacement towards the middle of the deprived area, as they do in vision (Kapadia et al., 1994). We also tested the influence of speed with which the moving object crosses the numb spot, and time between cessation of motion and localization test. Subjects

(n= 12) pointed to 60-g von Frey filaments applied to the skin of the forearm ~1 s or 10 s following back-and-forth brush motion at 15 cm/s, with a 10-cm gap (numb spot) in the middle. Scotoma traverse speed was either 15 cm/s or 100 cm/s. Brushing with no gap served as a control. The results show significant inward position shifts for peri-scotomatous targets compared to the control

(F[2,22] = 8.48, p = .002). The 100 cm/s traverse speed resulted in 8.9 mm total gap compression, significantly different from the control (p = .02, Bonferroni corrected), and the 15 cm/s speed in 5.9 mm compression. Our results show that a tactile scotoma modulates perceived position of nearby touch stimuli, and the difference between the two speeds suggests that speed of motion across the scotoma is relevant. The experiments also found that perceived filling-in of the artificial scotoma was more consistent with constancy for uniform filling-in, wherein the sensation in the surrounds and the gap is uniform, subtly different from traditional mechanisms of filling-in.

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3.2 Introduction

The orderly and high-resolution representation of the skin surface in the brain affords us the ability to localize touch with accuracy. These representations in the primary somatosensory cortex and higher-order areas can reorganise in response to increased usage (Merzenich & Jenkins, 1993;

Ragert et al., 2004) or changes in body shape (Ramachandran & Hirstein, 1998). As mentioned earlier, the mechanisms that link changes to the body with cortical reorganisation are unclear (see

1.4.2). One line of evidence is that if two locations are repeatedly stimulated simultaneously they will come to be represented adjacently (Braun et al., 2000b), through a probabilistic account such as

Hebbian learning (Wiemer et al., 2000). A different approach to investigating cortical reorganization is to induce injury. For instance, in animals reorganisation is investigated by partly blocking the physical stimulus, anaesthesia, nerve section, and other lesions (Merzenich & Jenkins,

1993). In humans, understanding is furthered by observing patients with amputation or brain lesions

(Medina & Rapp, 2014). The common link in these studies is that there is a missing patch of sensory input. Of interest to the current study is how a scotoma—a region devoid of sensory input—is treated by the somatosensory system.

In the past, scotomas have been observed or artificially induced in vision at various levels of the nervous system. A visual artificial scotoma can be induced by surrounding an unstimulated region with dynamic stimulation (Ramachandran & Gregory, 1991). Ramachandran and Gregory

(1991) show that a simple way this can be achieved at home is by fixating near to a small covered patch of a TV that is displaying snow. Surprisingly the brain does not resolve the scotoma as a void, but rather “fills-in” the patch. As described in Chapter 1, filling-in is the process by which the brain attributes sensations to a scotoma using information from the surround and past experience. Usually within seconds the patch will appear identical to the surrounds (Kuffler, 1953) with different time courses for the filling-in of the different qualia of the surround stimuli (Ramachandran & Gregory,

1991). In response to stimulation around an artificial scotoma, receptive fields of cortical neurons that initially fall inside the scotoma now expand to respond to stimuli falling outside the scotoma

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(De Weerd et al., 1995; Gilbert & Wiesel, 1992). The rapidity and robustness of the filling-in process may explain why patients with long term scotomas are often unaware of their existence

(Safran & Landis, 1996; Weiskrantz et al., 1974).

Given the robustness of the sensation of filling-in within a scotoma, Kapadia et al. (1994) tested if changes to receptive fields for neurons within a scotoma could shift the location of targets outside an artificial visual scotoma to be perceived inside the scotoma. Participants viewed a screen filled with dynamic spots, other than a small blanked out square a few degrees eccentric to their fixation point. When filling-in developed, a three-line bisection task, in which the lines were parallel to an edge of the scotoma, was given. Participants had to decide if the middle line was closer to the top line or bottom line. Kapadia et al. (1994) coined the terminology, peri- scotomatous, for targets presented at the edge of the scotoma, and exo-scotomatous for targets presented further away from the scotoma. Remarkably, when the line pattern was on the edge of the scotoma, in the peri-scotomatous region, participants judged the middle line as shifted closer to the middle of the scotoma. No such effect was observed if the line pattern was further away from the scotoma, in the exo-scotomatous region. These results were consistent with the claim that receptive fields inside the scotoma expanded, as observed in neurophysiological recordings in the cat visual cortex (Pettet & Gilbert, 1992). Such a receptive field expansion is likely specific to the neurons activated by the surround stimulus, leading to an effect that is stimulus specific. For example compression in the three-line bisection task is greatest for stimulus orientations that are in parallel with the direction of the surround stimuli used to induce the artificial scotoma (Tailby & Metha,

2004). Although these results are consistent with receptive field change they should be interpreted with caution, as the perceived location of each of the three lines could be subject to local position shifts.

In the touch domain it is obvious that filling-in effects occur, such as the tactile funnelling illusion (Gardner & Spencer, 1972) or the referral of thermal sensations (Green, 1977).

Furthermore, filling-in effects are observed for temperature (Green, 1977), and vibration (Kitagawa et al., 2009; Von Békésy, 1959). Geldard and Sherrick (1972) showed that five rapid taps at each of

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the wrist, mid-forearm, and elbow were perceived uniformly along the arm as if “a tiny rabbit were hopping from wrist to elbow”. Such an experience is also achieved with simpler stimulus patterns, including the utterly reduced rabbit that consists of only two taps (Trojan et al., 2010). Bayesian models, with the assumption that the touch arises from one object and has a low speed, can explain the position shift of the Cutaneous Rabbit Effect (Goldreich & Tong, 2013). If the two-tap version is bordered with motion provided by a brush moving across the skin, perceived motion is interpolated across the spatial gap (Essick et al., 1991) and the landing position of the brush is mislocalized with a large compressive position shift (Nguyen et al., 2016; Seizova-Cajic & Taylor,

2014). However, it is not known whether a non-moving touch stimulus applied after conditioning with brush motion also produces a large position shift or whether the changes are constrained to a test stimulus of the same kind as the conditioning stimulus. These large position shifts of the location of the moving target are likely bound by different mechanisms than the local mechanisms which cause position shifts for an artificial scotoma. In addition, preliminary findings suggest that representational momentum in touch differs from that in vision (Macauda et al., 2017). In vision, a moving object which disappears from view is perceived to be displaced forwards of the last position it was seen at, whereas in touch it can be perceived as displaced backward from this position depending on the reporting method used (Macauda et al., 2017)

One method of probing receptive field changes is to test localization on the edge of the scotoma. The perception of location can arise from a single neuron, for densely innervated regions of the body such as the hand, but only for very weak stimuli (Ochoa & Torebjörk, 1983). More commonly, location emerges from the pooled response of multiple neurons (Ghazanfar et al., 2000;

Koerber et al., 1993). Accordingly, areas such as the forearm which have poor spatial acuity should see changes in pooled response if receptive field sizes increase within the scotoma so that more neurones within the scotoma are now sensitive to touch in the peri-scotomatous region. The altered population response of the neurones should be mirrored by changes in perceived location.

The following experiments test if an artificial tactile scotoma would produce such a position shift. A static mechanical touch stimulus was used for testing and the scotoma was

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surrounded by a motion stimulus. In the main study, to test if filling-in is related to the amount of position shift the traverse time across the non-stimulated patch was varied. Filling-in occurs more consistently when the motion instantly skips the scotoma than when the traverse time is longer.

Secondarily, the persistence of the scotoma’s effect on touch localization was investigated. Two preliminary experiments were also performed to protect against known effects on spatial perception of intensity adaptation (Chapter 2, Schwartz et al., 2007a) and of nearby touch pressure (Ziat et al.,

2014).

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3.3 Materials and methods

Three experiments were performed. Two of these were preliminary experiments in which the apparatus and methods differed substantially from the main study. These two preliminary experiments were performed so that the main experiment could be set-up to account for any biases introduced by reductions in localization certainty due to adaptation from the brushing or from the presence of the sleeve used to fragment motion (described below, 3.3.2). The methods of all experiments are described first, followed by results and discussion.

3.3.1 Participants

The study was approved by the University of New South Wales ethics committee. Participants were all healthy individuals and provided their written informed consent, according to the procedure approved by the ethics committees. Two preliminary experiments and one main experiment were undertaken. Eight people (3F, 5M, aged 22-40), seven right handed, participated in preliminary experiment 1. Eight right handed people (3F, 6M, aged 21-38), were participants in preliminary experiment 2. For the main experiment, 12 participants (10F, 2M, aged 23-43 years), all right- handed, each attended on three days. Some participants were paid for their participation and some participants took part in more than one experiment.

3.3.2 Apparatus and Set-up

Participants were seated with their left forearm pronated and supported on an armrest placed perpendicular to the seat back. A graphics tablet was positioned parallel to the forearm so that the experimenter could see the forearm, but the participant could not see it (see Fig 2.1A). During all testing, participants were blindfolded. In preliminary experiment 1 and the main experiment the left forearm was fitted with a leather sleeve that had two rectangular 4.5-cm windows over the dorsum of the forearm. These windows were separated by a 10-cm metal-covered occluder, which was centered on the forearm. Touch stimuli were manually applied to the forearm by the experimenter using von Frey filaments as described for each experiment. For localization responses, participants

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pointed with a stylus held in the right hand to where they perceived the touch. This position was recorded through the graphics tablet.

For preliminary experiment 2 and the main experiment, stimulation of the forearm surface was achieved with paintbrushes (0.8 cm thick x 4 cm wide, fill density ~185 filaments per/cm2) of the type that could be bought at any hardware store. This stimulation produced a relatively consistent sensation of soft touch on the skin, even though at times it could feel prickly. To achieve sufficient pressure the brushes were positioned such that they splayed to some extent. The brushes were mounted on a carrier that was driven along a slider at 15 cm/s by a stepper motor (Excitron Au

Controllercoder model Au57-40M). The stepper motor was controlled using a custom program I wrote in Labview (code cannot be provided in appendix as Labview is a graphical programming language). The stepper motor accelerated rapidly at the start and end of each movement until smooth 15 cm/s motion was achieved.

3.3.3 Procedure

Two preliminary experiments were performed so that Experiment 1 could be set-up to account for any biases related to reductions in localization certainty from the presence of the sleeve itself or due to adaptation from the brushing.

3.3.4 Preliminary experiment 1

This preliminary experiment was completed to check that the skin pressure of the sleeve did not influence localization of touch, as previous studies have shown that other touch on the skin influences the spatial perception of a touch (Braun et al., 2005; Gentaz & Hatwell, 2004;

Gescheider et al., 1978; Ziat et al., 2014). One study in particular showed that sustained pressure on the skin resulted in repulsion of the perceived location of nearby touch stimuli (Day & Singer,

1964), although this finding has been debated on methodological grounds (Gilbert, 1967). A repulsive effect was also recently found when dynamic vibro-tactile stimulation was used (Li et al.,

2017).

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Touch stimuli were manually applied by the experimenter using a 60 g von Frey filament at four locations, which were centred on the forearm. The two innermost locations were 11 cm apart and the outermost locations were 3.5 cm further out. Participants pointed to the perceived location of touch in two blocks. In each block, ten stimuli were applied at each location with the order of location randomized. In one block, the sleeve was on the arm (Sleeve), in the other it was not on the arm (No Sleeve). The order of the blocks was randomly counterbalanced across subjects. There was a 2-minute rest period between the two blocks in which the sleeve was off the arm. At the end of the experiment participants were given the opportunity to comment on the difficulty of detecting and localizing the stimulus in each block. For each subject, the mean perceived location of each target was calculated for each block. Then, the distance between the perceived locations of the inner targets was computed, as was the distance between the perceived locations of the outer targets.

3.3.5 Preliminary experiment 2

This experiment measured change in the detectability of a touch stimulus to determine whether brushing of the region of skin to which the touch was applied resulted in adaptation. This control experiment, in conjunction with Experiment 2 in Chapter 2, allowed the selection of a sufficiently strong touch stimulus to avoid it being perceived as weak, and hence of uncertain localization, after adaptation. A line drawn on the arm a few centimetres distal to the elbow was used as the site for testing touch detection threshold. For the entire experiment, a paintbrush was in contact with the forearm. When it was stationary it was positioned at a location that was 7.5 cm distal to threshold testing site (to simulate the conditions for localization in the main experiment).

Touch detection threshold was measured using a three-alternative forced choice task. Each trial had two intervals, preceded verbally by “first” and “second” respectively. Touch to the arm was on the first or the second interval. After the second interval, the subject declared if they felt touch on the first or second interval, or no touch at all. The forced choice task was built into two interleaved staircases. A correct response resulted in use of a weaker von Frey filament for the next stimulus and an incorrect response, in use of a stronger von Frey filament. The termination rule for

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each staircase was five reversals. Detection threshold was computed as the average of the reversals of the two staircases. The maximal stimulus intensity for a reversal was then tested to determine whether it was consistently perceived each time it was presented. This was defined as a 'supra- threshold' stimulus for the purpose of the experiment. Subjects were then tested at this stimulus intensity. If they made correct detections ten times in ten trials, the intensity was designated supra- threshold. If they made a mistake, the stimulus intensity was increased by use of the next available von Frey filament. This procedure was repeated until 10/10 was reached.

Detection thresholds were then remeasured during application of the paintbrush along the skin of the forearm. This was postulated to lead to adaptation. The brush moved 10 cm up-and- down the arm, such that it crossed the testing line, at a speed of 15 cm/s for 4 minutes. The brush then stopped at the distal position. After this initial conditioning, a series of repetitions of 15 s of no brushing followed by six back-and-forth sweeps of the brush were performed. In each 15-s break, threshold testing continued. After this, the supra-threshold intensity was estimated and measured also between intervals of brushing.

3.3.6 Experiment 1

The effects of an artificial tactile scotoma were measured using pointing responses and phenomenological report. The main independent variable in the experiment was the presence of an artificial tactile scotoma, created by inserting a 10-cm gap in the path of a brush moving along the forearm. Three conditions were tested, Continuous, Spatial Gap, and Motion Gap. In the Motion

Gap condition the time to cross the gap was consistent with object’s prior velocity (15 cm/s) i.e.,

667 ms. By contrast, it was only 100 ms in the Spatial Gap condition.

The three conditions were presented on separate days in a counterbalanced order. Tactile localization was probed at locations next to the scotoma (0.5 cm; peri-scotomatous) or 4.5 cm away from it (exo-scotomatous). The distance of the exo-scotomatous location was chosen as 4.5 cm as this is greater than the two-point discrimination threshold on the forearm (Cody et al., 2008) so it could be expected to be relatively unaffected by changes to receptive fields outside of that range (

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dependent on the variability of receptive field sizes at different sites on the arm within and between individuals). The motion direction (proximal or distal) immediately before application of the touch stimulus was also manipulated to test for direction specific effects, and the delay between conditioning and test stimuli was varied (~1 s or 10 s) to examine the persistence of any shifts in perceived position.

