Multisensory Integration in Subclinical Neck Pain

by

Bassim Farid

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Health Sciences

in

The Faculty of Health Sciences Graduate Study Program

University of Ontario Institute of Technology

August 2016

© Bassim Farid, 2016

ABSTRACT I STATEMENT OF ORIGINALITY II ACKNOWLEDGEMENTS III FIGURES IV TABLES V ABBREVIATIONS VI

INTRODUCTION 1

THE PROBLEM (NECK PAIN AND ALTERED SENSORY PROCESSING) 1 EVIDENCE FOR ALTERED SENSORY INTEGRATION IN SCNP 1 PURPOSE & HYPOTHESES 7

LITERATURE REVIEW 8

OVERVIEW 8 OVERVIEW OF PAIN PATHWAYS AND SUBCLINICAL NECK PAIN 9 NOCICEPTION & PAIN PERCEPTION 9 SENSORIMOTOR INTEGRATION & NECK PAIN 10 AUDITORY AND VISUAL STIMULI 12 AUDITORY SYSTEM 12 VISUAL SYSTEM 13 CONCLUSION 13 MULTISENSORY INTEGRATION 15 BRAIN STRUCTURES 15 BIMODAL MULTISENSORY CONVERGENCE 17 CROSSMODAL CONVERGENCE 20 PAST SENSORY EXPERIENCE SHAPES INTEGRATION 20 MULTISENSORY INTEGRATION IN DIFFERENT POPULATIONS 22 EFFECTS OF AGING ON MULTISENSORY INTEGRATION 22 AGE-RELATED THEORIES 22 MEASURING MULTISENSORY INTEGRATION 26 INTRODUCTION 26 INTERSENSORY SYNCHRONY 27 TWO-ALTERNATIVE FORCED-CHOICE DISCRIMINATION TASK 29 COMPUTER HARDWARE & SOFTWARE 30 SUMMARY 32 STUDY ONE: PILOT MEASURING INTERSENSORY SYNCHRONY IN SUBCLINICAL NECK PAIN AND CHANGES AFTER CERVICAL MANIPULATION 33

INTRODUCTION 33 PURPOSE & HYPOTHESIS 34 METHODS 35 PARTICIPANT POOL 35 RESEARCH DESIGN 35 TEMPORAL ORDER JUDGMENT ANALYSIS 37 STATISTICAL ANALYSIS 37 RESULTS 38 AUDIOVISUAL TOJ 38 AUDIOTACTILE TOJ 39 DISCUSSION 43

STUDY TWO: MULTISENSORY INTEGRATION IN SUBCLINICAL NECK PAIN USING UNISENSORY AND MULTISENSORY RESPONSE TIMES 45

INTRODUCTION 45 METHODS 47 POPULATION 47 TWO-ALTERNATIVE FORCED-CHOICE DISCRIMINATION TASK 49 APPARATUS 50 DATA ANALYSIS 51 RESULTS 54 AUDITORY STIMULUS 55 VISUAL STIMULUS 56 MULTISENSORY STIMULUS 57 MULTISENSORY GAIN 58 REDUNDANCY CONTROL 59 DISCUSSION 61

SUMMARY & CONCLUSIONS 67

RATIONALE & PURPOSE 67 SUMMARY OF FINDINGS 67 PROSPECTIVE RESEARCH DIRECTIONS 68 CONCLUSION 69

REFERENCES 71 APPENDIX 77

STUDY ONE: JND BOXPLOTS 78 STUDY TWO: SAMPLE STATISTICAL ANALYSIS INCLUDING ASSUMPTIONS 80 TWO-WAY MIXED ANOVA AUDITORY 80 CHRONIC PAIN GRADE SCALE 82 EDINBURGH HANDEDNESS INVENTORY 84 HISTORY OF NECK PAIN / FLARE-UPS 85 THE NECK DISABILITY INDEX 86 NECK PAIN MINI-QUESTIONNAIRE 87 CONSENT 88 Abstract

Subclinical neck pain (SCNP) is recurrent neck pain marked by painful “flare-ups” and minimal

to no pain between flare-ups. It is associated with altered proprioception, slower mental rotation response times, and altered sensorimotor integration, leading to the possibility that multisensory integration is also affected. Effective multisensory integration is important for many tasks at home and at work, making it important to know if it is altered in SCNP

individuals, and whether any changes persist over time. A pilot study used a temporal order

judgement task to see if SCNP affected multisensory integration. This study revealed many

technical challenges due to aspects such as timing delays of the equipment used to present the

stimuli. In the second experiment, a two-alternative forced-choice discrimination task was used

to test for multisensory differences, specifically whether SCNP individuals have altered response times vs healthy controls, and the consistency of results over time. Response times were recorded at baseline and week 4. A two-way mixed ANOVA Indicated that auditory response times improved over time (p = 0.050) with no group differences. The SCNP group was slower at both visual and multisensory tasks (p = 0.046, p = 0.020, respectively), with no change for either group over 4 weeks, suggesting that these two stimuli are stable measures to use in future SCNP studies. multisensory integration, audio, visual, tactile, subclinical neck pain, response time, two- alternative forced-choice discrimination, temporal order judgement.

i Statement of Originality

I hereby declare that this thesis, to the best of my knowledge, is my own original work unless otherwise stated, and this material has not been previously submitted for a degree to this or any other institution.

ii Acknowledgements

I would like to give a special thanks to my supervisor Dr. Bernadette Murphy who has provided me with the utmost support in this thesis. Your opportunity has allowed me to learn so much, opening numerous doors, and I am very grateful for this. To Dr. Paul Yielder, your input over the years has helped me learn a lot and helped shape my thesis. To Dr. Michael Holmes, thank you for always being there when I needed help for my proposal, literature review, help with equipment, and many other aspects, I enjoyed our time throughout. To Hasan Shafiq, thank you for looking in to my work and always providing me with input. You have been present for every step of the way, and helped me throughout it. To Julianne, thank you for introducing me into multisensory integration since my fourth year. I have enjoyed working with you and learning from you. Your help with E-Prime has set me off to creating several programs. To Alyssa Furfaro-Argier and Shayla Muir, thank you for your help with collecting data, and going above and beyond with advertising for my study. To my sister Sehar, my brother Russan, my mother, and my father, thank you for believing and supporting me every step of the way. I will never forget everything you all have done for me. Last but not least, thank you Mr. Anderson, for being everything I needed every step of the way. I could not have done any of this without you. To the rest of the beautiful and interesting future, for whatever it may hold!

iii Figures FIGURE 1 THE EFFECTS OF PAIN OR INJURY ON SENSORY MOTOR INTEGRATION (TOP). A CHIROPRACTIC INTERVENTION ON THE ABOVE CYCLE (BOTTOM). MMI: MULTIMODAL INTEGRATION, OR MULTISENSORY INTEGRATION. ADAPTED FROM (TAYLOR & MURPHY, 2012). .. 4 FIGURE 2 A COMPARISON BETWEEN THE DIFFERENT TYPES OF MULTISENSORY NEURONS ALONG WITH UNISENSORY IN RESPONSE TO DIFFERENT SENSORY MODALITIES...... 19 FIGURE 3 THE NUMBER OF “AUDIO FIRST” RESPONSES PER SOA. JND AND PSS CAN BE SEEN ON THIS TYPE OF GRAPH. NEGATIVE SOA MEANS AUDIO FIRST, POSITIVE MEANS VISUAL. NOTE: SAMPLE GRAPH NOT DRAWN TO SCALE...... 28 FIGURE 4 XBOX 360 CONTROLLER USED TO DELIVER THE TACTILE STIMULUS THROUGH TWO VIBRATING MOTORS...... 36 FIGURE 5 GRAPHICAL DEPICTION OF THE AVERAGE SCORE FOR ALL SOAS FOR EACH GROUP AND TASK. THE X-AXIS POSSESSES THE STIMULI SOAS IN MILLISECONDS AND THE Y-AXIS POSSESSES THE PERCENT OF “AUDIO FIRST” RESPONSES...... 42 FIGURE 6 THE THREE POSSIBLE STIMULUS TYPES FOR THE PRESENTATION OF THE COLOR BLUE ...... 50 FIGURE 7 THE BASELINE MEAN RESPONSE TIME FOR ALL THE STIMULUS CONDITIONS PRESENTED WITH A COMPARISON FOR EACH GROUP ALONGSIDE EACH STIMULUS. ONE STANDARD DEVIATION CAPS ARE PRESENTED FOR EACH STIMULUS CONDITION AND GROUP...... 55 FIGURE 8 A COMPARISON OF CDFS FOR BOTH HEALTHY AND SCNP GROUPS. THE RACE MODEL IS DEPICTED IN ADDITION TO THE VISUAL, AUDITORY, AND MULTISENSORY CONDITIONS...... 60

iv Tables TABLE 1 DEMOGRAPHIC DATA OF PARTICIPANTS ...... 35 TABLE 2 JND AND PSS VALUES FOR ALL GROUPS FOR BASELINE AND WEEK FOUR AFTER OUTLIER REMOVAL ...... 38 TABLE 3 THE MEAN NUMBER OF RESPONSES THAT WERE BELOW 250 MILLISECONDS FOR EACH GROUP AND STIMULUS CONDITION, ALONG WITH ITS ACCURACY OF CORRECT RESPONSES (%)...... 54 TABLE 4 THE MEAN RESPONSE TIME (RT) IN MILLISECONDS, NUMBER OF PARTICIPANTS (N), MEAN ACCURACY IN PERCENT, AND THEIR STANDARD DEVIATIONS FOR EACH OF THE GROUPS AT BASELINE AND WEEK FOUR...... 54

v Abbreviations central nervous system (CNS) just noticeable difference (JND) perceived subjective simultaneity (PSS) sensorimotor integration (SMI) somatosensory evoked potential (SEP) stimulus onset asynchrony (SOA) subclinical neck pain (SCNP) substantia gelatinosa of Rolando (SG) temporal order judgement (TOJ)

vi Introduction

The Problem (Neck pain and altered Sensory processing)

Neck pain accounts for persistent musculoskeletal pain symptoms with significant disability in the general population (Hakala et al., 2006; Mikkelsson et al., 1999). Approximately

30-50% of people suffer from neck pain every year, which places a significant burden on the

health care system (Hogg-Johnson et al., 2008). A specific category of neck pain is subclinical

neck pain (SCNP) which refers to a lower grade neck dysfunction in which individuals have

intermittent symptoms and have not yet sought regular treatment (H. J. Lee, Nicholson, &

Adams, 2004; H. J. Lee, Nicholson, Adams, & Bae, 2005; H. Y. Lee, Wang, Yao, & Wang, 2008).