Set up for the three conditions

In the Continuous condition, participants wore a leather sleeve with a 19-cm window over the dorsum of the forearm, whereas in the Motion Gap and Spatial Gap conditions, participants wore the sleeve (described above) with two 4.5-cm windows separated by a 10-cm metal occluder (see

Fig 3.1). In the Continuous and Motion Gap conditions, a single paintbrush moved up and down the arm at 15 cm/s (described above), whereas in the Spatial Gap condition two brushes were used. The distance between these brushes was set at 8.5 cm to achieve a 100-ms traverse time over the scotoma. Only one of the brushes was in contact with the skin at any given time (see Fig 3.1). The exact traverse time in the Spatial Gap condition varied slightly trial-to-trial and between participants due to variation in brush splay. The brush could be driven off the skin at either end of the arm

(Proximal, Distal) and onto the sleeve, and it stayed there during localization testing. Brushing motions between tests were always at least one full forearm sweep, and at most three full sweeps.

Experiment 1 procedure

At the start of each session, a practice baseline block was done in which targets were presented at four locations for eight blocks. Targets were presented using von Frey filaments (60g) manually applied by the experimenter. As the stimuli were applied by the experimenter sitting to the left of the participant, any inadvertent skin stretch signal was likely in a medio-lateral direction.

Participants pointed with a stylus held in the right hand to where they perceived the touch. The stimulus was removed after pointing. At baseline, targets were presented in random order at four locations for eight repeats. Before conditioning began, to ensure participants understood the task they received two practice trials in which they pointed to the test stimulus after a sweep. Two

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blocks of subsequent testing each consisted of 64 trials (4 repeats x 4 locations x 2 directions x 2 delays), separated by a short break. A trial consisted of 1-3 brushing motions, application of the von

Frey filament, and a pointing response. The exact timing of the delay between brushing and filament application was subject to variation as it was given by the experimenter. After the two blocks participants completed a post-baseline set. After this, participants indicated where they had felt the brushing during the experiment by drawing on a standard arm template.

Figure 3.1. Diagram showing the brushing stimulation for Experiment 1. Continuous: the brush was continuous with the arm for the entire movement. Motion Gap: a 10-cm occluder prevented touch from being felt on the middle of the forearm. Spatial Gap: the brushes were set-up such that the 10-cm occluder was instantly traversed (100 ms).

3.3.7 Data analysis

Phenomenological report about the filling-in

At the end of the experiment participants drew on diagrams of an arm where and how intense the brushing felt. Each participant contributed three drawings per condition (the values for the three drawings were averaged as they were very similar). Drawings were scanned and each arm was split into ten segments along its length (each segment corresponding to approximately ~2-3 cm of actual participants' forearms, which were typically between 25 and 30 cm in length). The brightness of the

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shading was measured as the pixel intensity of a blank arm diagram minus the pixel intensity of the drawing, such that higher values correspond to darker sections of the drawing and indicate more intense feeling of brushing. Zero means no shading at all (no brushing felt) and 255 completely black.

Position uncertainty in localization responses (variable error)

Position uncertainty of pointing responses to the test stimulus was calculated as the standard deviation of their responses. It was computed separately for each participant for each combination of Condition, Location, Direction and Delay. The locations near the scotoma (2,3) were averaged as were the locations further away (1,4). Group mean values were compared using a four-way repeated measures ANOVA with factors Condition (Continuous, Motion Gap, Spatial Gap), Location (Peri- scotomatous, Exo-scotomatous), Motion direction (Proximal, Distal), and Delay (0, 10).

Bias in pointing responses (constant error)

To compare position shifts for locations adjacent to the scotoma to those that were further away, the distances between the Peri-scotomatous targets and between the Exo-scotomatous targets were computed. These were then expressed as the difference from their respective baselines such that higher values represent a compressive position shift relative to baseline. These were compared in a four-way repeated measures ANOVA with factors Condition (Continuous, Motion Gap, Spatial

Gap), Location (Peri-scotomatous, Exo-scotomatous), Motion Direction (Proximal, Distal), and

Delay (0, 10). The alpha level was set to .05 for all analyses.

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3.4 Results

3.4.1 Preliminary Experiment 1: Effect of nearby pressure on localization

Figure 3.2 shows that there was no difference between the conditions (Sleeve or No Sleeve) for computed extents between the Outer targets (p = .85) or between the Inner targets (p = .81), which were close to the edges of the occluder. Variable errors pooled across locations with (12.3 ± 1.0 mm) and without (12.0 ± 0.8 mm) the sleeve were not different (p = .84). Therefore, the occluding sleeve used in these experiments does not itself seem to influence the localization of touch stimuli presented adjacent to it.

Figure 3.2. Individual data for Preliminary experiment 1 (n = 8). Localization responses to mechanical touch stimuli were unaffected by the sleeve. A. Exo-scotomatous locations (1,4). B. Peri-scotamatous locations (2,3). Dotted horizontal lines indicate the distance between the targets.

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3.4.2 Preliminary Experiment 2: Intensity adaptation

Touch detection threshold changed from 0.13 (± 0.05) g before conditioning to 0.74 (± 0.10) g after conditioning, a highly significant change (p < .001; Fig 3.3). Similarly, the 'weakest supra-threshold intensity' was significantly increased by conditioning (p = .01), changing from 0.50 (± 0.18) g to

3.40 (± 0.90) g. Thus, conditioning by brushing the arm as planned for the main experiment resulted in substantial intensity adaptation. However, Experiment 2 in Chapter 2 compared localization of

Strong and Super strong stimuli and found that variable and constant errors were comparable across a wide range of supra-threshold stimuli. Therefore, a super strong stimulus given after adaptation with brushing should behave like a strong stimulus (i.e. be localized similarly). Together, the findings from these two experiments allowed us to select a stimulus intensity for the main experiment that was high enough so that even following adaptation its localization should remain unchanged.

Figure 3.3. Individual data for Preliminary experiment 2 (n = 8). A. Touch detection threshold was significantly increased by brushing (p < .001). B. Supra-threshold intensity was significantly increased by brushing (p = .01). Note some participants have identical values for supra-threshold intensity as the filaments increments are discrete.

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3.4.3 Experiment 1: Artificial tactile scotoma

Phenomenological report

Participants drew on templates of arms where they felt the brushing to be throughout the experiment, with darker regions indicating more intense brushing (see Fig 3.4). In this analysis, for which higher values are darker regions, each drawing was divided into ten bins. Mean intensity values for all bins on the arm were 11.2 (± 1.8 SE), 11.4 (± 2.3), and 23.3 (± 4.9) for Spatial Gap,

Motion Gap, and Continuous conditions, respectively. Thus, the perceived total intensity in the scotoma conditions was ~48% of the no scotoma condition. The total length brushed in each of the gap conditions (9 cm per sweep) was 46% of the length in the Continuous condition (19.5 cm per sweep). Therefore, this implicit computation suggested that the actual total intensity and the perceived total intensity were similar.

Figure 3.4. Representative drawings from a single subject for each session of Experiment 1. The drawings show where and how intense (shading) the brushing felt. Typically, Continuous motion was perceived as continuous. Often the spatial gap was perceived as continuous, but at an overall weaker intensity. The Motion gap condition was often perceived as discontinuous.

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A bimodal curve was observed in all conditions, including the Continuous condition that brushed the entire stretch of skin (Fig 3.5, given for illustrative purposes). That is, the function had peaks at either end and a dip in the middle. The reduction in perceived intensity of stimulation in the middle of the sweep was substantially more pronounced in the Motion Gap condition. In the middle of the drawing, a region of the arm that was only stimulated in the Continuous condition, there was still perception of brushing in the Spatial Gap condition (this was also observed for two participants in Motion Gap condition). The phenomenological drawings were not subject to quantitative analysis along the length of the arm due to inter-subject variability, the small number of data points available, and differences in the extent of the arm that was drawn on.

Figure 3.5. Plot showing group mean data (± 95% CIs, n = 12) for Experiment 1. The perceived brush intensity along the arm from the three conditions (Continuous, black circles; Spatial Gap, open circles; Motion Gap, open triangles). Drawings were binned into ten blocks. The vertical axis is pixel intensity, where higher values represent darker regions of the drawings and these are interpreted as representing more intense brushing).

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Position uncertainty in localization responses (variable error)

Group means (of variable errors) for the four locations from proximal to distal were 9.7 (± 0.5),

12.6 (± 1.1), 11.7 (± 0.7), and 9.0 (± 0.7) mm, respectively. For the analysis, the Peri-scotomatous locations (Inner) were averaged as were the Exo-scotomatous locations (Outer). A four-way

ANOVA showed a highly significant effect of Location (F[1,11] = 23.3, p = .001), with Peri- scotomatous locations localized with more uncertainty (12.2 ± 0.7 mm) than Exo-scotomatous locations (9. 3± 0.4 mm; Fig 3.6). The uncertainty for localization with ~1 s Delay was slightly higher (11.3 ± 0.7 mm) than for 10 s Delay (10.3 ± 0.4 mm), near significant (F[1,11] = 4.23, p =

.06). The difference between Distal (10.3 ± 0.5 mm) and Proximal motion directions (11.3 ± 0.6 mm) was not significant (F[1,11] = 3.71, p = .08). A significant interaction between Condition,

Direction, and Location was observed (F[6,66] = 2.48, p = .03). No main effect of Condition or of any other interaction was observed.

Figure 3.6. Group mean data (±95% CIs) of the variable error of localization responses for the Experiment 1 (n = 12). The Peri-scotomatous targets (Inner) were localized with more variability than the Exo-scotomatous targets (Outer, p = .001). Responses to targets presented at a ~1 s delay (left graph) were localized with slightly more variability than those at 10 s delay (right graph), although this was only near-significant (p = .06). The grey columns show the Continuous condition, the white columns the Motion Gap condition, and the hatched columns the Spatial Gap condition.

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Bias in pointing responses

The distance between pointing response to the Peri-scotomatous targets (and also the Exo- scotomatous targets) was calculated for each brushing condition. The difference from the distance between pointing responses at baseline was then calculated. A larger value for the differences indicates a compressive position shift relative to Baseline (a negative value indicating spatial dilation) as in the analysis presented below. The main finding was that the distance between inner targets was compressed in the presence of a tactile scotoma, as shown in Figure 3.7.

Figure 3.7. Mean differences between baseline and computed extents for Experiment 1 (± 95% CIs). For the Inner (Peri-scotomatous) targets there was a significant effect of condition. The Spatial Gap (hatched bars) condition was significantly compressed (p = .019) compared to Continuous (grey bars), and near significantly compressed (p = .062) compared to Motion Gap (white bars). For the Outer (Exo-scotomatous) targets, neither the Spatial Gap nor the Motion Gap were different from the Continuous condition although the Spatial Gap was significantly compressed compared to the Motion Gap (p = .024).

Data for the Inner and Outer distances were analysed separately, each with a three-way

ANOVA with factors Condition, Direction, and Delay. For the Inner distance, the analysis showed only a main effect for Condition (F[2,22] = 6.7, p = .005). The Spatial Gap condition (12.4 mm,

95% CI [5.1,19.7]) was significantly compressed (p = .019) compared to Continuous (-4.7 mm, CI

[4.6,13.9]) and was near significance (p = .062) compared to Motion Gap (2.7 mm, CI [-6.0, 11.1]).

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There were no effects of Direction or Delay. For the Outer distance, the analysis showed a main effect for Condition (F[2,22] = 4.3, p = .027). Spatial Gap was significantly compressed (p = .024) compared to Motion Gap. There was no effect of Direction but a significant main effect of Delay was also observed (F[1,11] = 8.1, p = .016) with 0 s (16.1 mm, CI [8.0-24.1]) more compressed than 10 s (7.6 mm, CI [1.2-15.4]).

We also tested for long lasting effects by comparing across conditions the computed distances in Baseline post-test to their values in Baseline pre-test. Separate one-way repeated measures ANOVA were performed for Inner and Outer targets. For the Inner targets there was no significant main effect of condition (F[2,22] = 0.62, p = .549. For the Outer targets there was a significant main effect of Condition (F[2,22} = 4.2, p = .027). Pairwise comparisons showed that

Spatial Gap was significantly (p = .008, -25.8 CI [-44.5,-7.1]) compressed compared to the

Continuous condition. The other pairwise comparisons were not significant.

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3.5 Discussion

We presented mechanical touch stimuli adjacent to a recently generated artificial tactile scotoma.

Peri-scotomatous and exo-scotomatous targets were mislocalized toward the middle of the scotoma

(Aim 2). Our analysis of the drawings revealed that participants were accurate at conveying the total amount of brushing stimulation in the different conditions. Interestingly, the Spatial Gap condition had a lower perceived intensity of brushing than Continuous in the areas that were stimulated, as if the scotoma was filled-in using the surrounding context via a feature-mixing mechanism.

We propose that the position shift of the tactile stimuli presented close to the edges of the scotoma was caused by increased responsiveness of the receptive fields of neurons within the scotoma. According to this claim, after conditioning, some of these neurons now respond to stimuli outside of the scotoma that they previously did not detect. Thus the unified signal from the signals of multiple neurons is as if the target were actually located inside the scotoma, as observed in visual studies (Kapadia et al., 1994; Tailby & Metha, 2004). On the body a similar phenomenon is observed when touch is applied to a digit adjacent to an anaesthetised digit. The touch is frequently mislocalized to the anaesthetised digit (Weiss et al., 2004). The current study found a position shift in the case where the intervention only influenced tactile sensation. An interesting property of our study that future experiments could test is if the receptive field changes are anisotropic, that is, is the expansion only occurs in the direction of the conditioning stimulation (motion).

The size of the position shift for tactile stimuli is difficult to compare to that observed at the edge of visual artificial scotomas as visual position shifts are often reported as shifts in visual angle.

However, as localization by pointing was used it is likely that the touch was represented in a similar external space as used for localizing a visual stimulus (Buchholz et al., 2013; Mueller & Fiehler,

2014; Yamamoto & Kitazawa, 2001). As touch is often localized in external eye-based co- ordinates, one way to compare the shifts is to work out what the position shift would be for a visual stimulus presented on the arm. Kapadia et al. (1994) report shifts of as much as 7.5 minutes of arc for stimuli placed at the edge of a 2.4-degree wide artificial scotoma. If we assume a viewing

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distance from the eyes to the forearm of 50 cm, their scotoma is projected as 2-cm long and would produce a 1-mm position shift (if we adjust their scotoma up to 10 cm it predicts a 5-mm position shift). In the current study, the compression of the distance between the peri-scotomatous targets was ~12 mm. That is a shift of ~6 mm on each side of the scotoma. Another way this comparison could be done is comparing the size of the shift in relation to modality specific receptive field sizes for the area, although, that might be functionally less relevant. It is encouraging that the size of the position shift here was of comparable order to that found in vision.

Many mechanisms could be responsible for changes to the receptive field geometry

(Cavanaugh et al., 2002; Chapman & Stone, 1996; Fiorani et al., 1992) . In touch, receptive field expansion has been observed in area 3b of somatosensory cortex in macaques following anaesthesia and has been attributed to a reduction in lateral inhibition (Calford & Tweedale, 1990).

Interestingly, receptive fields which are enlarged following amputation or retinal lesions shrink again over 1-2 weeks (Calford & Tweedale, 1988; Dreher et al., 2001) as if a corrective process exists. Consequently, although an inwards position shift has been observed for locations adjacent to artificial scotomas, one might expect that spatial perception could return veridical with time.

Our preliminary experiments suggested that it was not sufficient to simply cover a patch of skin for a position shift to be observed. Although the location of the targets from the occluded skin differed between the control and the main experiment, so it remains a possibility. The position shift only occurred when the surround was stimulated. Further, these experiments enabled us to select an appropriate stimulus intensity such that the compressive effects were not explainable by spatial biases for weak stimuli whereby weaker stimuli are mislocalized toward the middle of the forearm

(Steenbergen et al., 2014; Trojan et al., 2010) or the distribution of stimuli (Chapter 2). Moreover, as the exo-scotomatous targets were not shifted outwards, away from the conditioning stimulation, this suggests that the inward bias of the peri-scotomatous targets in the Spatial Gap condition was not simply a repulsive after-effect whereby localization is shifted away from an adapted region

(Cholewiak, 1976; Li et al., 2017). On the contrary, in the control condition (Continuous) the main study of this chapter showed an inwards position shift for the exo-scotomatous targets. Kapadia et

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al. (1994) observed a similar effect in their control condition in their study of visual scotoma. Their control condition was analogous to ours – they removed the occluding patch so that the whole screen was uniformly filled with random dots. The origin of this compressive bias is contentious. If the stimulus intensity we selected was not sufficient to overcome local adaptation then the effect could have been the regression to the mean, as observed in Chapter 2. If stimulus intensity was sufficient, the shortening could be a result of shrinkage of the perceived length of back-and-forth motion (Cavanagh & Anstis, 2013; Sinico et al., 2009) potentially influencing the skin-based representation of the body. Further studies are necessary to test this hypothesis.

The shift in the perceived position of touch was greater for the Spatial Gap condition than the Motion Gap condition in the study. It is difficult to explain how Spatial Gap would have led to greater changes in receptive field geometry than the Motion Gap. A possibility is that changes in global motion perception drove cortical reorganization. In Nguyen et al. (2016) we used three different contextual velocities to show that the perceived gap distance is consistent with a constant velocity mechanism. We proposed that the Spatial Gap condition results in stimulation of higher- order motion neurons which have feedback connections to lower-level local motion and position neurons. Repeated stimulation of these higher-order neurons could lead to receptive field changes in the position neurons via mechanism such as Hebbian plasticity. However, my study did not change the contextual velocities so there is a possibility it was perceived as in the two-tap version of the

Cutaneous Rabbit Effect. Under this possibility, two taps repeatedly presented close together in time result in changes to perception and cortical reorganization (Braun et al., 2000b; Wiemer et al.,

2000). Specifically, the perceived distance between the target locations shortens and the receptive fields for neurons corresponding to these areas expand toward each other. A future study could test these possibilities by using different contextual velocities and testing localization after stimulation.

Interestingly the size of the position shift in the Spatial Gap condition in this experiment was substantially smaller than in previous studies using the Spatial Gap stimulus (Nguyen et al.,

2016; Seizova-Cajic & Taylor, 2014). The size of the Spatial Gap shift was near significantly different from that in the Motion Gap condition for the inner locations and was significant for the

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outer locations. However, in these previous studies the end of a motion stimulus was localized in contrast to the static touch stimulus used in the current study. This discordance may have arisen because the conditioning only influenced stimulus specific neurons, which in this case were presumably higher-order motion neurons. This is consistent with the idea that motion after-effects in touch are generally only observed when the test stimulus contains motion (Watanabe et al.,

2007). Additionally, stimulus specificity has also been observed for artificial visual scotomas, whereby effects are greatest when the conditioning and test stimuli are matched in orientation

(Tailby & Metha, 2004). Another indication that the position shifts in the current experiment were separate from the previously described effect was that they were not influenced by the preceding direction of the conditioning stimulus. Previous studies were dependent on the test stimulus having crossed the artificial scotoma (see Nguyen et al., 2016). An alternative explanation for the smaller effect observed in this study is that as the test stimuli were presented after the conclusion of a brush sweep, the position shift may rapidly fade, although, the observation of similar position shifts at 1 and 10 s delays speaks against this hypothesis (unless the effect rapidly fades within the first second after motion). Therefore, the size of the position shift is likely related to the congruency between the conditioning motion stimulus and the static test stimuli. Further work is needed for a unifying explanation of the perception of continuous and discontinuous touch motion, and how it influences perceived position. An important consideration for testing the perceptual consequences of filling-in is whether the position of a static object and the instantaneous position of a moving object are coded using the same mechanism.

Gender differences within recruited participants could possibly contribute to the difference between this study and previous work. In general, females have been found to have better tactile acuity than males (Chen et al., 1995; Peters et al., 2009) and therefore would be less susceptible to spatial biases from tactile motion. In the study of Brugger and Meier (2015), using ninety participants, a tactile stimulus moving slowly towards the elbow is judged to have arrived at the elbow well before it touches it. On the left forearm this effect was ~2 cm larger for men than in women. On the right forearm there was no sex difference. In the study of Seizova-Cajic and Taylor

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(2014) participants were six females and four males, and the study was only performed for the left forearm. Participants in the current study were ten females and two males, similarly the stimulus was only ever on the left forearm. It was not possible to investigate the effect of gender on position biases as my studies sample sizes were too small. Future studies could counterbalance the arm tested and strive for an equal gender balance, and/or individualize the experimental stimuli to some measure of the participant’s tactile acuity (e.g. two-point discrimination or moving gap detection threshold).

Another factor that differed between this study and the previous studies of the Spatial Gap stimulus was that in this study the test stimuli were applied by the experimenter. It is well established that robot-controlled touch and interpersonal touch are perceived differently (Gallace &

Spence, 2010) with interpersonal touch being perceived with higher acuity (Basdogan et al., 1998).

Therefore, the test stimulus used in my chapter might have been less likely to show spatial bias.

There is good evidence that filling-in processes can have different time courses. For instance, there is almost instantaneous filling-in across the physiological blind spot (Ramachandran,

1992a) whereas an artificial scotoma can take seconds or longer to fill-in (De Weerd et al., 1995;

Gilbert & Wiesel, 1992). One hypothesis that seems consistent with our results is the active spreading hypothesis, where information from the edge of the scotoma propagates towards its middle to fill the gaps (De Weerd et al., 1995; Paradiso & Nakayama, 1991). In vision this spreading only seems to occur in areas higher than V1 (De Weerd et al., 1995) as if a dynamic surround might not induce filling-in of static features, given that the filling-in occurs at higher-order regions than those that process position of a static stimulus. Similarly, in our experiment the position information may have filled-in over a longer time course than the motion features.

The analysis of the drawings offers a clue of as to how these filling-in effects might occur.

In the Spatial Gap condition in which filling-in was perceived there was a reduction in perceived intensity in the stimulated regions and an increase in perceived intensity in the scotoma. This result closely mirrors observations in thermal referral studies in which perceived temperature of a neutral

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object applied to the middle finger is modulated by the temperature of objects applied to the adjacent fingers (Green, 1977). The referral of this thermal sensation to the middle finger seems to occur not from interpolation from the surrounds but rather from summation and averaging of the total thermal input (Ho et al., 2011). Ho et al. (2011) found that this resulted in a reduction in the apparent intensity of the temperature to the outer two fingers and an increase in apparent intensity of the temperature to the middle finger. This may relate to attributing the sensations to a single object that has a uniform temperature, given that it only works when all fingers receive purely thermal stimuli or all receive thermal-mechanical stimuli (Cataldo et al., 2016). Results consistent with feature-mixing rather than filling-in are also observed in vision (Geldard, 1976; Hsieh & Tse,

2009) and could stem from combinations of feature filling-in and boundary contour systems

(Grossberg & Todorovic, 1988). Therefore, multiple filling-in mechanisms could be responsible for the illusory perception within the scotoma.

The findings of this study could certainly be criticised for not testing if the occluder actually completely blocks the pressure of the touch on the skin. If it does not and the touch was felt in the middle, then participants should report feeling double sensations (i.e. the brush on the skin and the pressure of the other brush on the sleeve) in the Spatial Gap condition, which they did not.

It is possible that the pressure of the brush is felt through the occluder, as this possibility has never been tested. During piloting, when participants did feel the pressure of the brush through the occluder, they typically commented that it was felt as a dispersed and weak sensation over the entire area of the sleeve. Further, in the drawing analysis of the Motion Gap condition only two participants indicated a sensation of motion or brushing across the occluded region. These comments are not consistent with the adverse possibility of touch being felt through the occluder.

Future studies using fragmented motion might use the same method, or achieve it in a way that does not require a sleeve. Studies should report the brush materials and dimensions, as these can have important and unexpected influences on the percept, especially of discontinuous motion (Szaniszlo et al., 1998).

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Tremier et al. (in Pessoa & De Weerd, 2003) predicted that responses of neurons with receptive fields inside an artificial tactile scotoma would be correlated with sensations of filling-in.

Our study showed that the position shift was not completely contingent on filling-in, but it did appear to be modulated by whether motion or brush sensation was filled-in (Spatial Gap vs. Motion

Gap). In the Motion Gap condition there were only two participants who showed completion across the gap within the motion (based on their drawings). In the Spatial Gap condition, some participants commented (and their drawings indicated) that they not only perceived motion but also sensations of pressure and prickliness in the scotoma region.

The properties that are filled-in and their time courses might depend on the perceptual set of the participants. In vision filling-in processes are more rapid if they occur at the locus of attention

(De Weerd et al., 2006; Lou, 1999). If two lines cross the blind-spot, only the attended line is filled in (Ramachandran, 1992b). In touch, studies of the Cutaneous Rabbit Effect illustrate it is possible for participants to switch between hopping and smooth motion (filling-in) sensations at some temporal intervals (Carter et al., 2008; see also Harrar & Harris, 2007; Sherrick, 1968). In our experiment, at least one participant shifted their perceptual set between conditions as they freely offered that they “paid more attention to the properties of the brush” on one day and on another they “attended to the pattern of brushing”. In previous studies using the Spatial Gap stimulus participants were not just attending to the brush but also to its perceived end point of motion. In the current experiment it was not tested if the task changed the brushes’ phenomenological properties.

As in vision, these experiments have found that peri-scotomatous targets are mislocalized toward the middle of an artificial tactile scotoma. This position shift is consistent with the idea that there is increased responsivity of receptive fields of neurons lying within the scotoma. We propose that the filling-in sensation could arise from constancy for uniform sensation, which could be caused by multiple mechanisms. However, the position shift was much smaller than for previous studies that used a more specific test stimulus, suggesting that cortical reorganisation from motion is stimulus specific.

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Chapter 4: Tactile Motion Extent

4.1 Summary

The perceived extent of a tactile stimulus is dependent on its speed (Essick et al., 1991; Whitsel et al., 1986). Within the range of 5-25 cm/s it seems that tactile extent is perceived veridically. At lower speeds it feels longer and at faster speeds it feels shorter. My advisors Seizova-Cajic and

Taylor (2014) showed that inserting a spatial gap in a motion results in a perceived shortening of extent (as measured implicitly by pointing responses) but only when the gap is instantly skipped

(mimicking the situation of skin rearrangement). Such shortening seems to correlate with the perception of continuous motion that is felt when the gap is skipped, but not when the gap is crossed at the speed of brushing in the surrounds. The studies in this chapter used an explicit measure of perceived extent whereby participants chose a line from a visual display that they felt best matched the traverse distance of tactile motion on the forearm. When continuous and discontinuous (with rapid gap crossing) motions were used with equal sweep durations I found that perceived extent was equal. This observation suggested that in this case perceived extent is derived from end-to-end duration rather than some other stimulus feature. The experiments also showed that the perceived extent of a tactile motion stimulus reduces trial-to-trial. This shortening was likely a combination of local and higher-order mechanisms. Control experiments confirmed that these effects were not methodological biases. These experiments show that future studies on tactile motion extent should tightly control the motion duration and account for time-order effects.

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4.2 Introduction

We often experience fragmented motion in vision when a moving object is temporarily occluded. In touch, motion fragmentation can also be experienced, for instance from contact with irregular surfaces. Fragmented motion is important to understand as it could influence perception of movement, or perception of an object that is slipping out of one's hand, The spatially discrete touches of the Cutaneous Rabbit Effect discussed in Chapter 1, show substantial contraction biases of perceived location. These biases are dependent on the stimulus intensity and duration, the spatial and temporal intervals between stimuli, and the locus of attention. There is less known about the processing and perception of fragmented tactile motion which contains continuous components.

Essick et al. (1992) showed that the perceptual resolution of fragmented tactile motion is dependent on the speed relative to the size of the spatial gap in the motion. That is, for longer spatial gaps a higher speed is required for smooth motion perception, else the motion feels discontinuous. This occurs because the somatosensory system has a preferred speed for perceiving apparent motion for a given spatial gap, perhaps based on the probability that it is a single moving object which has crossed the gap (Kirman, 1974). At the range of speeds which produce perception of smooth continuous motion in spite of the fast crossing of the gap, it appears that either space and/or time must yield to produce the percept. If time gives in then the motion fills-in the spatial gap. If space gives in then one possibility is that the motions are stitched together such that the spatial gap is reduced.

Critically, in their study, Seizova-Cajic and Taylor (2014) modulated the relation between the speed outside the gap and the speed across the gap. Their study showed that at rapid crossing times the spatial gap between two motion segments partly shrinks rather than being filled-in with motion. Participants in their study and its follow-up study (Nguyen et al., 2016) perceived continuous motion when the crossing time was rapid. For a 10-cm gap they found that perceived position of the brush when it ended its motion adjacent to the gap was shifted into the gap by 2-3 cm, thus the perceived size of the gap was halved. In the study of Nguyen et al. (2016) the gap

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crossing time was held constant, while the before-and-after the gap speed was either 7.5, 15, or 30 cm/s. Interestingly, the perceived size of the gap (computed from localization of the brush motion) shrank at lower speeds. This finding was consistent with the idea of constant velocity, that the contextual speed is used to perceive the distance for the gap from the crossing time of the gap (i.e. in the same amount of time a slower speed will move less far). It is not known if this reduction in implicit extent of the spatial gap is mirrored with a reduction in an explicit measure of the motion extent. As discussed previously (1.2.9), alterations in implicit measures of extent do not necessarily mean that an explicit measure of extent will come to the same conclusion.

The difference between implicit and explicit measures could arise from how they are derived from the somatosensory cortex and higher-order areas (e.g. localization requires knowledge of limb position). Implicit measures of extent, such as independent localization of its two endpoints, could rely upon use of the pooled signal from multiple neurons in S1. That is, the centroid of the responses of the neurons stimulated by a touch, could be used for localization of each endpoint.