Subclinical neck pain represents a promising model to investigate the long term consequences

of altered sensory input from the neck because participants have pain free days on which the

impact of SCNP on sensorimotor and multimodal integration can be investigated without the

confounding effect of acute pain. Altered sensory feedback from a dysfunctional neck or spine,

has the potential to change the way that other somatosensory feedback is processed, leading

to altered sensorimotor integration (SMI) (Haavik-Taylor & Murphy, 2007a; Taylor & Murphy,

2010a, 2010b, 2012). It is hypothesized that other sensory modalities such as visual and

auditory inputs are also processed differently causing altered multisensory integration (Taylor &

Murphy, 2012), and this thesis begins to address this question.

Evidence for Altered Sensory Integration in SCNP

The neck muscles are innervated by the cervical plexus, the vagus (X) nerve, and the accessory

nerve (XI). The vast majority of sensory neurons in the neck are found within the cervical

1 muscles. Altered afferent (sensory) input due to repetition and overuse changes the way that sensory information is processed by causing neuroplastic changes in central nervous system

(CNS) processing (Byl & Melnick, 1997; Haavik-Taylor & Murphy, 2007a, 2007b). Several studies

have provided evidence associated with altered proprioceptive and neuromuscular function

(Bränström, Malmgren-Olsson, & Barnekow-Bergkvist, 2001; Falla, Bilenkij, & Jull, 2004; Gogia

& Sabbahi, 1994; Paulus & Brumagne, 2008). With altered proprioception, individuals with neck

pain had relocation inaccuracy in natural head posture and other complex predetermined

positions, which was especially seen in whiplash patients (Kristjansson, Dall'Alba, & Jull, 2003).

Research has suggested that the altered afferent input arising from SCNP and stiffness leads to

altered sensorimotor integration (SMI), thus resulting in improper motor response at the

effector muscles (Haavik-Taylor & Murphy, 2007a). Evidence indicates that in individuals with

neck pain, treatment has the ability to improve somatosensory processing as well as elbow joint

position sense (Haavik-Taylor & Murphy, 2011). Cervical spine manipulation has also been

shown to improve reflex excitability, cognitive and sensory processing, and motor output, in addition to its conventional role in pain management (Herzog, Scheele, & Conway, 1999;

Murphy, Dawson, & Slack, 1995; Suter, McMorland, Herzog, & Bray, 1999, 2000), providing

evidence of the impact of treatment at many levels of CNS processing.

A recent model, see Figure 1, suggests that a cycle occurs when altered sensory feedback is

received from a dysfunctional neck or spine (Taylor & Murphy, 2012). When altered

proprioceptive feedback from muscles and joints occurs, there is a re-weighting of sensory

information leading to altered SMI and multisensory integration, causing maladaptive

neuroplastic changes to kinetic and kinematic body representation. This rewiring changes

2 performance and motor control, which leads to reduced function and mobility, and causes muscle tightness, ultimately causing the cycle to repeat, worsening the condition. It is hypothesized that treatments such as chiropractic care may help restore proprioceptive input from muscles and joints, allowing a circle of improvement. Cervical manipulation in patients with neck pain and/or stiffness has been shown to alter cortical processing and SMI, which was seen in amplitude changes in the somatosensory evoked potential (SEP) (Haavik-Taylor &

Murphy, 2007a; Taylor & Murphy, 2010a).

Areas such as the thalamus have been found to possess interactions between multisensory and

SMI (Cappe, Morel, Barone, & Rouiller, 2009). The superior colliculus is an example of a multisensory area with access to efferent projections of premotor and motor areas of the spinal cord and the brainstem involved in superior colliculus mediated attentive and orientation behaviours (Meredith & Stein, 1986b).

Different populations have been observed to have altered SMI and multisensory integration. A recent study by Holt, Haavik, Lee, Murphy, and Elley (2016) found that seniors have altered sensorimotor feedback that may increase their risk of falling. With chiropractic intervention, the seniors had improved sensorimotor and multisensory integration, reducing their risk of falls. Stroke patients suffering from unilateral parietal damage had altered visual temporal perception when presented with two bilateral bars, thus performing poorly on the temporal order judgement (TOJ) task (Rorden, Mattingley, Karnath, & Driver, 1997). On the other hand,

Laurienti et al. (2006) found that the elderly population had stronger audiovisual multisensory integration in a two-alternative forced-choice discrimination task when compared with younger adults.

3

Figure 1 the effects of pain or injury on sensory motor integration (top). A chiropractic intervention on the above cycle (bottom). MMI: multimodal integration, or multisensory integration. Adapted from (Taylor & Murphy, 2012).

4 Multisensory processing is described as the influence that a sensory modality has on activity

generated by a different sensory modality. Older models had synonymously used the term

“multisensory” with “bimodal” (or trimodal), where the neuron can be stimulated by the

independent presentation of more than one sensory modality. Recent models now define multisensory convergence as either the termination of multiple sensory projections (e.g. projections of visual and auditory neurons terminating at the same target area), or through cross-modal projections (e.g. projections of visual neurons to an auditory target area). Altered

afferent input from the neck in SCNP may influence multisensory integration in both ways.

Multisensory pathways were first assessed by injecting tracers into the superior temporal

sulcus in monkeys (Seltzer & Pandya, 1980). The most notable multisensory area discovered,

functionally and anatomically, is the superior colliculus of the midbrain. In addition to the visual

and auditory pathways, somatosensory inputs, from either the somatosensory cortex or the

trigeminal nucleus, terminate at the mediolateral extent of the middle portion of the

intermediate layers of the superior colliculus (Harting, Feig, & Van Lieshout, 1997; Harting,

Updyke, & van Lieshout, 1992; Harting & Vanlieshout, 1991). These are only the most relevant examples to this thesis, which link SMI and multisensory pathways; there are many other areas in which somatosensory projections interact with auditory and visual areas (Cappe & Barone,

2005).

To determine whether multisensory integration is altered in SCNP and whether any changes can be improved by treatment, a reliable measurement tool is essential. Meredith and Stein

(1986b) directly measured the activity of multisensory neurons in the superior colliculus in animals. Multisensory stimuli have been found to result in many behavioural and perceptual

5 enhancements (Forster, Cavina-Pratesi, Aglioti, & Berlucchi, 2002; Frens, Van Opstal, & Van der

Willigen, 1995; Laurienti, Kraft, Maldjian, Burdette, & Wallace, 2004). Intersensory synchrony,

an aspect of multisensory integration, is the ability to synchronize simultaneous stimuli. There

are two popular techniques that measure intersensory synchrony behaviourally, the

simultaneity judgement task and the temporal order judgement (TOJ) task. Each ask an

participant to judge the relative timing of two stimuli from different modalities. The

simultaneity judgement task asks whether the two stimuli were simultaneous or not. In a

multisensory TOJ task, two stimuli of different modalities are presented at different stimulus

onset asynchronies (SOA), or separated at different durations, and the participant must answer

which stimulus came first (Dixon & Spitz, 1980). A poor performance in a TOJ task is seen when an individual requires a longer SOA to distinguish which stimulus came first. The just noticeable

difference (JND) is a measurement tool that looks at the smallest interval in which the

participant can reliably determine which modality came first. The smaller the JND interval, the

stronger the intersensory synchrony. In another technique, the two-alternative forced-choice

discrimination task, participants response times are compared between unisensory and

multisensory stimuli (Laurienti et al., 2006). The difference in response times between the

unisensory stimulus with the fastest response times and the multisensory stimulus is seen as

the multisensory gain. In other words, when a multisensory stimulus invokes a quicker response

time than the fastest unisensory stimulus counterpart, there is a gain (lower latency) for a

multisensory stimulus. The lower the multisensory gain, the weaker the multisensory

integration.

6 Purpose & Hypotheses

In this thesis multisensory integration is measured in adults with SCNP. The thesis will utilize the

TOJ task and Laurienti et al.’s (2006) two-alternative forced-choice discrimination task to test multisensory integration. The hypothesis is that participants with SCNP will have altered multisensory integration in comparison to healthy (no neck pain) participants, which will be seen by larger JND values in the TOJ task involving somatosensory input, smaller JND for task not involving somatosensory input, and high response times in the two-alternative forced- choice discrimination task, but larger multisensory gain.

7 Literature Review

Overview

This literature review starts with an overview of the neuroanatomy of neck pain and of multisensory integration, it then discusses factors affecting multisensory integration such as age, and ways to measure multisensory integration behaviourally in humans.

8 Overview of Pain Pathways and Subclinical Neck Pain

Nociception & Pain Perception

Nociception is the sensory response to a noxious or potentially noxious stimuli. “A” neuronal

fibers are involved with the initial, sharp sensation of pain while the “C” fibers are associated

with deep, lasting pain. The thalamus is the site where a nociceptive stimulus is filtered and

transmitted to upper areas of the brain, where it will lead to pain perception (Benevento &

Standage, 1983).

Structures Involved with Nociception

Substantia Gelatinosa of Rolando & Nucleus Proprius

The substantia gelatinosa of Rolando (SG) is the second lamina in the spinal cord (Cervero &

Iggo, 1980). The SG receives its nociceptive fibers from dorsal roots of the lateral division of the

roots and Lissauer’s tract (Cervero & Iggo, 1980). The nociceptive fibers are relayed from the SG

to neurons in the spinothalamic tract (Cervero & Iggo, 1980); here the SG is considered

secondary neurons, or tract cells.

The nucleus proprius is the laminae 3-5 portion in the spinal cord, the first synapse of the

spinothalamic tract. This section of the spinal cord also relays nociceptive signals.