Extent judgments could use receptive field counting, wherein perceived extent seems to relate to the number of cortical receptive fields that span the space between the two endpoints of the extent

(Longo & Haggard, 2011). Although there is some evidence for this model, the distortion of judgments of extent on different body parts is less than expected from S1 maps (Taylor-Clarke et al., 2004), suggesting that other processes must also contribute to extent (Medina & Coslett, 2010).

One hypothesis is that these higher-order processes bring the extent into a visual reference frame

(Eads et al., 2015; Taylor-Clarke et al., 2004). As spatial distortions for tactile and visual body representations are in opposite directions (Linkenauger et al., 2015) the integration of the two representations could bring an extent into veridical spatial co-ordinates. Hence, the visual line- matching task used in this chapter does not necessarily require any additional spatial computations than other measures of extent (e.g. tactile extent comparisons). The first study in this chapter set out to test if extent was modulated by motion fragmentation.

Another factor which influences the perceived extent of motion is the velocity, and this provides an alternative interpretation for reductions in perceived extent of fragmented motion.

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Multiple studies have found that perceived motion extent shortens with increasing speed and elongates with decreasing speed (Hall & Donaldson, 1885; Langford et al., 1973; Whitsel et al.,

1986). Whether this is an effect of speed or of motion duration remains unknown (e.g. Essick et al.,

1991), as distance, duration, and speed are interdependent. These studies tend to show that perceived motion extent is veridical within the range of 5-25 cm/s (Macauda et al., 2017). Perceived extent is modulated by velocities outside this range; a ten-fold increase in speed results in a halving of perceived extent (Whitsel et al., 1986). Typically the motions used in these studies have been over distances of 4 to 16 cm, so it is unknown if these biases generalise to longer distances. The

Cutaneous Rabbit Effect, which produces similar spatial perception to continuous motion, results in shortening biases at substantially longer distances (Geldard, 1975) so we might expect similar velocity dependent biases for continuous motion over the 24 to 30 cm extents used within this chapter.

These extent distortions observed when introducing fragmentation into motion or by varying velocity are difficult to study as distance, duration, and speed are inherently linked.

Therefore, multiple experiments were performed in this chapter. This chapter tests if the perceived extent of fragmented motion is reduced when the spatial gap is rapidly crossed. If so this would be consistent with the constant velocity (and/or acceleration) hypothesis of tactile motion perception.

Follow-up experiments tested if this was explainable due to extent being judged from the motion sweep time. As a novel finding of shortening in perceived extent with repeated judgments was found, further experiments were performed to confirm this was not simply a response bias.

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4.3 Materials and general methods

Multiple experiments were conducted in this chapter to address questions about how the perceived extent of tactile motion is influenced by its speed and its continuity.

4.3.1 Participants

The studies were approved by the University of New South Wales ethics committee. Participants were all healthy individuals and provided their written informed consent, according to the procedure approved by the ethics committee. Some participants were paid for their participation and some participants took part in more than one experiment.

4.3.2 Apparatus and set-up

The experimental set-up to provide tactile stimulation to the arm and to allow extent judgments was similar across experiments. Initially, air jets were going to be used as they seemed to offer an easy way of providing consistent pressure along the arm. However their design proved too difficult for the time constraints of the thesis so brushes were used (see Appendix B). Tactile motion provided by a brush is a natural stimulus (i.e. it has pressure, skin stretch, and texture).

Stimulation with Wrap-Around Brush

Participants were seated with their left forearm held (in a horizontal position) neutral between supination and pronation and supported on an armrest placed perpendicular to the seat back. The armrest only contacted the arm at the elbow and at the hand. The elbow rested in a padded sling and the hand lightly gripped a pole (supported with padding under the hand). Hence, most of the forearm was in mid-air. A piece of cardboard was positioned parallel to the forearm so that the experimenter could see the forearm, while the participant could not (Fig 4.1A).

Stimulation of the forearm surface was achieved with channel strip brushes (0.4 cm thick,

0.007” Nylon fill) that were curved so that they maintained contact around the circumference of the forearm. The wrap-around stimulation was achieved using a pair of brushes, which hung touching

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each side of the arm. The brushes were attached to brackets above the arm that were free to pivot in the direction perpendicular to the length of the arm. This mechanism enabled the brushes to provide light pressure on the arm, even as the sliding device moved the brushes up-and-down the arm. This produced a relatively consistent sensation of soft touch on the skin, although at times it could feel prickly. To achieve sufficient pressure the brushes were positioned such that they splayed to some extent.

Figure 4.1. Method of stimulation and line-matching task. A. The wrap-around brush stimulation used in the experiments in this chapter. B/C. The line-matching displays used in the studies. The lines were of randomly varying lengths, were randomly ordered, and had the hexadecimal codes randomly assigned to them. B. Screenshot of the adapting line-matching display used. The display adapted with the participants' responses. C. Screenshot of the constant line-matching display used.

The brushes were mounted on a carrier that was driven along a slider by a stepper motor

(Excitron Au Controllercoder model Au57-40M). The stepper motor was controlled using a custom program (written by the experimenter in Labview). The stepper motor accelerated rapidly at the start and end of each movement until smooth motion was achieved within 1-2 cm from the beginning of the path.

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Extent Judgment through Line Matching

Previous experiments have measured perceived extent by applying a standard extent elsewhere on the body. Participants were to judge if it is longer or shorter than the test extent. This method was impractical for the current study as the extents used were long and the available body parts which could be used for testing with similar extents (without crossing joints) have poor spatial acuity.

These experiments measured perceived extent using a visual line matching task.

Participants faced a screen that displayed lines of varying lengths, each with a hexadecimal value adjacent to it (Fig 4.1B/C). Participants were asked to pick the line that was the closest match to the length of the skin that was brushed from one end to the other (i.e. the full extent touched).

Lines were displayed horizontally on the screen and were ordered randomly. For each extent judgment, a new display was provided with new random hexadecimal values. To choose a line from the display, the participant verbally reported the hexadecimal value that was adjacent to the line.

The experimenter recorded this choice by selecting from a list of responses provided through the

Labview program.

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4.4 Experimental studies

The specific methods, results, and a brief discussion for each experiment are below.

4.4.1 Experiment 1: Perceived extent of fragmented tactile motion

This study was conducted to test if the perceived extent of the Abridging stimulus (Seizova-Cajic &

Taylor 2014), also called the Spatial Gap stimulus (Chapter 3), is less than its physical extent. The

Spatial Gap stimulus was used as previous studies (Seizova-Cajic & Taylor 2014) showed its perceived motion path, as measured by pointing to the motion endpoint, was perceived to have shrunk by ~50%. The choice of a control condition proved problematic. A control for judging extent of a fragmented motion should account for confounds of time, speed, motion fragmentation, and stimulus size (the area the stimulus touches), but these parameters are interdependent. Changing the thickness of the brush (i.e. the physical length of the brush that contacts the skin in the direction of motion, not the width) did not seem to influence velocity judgments in one study (Essisk et al.,

1996), however it used only five participants. Even so this presents the possibility to change the brush thickness and maintain all other parameters as a control stimulus for motion fragmentation.

Participants and set-up specific for Experiment 1

Seven participants (4F, 3M, aged 25-61), all right-handed, attended on two days. The wrap-around brush was used to apply brushing stimulation to the left forearm. In the Spatial Gap condition, the left forearm was fitted with a metal wrap-around sleeve that occluded the middle 12 cm of the forearm such that no brushing was felt there. The sleeve was removed for the No Gap condition.

For both conditions, two sets of paired brushes were mounted at an ~11 cm separation on the carrier that was driven along the slider at 15 cm/s under the control of a custom Labview program (coded by the experimenter). With no occluder, both pairs of brushes were on the skin at all times (such that the effective length of the brush is greater, that is it spans ~11 cm along the arm compared to

~0.4 cm of the single brush). When the occluder was present, only one pair of brushes touched the skin at a time (one moved onto the occluder while the other moved off). Given a brush separation of

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11 cm, the slider only had to move 13 cm and 19 cm to achieve the 24 cm and 30 cm motion paths.

As in the previous chapter we cannot be certain if the occluder was completely effective.

For every test sweep, the participant was presented with a display of seven lines of varying lengths (with uniform increments between the line distances). Participants were to pick the line that was the closest match to the length of the skin that was brushed from one end to the other. Separate line displays were used for each test length. Initially the mean of the line display matched the physical extent of the test motion. The set of displayed lines updated every six responses so that its mean was equal to the mean of the previous six responses. This manipulation meant there was always a line available for participants to select in the case that perceived length changed substantially with time (as expected from piloting).

Design for Experiment 1

The effects of an artificial tactile scotoma on perception of extent were measured using a line matching task. The main independent variable was the presence of a 12-cm scotoma (occluder) in the middle of the motion path. The occluder was on the skin in the Spatial Gap condition, such that only one of the two pairs of brushes was on the skin at any given time. The other brush was on the occluder and could not stimulate the skin. The two conditions were tested on separate days in a counterbalanced order. Test motion paths were of two different lengths: 24 and 30 cm. The motion paths were presented an equal number of times in Proximal or Distal directions. The 30-cm test length was always preceded by a sweep in the opposite direction, whereas the 24-cm test length was preceded equally by a sweep from either direction.

Procedure for Experiment 1

At the beginning of each session, participants completed a practice distance judgment task for a moving visual stimulus to ensure that they were judging the correct property of the brushed length

(i.e. the end-to-end length of the skin that was brushed, not the distance moved by the slider or the inside-to-inside brushed distance). The first block of testing then began. In this block, test sweeps of the two lengths (24 cm, 30 cm) in a proximal or distal direction were given for a total of 64 repeats.

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There was at most a single back-and-forth sweep between test sweeps. This short block was designed to test for an immediate effect of the brushing and to minimise adaptation to the motions.

After this block, conditioning with 100 back-and-forth 30-cm sweeps commenced, during which participants made judgments of the length for four repeats over two directions. These judgments were not included in the analysis; they were to ensure that participants attended to the sensations arising from the brushing stimulus. Following this conditioning period a block of testing began, of

64 repeats contained within a top-up adaptation paradigm. Top-ups between tests were approximately three sweeps, designed to sustain any adaptation induced in the conditioning period.

The blocks were always run in a fixed order to test if exposure influences perceived tactile distance.

Data analysis for Experiment 1

Raw data were tactile distance judgments which were expressed in cm. Trials were grouped into blocks of eight for analysis. Group mean values were compared using a four-way repeated measures

ANOVA with factors Condition (Spatial Gap, No Gap), Block (1,2,3,4), Exposure (Short, Long), and Length (24 cm, 30 cm). The alpha level was set to .05 for all analyses.

Results for Experiment 1

The results of Experiment 1 show large changes in perceived extent over time for both the Spatial

Gap stimulus and the control condition (Fig 4.2). The four-way repeated measures ANOVA showed significant effects of Block (F[3,18] = 14.8, p = .007, Greenhouse-Geisser corrected), Exposure

(F[1,6] = 10.3, p = .018), and Length (F[1,6] = 251.8, p < .001). Condition was non-significant

(F[1,6] = 0.18, p = .685). No pairwise comparisons of Block were significant. When the lengths were averaged, the first Block (23.9 [20.7, 27.1] cm) and last Block (19.6 [13.8,25.4] cm) were significantly different by pairwise comparison (p = .051). This suggested that within Short and

Long exposures there was perceived shortening of extent over time.

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Discussion for Experiment 1

This study presented some unexpected findings. 1) The control condition was as effective at inducing contraction of extent as the Spatial Gap condition. 2) The contraction of extent that occurred across Block appeared to be less related to the degree of exposure to the brushing stimulus than to the repeated judgments (i.e., there was little effect of the 100 sweeps between the judgment blocks).

Therefore, multiple control experiments were performed. These controls were necessary as we used a novel reporting method and were testing tactile motion extent which has not often been tested. The control experiments were designed to test if the line matching method introduced any biases, and if repeating the stimuli caused any bias.

SPATIAL GAP CONTROL

Exposure to ordered runs Figure 4.2. Group mean data (± 95% CIs) of judgments of perceived tactile motion extent in Experiment 1. The analysis showed that there was a significant effect of Block (p = .007) and of Exposure (p = .018, S = Short, L = Long). There was no difference between the Spatial Gap and Control conditions (p = 0.685). Vertical grey bars indicate the conditioning period (100 back-and-forth motions). Dotted horizontal lines show 24 (unfilled circles) and 30 cm (filled circles) test lengths.

There were multiple possibilities as to why we observed shortening in the control condition in conjunction with that in the fragmented condition. One possibility was that perceived extent is judged from the sweep time between the endpoints of motion (e.g. Essick et al., 1991). In study 1 the sweep time was identical in the Spatial Gap and control conditions. In a follow-up study we tested if sweep-duration matched stimuli led to a similar shortening (Control Experiment 1a).

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There are other possibilities pertaining to the control condition, however these are difficult to investigate due to its complex spatiotemporal properties. One way the stimulus, in which two sets of brushes encompassed the forearm with a 11-cm distance between them, may have been resolved is as if the two sets of brushes perceptually fused to form one smaller object (Peelen et al., 2010;

Von Békésy, 1959), thus the perceived extent would have reduced. Critically, in this study no participants volunteered that they felt the two sets of brushes as one object. Another possibility is that participants were not judging the complete end-to-end extent, but rather the motion extent (i.e. the distance the brush-holder moved). The moving two-point stimulus was not used as a control in further experiments.

Another possibility is that the adaptive line display used in the study caused a response bias.

This judgment dependent bias would occur if participants used a strategy of selecting a particular line from the set each time under the assumption that the set of lines displayed was constant. Hence, if the initial lines they selected were shorter than the mean of the line display they would pick shorter and shorter lines each time the display updated. This possibility was tested by using a line display which did not adapt to the responses given (Control Experiment 1d).

The shortening may also have been observed because perceived motion shortens with repetition, as found in vision for one-way (Nakajima & Sakaguchi, 2016) and back-and-forth

(Sinico et al., 2009) motion. To examine this possibility, we tested if repeated judgments of an imagined line or of a static block applied to the forearm shortened with repeated judgments (Control

Experiment 2).

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4.5 Control experiments

4.5.1 Control experiment 1a: Extent Judgment with Duration of Continuous Brushing Matched to that of the Spatial Gap stimulus

The Spatial Gap motion (or the control stimulus with two pairs of brushes) travels the 24 and 30 cm extents at speeds (27 and 22 cm/s) that produce perceived shortening of the motion path based on previous studies (Whitsel et al., 1986). However, previous studies investigating perceived tactile motion extent used much shorter distances, so this experiment was necessary to test if motion speed could explain the shortening observed for 24 and 30 cm test motions in Experiment 1.

Methods

Eight people (5F, 3M, aged 25-32), all right-handed participated in this experiment. The experimental set-up here was as in Experiment 1, except only one pair of brushes was used and there was no occluder. Participants attended on one day. The session consisted of 64 judgments of brush traverse length which was equally counterbalanced for 24 cm and 30 cm lengths in proximal and distal directions. The brush moved at 27 cm/s for the 24 cm motion and at 22 cm/s for the 30 cm motion. The brush sweeps in between judgments were the minimum number necessary to get to the start of the next test motion. The randomization of test motions was in blocks of 16. Trials were grouped into blocks of four for statistical analysis.

Results and discussion

A two-way repeated measures ANOVA showed a highly significant effect of Length (F[1,7] = 83.2, p < .001) and Block (F[7,49] = 7.5, p = .015, Greenhouse Geisser corrected). The interaction was not significant. This study shows that continuous motion that is matched to the sweep duration of

Experiment 1 is perceived to shorten with repeated judgments (Fig 4.3).

A further analysis was required between this experiment and the short block of the Spatial

Gap condition in Study 1 to determine if the effect size was similar. As a between groups analysis was necessary the test motions were pooled together to increase statistical power to detect a

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difference if it exists. The difference for each experiment between the first four trials and last four trials was computed. A t-test between experiments on this difference between blocks for Spatial

Gap (4.2 ± 3.1 (SD) cm) and time-matched continuous sweep (4.4 ± 4.2 cm) was non-significant (p

= .93). This suggests that the fragmentation of motion in Study 1 had no effect on the shortening that occurs with repeated judgments. However, my experiment was unable to differentiate if the shortening observed in fast continuous and fragmented motion results from different mechanisms.

Figure 4.3. Perceived extent of tactile motion judgments in three different control experiments. Dotted horizontal lines in each figure indicate the 24 (unfilled circles) and 30 cm (filled circles) test motion lengths. Significant shortening was observed with Block for 15 cm/s (p = .017, Control Experiment 1b) and time- matched (p = .015, Control Experiment 1a) control experiments but not for the 5 cm/s control experiment (p = .386, Control Experiment 1c).

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4.5.2 Control experiment 1b: Continuous brushing tactile extent

Given that as much as four cm shortening was observed for test motion stimuli that were on the edge of the range previously thought to be judged veridically (Whitsel et al., 1986) it was of interest to test if a slower speed could be used as control. We wanted to know how close the judgments were to the traversed distance and if there were any time order effects. We used 24 cm and 30 cm test motions at 15 cm/s.

Methods

Eight people (5F, 3M, aged 25-42), all right-handed, participated in the experiment. Participants picked the line that they felt matched the distance traversed by the test motion. Participants received

64 test motions: 16 test motions at 15 cm/s of each combination of Length (24 cm, 30 cm) and

Direction (Proximal, Distal). The randomisation of test motions was in blocks of 16. Trials were grouped into blocks of four for statistical analysis.

Results and discussion

A two-way ANOVA showed a significant shortening of perceived length with Block (F[7.56] = 5.6, p = .017, Greenhouse Geisser corrected; Fig 4.3), with pairwise comparison showing the first Block

(25.4 [21.9,28.7] cm) was not significantly different (p = .899) from the last Block (21.8 [17.9,25.8] cm). A highly significant main effect of Length was also observed (F[1,8] = 43.1, p <.001). The interaction was non-significant. This study suggests that the perceived traverse length of a tactile motion stimulus of moderate speed reduces with repeated presentation.

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4.5.3 Control experiment 1c: Low speed

Given that substantial shortening was observed at 15 cm/s it is plausible that the speed-dependence of tactile motion extent perception also varies by the extent used. One possibility is that at the extents used here (24, 30 cm) the speed range over which they are perceived veridically is much lower than for shorter extents. This experiment asked if a lower speed than the previous experiment was unaffected.

Methods

Eight people (4F, 4M, aged 21-32), all right-handed participated in the experiment. The methods were as in the previous experiment, except that all test motions (24 cm and 30 cm) were at 5 cm/s.

The session consisted of 64 judgments of brush traverse length which was equally counterbalanced for 24 cm and 30 cm lengths in proximal and distal directions.

Results and discussion

As shown in Figure 4.3, a two-way repeated measures ANOVA showed a significant effect of

Length (F[1,5] = 32.9, p = .002) but no effect of Block (F[7,155] = 1.1, p = .386).

To test if perceived extent differed for the different speeds of these three control experiments further analysis was performed. For each experiment the test motions were pooled and the difference between the first and last blocks computed. T-tests were performed for each combination, with a Bonferroni correct alpha level of 0.017, none of which were significant (1a vs.

1b, p = .68; 1b vs. 1c, p = .46; 1a vs. 1c, p = .24). This suggests that the effects observed were dependent on repeated tactile motion and not the speed itself.

These control experiments using continuous tactile motion at different speeds uncovered a time- order dependent shortening bias. However, the possibility remained that the shortening with repeated judgment arose from methodological bias from the line matching display. This was tested in the next experiments.

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4.5.4 Control experiment 1d: Non-adapting display

This study tested if shortening was still observed when the display was not updated based on participant response. This was to test if adapting the display in response to the participant’s responses (i.e., shortening the mean length of lines in the display if the participant chose lines shorter than the initial mean, or increasing the mean length after longer judgments) could have caused the reported shortening of the test motion with repeated judgments.

Methods

Eight people (4F,4M, aged 21-32), all right-handed, participated in this experiment. The methods were identical to the previous experiment, the only changes being the test motion velocities and the line display. The test motions were time-matched to Experiment 1 (i.e. 24 cm test motion was at 27 cm/s and the 30 cm test motion at 22 cm/s), but only 32 repeats total were done. The display used for judgment of both the 24 cm and 30 cm test motions had 12 lines: the middle line of the display was 25 cm, with the other lines between 10 and 40 cm. The distribution of lines displayed did not adapt in response to the participant's responses.

Results and discussion

A two-way repeated measures ANOVA showed a highly significant effect of Length (F[1,7] = 37.1, p <.001) and a significant effect of Block (F[3,21] = 10.4, p <.001; Fig 4.4). The interaction was non-significant. The degree of shortening observed here (2.8 cm) appeared to be similar to that in the time-matched control of Control Experiment 1a (2.9 cm, difference between blocks 1 and 4).

Therefore the observed shortening with repeated judgments is unlikely to represent a bias introduced by the adaptive line-matching methodology.

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Figure 4.4. Perceived extent of tactile motion in Control Experiment 1d. The line-matching display was constant. A highly significant effect of Block was found (p < .001). Horizontal dotted lines indicate 24 (unfilled circles) and 30 cm (filled circles) lengths.

This experiment has shown that the perceived extent of continuous tactile motion shortens with successive judgments. Importantly it has confirmed that the shortening was not a methodological bias resulting from the adapting display. One possibility is that a line-matching display always causes shortening with time. An additional consideration is that although participants judged tactile motion extent, the sound from the slider could be used to estimate the distance moved. Additional experiments were required to test if the shortening of perceived extent always occurs for a line-matching display, if it was specific to tactile motion, or if it was a bias resulting from sound.

A possible interpretation of the apparent contraction of the extent of tactile motion over time was that it was a feature of repeated judgments of extent. Three experiments were conducted to test if the shortening with repeated judgments was dependent on the property being judged. In the first experiment, participants repeatedly judged the extent of an imagined 25-cm line and in the second, they repeatedly judged the extent of a 25-cm block applied to the skin (static touch stimulus). In the third experiment, participants judged extent from the sound accompanying motion of the brush apparatus.

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4.5.5 Control experiment 2a: Imagined line matching

This control experiment was designed to test if time-order effects in line matching are independent of the stimulus.

Methods

Eight people (2F, 6M, aged 24-32), all right-handed, participated in the experiment. On each trial participants imagined a 25-cm line. The participants then picked the line that they felt was closest in length to their imagined line from a display set of seven lines on the monitor in front of them. The display set had an initial mean length of 25 cm and adapted to participants’ responses. A 5-s rest was given between trials. Each participant completed 32 trials.

Results and discussion

Responses were averaged in blocks of four trials before analysis. A one-way repeated measures

ANOVA showed no significant effect of Block (F[7,49] = 0.18, p = .98, Greenhouse Geisser corrected; Fig 4.5). This study demonstrates repeated estimates of a specified extent are stable and veridical. Additionally, it shows that an adaptive line display does not in itself lead to time order effects with repeated judgments.

4.5.6 Control experiment 2b: 25-cm block line matching

This control experiment was designed to test if the line matched to a constant static tactile stimulus changed with repeated judgments.

Methods

Eight people (3F, 5M, aged 24-32), all right-handed participated in the experiment. On each trial a

25-cm long aluminium block (5 cm wide, 326 g) was placed on the participant’s forearm. The placement was randomly varied a few cm trial-to-trial, but was overall centred on the forearm. On each trial participants picked the line that they felt was closest in length to the block from an adaptive display set of seven lines. A 5-s rest was given between trials. Each participant completed

32 trials.

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IMAGINE STATIC TOUCH

Figure 4.5. Perceived extent judgments for constant non-moving stimuli in two separate experiments. In Control experiment 2a when participants imagined a 25-cm line on every trial and then judged its length, there was no shortening with Block (p = .98). In Control Experiment 2b, a 25-cm aluminium block was applied to the arm on every trial, its perceived extent was also unchanged by Block (p = .87). Horizontal dotted line indicates 25 cm.

Results and discussion

Responses were averaged in blocks of four prior to analysis. A one-way repeated measures

ANOVA showed no significant effect of Block (F[7,49] = 0.16, p = .87,Greenhouse Geisser corrected; Fig 4.5). This study showed that the previously observed time order effects for a tactile stimulus only occur when its extent is defined by motion.

4.5.7 Control experiment 2c: Judging length from sound

As the slider used to carry the brushes produced sound, this study tested if participants could use the sound of the motion to judge its traverse length, and if judgments using this cue shorten with repeated responses.

Methods

Eight people (4F, 4M, 25-32), all right-handed participated in the experiment. In this experiment the brush was not applied to the arm (i.e participants could only use the sound to judge the length, Fig

4.6A). Participants heard the sound of eight test motions at 15 cm/s of each combination of Length

(24 cm, 30 cm) for a total of 32 judgments. The direction of motion was randomly counterbalanced.

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Figure 4.6. Judgments of the perceived extent of a moving sound. A. Participants judged the distance of a moving sound. B. Participants were easily able to differentiate the two lengths. There was a highly significant effect of length (p < .001) and no effect of Block. Horizontal dotted lines indicate 24 (unfilled circles) and 30 cm (filled circles) lengths.

Results and discussion

Responses were averaged into blocks of four prior to analysis. A two-way repeated measures

ANOVA showed a highly significant effect of Length (F[1,7] = 81.6, p <.001) but the effect of

Block was not significant (F[3,21] = 1.9, p = .146; Fig 4.6B). Although there appeared to be a slight shortening with Block this shortening was mostly due to one individual outlier. This experiment showed that participants can apparently accurately judge motion distance using only auditory information. Further, auditory inputs are not the source of the previously observed tactile motion shortening bias.

Discussion for Control experiment 2

These experiments have found that the observed shortening bias is specific to a tactile motion stimulus. Critically, no shortening was observed in the perceived extent of a 25-cm imagined line, a

25-cm aluminium block placed on the forearm, or of a moving sound stimulus.

Control experiment 2c did not determine if participants tracked the brush movement by localizing the sound or if they judged distance from the tone duration, both of which have been found to influence spatial representations of the body when paired with tactile stimulation (Tajadura-Jiménez et al., 2017; Tajadura-Jimenez et al., 2012). Although this study found that tactile motion extent

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judgments were confounded with the sound of the brush/motor moving, it was not practical to block out the sound of the slider which was in the range of 60-70 dB when measured adjacent to a participant’s ear. Sounds emanated from the stationary motor and also the moving parts of the apparatus (slider). When the motor was uncoupled from the slider, the sound reduced to 30-40 dB, suggesting that a moving sound source was available to contribute to participants' judgments.

However, some participants had participated in previous studies, so it is entirely plausible that they had learned a rule of thumb for how far the brush should move for a given time. With only eight participants in total it is not possible to compare the results of naïve and trained participants within these data.

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4.5.8 Control experiment 3: Effect of repeated stimulus presentation without repeated judgments of extent

Having established that the bias was constrained to repeated judgments of a tactile motion stimulus the next step was to test if it required the repeated presentation of the stimulus or the repeated coupling of stimulus and response.

Methods

Eight people (4F, 4M, 24-32) participated in the experiment. Participants received 16 test motions at 15 cm/s of each combination of Length (24 cm, 30 cm) and Direction (Proximal, Distal).

Participants only made line judgments for the first eight and last eight test motions of the 64 total test motions. The randomization of test motion was in blocks of eight. The line display was extinguished for the intervening motions. Although participants did not judge these motions, they were instructed to direct their attention to the feeling of the brush during them. They were specifically instructed not to attend to the traverse length of the brush on these trials.

Results and discussion

The mean was calculated for each of the first four trials and the last four trials of each length. A two-way repeated measures ANOVA showed a significant effect of Block (F[1,7] = 9.8, p = .017) and a highly significant effect of Length (F[1,7] = 50.6, p <.001; Fig 4.7). The interaction was non- significant. Perceived length reduced on average by 1.6 cm from the first to last block.

This experiment was inconclusive, as only mild shortening was observed when there were many stimuli before judgments. A between subjects comparison of the difference between blocks in this experiment and in control experiment 1b (also 15 cm/s motion) was performed. The t-test between this study (1.56 ± 1.4 cm (SD)) and the 15 cm/s study (3.50 ± 4.3 cm (SD)) was not significant (p = .25). However, as attention was not measured, we still cannot be certain of how the stimulus, attention, and making judgments influence perceived motion extent.

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Figure 4.7. Group mean data (±95% CIs) of perceived extent judgments of a 15 cm/s tactile motion stimulus for Control Experiment 3. In this study there were 64 test motions, but responses were only made for the first and last eight motions (24 cm, unfilled circles, 30 cm, filled circles). There was a significant difference between blocks (p = .017). Horizontal dotted lines indicate the 24 and 30 cm test motion lengths.

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4.6 Discussion

The experiments in this chapter were designed to test the effects on perceived extent of changing the fragmentation and velocity of a motion stimulus which wrapped around the arm. Introducing an instantly skipped spatial gap in motion resulted in substantial shortening of perceived extent over time. However, a similar effect was obtained when the sweep duration was matched with un- fragmented motion. This suggests that perceived extent could be derived from, or influenced by sweep duration. Unexpectedly, I found that the perceived extent of a continuous tactile motion does not remain stable but reduces with repeated judgments. As a result of this unexpected finding much effort was put into finding the source of this bias. This proved difficult, with many control studies performed (which limited the sample size in each due to time constraints) with no definitive conclusion reached.

The observation that participants could judge length from the sound of the apparatus that moved the brushes raised an intriguing possibility. Did participants in the previous experiments not make use of auditory information when judging motion extent, or was it integrated to stabilise against an even larger effect of tactile motion? If participants did not use the auditory information in previous experiments then removing it should not influence tactile motion perception. If participants did use the auditory information in previous experiments, then if the auditory component of the stimulus was removed a larger spatial bias might be observed. This possibility was not further tested.