Anterolateral Columns

The anterolateral columns relay information about pain, temperature, and coarse touch (Lundy-

Ekman, 2007). Fast, sharp pain is relayed from the spinothalamic trigeminal lemis while slow,

dull, throbbing ache is from the spinolimbic, spinoreticular, and spinomesencephalic tract

(Lundy-Ekman, 2007).

9 Spinothalamic Tract

The spinothalamic tract contains information about crude touch (anterior spinothalamic tract), and pain and temperature (lateral spinothalamic tract). The spinothalamic tract can be described in three neuronal orders, in order of ascending information. The first-order neuron

receives information from the peripheral nervous system, travels through Lissauer’s tract, and synapses at the dorsal horn of the spinal cord to the secondary neurons (SG or nucleus proprius). The secondary neurons decussate to the anterolateral corner, 1-2 spinal nerve segments above. The neurons travel into the rostral ventromedial medulla, and synapse in the thalamus in various regions: medial dorsal, ventral posterior lateral, and ventral posterior medial nuclei. These sites can send the signal to the primary somatosensory cortex (ventral posterior lateral), cingulate cortex (medial dorsal), and the insular cortex (ventral posterior medial; face) (Lundy-Ekman, 2007).

Sensorimotor Integration & Neck Pain

The sensory system and motor system have a synergistic relationship, in which both systems help build one another. The building process may be seen in the CNS’s ability to plasticize, where it rewires itself to adapt to changes in the environment. These changes can be subjectively positive (adaptive) for the individual or negative (maladaptive). The somatosensory system is a crucial aspect of sensorimotor integration (SMI) because it possesses receptors such as thermoreceptors, mechanoreceptors, chemoreceptors, and photoreceptors, thus contributing to sensory modalities such as proprioception and pain (nociception). Nociceptive pain has been found to cause maladaptive changes to SMI through altered motor output

(Arendt-Nielsen, Graven-Nielsen, Svarrer, & Svensson, 1996; Farina, Arendt-Nielsen, Merletti, &

10 Graven-Nielsen, 2004; Hodges & Richardson, 1996; H. J. Lee et al., 2005; Suter et al., 1999,

2000).

The changes that cause the altered afferent input are still a topic of debate, as the cause may be due to changes to the sensory receptor itself or to the central control of the receptor. The changes that occur from this enter into a positive feedback loop. When changes occur to the motor neuron, sensory receptor, or sensory apparatus, central control becomes altered, which in turn causes further changes to afferent input. A similar feedback loop can be found in Figure

1. When altered proprioceptive feedback from muscles and joints occurs, there is a re- weighting of sensory information leading to altered SMI and multisensory integration, causing maladaptive neuroplastic changes to kinetic and kinematic body representation. This rewiring changes performance and motor control, which leads to reduced function and mobility, causing muscle tightness, ultimately causing the cycle to repeat worsening the condition. It is hypothesized that treatments, such as chiropractic care may help restore proprioceptive input from muscles and joints, facilitating a circle of improvement. Areas such as the thalamus have been found to possess interactions between multisensory (audio, visual, etc.) and SMI (Cappe et al., 2009). The superior colliculus, an area dense with multisensory neurons, possesses access to efferent projections of premotor and motor areas of spinal cord and brainstem involved in superior colliculus mediated attentive and orientation behaviours (Meredith & Stein, 1986b), some that involve the saccadic movement of the eye and neck. This leads to the possibility that multisensory integration may be altered in individuals with neck pain.

11 Auditory and Visual Stimuli

In order to effectively understand multisensory integration, it is important to see how different modalities lead into a converging path. Thus, in addition to the previous nociceptive aspect of the somatosensory system in the previous chapter, this chapter will analyze the neural pathways of the auditory and visual system before their point of convergence in the several multisensory areas.

Auditory System

Cochlear Nerves

The cochlear nerve makes up a part of the vestibulocochlear nerve, the eighth (VIII) cranial nerve. All the targeted projections of the brainstem do not receive information from every cell population in the cochlear nucleus, and none of the cell populations project to all the targeted areas of the brainstem (Cant & Benson, 2003). Lorente de Nó (1933) claimed that there are “no less than 40 or 50 types of neurons” in the cochlear nucleus. The cochlear nucleus is broken down to three components: the anteroventral cochlear nucleus (AVCN), the posteroventral cochlear nucleus (PVCN), and the dorsal cochlear nucleus (DCN). There are three major tracts that the axons can take: the ventral acoustic stria (trapezoid body), the intermediate acoustic stria, and the dorsal acoustic stria.

Projections

Axons from the AVCN and anterior part of PVCN travel in the trapezoid body (TB). Axons from the posterior aspect of the PVCN travel via the intermediate acoustic stria. Axons from the DCN

12 travel via the dorsal acoustic stria. These projections diverge into several different processing

sites.

Visual System

Ascending Neural Pathways

The nerve impulses from the optic nerve pass through the optic chiasm (Huether & McCance,

2012). The inner nerves cross to the opposite side and join fibers with the outer half to form the

optic tracts (Huether & McCance, 2012). Most of these fibers synapse into the dorsal lateral

geniculate nucleus (LGN) (Huether & McCance, 2012). Some of optic nerves are sent to the

superior colliculus in the midbrain, where it can aid in controlling eye movements (saccades)

(Nolte, 2002) and other multisensory features (Meredith & Stein, 1986b).

Lateral Geniculate nucleus

Both the left and right hemispheres of the brain have a lateral geniculate nucleus (LGN). The

LGN acts as a relay center in the thalamus for visual information. From the LGN neurons are

sent through the optic radiation, which is sent to the primary visual cortex of the occipital lobe.

The LGN can also receive information from the primary visual cortex and the optic tectum; it is

not only a relay, but also a processing site.

Conclusion

Each sensory modality takes a unique pathway to and within the brain, some of these pathways

lead to a multisensory processing site. If more than one type of modality is entering this site

(bimodal) or if a modality meets with another modality (cross-modal), with appropriate spatial

13 and temporal conditions, a multisensory integration of that stimulus will occur in a specific population of multisensory neurons along with unisensory processing.

14 Multisensory Integration

Brain Structures

The vital area of interest in multisensory integration is the merging of inputs from different

sensory modalities onto single, individual neurons. Multisensory neurons can be found in cortical and subcortical areas, as well as corticotectal (interaction).

Subcortical (tectal)

Midbrain - Superior Colliculus (Latin, upper hill)

The corpora quadrigemina (Latin, quadruplet bodies), the roof of the mesencephalon

(midbrain), is composed of two inferior colliculi and two superior colliculi. The superior colliculi

(plural) is often called the superior colliculus (singular) split into two regions: the superficial

layer containing areas such as the stratum opticum (lamina II; SO) that receives direct visual

input from the retina (retinocollicular) and visual cortex (corticocollicular); and the deep layers

in which multiple sensory modalities (e.g. auditory, visual, and somatosensory) innervate. The

superior colliculus is also often referred to as the optic tectum, or simply tectum in mammals.

Visual information from the right eye innervate the left superior colliculus and vice versa.

Vanegas (1984) describes the superior colliculus as possessing 7 layers. The superficial layers are composed of the stratum zonale (lamina I; SZ), stratum griseum (lamina II; SGS), and the

stratum opticum (lamina III; SO). The intermediate layers are composed of the stratum griseum

intermedium (lamina IV; SGI) and the stratum album intermedium (lamina Vl; SAI). Lastly, the

deep layers are composed of the stratum griseum profundum (lamina VI; SGP) and the stratum

album profundum (lamina VII; SAP). Many of the intermediate and deep layer cells project to

15 motor and premotor areas that are responsible for orientation of the eyes, pinnae, and head

(Meredith & Stein, 1986b). Axons arising from here will caudally and contralaterally enter the ventral funiculus of the spinal cord, but synapse only in the medial grey matter of the cervical levels of the cord. The superior colliculus is perhaps the most evident site of multisensory convergence, as it has neurons that respond to more than one modality (Drager & Hubel, 1975;

Hartline, 1984; Meredith & Stein, 1986b; B. Stein, 1984; B. E. Stein & Meredith, 1993).

Corticaltectal Interaction

Anterior Ectosylvian Sulcus (Felines)

The anterior ectosylvian sulcus is found between the parietal, temporal, and frontal lobes, and is known as the most noteworthy interaction of the cortical and tectal system with respects to multimodal integration. Researchers have labelled this area as a “polysensory” location, where many sensory modalities integrate (Clemo, Meredith, Wallace, & Stein, 1991; Clemo & Stein,

1982; Wallace, Meredith, & Stein, 1992). The anterior ectosylvian sulcus is comprised of three unimodal regions: the ventral bank of sulcus, the anterior ectosylvian visual area (site of visual processing) (Benedek, Mucke, Norita, Albowitz, & Creutzfeldt, 1988; Mucke, Norita, Benedek, &

Creutzfeldt, 1982; Norita et al., 1986; Olson & Graybiel, 1987); a somatosensory area, the fourth somatosensory cortex (Burton & Kopf, 1984; Clemo & Stein, 1982, 1983); and an auditory area, the field anterior ectosylvian sulcus (Clarey & Irvine, 1986). At the border of these regions are multisensory neurons (Clemo et al., 1991; Wallace, Ramachandran, & Stein,

2004).

16 Bimodal Multisensory Convergence

Multisensory neurons are classified as neurons that are influenced by afferent input from more than one modality. Multisensory systems are able to converge simultaneous (or near simultaneous) and spatially neighbouring stimuli. These multisensory systems possess an intricate set of neurons that process the multisensory stimulus. The convergence can take place through the termination of multiple sensory projections (e.g. projections of visual and auditory neurons terminate at a target area), or through cross-modal projections (e.g. projections of visual neurons to an auditory target area).

Bimodal multisensory neurons are neurons that respond to two modalities, as opposed to the one modality in unisensory neurons. Signals in both modalities do not have to be presented for the multisensory neuron to be activated. Unisensory neurons will respond to stimuli in only one modality, whether it is presented to the participant by itself or as part of multisensory input.

For example, a unisensory visual neuron will respond to a visual stimulus alone, to the visual signal of a multisensory audiovisual stimulus, but not to an audio stimulus alone. In a multisensory bimodal neuron, the cell will respond to each of the two sensory modalities alone, or when presented simultaneously.

For an enhanced bimodal neuron, the activity due to the multisensory stimulus is less than the combined activity due to each of the unisensory stimulus. For example, consider the activity level of an auditory stimulus in an enhanced bimodal neuron to be x%, the activity level due to the multisensory stimulus on the neuron will then be less than 2x%. In a bimodal suppressed neuron, the multisensory stimulus results in a lower activity level than for the lowest unisensory stimulus. In a superadditive bimodal neuron, the activity level of the multisensory

17 stimulus is more than the combined activity level from a unisensory stimuli. Subthreshold neurons are not true bimodal neurons, but they are multisensory. They are not bimodal neurons because they do not react to both modalities individually, but show a different activity level for the multisensory stimulus when compared with the one unisensory stimulus it reacts to. See Figure 2 for a diagram of the different types of multisensory and unisensory neurons in response to sensory modalities. In addition to bimodal cells, there are trimodal cells that respond to three modalities, sometimes as true trimodal, other times as subthreshold.

18 Unisensory Neurons Visual Auditory Activity Activity

V A VA V A VA

Stimulus Modality Stimulus Modality

True Bimodal Neurons Enhanced Superadditive Supressed Activity Activity Activity Multisensory NeuronsMultisensory

V A VA V A VA V A VA Stimulus Modality Stimulus Modality Stimulus Modality

Subthreshold Neurons Visual Auditory

Activity Activity

V A VA V A VA Stimulus Modality Stimulus Modality

Figure 2 A comparison between the different types of multisensory neurons along with unisensory in response to different sensory modalities.

The magnitude of action varies from cell to cell and even within the same cell as a function of

stimulus parameters (receptive field, number of impulses, etc.) (Meredith & Stein, 1986b). Each neuron following the several response profiles is an important concept because it would be useless if each neuron had the same specifications, where the redundancy would not provide the CNS with meaningful information. Studies have found that temporal and spatial factors are

19 responsible for determining whether an enhancement or depression from a multisensory

stimulus (Meredith & Stein, 1986a; Nemitz, Meredith, & Stein, 1984).

This information is vital to understanding how multisensory integration occurs at the neuronal

level. With additive and supressed responses, it is important to understand that multisensory

integration can have both a positive and negative effect. Whether stimuli are semantically

congruent (see Past Sensory Experience Shapes Integration on Page 20) must also be

considered when designing multisensory integration experiments.

Crossmodal Convergence

There are two types of termination patterns in multisensory convergence: the termination of multiple sensory projections (e.g. projections of visual and auditory neurons terminate at a target area, sometimes referred to as bimodal), or through cross-modal projections (e.g. projections of visual neurons to an auditory target area). The crossmodal phenomena was demonstrated when tracers were injected felines’ anterior dorsal bank of the anterior ectosylvian sulcus (somatosensory area), and were found to produce retrograde labeling in the posterior aspect of the anterior ectosylvian sulcus (auditory field) (Reinoso-Suarez & Roda,

1985). These crossmodal projections are significant as a similar phenomenon may occur with altered somatosensory input of the neck from SCNP projecting onto other sensory sites of the brain, possibly hindering multisensory integration.

Past Sensory Experience Shapes Integration

The semantics of the auditory and visual components of a multisensory stimulus may play a significant role in determining multisensory behaviour (e.g. response time). For example, a

20 “natural” (possibly conditioned by past experiences) multisensory stimulus may be a visual stimulus of a police vehicle and the sound of a police siren. In a situation such as this, not only are the two unisensory stimuli spatially and temporally adjacent, but also semantically congruent due to learned links between each of the sensory modalities to an object or event.

Laurienti et al. (2004) studied the response times (behavioural performance) in semantically congruent and incongruent multisensory stimuli in a two-alternative forced-choice discrimination task. They found that a semantically congruent multisensory stimulus increased task performance (faster response times) while the semantically incongruent multisensory and dual-visual (paired unimodal) stimuli decreased task performance (slower response times).

21 Multisensory Integration in Different Populations

Effects of Aging on Multisensory Integration

Multisensory integration changes significantly over lifespan, where the change has been shown to have varied results. Laurienti et al. (2006) demonstrated, using a two-alternative forced-

choice discrimination task design utilizing response times with redundant information, that the elderly had a larger response time difference than young adults between the multisensory stimulus and unisensory stimulus, indicating a larger multisensory gain.

Wille and Ebersbach (2016) determined that adults and older children (9-year-olds and above) ignored auditory components in a discrimination task consisting of an audiovisual stimulus,

however the younger children (6-year-olds) show dominance in the auditory component of the

bimodal stimulus. An example of this dominance in adults can be seen in the ventriloquist

effect, in which the perceived sound location is spatially shifted to the visually dominant area, away from the true auditory source (Slutsky & Recanzone, 2001). The Colavita effect is another example in which vision dominates over other senses, and sometimes may even mask the auditory component of the multisensory stimulus (Colavita, 1974).

Age-Related Theories

Cognitive Differences

Salthouse (2000) attributes many cognitive variables found to be related to aging. Cognitive slowing and redundancy (e.g. the fact that people generally respond faster to two targets presented simultaneously than to either of the targets presented alone) is one of the theories used to explain why multisensory enhancements may be seen in older adults. There are several

22 studies that have been shown a general slowing of cognitive processes within the elderly

population (Cerella, 1985; Salthouse, 2000; Verhaeghen & Salthouse, 1997). If cognitive slowing

was not occurring, then the differences that would occur between the young and elderly

population (sensory and motor processing/response) would be consistent regardless of the

task. When dealing with more demanding tasks, cognitive slowing becomes more evident in the

elderly, in comparison with easier tasks, as can be seen in Verhaeghen and De Meersman’s

study (1998). In multisensory integration, redundant information is being delivered (e.g.

auditory and visual), in comparison to a unisensory input. This is why a unisensory task may be more sensitive to showing the effects of cognitive slowing, as there is no redundancy. In order to best account for general cognitive slowing, specifically in a sensorimotor processing response time tasks, several researchers have created a model using linear or non-linear functions

(Cerella, 1985; Cornelissen & Kooijman, 2000; Myerson, Hale, Poon, Wagstaff, & Smith, 1990;

Salthouse, 1988). When analyzing the differences in response time tasks with age, these linear and non-linear functions can account for the differences in response time, due to general cognitive slowing. Thus, when looking at multisensory, or any other response time tasks, and when comparing groups with significant age differences, a researcher can use the above models to determine whether the difference between groups lies in age-related cognitive slowing, or elsewhere. Laurienti et al. (2006) used such models to account for general cognitive slowing, and yet still found enhanced multisensory integration in older adults, suggesting that multisensory integration was enhanced beyond the differences (for multisensory gain) caused by general cognitive slowing.

23 Inverse Effectiveness

Older adults may exhibit a deterioration in all sensory systems in addition to general cognitive

slowing. These changes occur both in the peripheral nervous system, the sensory organ, or how

the CNS processes the information from these organs. The reduced sensitivity or acuity from these organs may inversely cause an increase in effectiveness in multisensory integration. In other words, decreasing the effectiveness of individual sensory modalities increases the effectiveness of multisensory neurons. Meredith and Stein (1986b) best describe this as “…the percentage change of enhanced interactions was generally inversely related to the vigor of the responses that could be evoked by presenting each unimodal stimulus alone and suggests that the potential for response amplification was greatest when responses evoked by individual stimuli were weakest”. Hairston et al. (2003) showed evidence for inverse effectiveness, where healthy participants, with artificially degraded vision (induced myopia), had their localization skills enhanced for audiovisual conditions, whereas in normal conditions the localization for multisensory conditions was similar to unisensory conditions.

Selective Attention

In addition to stimulus factors that affect signalling in peripheral sensory organs (timing, location, and intensity of stimulus), there are also top-down control mechanisms that affect multisensory integration. Two of these factors are semantic congruence (Laurienti et al., 2004) and selective attention (Alsius, Navarra, Campbell, & Soto-Faraco, 2005; Mozolic,

Hugenschmidt, Peiffer, & Laurienti, 2008; Talsma, Doty, & Woldorff, 2007; Talsma & Woldorff,

2005).

24 Selective attention to one sensory modality can reduce or diminish the multisensory advantage in a multisensory stimulus, when compared to divided attention between the two presented modalities (Mozolic et al., 2008; Talsma et al., 2007). In other words, it is important for a task to require distribution of attention across sensory modalities in order for multisensory integration to effectively occur and accurately be measured. Though sounding counterproductive, a possible reason why selective attention to a specific modality reduces the effectiveness of the other modality, and also attenuates multisensory integration, is that it may be acting as a filter to reduce the effects of non-matching (not semantically congruent) competing stimuli. This filter hypothesis was disproven in the second part of Mozolic et al.’s (2008) experiment, where semantically incongruent stimuli did not provide any benefit to modality-specific selective attention compared with divided attention.

25 Measuring Multisensory Integration

Introduction

In order to properly assess differences in multisensory integration, valid, reliable measurement

tools are required. The best techniques for use in primates and felines are invasive, usually

penetration of electrodes into the bimodal neurons in the superior colliculus (Meredith & Stein,

1986a, 1986b). Though these techniques enable the measurement of the activity of bimodal neurons in animals, they are generally not applicable for humans.

The neurophysiological studies of cells in the superior colliculus has provides some insight into how these neurons may function in more “natural” conditions in the environment. The precise mechanism associated with the behavioral enhancement of response time facilitation in multisensory processing is not yet known. One proposed mechanism for this behavioral enhancement is neuronal processing that can be found in the beta frequency range (~13-30

Hz). Senkowski et al. (2006) found that the association between oscillatory beta activity and multisensory integration was directly linked to multisensory response time facilitation effects.

The behavioural and perceptual changes due to changes in multisensory integration have been investigated in an array of studies (Forster et al., 2002; Frens et al., 1995; Laurienti et al., 2006;

Laurienti et al., 2004).