Although perceived extent similarly shortened for Spatial Gap and a time-matched continuous sweep, this shortening may have been via different mechanisms in the two stimulus patterns. The spatial gap perception could be explained by a preference for perception to represent motion at constant or smooth velocity. This could be achieved by the signal of global long-range motion neurons connecting to local position neurons (Nguyen et al., 2016). To test if this hypothesis explains perception of a fragmented motion stimulus, a study could use longer crossing time than predicted for an object moving at a constant velocity. If a longer crossing time of the gap led to a

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spatial dilation, it would be consistent with the constant velocity model, as well as the probabilistic model of Wiemer et al. (2000) and observations of a constancy for velocity (Collyer, 1976).

Whereas if it did not it would be more consistent with the Bayesian model of Goldreich (2007). If the former were observed, these possibilities could be differentiated by shifting the position of the spatial gap, earlier or later into the motion. If constant velocity is adhered to then the path shrinkage may be greatest if the gap is later in the motion, after the velocity context has been set (Hidaka et al., 2009)

Different hypotheses have been put forward for the mechanisms through which velocity influences perceived extent, from low-level somatosensory processes to higher level cognitive processes. Whitsel et al. (1986) propose that persistent firing of slowly adapting afferents could lead to spatial distortions, although it is unclear if these could lead to distortions as substantial as those observed. At higher levels a possibility is that there is uncertainty about the motion stimulus in which case it might be served by a Bayesian model as in the cutaneous rabbit effect (Goldreich,

2007). Further work is required to tease out the neural mechanisms of the processing of fragmented tactile motion.

The perceived shortening of the tactile motion stimulus with repeated judgments was a novel finding in touch. A similar effect has been observed in vision, whereby repeated presentations of a movement pattern result in a slowing of its perceived speed (Thompson, 1981). If the perceived speed reduces, then the perceived extent of the motion could reduce, as long as perceived duration does not reduce. This shortening could be explained by contrast adaptation effects. Adaptation, both peripherally and centrally, could lead to a reduction in the perceived contrast of the motion stimulus

(i.e. more difficult to detect and localize the moving object). In line with this idea, a moving object with less contrast is perceived as having moved a shorter distance (Anstis, 2003). However, this seems an unlikely reason as the perceived distance slightly increased after the conditioning period between short and top-up conditioning. Interestingly, even when contrast (intensity) adaptation is controlled for, visual studies suggest that the perceived extent of an oscillating object shortens

(Cavanagh & Anstis, 2013; Sinico et al., 2009). In touch, motion adaptation on the fingers reduces

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perceived speed, independent of the motion direction (McIntyre et al., 2012).Therefore, we could expect that adaptation with back-and-forth or only single direction motion would result in reduced tactile extent perception. A further possibility is that motion adaptation is speed dependent, in that adaptation at one speed might not cause changes to the perception of a different speed, however there is no evidence of speed tuning in touch (McIntyre et al., 2012). Future work could consider tactile extent adaptation (Calzolari et al., 2017) or duration adaptation (Pariyadath & Eagleman,

2012).

Macauda et al. (2017) raise the possibility that shortening could arise if the limb landmarks act as boundaries at which the motion stimuli are perceived to turn around. However, this was not consistent with my results, which would have seen differences in the amount of path shortening for the 24 and 30 cm test motions, given their endpoints were different in regards to the elbow and wrist landmarks. Given that the shortening seemed invariant of the joints, it is possible that tactile motion is influencing the brain regions which represent limb length. This possibility was explored in the next chapter.

There were multiple findings from this chapter concerning the perception of tactile motion.

The initial experiments suggest that the perceived extent of continuous and discontinuous motion is similar, as long as their duration is similar. This differed from expectations based previous findings, which suggest that discontinuous motion as in Spatial Gap influences perceived location (Nguyen et al., 2016; Seizova-Cajic & Taylor, 2014). My experiments also identified a shortening of perceived extent of repeatedly presented motion. Control experiments confirmed that the observed biases were dependent on tactile motion and were not a methodological bias from using an adaptive line display.

It is not clear why there was perceived shortening of the motion path with repeated judgments.

Possible explanations include the influence of response-dependence, attention, extent or duration adaptation and/or Bayesian mechanisms. The experiment testing if the shortening was dependent on repeated responses was inconclusive as attention was not measured.

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Chapter 5: Body Metrics

5.1 Summary

This chapter investigated if the perceived extent of the forearm is modulated by tactile motion on the forearm. Three studies were performed. The first study took advantage of the perceived shortening of tactile motion found in the previous chapter. If this effect shortens the skin-based representation of the forearm it could shorten perceived forearm length (structural representation).

However, the study found no influence of tactile motion on perceived forearm length. One possibility was that tactile motion does not influence skin-based representations or that skin-based representations do not feed into structural representations. An alternative interpretation was that tactile motion would only result in a perceived shortening of the forearm if the tactile motion itself was judged to shorten during the same time period. This, as described in section 4.5.8, seemed contingent on repeated responses. The second study explored this hypothesis by interleaving judgments of tactile motion extent and forearm length. A substantial shortening of perceived forearm length was observed. The third study tested if this shortening was specific to the brushed forearm, or if the shortening of perceived tactile motion extent caused a response bias for all spatial judgments. Whilst the study had methodological difficulties, it suggested that perceived shortening was specific to the brushed arm. Together, these results suggest that in certain circumstances spatial biases observed for tactile motion can extend to structural representations of the body.

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5.2 Introduction

The previous chapter investigated perceived tactile motion extent; this chapter investigates the possible influence of the tactile percept on perceived limb length. Information about the relations between different parts of our body, and the size and shape of the individual parts seems important for knowing what actions our body affords us within our environment and how we can achieve that action. For instance, when reaching into a cookie jar, one might want to know if their hand will fit through the opening and if their arm is long enough to reach in and grasp the cookie. There are multiple ways that these body metrics could come to be represented.

Craske et al. (1984) proposed that cutaneous receptors contribute to the representation of body metrics:

One possibility that we want to raise here is that the surface of the skin contributes a map

of the space occupied by a limb. This, in conjunction with information about joint angle,

could serve as a basis for judgments about how far away from the body a given point on a

limb may be. (p. 308)

In their study of this hypothesis they used a tactile- discordance of touching one hand to the other arm (i.e. they used an apparatus which displaced the touch directed to one location to a different location on the touched arm). If the touches perceptually fused to the same location, as in previous studies using two stimuli at different locations (Von Békésy, 1959), then could this change the perceived forearm length? This intervention resulted in changes to perceived limb length, as measured from participant's judgments of a visual stimulus in relation to limb landmarks. However,

Gildersleeve (2012) found the limb shortening was not reproducible, potentially as the initial study did not explicitly test limb length.

Despite this, other studies seem to show that somatosensory information is important for representing the size and shape of the limbs, as shown by surgical elongation of a limb (Cimmino et al., 2013), anaesthesia (Gandevia & Phegan, 1999), or from distortions relating to the unequal

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allocation of cortical space of different body parts in somatosensory areas (Longo & Morcom,

2016; Weber, 1834). The connection of skin-based representations and body metrics is apparent in a study in which the upper-arm of a patient was surgically elongated (Cimmino et al., 2013). The patient showed changes in basic touch sensation (sensitivity and two-point discrimination) as well as rapid changes to the perceived body image. Analogous findings were made in a study where leg length was surgically modified, whereby a body schema test showed that the cognitive representation of the body had updated to match the elongation (Di Russo et al., 2006). Although the above studies are not conclusive, limb segments are diffusely segregated within the skin-based representation of S1 (Sur et al., 1980) which modelling suggests arises from experience-dependent plasticity (Stafford & Wilson, 2007), thus it seems plausible that skin stimulation could change perceived limb length.

In subtle contrast, Longo and Haggard (2010) suggest that there is no single receptor which directly contributes to perceived limb length. One of the first studies which supports this hypothesis is Gross et al. (1974), who found that the perceived length between the elbow and fingers reduced

(as measured implicitly by pointing to these landmarks) when vision of the limb was removed. This hypothesis is further highlighted by the influence of multisensory inputs on perceived limb length

(De Vignemont et al., 2005; Tajadura-Jiménez et al., 2017; Taylor-Clarke et al., 2004). Given these effects of multisensory integration, it seems probable that higher-order structural representations of the body are used to store perceived limb length (Longo, 2017). For instance, the cerebellum contains discontinuities consistent with the limb boundaries (Stoodley & Schmahmann, 2009). One possibility, relevant to this thesis, is that information from skin-based representations feeds into these structural representations. If this is so we would also expect that changes to skin-based representations result in changes to structural representations, but perhaps to a lesser degree than if only skin input was used to represent the limbs.

A third possibility is that body metrics are not represented, or even learnt. Rather than using knowledge of limb segments length to control a reaching movement (Ivanenko et al., 2011) one might learn associations between joint angles and where the endpoint of the limb is in space (Loeb,

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1999). Psychophysical evidence does back this viewpoint, with judgments of limb endpoint position better than those of joint angle (Soechting & Ross, 1984). This suggests that either the associations

(of joint angles and limb endpoint) are stored in a body representation or that body metrics themselves are stored in a representation.

In the following studies, we used judgment of forearm length as the distance between the elbow and wrist landmarks as we were interested in measuring changes to structural representations.

In contrast, if extent was defined by the touch at the wrist and a touch at the elbow, participants may have only accessed a skin-based representation to make the judgment. This distinction between skin-based and structural representations of the limbs has been previously identified by others in behavioural studies and in lesion patients (e.g. Longo et al., 2015; Sirigu et al., 1991). Within structural representations, another difficulty is that we also have a concept of what a ‘normal’ limb looks like, and might defer to this when making perceived limb length judgments. Using line matching, as in this chapter, rather than image/template matching can help overcome these problems (Longo, 2017).

In the previous chapter it was found that the perceived extent of a tactile motion stimulus, which wrapped around the forearm, shortened with successive judgments. If the tactile motion stimulus influences skin-based representations it might also influence structural representations, similar to other spatial illusions which have been shown to influence both tactile extent and limb length judgments (De Vignemont et al., 2005; Longo et al., 2009; Taylor-Clarke et al., 2004).

Although, it is unclear from these studies if the updating of skin-based and structural representation are interdependent. The objective of this chapter was to test if tactile motion elicited changes in perceived limb length.

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5.3 Materials and methods

The experimental set-up to provide tactile stimulation to the arm and to allow judgments of tactile motion extent and forearm length was similar across experiments.

Stimulation with Wrap-Around Brush

The wrap-around brush set-up was the same as in Chapter 4 (Fig 4.1). Briefly, participants were seated with their left forearm held neutral between supination and pronation and supported on an armrest placed perpendicular to the seat back. The armrest only contacted the arm at the elbow and at the hand such that most of the forearm was in mid-air. Stimulation of the forearm surface was achieved with channel strip brushes (0.4 cm thick, 0.007” Nylon fill) that were curved so that they maintained contact around the circumference of the forearm.

The wrap-around stimulation was achieved using a pair of brushes, which hung touching each side of the arm. The brushes were mounted on a carrier that was driven along a slider by a stepper motor, controlled using a custom program (Labview).

Extent Judgment through Line Matching

Participants faced a screen that displayed lines of varying lengths, each with a hexadecimal value adjacent to it. Lines were displayed horizontally on the screen and were ordered randomly. For each extent judgment, a new display was provided with new random hexadecimal values. To choose a line from the display, the participant verbally reported the hexadecimal value that was adjacent to the line.

For judgments of forearm length participants were instructed to select the line that they felt was the closest match to their forearm length. The experimenter explained and demonstrated to them that this meant the straight-line distance between the elbow-crease and the wrist-crease.

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5.4 Experimental studies

The specific methods, results, and brief discussion for each experiment are below.

5.4.1 Preliminary experiment 1: Effect of tactile motion on perceived forearm length

This experiment was designed to test if the time-order effects, in which the perceived tactile traverse length decreased, will also be observed for perceived forearm length.

Methods

Eight people (4F, 4M, aged 22-32), all right-handed, participated in the experiment. Participants made forearm length judgments (Fig 5.1A) after a tone that was given after each test motion, some of which were 24 cm and others, 30 cm. Test motions were at 15 cm/s. A total of 64 judgments were made. The line display for this experiment had seven lines (Fig 4.1B), and periodically adapted to the mean of the previous six responses (that is it adapted after the first six trials, then after the second six trials and so on). The mean of the line display was initially centered on the test motion used.

Results and discussion

Responses were averaged into blocks of four before analysis. A two-way repeated measures

ANOVA showed that there was an effect of prior test motion (F[1,7] = 6.3, p = .04). There was no effect of Block (F[7,49] = 2.4, p = .147, Greenhouse Geisser corrected; Fig 5.1B). The interaction was near-significant (F[7,49] = 2.1, p = .063). The mean perceived forearm length was 25.9 (CI:

21.6-30.3) cm for the 30-cm test motion and 23.9 (CI: 18.9-29.1) cm for the 24-cm test motion.

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In contrast to tactile motion extent judgments for a 15 cm/s motion, the perceived forearm length was not changed with repeated tactile motions and judgments. It was interesting to note that perceived forearm length was modulated by the tactile motion that preceded each judgment, with 30 cm motions leading to longer judgments than 24 cm motions. However, as the display was initially centred at the test motion length, the effect of test motion length could have been a display-driven response bias. This methodological confound was removed in the subsequent experiments.

Figure 5.1. Forearm length judgment task and results. A. Judgments were of perceived forearm length (i.e. distance between elbow and wrist). B. Group mean data (±95 % CIs) of perceived forearm length judgments in Preliminary Experiment 1. Judgments made when the preceding test motion was 24 cm (unfilled circles) or 30 cm (filled circles) were significantly different (p = .04). However, with prolonged exposure (operationalized as Block order) the difference between the test lengths was different with Block; as shown by the near-significant Length*Block interaction (p = .06). The dashed horizontal lines indicate the 24 and 30 cm test motion lengths.

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5.4.2 Preliminary experiment 2: Intermingled judgments of tactile motion extent and forearm length

One explanation as to why no time-order effect was observed in Preliminary experiment 1 is the apparent response dependence of the shortening observed for the tactile motion stimulus (4.5.8).

That is, the perceived extent of the tactile motion appeared less affected by exposure to the brushing stimulus without repeated judgments than when repeated judgments were made. If perceived shortening of a tactile motion stimulus drives perceived shortening of forearm length, a possibility is that one must be aware (i.e. pay attention to) of the shortening of the tactile motion. To allow for this possibility, the current study intermingled judgments of perceived extent of tactile motion with forearm length judgments.

Methods

Seven people (4M, 3F, aged 25-61), all right-handed, took part in the study. In this study judgments of forearm length and tactile motion extent were intermingled. The constant line display (Fig 4.1C) was used. A total of 64 judgments were made. Forearm length judgments were made for trials 1-4,

21-24, 41-44, and 61-64. Tactile motion extent judgments were made for trials 5-20, 25-40, and 45-

60. Brush motions were equally counterbalanced between 24 and 30 cm length in both directions

(proximal, distal). Brush motions were at 40 cm/s. The judgments were grouped into blocks of four for analysis.