There are special behavioural tasks that use non-invasive technique to measure multisensory integration in humans. Each group of tasks looks at a specific aspect of multisensory integration. For example, tasks utilizing intersensory components look at how accurately a person can perceive two stimuli, in this case multisensory, as synchronous [e.g. Zampini et al.’s

26 (2005) temporal order judgement (TOJ) task]. In a different task, researchers measure the

“gain” (response time reduction) from a unisensory stimulus to a multisensory stimulus, such as

Laurienti et al.’s (2004) two-choice audiovisual discrimination task. This thesis includes two

experiments which use these two non-invasive techniques to compare multisensory integration

in SCNP and healthy individuals.

Intersensory Synchrony

In two popular experimental techniques to measure intersensory synchrony, participants are

asked to judge the relative timing of two stimuli from different modalities. One task, the

simultaneity judgement task, asks whether the two stimuli appeared to be simultaneous or not.

The second technique, a multisensory TOJ task, uses two stimuli in different modalities presented at different stimulus onset asynchronies (SOA), to which the participant must answer which stimulus came first (Dixon & Spitz, 1980). The just noticeable difference (JND) and the point of subjective simultaneity (PSS) are dependent measures that describe how well the participant is performing. JND is the smallest temporal interval at which a participant can reliably determine which modality came first. The smaller the JND interval from the center

(PSS), the better an participant can judge small (in magnitude) SOAs, and thus possesses strong intersensory synchrony. For example, if a person possesses a JND value of 50 ms (and PSS of zero), that means he/she can reliably distinguish which stimulus came first when their onsets are as little as 50 ms apart, possessing a stronger intersensory synchrony ability than a person with a JND value of 75 ms. The steeper the slope of a SOA vs response graph, the better the intersensory synchrony, and the smaller the JND. The PSS is a point at which the participant is maximally unsure about the temporal order. PSS does not necessarily reveal if intersensory

27 synchrony is altered, instead, it shows what modality the participant prefers. See Figure 3 for a

graph that depicts the JND points, where the PSS point sits between the two ranges.

Figure 3 The number of “audio first” responses per SOA. JND and PSS can be seen on this type of graph. Negative SOA means audio first, positive means visual. Note: sample graph not drawn to scale.

For example, Zampini et al. (2005) describe a TOJ task as well as the tools to measure TOJ: JND and PSS. The experiment design consisted of 10 SOAs (-200 ms, -90 ms, -55 ms, -30 ms, -20 ms,

+20 ms, +30 ms, +55 ms, +90 ms, and +200 ms), where negative values represented an audio

stimulus being presented first. Individuals with normal hearing and touch and who were naïve

to the purpose of the experiment (never participated in a TOJ before) performed a TOJ task. In

the second experiment, 10 participants who had taken part in a TOJ task previously underwent the TOJ task. In the last experiment, participants used electrocutaneous stimulators instead of

28 vibrotactile stimulation. The results showed that the naïve participants did poorly when compared to the experienced participants, as seen in the JND values. The spatial aspect of the test did not make a difference for any of the three experiments. Lastly, the electrocutaneous

stimulator did not make a significant difference when compared to a vibrotactile stimulator. All

of these findings are important when considering an experimental design for a TOJ task, as they

show whether or not certain aspects influence the results.

A TOJ is analyzed in a strict fashion. Zampini et al. (2005) began by recording the number of

“audio first” responses for each SOA (total of 20 responses per SOA). A graph similar to this can be seen in Figure 3. The standard deviation was calculated along with the z-score at each SOA.

Since most of the ±200 ms responses are usually perfect, they were excluded from the analysis as they did not affect the normal distribution. A z-score of response probability versus SOA graph was then created for every participant with a line of best fit, and the slope (m) and y- intercept (b) was recorded. PSS was calculated by dividing the negative of the y-intercept by the slope (-b/m). JND was calculated by dividing 0.675 from the slope (0.675/m).

Two-Alternative Forced-Choice Discrimination Task

Laurienti et al.’s (2004) two-alternative forced-choice discrimination task compared response times for unisensory stimuli to multisensory stimuli. The larger the difference between unisensory and multisensory, the greater the multisensory gain. A trial consisted of either an auditory stimulus alone, visual stimulus alone, or a multisensory stimulus (auditory and visual), all in pseudo-random order. The participants were asked to discriminate between the colors blue or red, presented audibly through the verbalization of the color names for 300 milliseconds (a voice says the word “blue” or “red”), visually through a circle filled with the

29 corresponding color on a black background for 250 milliseconds, or simultaneously presenting

both stimulus modalities. A trial began with a fixation cross in the center of the screen for 1

second, followed by the stimulus, and lastly a black screen for 8 seconds for extra time for responses. A response would skip the remaining time in the trial and begin the next trial.

Computer Hardware & Software

In order to ensure accurate data collection, the characteristics of the software and hardware peripherals must be considered strictly. The following sections discusses important aspects of hardware and software which are important to consider when designing multisensory integration experiments, since temporal (Nemitz et al., 1984) and spatial factors (Meredith &

Stein, 1986a) are both used to determine the strength of multisensory integration.

Response Input

Choosing a quick, effective, and accurate, method to record a response from the participant is just as important as control in displaying a stimulus. The two main response inputs used in research are the keyboard and the response box. The keyboard is the most common input for a computer. The two types of common interfaces for the keyboard are PS/2 and USB. This paper will concentrate on the latency differences. The PS/2 keyboard almost instantly sends the keypress to the computer. A computer reads keypresses from a USB keyboard based on a certain frequency, or “sweeps”, which is exclusively based on the firmware and driver of the keyboard. A good USB gaming keyboard possesses a sweep rate of about 1000 sweeps per second, thus providing a maximum latency of 1 millisecond.

30 Sound Output

In order to quickly send sound to an audio peripheral, good hardware, software, and drivers are

required. Every version of Windows handles sound processing differently. Windows 7 has more

stages than Windows XP in processing and outputting sound. Thus, Audio Stream Input/Output

(ASIO) drivers were made to maximally decrease latency at the cost of sound quality

(modifiable). The hardware, specifically the sound card, also plays a significant role in latency.

Older computers with built-in (integrated) sound cards produce larger latencies and variation

than newer computers and computers with dedicated sound cards. The software managing the

sound output also plays a role. Using a combination of good hardware, software, and drivers

can significantly reduce audio latency.

Visual Output

An additional source of timing errors is the presentation of graphics. If the image being

displayed is large in pixel density, the computer will take longer to retrieve the information from the drive. Preloading graphics in random access memory (RAM) before retrieval will greatly reduce latency. The monitor that renders the graphics also plays a significant role. Each monitor possesses a latency from when it is given information to when it presents it. Most monitors advertise a gray-to-gray latency, which provides the latency for a monitor to completely display a gray image. Another important aspect in monitors to consider is the frame refresh rate, such that the higher the refresh rate, the lower the maximum latency. For example, if a monitor has a refresh rate of 60 Hz, it means that the monitor refreshes its frame every 16.7 milliseconds. If a new graphic was presented to it the moment it refreshed from a previously presented image, it would take a full 16.7 milliseconds to produce the new image,

31 excluding the time of the monitory grey-to-grey latency. If for example the monitor had just refreshed and 10.0 milliseconds later, the graphic card pushes new information, it would take another 6.7 milliseconds before the new frame could be shown, unless the graphic card pushes new information before that.

Summary

In summary, there are clear differences in SMI in SCNP individuals. At least one study of elderly individuals has found that chiropractic care in elderly individuals enhanced multisensory integration in addition to enhanced SMI, suggesting that multisensory integration may be compromised in those with SNCP. The two best ways to measure multisensory integration appear to be TOJ and Laurienti et al.’s (2006) two-alternative forced-choice discrimination tasks. In order to study multisensory integration in SCNP, and the reliability of its measurement in SCNP, both these methods will be used. Study One of this thesis describes the development and piloting of a TOJ task while Study Two measures the reliability over time and differences in

SCNP individuals of a two-alternative forced-choice discrimination task to measure multisensory integration.

32 Study One: Pilot Measuring Intersensory Synchrony in Subclinical Neck

Pain and Changes After Cervical Manipulation

Introduction

Subclinical neck pain (SCNP) is a classification of a chronic low grade neck pain for which the

individual has not yet sought regular treatment (H. J. Lee et al., 2004; H. J. Lee et al., 2005; H. Y.

Lee et al., 2008). Altered neuromuscular function and proprioception have been associated

with neck pain (Bränström et al., 2001; Falla et al., 2004; Gogia & Sabbahi, 1994; Paulus &

Brumagne, 2008). With altered proprioception, individuals with neck pain had relocation inaccuracy in natural head posture and other complex predetermined positions, which was especially seen in whiplash patients (Kristjansson et al., 2003). Research has suggested that the altered afferent input arising from the SCNP and stiffness leads to altered sensorimotor integration (SMI), thus resulting in the improper motor response at the effector muscles

(Haavik-Taylor & Murphy, 2007a).

Cervical spine manipulation has also been shown to change reflex excitability, cognitive and sensory processing, and motor output, in addition to its conventional role in pain management

(Herzog et al., 1999; Murphy et al., 1995; Suter et al., 1999, 2000), providing evidence of the impact of cervical spine manipulation at many levels of central nervous system processing.

Cervical manipulation in patients with neck pain and/or stiffness has been shown to alter

cortical processing and SMI, which was seen in amplitude changes in the somatosensory evoked

potential (SEP) (Haavik-Taylor & Murphy, 2007a; Taylor & Murphy, 2010a).

33 It is hypothesized that information in other sensory modalities such as visual and auditory

inputs is also processed differently causing altered multisensory integration (Taylor & Murphy,

2012). Previous research has shown that multisensory integration in elderly population is enhanced when compared to young adults, as was observed in a two-alternative, forced choice discrimination task involving measuring response times (Laurienti et al., 2006). Another study demonstrated that the elderly have weak multisensory integration, found through a sound induced flash illusion, as well as weak SMI (Holt et al., 2016).

Another technique to measure multisensory integration is through the intersensory aspect, which can be done through a multisensory TOJ task. The task uses stimuli presented in two modalities that are presented at different times, stimulus onset asyncrhonies (SOAs), to determine how well a person can distinguish which stimulus came first, especially when the stimuli are near synchronous.