Results and discussion

One-way repeated measures ANOVA on forearm length showed a significant effect of Block

(F[3,18] = 3.8,p = .03). This result is depicted in Figure 5.2, showing that perceived forearm length decreased with Block, from 28.5 (22.3,34.7) cm to 25.0 (17.5, 32.5) cm. No pairwise comparisons were significant.

To test if changes to forearm length were related to perceived tactile motion extent, the change was calculated for each participant between their first and last blocks. The 24 and 30 cm tactile motion extents were combined to increase power. As an exploratory measure a simple linear regression was

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done of change in perceived forearm length on change in perceived tactile length. A significant regression coefficient was found (F[1,5] = 67.1,p = .025), with an r2 of 0.67.

Figure 5.2. A. Group mean data for Preliminary Experiment 2 (±95% CIs) of perceived forearm length (unfilled triangles), and tactile motion extent (24 cm, unfilled circles; 30 cm, filled circles). The dashed horizontal lines indicate the 24 and 30 cm test motion lengths. B. Regression of change in perceived Forearm Length (vertical axis) on change in perceived tactile motion extent (horizontal axis).

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5.4.3 Experiment 1: Perceived extent of forearm length: Effect of response dependent tactile motion path shrinkage

Following the findings of the previous study, one possibility was that the spatial distortion was a general response bias arising from the perceived shortening of the tactile motion. In this study, the lengths of the brushed and un-brushed forearms were both judged. If it was not a general response bias then shortening of the perceived length of only the brushed forearm should occur.

Methods

Eight people (3M, 5F, aged 22-33), all right-handed participated in this study. As before, tactile motion was used. The non-adapting 12-line display was used. Motion distances of 24 and 30 cm were used, which were randomly given (direction was also randomised). Judgments consisted of two blocks of 68 trials, which were separated by a 20-30-minute break. Within each block participants judged forearm length for trials 1-4, 17-20, 33-36, 49-52, and 65-68; and tactile motion extent for trials 5-16, 21-32, 37-48, and 53-64. The critical difference between the blocks was that in one the forearm length judgments were for the left arm (Brushed arm) and in the other they were for the right arm (Unbrushed arm). The order of the blocks was equally counter-balanced between participants. Due to mechanical problems with the stepper motor used in the previous studies, a new motor was used in this study (Excitron X57-40M). This motor was prone to miss-stepping on approximately one in every 20 trials, so a substantial number of trials were not completed (one motor event sometimes led to disruption of more than one trial), as the experimenter had to manually move the slider to the position for the next motion.

Results

A two-way repeated measures ANOVA showed that there was a significant effect of Block (F[4,28]

= 2.79,p = .046; Fig 5.3). There was no main effect of Arm (F[1,7] = 0.25,p = .63), however, the

Block*Arm interaction was significant (F[4,28] = 3.39,p = .022). Separate one-way repeated measures ANOVA on brushed arm (F[4,28] = 7.1,p<.001) and non-brushed arm (F[4,28] = 0.32,p =

.875) showed that this effect of block was only in brushed arm. The pairwise comparison of the first

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block (27.0 [23.1,30.8] cm) and fifth block (23.3 [19.2,27.3] cm) showed a highly significant shortening (p = .001).

Figure 5.3. Perceived extent of the forearm in Experiment 1 (group mean data ± 95% Cis). The were no effects of Block or Arm. However, the interaction was significant (p = .022), showing that only the perceived length brushed arm (filled circles) shortened with Block, whereas the un-brushed arm (unfilled circles) did not.

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5.5 Discussion

This chapter set out to investigate if structural representations of limb length were modulated by a tactile motion stimulus. The previous chapter had shown that perceived length of a tactile motion stimulus shortens with repeated presentation and judgment of the stimulus. We expected that if this stimulation resulted in changes to skin-based representations and if skin-based representations influence structural representations, that this stimulation should shorten perceived forearm length.

The first study showed that perceived forearm length was dependent on the length of the tactile motion that was given before the judgment. However, as the line display was initially centred on this test motion extent, it may have been a methodological bias. The first study also showed that perceived forearm length did not shorten with repeated presentation of tactile motion. One reason for this may have been that perceived tactile motion extent might only shorten if it is repeatedly judged. As no judgments of tactile extent were included, we could not necessarily expect tactile motion dependent shortening of perceived forearm length. In the second study, participants judged perceived motion extent and forearm length within the same block of trials. With this change to study design, perceived forearm length shortened by ~ 4 cm (Aim 3). In the final study, we included a control condition to ensure that the perceived shortening was constrained to the stimulated location. In this case, only the brushed forearm was perceived to shorten.

One assumption of the findings of the second and third experiments of this chapter

(Preliminary Experiment 2 and Experiment 1) was that the tactile motion influenced skin-based representations, when equally it could have directly modulated the structural representation. Tactile motion could directly influence structural representations if these representations simply contain the distance between the landmarks. If tactile motion on the forearm is perceived to traverse these two landmarks (elbow, wrist) in less time than expected, it is possible that the perceived distance between them shrinks. In these studies, this potential shortening came as perceived extent of tactile motion shortened with repeated judgments. Alternatively, tactile motion may have influenced skin- based representations of the body, if these are used to update structural representations this would

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have led to shortening. However, it is unclear how repeated tactile motion would lead to shrinkage of the length skin-based representation of the forearm. These experiments did not pursue these possibilities any further. The relation between skin-based and structural representations is potentially difficult to measure, as different instructions in regards to body representations can give the same result. For instance, when judging the distance between tactile stimuli applied to the hand, the same response is given regardless of whether participants make reports based on what they know or what they feel (Tamè et al., 2017).

In the most well-known illusion to influence perceived limb length, the Pinocchio effect, the tactile-proprioceptive stimulus also changes perceived tactile extent. To elicit this effect, the participant holds their nose with one hand, whilst the elbow flexors of that arm are vibrated.

Vibrating the muscle activates muscle spindles (proprioceptors) giving the illusion that the hand is moving away from the body (Goodwin, 1972; Taylor et al., 2017). The perceived movement of the hand, which is in contact with nose, resulted in perceived elongation of the nose (Lackner, 1988).

De Vignemont et al. (2005) showed that the Pinocchio illusion (applied to a finger) led to elongation of both the perceived limb length and a tactile extent presented within that limb. This observation, in conjunction with findings when a limb is surgically modified (Cimmino et al., 2013) suggest that skin-based and structural representations are in some way linked. If true, and if changes to skin-based representations result in changes to structural representations then this is in line with the hypothesis of Craske et al. (1984), that cutaneous inputs contribute to perceived limb length.

Further work is required to confirm this hypothesis.

A methodological problem encountered in Experiment 1 was that there were some trials in which the motor stalled and did not complete the motion. When this occurred it was noisy which could have startled participants. Touch that is perceived as threatening can influence how it is processed, for instance being felt closer to the body (Ferri et al., 2015; Haan et al., 2016; Taffou &

Viaud-Delmon, 2014). In Experiment 1, no judgment was made on 5% of the forearm trials in comparison to less than 1% for Preliminary Experiment 2. Further, the left forearm length was perceived as longer than the right forearm length at the start of Experiment 1. Given that shortening

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was observed in Preliminary Experiment 2 it seems unlikely that these events of the motor influenced the perceived forearm length in Experiment 1. These technical difficulties did however limit the number of subjects in Experiment 1, which in turn limited the power to test the hypotheses associated with the experiment.

In conclusion, this chapter has provided evidence that the perceived length of the forearm can be altered using tactile motion. This shortening seemed to be dependent on perceived shrinkage of the tactile motion extent, as in the first preliminary experiment in which only forearm length was judged there was no time-order effect. In the second preliminary experiment, judgments of tactile motion extent and of forearm length were intermingled, resulting in shortening with block of the perceived forearm length. In the main experiment, the perceived length of the other arm (non- brushed) was also measured, to ensure that the effect was not simply a response bias. The perceived forearm length only shrank with block for the brushed arm and not for the non-brushed arm. Future work could differentiate if brushing directly influences structural representation or if it influences skin-based representations which could feed into structural representations.

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Chapter 6: General Discussion

This chapter summarises the findings of the studies of this thesis, their contributions to the understanding of the spatial and temporal features of tactile perception, implications for clinical populations, and possible future directions. The experiments of this thesis investigated tactile localization, how context modulates spatial tactile perception, and structural body representations.

In Chapter 2 I demonstrated how touch localization errors are minimised when uncertain. The first experiment found that they were biased toward the middle of the arm, perhaps as a result of long- standing prior experience. In the second experiment, I used different recent distributions of touch so that the middle of the forearm and the recent history had different spatial centres. Here I found that when uncertain, touch localization was biased toward the recent history of touch (Aim 1). In

Chapter 3 I tested how the context influences localization, using an artificial tactile scotoma. As in studies in vision, my results were consistent with an increase in the sensitivity of receptive fields that fall within the scotoma, which I indirectly demonstrated by showing localization errors towards the middle of the scotoma (Aim 2). In the final chapters I investigated the perceived extent of a moving tactile stimulus and of perceived forearm length. One unexpected finding was that the experiments suggested that perceived extent is unaffected by motion fragmentation (Aim 3). These experiments also found that the perceived extent of tactile motion reduces with repeated judgments.

This path length shortening was also demonstrated to modulate perceived forearm length. The following discusses the implications of these studies, connects these findings to the literature, then outlines limitations and clinical implications.

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6.1 Touch localization

In the everyday situation, the somatosensory system is challenged with fluctuations in touch pressure which can cause a touch to be difficult to localize. The experiments described in Chapter 2 increase our understanding of the stabilization of tactile location perception. The findings advanced our knowledge of touch localization, by showing it likely uses a strategy whereby the current and prior sensory inputs are flexibly weighted depending on the situation (Aim 1). In addition, the findings suggest that when uncertain, touch localization mostly relies on a small window of recent history to stabilize the percept. However, our data also seemed to show an effect of longer term tactile history that was independent of uncertainty. This observation suggests that expectations built from multiple priors influence tactile localization, in agreement with the hypothesis of short and long term priors (Series & Seitz, 2013). Priors in touch represent an interesting avenue for future research, to test if and how they influence the perceived location of touch.

When touch location was uncertain, my results were most consistent with the use of a small window of the prior history to aid in localization. A possible mechanism is serial dependence, whereby the most recent stimulus locations are most heavily weighted (Fischer & Whitney, 2014;

Medina & Duckett, 2017). While one study suggested that serial dependence did not operate for tactile localization in healthy individuals, this was only tested using strong stimuli (100g, Medina &

Rapp, 2014). However, two individuals in the same study who had somatosensory damage, showed serial dependence, possibly as a result of locational uncertainty from the reduction in available cortical space (White et al., 2010). Due to the slow time-course at which cortical reorganization takes place, it seems unlikely that S1 could represent a short-term prior. Therefore, other body representations (see 1.2.1, 1.2.7) such as those in the superior colliculus, cerebellum, and parietal areas could be responsible for these position shifts and are potential candidate locations for short- term tactile priors. The serial dependence mechanism in touch could be tested by carefully controlling the randomization of the order of test stimuli and measuring how localization is

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modulated by the previous stimulus location, as performed in visual studies of serial dependence

(Fischer & Whitney, 2014).

To assess the influence of a long term prior on localization, a possibility is to measure the naturally occurring prior statistics of touch on the skin. Studies have measured (Ingram et al., 2008) or controlled (Häger-Ross & Schieber, 2000) the natural statistics of body movements, which could inform the natural statistics of touch. However, no-one has directly measured the natural statistics of touch. If Bayesian inference is used for touch localization then we could expect it to be biased towards this prior. In touch, as we use our hands to explore the world, the prior likely peaks at the hand compared to more proximal locations along the arm. The distorted body representation of the primary somatosensory cortex, in which behaviorally relevant body parts receive more space, could contain this long-term prior. This notion is consistent with the finding that weeks of tactile stimulation that are necessary to result in cortical reorganization and changes to tactile localization

(Braun et al., 2000b; Craig, 1993). Whether there are many separately stored representations and priors remains an open question.

Even though I did characterize some of the spatial biases that arise when uncertain this was in the relatively contrived conditions of the lab environment. In our everyday lives the experience of touch is much more complex, as it is subject to modulation by other senses, our environment, and our goals. Examples of modulation include attention, inputs from other senses, body movements, and the urgency to act on the touch sensation. In Chapter 3 I attempted to account for one of these contextual influences, different spatiotemporal patterns of touch, on touch localization.

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6.2 Tactile motion perception

One challenge to tactile motion perception that can arise naturally is fragmentation. Collectively, the studies presented in Chapter 3 using an artificial tactile scotoma showed a localization bias similar to that of an artificial visual scotoma. Inwards localization biases were found for the locations bordering the scotoma (Aim 2). The direction and size of the position shifts was consistent with a mechanism in which neurons with receptive fields inside the scotoma now responded to stimuli placed outside of the scotoma. The results also showed that participants perceived the motion to be more continuous when it rapidly crossed the spatial gap. In Chapter 4 I tested if these local spatial distortions were observed for perceived tactile extent of the motion itself. Interestingly they were observed not only in the Spatial Gap condition but also when the motion sweep time of a continuous motion was matched to the Spatial Gap condition. In addition, a novel path shortening was perceived with repeated judgments. These experiments are discussed below in regards to touch localization and phenomenology, and the avenues they provide for future work.

The localization biases for touch stimuli adjacent to a tactile scotoma were most readily explainable by receptive field changes within and outside of the scotoma (Kapadia et al., 1994;

Pettet & Gilbert, 1992). A stimulus on the edge of the scotoma now activated receptive fields corresponding to the inside of the scotoma and was now felt inside the scotoma, just like in a study of finger anaesthesia (Weiss et al., 2004). Receptive field changes remain an open question for an artificial tactile scotoma. A possibility in my study, which only used motion in one plane to induce the scotoma, was that the changes in receptive field size were anisotropic (i.e. that they only changed within the motion plane). These claims would best be tested by measuring cortical receptive field geometry before and after the artificial tactile scotoma stimulation. Behaviorally this could be assessed by testing localization (or extent) on the edges that are parallel to the motion direction used to make the scotoma. Future studies could pair this paradigm with microneurography and/or brain imaging to confirm that the position shifts do correspond to changes in receptive field geometry.

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The amount of mislocalization in my tactile scotoma study was much less than observed in past studies (Nguyen et al., 2016; Seizova-Cajic & Taylor, 2014). An obvious difference is stimulus specificity, as in these previous studies the conditioning and test stimuli were the same, whereas in my study the test stimulus was independent and given at a delay. Position shifts from visual artificial scotomas have been observed to be stimulus-specific and subject to rapid decay after cessation of conditioning (Tailby & Metha, 2004). Stimulus specificity of the abridging effect could be tested using a test stimulus that contains local motion (e.g. skin stretch).