Purpose & Hypothesis

The goal of this pilot study was to determine whether participants with SCNP have an altered

multisensory integration, in comparison to participants (no neck pain), using the TOJ method to

measure multisensory integration and whether spinal manipulation is able to improve

multisensory integration. It hypothesized that participants with SCNP will have altered

multisensory integration, which will be seen by larger JND values for tasks that involve

somatosensory input, and lower JND for those that do not (inverse effectiveness), and will be improved after a cervical manipulation treatment.

34 Methods

Participant Pool

8 control SCNP participants, 10 SCNP treatment participants, and 8 healthy participant controls

were chosen. SCNP and neck pain severity was determined using a Chronic Pain Grade Scale

developed by Von Korff et al. (1996), please see page 82 of the appendix. The activities of daily

living were assessed using the Patient Specific Functional Scale (Stratford, 1995). Any

participants who had previously experienced whiplash were excluded. See Table 1 for

demographic data.

Number of Age (years) and Number of Group Participants standard deviation females Healthy 8 22.0 ± 2.1 4 SCNP control 8 20.5 ± 2.0 4 SCNP treatment 10 22.0 ± 2.4 7 Table 1 Demographic data of participants

Research Design

Apparatus & Stimulus Conditions Participants were seated comfortably at a desk with a laptop (Lenovo T500 series) with two

amplified external speakers beside it. The speakers and laptop were held at a constant location

along with the participant’s seating. The volume on the speakers was set to 50% and maximum

on the laptop. Brightness was set to maximum on the laptop. The auditory beeps were set to

784 Hz. A constant background tone was being played at 69.3 Hz to mask any extraneous

sounds not generated as part of the experiment. A modified Xbox 360 controller with no circuit

board (only vibration motors) was used to induce vibration for the tactile stimulus through a

USB to parallel FIFO ("first in, first out") device for E-Prime 2.0 software (Psychology Software

Tools, Sharpsburg, Pennsylvania), see Figure 4. The laptop display had a refresh rate of 60 Hz.

35 Two sets of data were collected, one at baseline and another at week four. The SCNP group was split into two subgroups: the treatment group and the other, the control, received passive head movement and spinal palpitation.

Figure 4 Xbox 360 Controller used to deliver the tactile stimulus through two vibrating motors.

Temporal Order Judgement Task A TOJ task was created using E-Prime 2.0 software (Psychology Software Tools, Sharpsburg,

Pennsylvania) to present the different stimuli and record the responses on a computer. The duration of the audio stimulus was 120 ms, tactile for 90 ms, and visual for 90 ms. The task was separated into a program for testing audio/tactile and audio/visual input. The SOAs were -200 ms, -90 ms, -55 ms, -30 ms, -20 ms, +20 ms, +30 ms, +55 ms, +90 ms, +200 ms (negative = audio presented first, positive = visual/tactile). Two practice blocks were presented, then five test blocks. Feedback was provided on 67% of the practice trials. Each block consisted of four of each of the SOAs for a total of 40 trials. After the presentation of the stimuli, an option was given, asking the participants to indicate which stimuli was presented first. “B” on the keyboard was used to indicate that a beep was presented first, or “V” for vibration (or visual flash depending on the test).

36 Temporal Order Judgment Analysis

The number of “audio first” responses were tallied for each SOA (total of 20 responses per

SOA). An example of this type of graph can be seen in Figure 3 on Page 28. The standard deviation and z-score was calculated for each SOA. Because most of the ±200 ms SOA responses were perfect, they were excluded from the analysis later as they did not affect the normal distribution. A z-score versus SOA graph was created for every participant with a line of best fit, and the slope (m) and y-intercept (b) was recorded. PSS was calculated by dividing the negative y-intercept by the slope (-b/m). JND was calculated by dividing 0.675 by the slope

(0.675/m).

Statistical Analysis

All statistical tests were completed using SPSS version 23 (International Business Machines

Corporation, Armonk, New York). The mean JND and PSS were analyzed separately using a two- way [1 between-factor (participant group = treatment vs. sham vs. healthy group) x 1 within- factor (test time = baseline vs. week 4)] mixed ANOVA for each task. In order to run the ANOVA, the following assumptions were considered. Outliers were identified using boxplots which were defined as having more than 1.5 box-lengths from the edge of the box then removed for both baseline and week-4 measurements, see Study One: JND Boxplots on Page 78 of the appendix.

Shapiro-Wilk’s test was used to test for data normality. Mauchly’s test of Sphericity to test for

variance of the differences between groups did not apply since the dependent variable was

only measured at two levels. In order to test homogeneity of error variance, Levene’s test of

equality of error variances was used. Any significance in the homogeneity of covariances test,

Box’s test for covariances, were noted and thus interaction effects were not assessed. Partial

37 eta-squared (η2) was calculated for effect size, where small was interpreted as 0.01, medium as

0.06, and large as 0.14.

Results

Baseline Week Four Group Audio-Visual Audio-Tactile Audio-Visual Audio-Tactile JND PSS JND PSS JND PSS JND PSS Healthy -92.37 ± 17.6 0 -77.19 ± 0.64 0 -85.17 ± 7.4 0 -76.74 ± 3.5 0 Control -84.56 ± 7.8 0 -75.02 ± 2.0 0 -79.08 ± 4.3 0 -79.23 ± 7.7 0 Treatment -82.85 ± 22.4 0 -77.59 ± 0.4 0 -78.39 ± 4.6 0 -74.75 ± 1.0 0 Table 2 JND and PSS values for all groups for baseline and week four after outlier removal

Audiovisual TOJ

JND

Using the boxplot outlier feature in SPSS (International Business Machines Corporation,

Armonk, New York), the descriptive statistics identified 5 outliers for values greater than 1.5

box-lengths from the edge of the box, or extreme outliers greater than 3.0 box-lengths, thus

these participants were excluded from this test. At baseline, participant #25 (SCNP treatment)

had an outlier and participant #15 (SCNP control) had an extreme outlier. At week-four participant #8 (healthy) and 23 (SCNP treatment) had outliers and participant #10 (SCNP control) had an extreme outlier. All JND values were normally distributed in all data cells, as assessed by Shapiro-Wilk’s test (p > 0.05). Levene’s Test of Equality of Error Variances was used to determine if there was homogeneity of variance and the assumption of homogeneity of variances was not violated (p > 0.05). Box’s test of equality of covariance matrices was used to test for homogeneity of covariances, where there was homogeneity of covariances (p = 0.365).

The main effect of test time showed no statistically significant difference in mean JND at the different test times, F(1, 18) = 2.225, p = 0.153, partial η2 = 0.110, a large effect size. The main

38 effect of participant group showed that there was no statistically significant difference in mean

JND between the groups F(2, 18) = 1.414, p = 0.269, partial η2 = 0.136. The two-way mixed

ANOVA for the audiovisual TOJ demonstrated no significant interaction between test times and

participant groups on JND F(2, 18) = 0.046, p = 0.955, partial η2 = 0.005.

PSS

The ANOVA test was unable to come up with results as the values for PSS were miniscule.

Using the boxplot outlier feature in SPSS (International Business Machines Corporation,

Armonk, New York), the descriptive statistics identified 2 outliers for values greater than 1.5

box-lengths from the edge of the box, or extreme outliers greater than 3.0 box-lengths, thus

these participants were excluded from this test. At baseline, no participants had outliers. At

week-four, participant #7 (healthy) and 22 (SCNP treatment) possessed outliers. All PSS values

were normally distributed in all data cells, as assessed by Shapiro-Wilk’s test (p > 0.05).

Levene’s Test of Equality of Error Variances was used to determine if there was homogeneity of

variance and the assumption of homogeneity of variances was not violated (p > 0.05). Box’s test

of equality of covariance matrices was used to test for homogeneity of covariances, where

there was homogeneity of covariances (p = 0.095).

Audiotactile TOJ

JND

Using the boxplot outlier feature in SPSS (International Business Machines Corporation,

Armonk, New York), the descriptive statistics identified 8 outliers for values greater than 1.5

box-lengths from the edge of the box, or extreme outliers greater than 3.0 box-lengths, thus

39 these participants were excluded from this test. At baseline, participant #2 and 17 had outliers

and participant #3 (healthy), 12 (SCNP control), 19 (SCNP treatment), and 21 (SCNP treatment) had extreme outliers. At week-four participant #18 (SCNP treatment) had an outlier and participant #21 (SCNP treatment) had an extreme outlier. All JND values, except healthy week-

four, were normally distributed in all data cells, as assessed by Shapiro-Wilk’s test (p > 0.05).

Levene’s Test of Equality of Error Variances was used to determine if there was homogeneity of

variance and the assumption of homogeneity of variances was violated (p < 0.05). Box’s test of

equality of covariance matrices was used to test for homogeneity of covariances, where there

was no homogeneity of covariances (p = 0.005), and thus the interaction effects were not

analyzed.

The two-way mixed ANOVA for the audiotactile TOJ showed no statistical significance in the

main effect of test times for JND, F(1, 16) = 0.846, p = 0.371, partial η2 = 0.050. The main effect

of group showed that there was no statistically significant difference in mean JND between

participant groups F(2, 16) = 0.482, p = 0.626, partial η2 = 0.057.

PSS

The ANOVA test was unable to come up with results as the values for PSS were miniscule.

Using the boxplot outlier feature in SPSS (International Business Machines Corporation,

Armonk, New York), the descriptive statistics identified zero outliers for values greater than 1.5

box-lengths from the edge of the box, or extreme outliers greater than 3.0 box-lengths, thus no

participants were excluded from this test. All PSS values were normally distributed in all data cells, as assessed by Shapiro-Wilk’s test (p > 0.05). Levene’s Test of Equality of Error Variances

40 was used to determine if there was homogeneity of variance and the assumption of

homogeneity of variances was not violated (p > 0.05). Box’s test of equality of covariance matrices was used to test for homogeneity of covariances, where there was homogeneity of covariances (p = 0.365)

41 1 Healthy Cx 1 Healthy Cx

0.8 0.8 Pre- Audio Pre- Audio Visual Tactile 0.6 0.6 Post- Audio Visual Post- Audio 0.4 0.4 Tactile

0.2 R² = 0.9895 0.2

0 0 -300 -200 -100 0 100 200 300 -300 -200 -100 0 100 200 300

1 Neck Cx 1 Neck Cx

0.8 0.8 Pre- Audio Tactile Pre- Audio Visual 0.6 0.6 Post- Audio Visual Post- Audio Tactile 0.4 0.4

0.2 0.2

0 0 -300 -200 -100 0 100 200 300 -300 -200 -100 0 100 200 300

Neck1 Treatment Neck1 Treatment

0.8 Pre- Audio Visual 0.8 Pre- Audio Tactile 0.6 0.6 Post- Audio Visual Post- Audio Tactile 0.4 0.4

0.2 0.2

0 0 -300 -200 -100 0 100 200 300 -300 -200 -100 0 100 200 300

Figure 5 graphical depiction of the average score for all SOAs for each group and task. The x-axis possesses the stimuli SOAs in milliseconds and the y-axis possesses the percent of “audio first” responses.

42 Discussion

The PSS values were too small for the statistical tests to be run and none of the tests showed any significance for the JNDs over time. Many assumptions were violated, such as normality after removing outliers, Box’s test of equality of covariance matrices, and Levene’s Test of

Equality of Error Variances. The removal of outliers, as assessed by the boxplot, meant that one or two participants per experiment did not have their data included, which lowered the power of the experiment. However, it was necessary to remove these outliers as the data indicated that they were not actually performing the task effectively (e.g. they weren’t just bad at the task, their values suggested that they weren’t even paying attention to the task), and hence it would not have been valid to include them.

It is probable that the TOJ method used may not have been effective in showing differences due to technical issues. Issues with timing aspects due to the technical specifications of the equipment and issues with task programming are evident within the results. In order to efficiently test multisensory integration, spatial, temporal, and intensity factors must be carefully considered. During the creation of the experimental design, these aspects were not considered, as the study design was based on past studies where these elements were not detailed in the methods. The importance of technical specifications in these sorts of experiments has recently been discussed by Bauer (2015). The laptop screen refresh rate, 60

Hz, was low, thus increasing latency. The graphical processor was weak and produced long latency as well as it was an integrated graphics card within a laptop. The sound card within the laptop and the driver were not built to decrease audio latency to minimum. The task, which was created through E-Prime 2.0, had several bugs. In some trials, especially the lower SOA

43 magnitude trials, the stimuli were being cut off earlier than required. In future studies, careful

consideration should be placed on the temporal aspect of the experimental setup.

Because of the above errors, the data were neither reliable nor valid. The PSS values were near zero, where it should be either negative or positive by a few milliseconds, such as in Zampini et al.’s (2005) research. Many participants had JND values greater than 100 milliseconds. This could mean that many participants did not understand the task or that stimuli were not effectively presented and data effectively recorded.

The consistency of the measurements over time was not very good for the TOJ task. One possible reason for this is there may be an experience or learning factor involved with the TOJ task. Zampini et al. (2005) have shown that participants that were experienced in the TOJ task performed better than those who were not. Thus, TOJ tasks may not be the best way to effectively measure multisensory integration in longitudinal studies.

“Study Two: Multisensory Integration in Subclinical Neck Pain Using Unisensory and

Multisensory Response Times”, the next chapter includes the results of a second experiment which addressed these technical issues encountered in this pilot study along with a new methodology.

44 Study Two: Multisensory Integration in Subclinical Neck Pain Using

Unisensory and Multisensory Response Times

Introduction

Neck pain has accounts for persistent musculoskeletal pain symptoms with significant disability in the general population (Hakala et al., 2006; Mikkelsson et al., 1999). Approximately 30-50% of people suffer from neck pain every year, which places a significant burden on the health care system (Hogg-Johnson et al., 2008). A specific category of neck pain is subclinical neck pain

(SCNP) which refers to a lower grade neck dysfunction where individuals do not have constant symptoms and have not yet sought regular treatment (H. J. Lee et al., 2004; H. J. Lee et al.,

2005; H. Y. Lee et al., 2008).

Altered afferent input through repetition and overuse changes in the way that sensory information is processed by causing plastic changes in the central nervous system (Byl &

Melnick, 1997; Haavik-Taylor & Murphy, 2007a, 2007b). Several studies have provided evidence for altered proprioceptive and neuromuscular function (Bränström et al., 2001; Falla et al.,

2004; Gogia & Sabbahi, 1994; Paulus & Brumagne, 2008). Further research has suggested that the altered afferent input arising from the SCNP and stiffness leads to altered sensorimotor integration (SMI), thus resulting in the improper motor response at the effector muscles

(Haavik-Taylor & Murphy, 2007a). It is hypothesized that other sensory modalities such as visual and auditory inputs are also processed differently causing altered multisensory integration

(Taylor & Murphy, 2012).

45 Previous research has shown that multisensory integration in populations like the elderly is

enhanced, as can been seen in a two-alternative, forced choice discrimination task involving measuring response times (Laurienti et al., 2006). Another study demonstrated that the elderly have both altered SMI and multisensory integration (Holt et al., 2016). Tasks such as the TOJ may not be effective at measuring multisensory integration as there is an experience component that “increases” multisensory integration (Zampini et al., 2005).

Areas in the thalamus integrate sensorimotor and multisensory processes (Cappe et al., 2009).

The superior colliculus is one example of a multisensory site which possesses access to efferent projections of premotor and motor areas of spinal cord and brainstem involved in superior colliculus mediated attentive and orientation behaviours (Meredith & Stein, 1986b), some that involve the saccadic movements of the eye, and neck movements, or “gaze shifts”. In addition to two sensory modalities terminating in a target area, a crossmodal projection of one sensory modality can also converge onto a different sensory site (Reinoso-Suarez & Roda, 1985).

Hairston et al. (2003) showed evidence for inverse effectiveness, where healthy participants, with artificially degraded vision (induced myopia), had their localization skills enhanced for audiovisual conditions, whereas in normal conditions the localization for multisensory

conditions was similar to unisensory conditions. These papers may suggest that a similar effect

may occur in the SCNP population, where that multisensory integration may be enhanced, due to ongoing alterations in sensory feedback from the neck joints and muscles which lead to degraded somatosensory input, similar to the degraded vision.

There are numerous different methods that can be used to measure multisensory integration

(Laurienti et al., 2006; Laurienti et al., 2004; Meredith & Stein, 1986b; Zampini et al., 2005). A

46 popular task that utilizes behavioural enhancements from multisensory integration is a two-

alternative forced-choice discrimination task with semantically congruent redundant stimuli

(Laurienti et al., 2006; Laurienti et al., 2004). When measuring multisensory integration,

temporal and spatial factors of the equipment used to present the stimuli must be carefully

considered when designing a task, as both timing and location of stimuli may reduce or deplete

multisensory activity (Meredith & Stein, 1986a; Nemitz et al., 1984). Unfortunately, many

studies fail to state or consider in detail the equipment being used in multisensory tasks, which

can hinder the results (Laurienti et al., 2006; Laurienti et al., 2004). This study will carefully

consider temporal and spatial aspects when designing the study.

The purpose of this experiment was to determine if there are any differences in multisensory

integration and response times in individuals with SCNP when compared to healthy (no neck

pain) participants. It was hypothesized that individuals with SCNP will possess slower response

times for both unisensory and multisensory stimuli, but enhanced multisensory integration.

Methods

Population

Participants were recruited from a university campus using advertisements in courses and

around the campus, and word-of-mouth. The groups of participants being recruited were young

adults (18-27 years old) differentiated by whether they had SCNP or not. The mean age for the

healthy controls, (n = 13 , 6 males) was 21.1 ± 2.1 years and for the SCNP (n = 12, 5 males) was

22.0 ± 2.1 years. The Edinburgh handedness scale (Oldfield, 1971) was used to determine which hand was dominant because the responses were performed with the right hand and it was

47 important to ensure that the number of left handed and ambidextrous individuals were similar

between the neck pain and control groups in case there were differences in movement or processing speed with the right limb, which would not have been the dominant limb for all

participants. The healthy control group had 7 right handed, 4 ambidextrous, and 2 left handed

participants, and the SCNP group had 9 right handed, 2 ambidextrous, and 1 left handed

participant.

A screening interview with questionnaires was performed to remove individuals with any

recent (last 5 years) history of epilepsy, any recent (last 5 years) history of head injury with loss

of consciousness, stroke, brain surgery, Parkinson’s disease, attention deficit-hyperactivity

disorder, psychiatric disorders other than treated depression, diabetes, serious vision problems

(other than refractive errors or astigmatism), color blindness, or uncorrected hearing problems

which might impact their capacity to perform the experiment.

SCNP participants must not have had chiropractic treatment in the month prior to the baseline

testing and they were required to delay treatment until after the 4-week measurement session

had occurred. Participants were excluded if they had previously experienced whiplash. The

participants had to have minimal to no neck pain on the actual testing days so that slower

movements in response to pain, would not confound the response time measurements. A

visual analogue scale with minimal pain severity on the left end of the scale and maximal pain

severity on the right was used to test the pain during the day of the study (no numbers between). A chronic pain grading scale was used to determine the severity of the neck pain in

general (Vonkorff, Ormel, Keefe, & Dworkin, 1992). Participants were asked to provide the

history, frequency, duration, location, and severity on the day of testing and during neck pain

48 flare-ups in the previous 6 months. Ethical approval was received through the University of

Ontario Institute of Technology Research Ethics Board. All participants had provided written consent before participating.

Two-Alternative Forced-Choice Discrimination Task

Multisensory integration was measured using a two-alternative forced-choice discrimination task that was similar to Laurienti et al.’s (2004) task. A trial consisted of either an auditory stimulus alone, visual stimulus alone, or a multisensory stimulus (auditory and visual), all in pseudo-random order. The participants were asked to discriminate between the colors blue or red, presented audibly through the verbalization of the colors for 300 milliseconds (a female voice says the word “blue” or “red”), visually through a circle filled with the corresponding color on a black background for 250 milliseconds, or simultaneously presenting both stimulus modalities for one colour (never conflicting colours). A trial began with a fixation cross in the center of the screen for 1 second, followed by the stimulus, and lastly a black screen for 8 seconds. From the onset of when the stimulus is presented by the program, the participant’s key press is able to be recorded and will initiate the next trial, enabling participants to skip the extra time allocated in the trial, if their responses are quicker. See Figure 6 for a visual representation of all three stimulus presentations for the color blue.