The feeling of fragmented tactile motion was modulated by the time the stimulus took to cross the spatial gap, in that more rapid crossing felt more continuous, consistent with Seizova-

Cajic and Taylor (2014). In the critical Spatial Gap condition the sensation profile was similar to the continuous brushing condition, however there was substantial inter-individual variability (similar to

Essick et al., 1992; Sherrick, 1968), suggesting that the instruction and task are important in resolving the sensory input (Sherrick, 1968; Takahashi & Kitazawa, 2017). Fragmenting motion for a given speed did not influence extent judgment any further (Aim 3). It may be that fragmentation and velocity adjust perceived extent via different mechanisms, as shown by influences of local motion (as found in fragmented motion) on global motion perception (Craig, 2003; Craig & Busey,

2003; Seizova-Cajic et al., 2014). In studies of tactile temporal order judgments (using apparent motion like stimuli) with the arms crossed, at low temporal intervals some individuals are more susceptible than others to judgment reversal. Recently, Takahashi and Kitazawa (2017), showed that differences in alpha rhythms, mostly arising in posterior parietal areas are responsible for these variations. The authors identified three regions where these alpha rhythms could interact with tactile spatiotemporal perception. These are the middle temporal area (MT, Takahashi et al., 2012), the precuneus (Jörntell et al., 2014), and parietal areas (Kitada et al., 2003). Of these regions only the parietal areas receive major inputs from S1. The perceptual resolution of the spatial gap stimulus in my studies seems to rely on spatiotemporal processing and tactile object binding. These processes respectively seem to take place in S1 (Blankenburg et al., 2006) and parietal areas (Kitada et al.,

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2003; Peelen et al., 2010), suggesting this could be a promising pathway to investigate in conjunction with attention modulation.

Interestingly, the experiments with continuous tactile motion uncovered a perceived shortening bias with repeated judgments. Given that I used back-and-forth motion, and not motion in a single direction the shortening could occur through an expectation for oscillating motion.

Exactly how this expectation for back-and-forth motion would influence perceived path length is unclear, especially given studies in vision have found perceived path shortening for back-and-forth motion (Sinico et al., 2009) as well as single motions (Nakajima & Sakaguchi, 2016). Macauda et al. (2017) propose that the shortening could occur if the boundaries of the limb are used as anchors to perceive the point at which motion reverses direction. However, as discussed earlier my studies consistently found shortening of two different test motion distances, so a framing effect seems an unlikely explanation. The possibility remains that it is an adaptation to speed (McIntyre et al.,

2012), duration, or distance (Calzolari et al., 2017).

Path shrinkage could be explainable by local adaptation, whereby the perceived touch intensity diminishes with exposure. In vision, low contrast moving objects are perceived to move less distance than higher contrast objects (Anstis, 2003). In touch the compressive effects of the

Cutaneous Rabbit Effect are more pronounced for weak stimuli (Tong et al., 2016). In the case of reduced touch motion intensity, one might be more uncertain about the position of the motion and refer to prior expectations (as in CRE - Tong et al., 2016), similar to results in static touch in

Chapter 2. To my knowledge no one has experimentally manipulated the prior expectation for speed in the tactile domain. In contrast, the manipulation of the velocity prior in vision, by exposure to over 700 high (or low) stimulus speeds, has been demonstrated to influence motion perception

(Sotiropoulos et al., 2011). Stocker and Simoncelli (2006) suggest that this velocity prior might be located in the middle temporal (MT) area, but this is subject to experimental verification. Given that area MT is also activated by continuous tactile motion (Amemiya et al., 2017) and apparent tactile motion (Takahashi et al., 2012), this represents a good candidate location to test for the neural representation of tactile velocity priors. Priors for duration or distance could also be considered.

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6.3 Structural representations

The experiments within the thesis on perceived limb length were exploratory in nature, but did produce a modest reduction of ~ 4 cm in perceived limb length (Aim 3). We did not explore if the perceived shortening of the tactile motion resulted in changes to skin-based body representations.

Therefore we cannot be certain if the modulation of structural representation was a direct result of tactile motion shortening or if it arose from changes to the skin-based representation. Results from studies of the Pinocchio effect (De Vignemont et al., 2005) and of surgical limb modification

(Cimmino et al., 2013) suggest that skin-based and structural representations are coupled in some way. If skin-based representations feed into structural representations this would be in agreement with Craske et al. (1984), but this awaits experimental verification. Further work is necessary to confirm that the tactile motion stimulus used in this thesis influenced skin-based representations.

An interesting line of research from this study could be to see if the forearm length distortion is not just present in the body representation used for perception (body image), but also that used for action (body schema). This hypothesis could be tested by having participants reach to a target when they do not have vision of their limb. Other bodily distortions, such as the rubber hand illusion have been shown to influence reaching action (Newport et al., 2010). Alternatively, a more functional task could be used. If humans track how far they walk based on metrics of the body within the body schema and the number of steps taken (Ivanenko et al., 2011), then applying tactile motion to the legs could modulate how far someone perceives themselves to have walked.

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6.4 Limitations and methodological recommendations

The results of Chapter 2 also have implications for the experimental design of future tactile localization studies. Many previous studies have not controlled stimulus intensity to counter spatial biases that are observed for weak touch. The quality of touch sensation could degrade as a result of intensity adaptation, movement (Chapman et al., 1987), or short stimulus presentation duration. In one of the few studies to account for the effect shown in Chapter 2, Tong et al. (2016) showed that the compressive bias of the Cutaneous Rabbit Effect, measured by extent judgments, was increased by using weaker stimulus intensities. Future studies investigating any spatial properties of tactile perception will also need to consider and control for these effects of touch intensity, else they risk being confounded with biases towards the recent touch history. Specifically, they should report the stimulus type and its strength relative to detection threshold.

In studies of tactile motion the brush stimulus itself could also produce different results, if its size, stiffness, and density differ. For instance, when using a moving brush, Edin et al. (1995) found that as brush stiffness increased there was an increase in normal force (i.e. oblique to the skin) and a decrease in tangential force (skin stretch). They found that these force variations led to substantial differences in activation patterns of cutaneous mechanoreceptors. They also measured receptive field geometry using static stimuli that were four times threshold force. If motion stimuli of an equal normal force were used, they found that some cutaneous receptors responded when the stimulus was as far away as 3-4 times the diameter of their receptive fields for a static stimulus.

Therefore when discontinuous motion is achieved using a moving brush, neurons with receptive fields corresponding to the spatial gap could respond to the brush, depending on its stiffness. A commonly used alternative to brushing which enables tighter control of force and the spatiotemporal properties of motion is vibro-tactile stimulation. In an observation that is still true today, Craig and Sherrick (1969) point out that many studies using vibro-tactile stimuli only report the number and size of stimulation sites, and the vibration amplitude and frequency. They found that the force and skin indentation of the stimulus can also influence perception. Further, while

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vibro-tactile stimulation overcomes the methodological issues with mechanical brushing it cannot easily provide the local motion (and texture) experience of natural touch. Spatiotemporal patterns and skin stretch are considered by some to constitute the two peripheral sources of information for tactile motion (Olausson & Norrsell, 1993), thus a stimulus with both is preferable. Future studies should report all parameters of the stimulation and exactly how fragmentation is achieved. Perhaps, we need a von Frey filament-like stimulus for motion studies.

A widespread limitation of the studies in this thesis was that the stimulation and judgments were only ever made for the left forearm. Therefore, the findings of the thesis do not necessarily generalise to other regions of the body or stimulus patterns which cross the joints. For instance, some have found that the non-dominant arm has less acuity for tactile motion perception (Lechelt &

Tanne, 1976). Handedness, also, can influence the perceived length of the forearm (Linkenauger et al., 2009), so studies should ideally counterbalance the conditioned arm where possible.

Consequently, effects observed in this thesis, which were typically on the non-dominant hand, might be less if measured on the other side of the body. For instance, the limb shortening effect observed in Chapter 5, could simply be a response bias that is constrained to one hemisphere.

Importantly, others experiments have uncovered similar biases at other body parts for tactile localization when uncertain (Schweizer, 2000) or adjacent to a void (Weiss et al., 2004), and for perceived motion extent (Szaniszlo et al., 1998). If tested, we expect the spatial biases of the thesis generalise to other body parts, as long as the stimulation pattern is adjusted to account for differences in receptive field geometry and density.

The differing methods used to measure perceived tactile motion extent brings to mind

Titchener’s stimulus-error. He noted that how participants report perceiving something depends on whether they include their a priori knowledge of the stimulus. Differences between participants or task instructions could lead to them reporting what they felt or what they believed, which could lead to different results (Tamè et al., 2017). Ekroll et al. (2016) showed that a finger-shortening illusion was much stronger when apparent instructions (feel) were given than when objective instructions

(think) were given. In my experiments participants were always given apparent instructions. It is

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unknown if spatial distortions would have been observed if objective instructions were given. One interesting line of research would be to test if the changes to spatial perception also occur for objective instructions.

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6.5 Clinical implications

This research has indirect clinical implications for those with disordered touch sensation. Stroke patients with damage to somatosensory areas exhibit distorted spatial perception (Birznieks et al.,

2016; Denny-Brown et al., 1952), often toward the middle of the stimulus space even when supra- threshold stimuli are used (Rapp et al., 2002). The spatial representation of touch can recover over many months (Birznieks et al., 2016) potentially by experience dependent plasticity (Medina &

Rapp, 2014). In my studies, using a strong stimulus reduced spatial bias, however we cannot simply give these stroke patients more intense stimuli to resolve their spatial distortions. A possibility in these stroke-patients is that the body representation within somatosensory cortex is damaged; accordingly higher-order representations might be able to correct for this and take on a long-term prior. Increasing the exposure to the regular statistics of the touch environment (Chapter 2) or using motion (Chapter 3) could hasten the process of restoring an orderly map of the skin.

Beyond disordered touch sense; there are other neurological conditions that could benefit from an improved understanding of spatial representations. If we do succeed in making lasting changes to skin-based body representations, motion as an organizing principle could be used to treat the many instances of neurological disorders of body representations, from damage through stroke to anorexia (De Vignemont, 2010; Medina & Rapp, 2014) or even conditions of scrambled visual perception (Hess, 1982). With other senses often being dominant over touch (Ernst & Banks, 2002;

Hollins & Goble, 1988), a potential next step is enriching these tactile stimuli with multisensory inputs and self-generated movements, given that body representations are influenced by multisensory inputs (Schaefer et al., 2013; Serino & Haggard, 2010). It will, of course, be critical to understand the connections between distortions observed in healthy individuals and those with neurological disorders, before we can begin to correct disorders of body representation.

Even though touch has been, and will for the near future remain, the primary sense with which we interact with our surrounds, it is clear, that looking ahead, we will interact more and more with human-machine interfaces, neuro-prosthetics, and other augmentations of the self. For

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instance, one approach to making artificial skin is to learn the neural processes that underlie the complex experience that is our sense of touch (McGregor et al., 2011). We will need to optimise the embodiment of prosthetic devices (Kilteni et al., 2015) and determine if tactile pathways have the necessary bandwidth to connect with these devices (Bach-y-Rita et al., 1969; Novich & Eagleman,

2015), as well as realising the ethical and legal implications of projecting the self onto such external devices.

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6.6 Conclusion

This thesis has contributed to our knowledge of relatively basic properties of touch perception and provided evidence that the sensory information available and the task itself can influence the reported percept. I found that when uncertain about touch location, the sensory system relies upon the recent history of touch. It was also shown that the perception of filling-in might differ from basic changes to the receptive fields within an artificial tactile scotoma. My studies also showed spatial biases for tactile motion, which were dependent on the speed and repeated judgments of tactile motion. These experiments suggest that future studies in touch sense should note the effects of stimulus intensity, changes to receptive fields, motion duration, and time-order effects when judging tactile motion. Finally, using a novel apparatus I showed that tactile motion can modulate our conscious bodily experience, as demonstrated with shortened forearm perception. Continuing research in this area is of interest for movement control, human-machine interfaces, clinical rehabilitation and neurology, and psychiatric disorders.

138 Appendix A

Appendix A: Variable error – effect of drift

In Chapters 2 and 3, the variable error for each participant for each location and condition was used as a measure of localization uncertainty. This was computed under the assumption that when there is more uncertainty that localization will be more influenced by the recent history of touch and the context. However, my measure of variable error was susceptible to bias from time-order effects of constant error. That is, if its perceived position drifts over time then it will have a larger variable error. So my measure of variable error has an uncertainty component and a potential time-order component (when time-order effects are observed). van Beers et al. (1996) propose an elegant solution to this problem, wherein each participant's data is regressed on time (block). The variable error is then measured as the mean deviation of responses from the line of best fit. This method was not utilized here, as there were not enough data in most instances. In Chapter 2 the method would have been difficult to employ due to drifts of the perceived position of the whole distribution and drift in limb position. Chapter 3 did not consider any time-order effects, although these could be expected to have been observed, and influence the variable error.

139 Appendix B

Appendix B: Development of the wrap- around brush

We wished to develop a wrap-around brush for the experiments of Chapters 4 and 5, under the assumption that the skin-based representation of the whole circumference of the forearm would have to change to produce robust distortions to perceived forearm length (rationale: Szaniszlo et al.

(1998) show that smooth motion perception for discontinuous motion is improved when the motion stimulus is larger).

These experiments required fragmented touch motion of a stimulus that wraps around the forearm. This is difficult to achieve as the taper of the forearm is not uniform and there is substantial between-individual variation in forearm length and shape. Initially I intended to use jets of air as the stimulus in these experiments. Air jets were potentially ideal as they can be easily adjusted to the taper of the arm and quickly switched on-and-off to achieve fragmented motion.

Several methods of implementing air jets were tested, however these proved unsuccessful in producing an air jet which could focally stimulate a small patch of skin. Others have successfully developed air jets that can be used for many spatiotemporal configurations so future studies on this topic using air jets are certainly possible (see https://www.disneyresearch.com/). Electro-cutaneous and vibro-tactile stimuli were also considered, however these do not contain the natural properties of moving tactile stimuli of local motion and texture. Additionally, as discussed earlier (1.2.4) electro-cutaneous stimuli do not provide the usual pressure cues of touch.

We reverted to using brushes on the arm (see Fig. 1 below). Channel strip brush was bent to roughly the contour of the forearm. The wrap-around stimulation was achieved using two of these brushes, which hung touching each side of the arm. The brushes were attached to brackets above the arm that were free to pivot in the direction perpendicular to the length of the arm. This mechanism

140 Appendix B

enabled the brushes to provide light pressure on the arm through the action of gravity, even as the sliding device moved the brushes up-and-down the arm.

Figure 1. Photo of the wrap-around brush apparatus. The elbow rested in a padded sling and the hand lightly gripped a pole, such that the forearm was not touching anything. Wrap-around brushing was achieved using a pair of curved brushes. These were independently attached to the slider above, so that as the slider moved they maintained slight pressure on the forearm.

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