The test began with a series of practice trials that were performed as many times as needed until both the participant and the researcher felt they understood the task and how to perform it. For the task, participants were instructed to “respond as quickly and as accurately as possible”. The participants were instructed to press “v” on the keyboard with their index finger when they saw and/or heard the color red, press “b” with their middle finger for blue, and to

49 ignore the green stimulus. The unisensory stimulus were presented for 43 trials for each colour

(red or blue) within each stimulus type (auditory or visual), while the multisensory stimulus for

red and blue was presented for 63 trials each. The green stimulus was presented for only ~10%

of the total trials and its responses were not analyzed, as its purpose was to keep participants

from anticipating the answer, which could have occurred if there were only two possible

choices. Auditory

Auditory verbalization of the word blue (~300 ms)

Visual

Blue visual stimulus (250 ms) Response period (8 s) Fixation period (1 s) Multisensory response recording begins at the initial presentation of stimulus and continues to end of response period.

Auditory and visual stimulus of blue presented simultaneously (~300 ms) Figure 6 The three possible stimulus types for the presentation of the color blue

Apparatus

The task was created and recorded through the E-Prime 2.0 software (Psychology Software

Tools, Sharpsburg, Pennsylvania) in a Windows 8.1 desktop computer (Dell Optiplex 7020). The responses were recorded on a 1000 Hz polling Razer BlackWidow Ultimate Stealth mechanical keyboard. The visual stimulus was presented on a 60 Hz monitor (SyncMaster 2220WM) using a

50 DVI cable with a 5 millisecond gray-to-gray latency. The sound stimulus was presented on two

speakers side-by-side to the monitor. The speakers were connected to a SoundBlaster Audigy

FX soundcard with ASIO drivers to maximally reduce sound latency. The volume of the speakers was adjusted to a comfortable and easily discriminable level for each participant. The participants were seated comfortably at a constant distance from the monitor/speakers. The test was conducted again after 4 weeks.

Data Analysis

Each participant’s responses were analyzed separately. Outliers were removed from the response times, which were defined as responses greater than 2 standard deviations from the mean response time for each participant. Responses under 250 milliseconds were not eliminated (unlike Laurienti et al.’s study (2006)), as participants continued to possess high accuracy in this low range, see Table 3. For example, one participant had 21 responses lower than 250 milliseconds, but only one incorrect. In keeping with the Laurienti et al.’s study (2006), incorrect responses were included for response times. Response time and accuracy for the green stimulus were not analyzed.

Though the comparison of the mean accuracy through statistical tests was not the concern of the study, the mean accuracy was still calculated for reference. All statistical tests were conducted using SPSS version 23 (International Business Machines Corporation, Armonk, New

York). The mean response time was analyzed using a two-way [1 between-subjects factor

(participant groups = SCNP vs. healthy) x 1 within-subjects factor (test time = baseline vs. week

4) mixed ANOVA for each stimulus condition. To compare the multisensory gain between the two groups, the difference in response times between the fastest unisensory stimulus (visual)

51 and multisensory stimulus was calculated for baseline and compared using an independent t-

test. If the two stimuli being compared in the multisensory gain possessed no difference at

baseline and 4-weeks, the response time for the two were averaged in the test.

During preliminary data collection, it was observed that factors such as poor motivation,

performance anxiety, inattention, or a lack of understanding of the task requirements, all lead

to prolonged response times that did not reflect true task performance. Therefore, participant outliers were calculated and removed for each group using boxplots with more than 1.5 box-

lengths from the edge of the box. Studentized residuals were then calculated to ensure all data were between -3 to +3 residual values. This ensured that individuals whose results were different than the group mean because they didn’t perform the task as required, did not skew the genuine results. Shapiro-Wilk’s test was used to test for data normality. Mauchly’s test of

Sphericity to test for variance of the differences between groups did not apply since the

dependent variable was only measured at two levels. In order to test homogeneity of error

variance, Levene’s test of equality of error variances was used. Any significance in the

homogeneity of covariances test, Box’s test for covariances, were noted and thus interaction

effects were not assessed. Partial eta-squared (η2) was calculated for effect size, where small

was interpreted as 0.01, medium as 0.06, and large as 0.14. To compare the multisensory gain, an independent two-sample t-test was conducted.

In order to control for the gain that may be seen in multisensory due to the redundant nature

of the stimulus, cumulative distribution functions (CDFs) were plotted. Multisensory data were

compared with the predicted gain from the redundancy of the stimulus to determine if the

multisensory gain that may be seen was simply due to the redundancy effect (Miller, 1982).

52 This model, known as the race model, is calculated from a CDF by joint probability of the

unisensory conditions [(pAuditory + pVisual) – (pAuditory × pVisual)]. If the probability of the multisensory conditions is larger than the joint probability of the unisensory conditions, then the race model is violated, which suggests a neural integration (multisensory integration) of the two unisensory stimulus (Miller, 1982).

The CDF analysis was performed by analyzing each participant separately. Each participants’ cumulative frequencies were placed into time bins, which were created starting from 100 ms with an increment of 10 ms up to 1600 ms. The percent frequency distribution for each bin was averaged for each group to ensure the results reflected the group and not outlying bins or participants. With the CDFs obtained for each unisensory stimulus, the race model was calculated for each participant. Deviations from the race model were calculated by subtracting the probability of the race model from the probability of the multisensory conditions for each bin. A one-sample t-test was conducted for each time bin in each group and was compared to zero (no gain), where significant (p ≤ 0.05) deviations for each time bin was identified. A two- sample t-test was conducted to compare the deviations between the two groups, where significant (p ≤ 0.05) deviations for each time bin between the groups were identified.

53 Results

Stimulus type presented (total responses) Visual (86) Auditory (86) Multisensory (126) Week 0 4 0 4 0 4 SCNP Responses # of Responses < 250 ms 1 0.25 0 0 0.83 1.08 < 250 ms Accuracy (% correct) 83 67 n/a n/a 30 62 Control Responses # of Responses < 250 ms 1.42 2.92 0.08 0.08 3.33 3.42 < 250 ms Accuracy (% correct) 76 86 100 0 78 98 Table 3 The mean number of responses that were below 250 milliseconds for each group and stimulus condition, along with its accuracy of correct responses (%).

The mean responses below 250 milliseconds and mean accuracy can be found in Table 3. There

were a total of 86 audio and visual responses, and 126 multisensory responses by default, not

including green responses. The mean accuracy is reported in Table 4. The mean accuracy for

the healthy controls and SCNP groups exceeded 95% in all stimulus conditions. In all conditions except one (week 4 visual), the SCNP group possessed larger variation than the control.

Week 0 Week 4 Auditory Visual Multisensory Auditory Visual Multisensory RT 576 (64) 444 (69) 450 (70) 550 (74) 433 (42) 443 (55) SCNP Accuracy 97.3 (3.0) 96.2 (5.0) 95.8 (4.4) 96.6 (4.4) 95.8 (4.7) 96.3 (5.2) n 11 11 12 11 11 12 RT 552 (43) 396 (35) 396 (35) 533 (61) 396 (49) 392 (51) Control Accuracy 97.3 (2.3) 96.6 (2.9) 96.8 (2.6) 95.6 (2.7) 96.8 (1.7) 96.7 (3.6) n 12 12 12 12 12 12 Table 4 The mean response time (RT) in milliseconds, number of participants (n), mean accuracy in percent, and their standard deviations for each of the groups at baseline and week four.

The mean response times for both SCNP and healthy controls are reported in Table 4 and

Figure 7. Response times for the auditory stimulus were slower for the group with SCNP by a

mean difference of 24 milliseconds baseline and 17 milliseconds at week four, while the

response times for the visual stimulus was slower by 48 milliseconds baseline and 37 milliseconds at week four, when compared to the control group. The response times for the

54 multisensory stimulus possessed a difference of 52 milliseconds at baseline and 47 milliseconds

at week four between the groups, where the group with SCNP were slower.

Response Time (baseline) 650

600

550

500

450 Healthy

400 SCNP Response time (ms) 350

300 Auditory Visual Multisensory Stimulus

Figure 7 The baseline mean response time for all the stimulus conditions presented with a comparison for each group alongside each stimulus. One standard deviation caps are presented for each stimulus condition and group.

*Note: All assumptions and their tests along with the two-way mixed ANOVA can be found in Study Two: Sample Statistical Analysis Including Assumptions on Page 80 of the appendix. Auditory Stimulus

Using the boxplot outlier feature in SPSS, the descriptive statistics identified two outliers (1

SCNP participant, 1 control participant) for values greater than 1.5 box-lengths from the edge of

the box, thus these participants were excluded from this test. The studentized residuals for

week 0 and 4 then produced no values <-3 or >3. All response times were normally distributed

in all data cells, as assessed by Shapiro-Wilk’s test (p > 0.05). Levene’s Test of Equality of Error

Variances was used to determine if there was homogeneity of variance and the assumption of

homogeneity of variances was not violated (p > 0.05). Box’s test of equality of covariance

55 matrices was used to test for homogeneity of covariances, where there was homogeneity of

covariances (p = 0.256).

The main effect of test time [SCNP week 0 (576±64 ms) vs week 4 (550±74 ms) and control week 0 (552±43 ms) vs week 4 (533±61 ms)] showed a statistically significant difference in mean auditory response time at the different time days, F(1, 21) = 4.306, p = 0.050, partial η2 =

0.170, a large effect size. The main effect of group showed that there was no statistically

significant difference in mean auditory response time between the two participant group F(1,

21) = 0.799, p = 0.382, partial η2 = 0.037. The two-way mixed ANOVA for the auditory stimulus

demonstrated no significant interaction between test days and participant group on auditory

response time F(1, 21) = 0.082, p = 0.778, partial η2 = 0.004.

Visual Stimulus

Using the boxplot outlier feature in SPSS, the descriptive statistics identified three outliers (1

SCNP participant, 1 control participant with two outliers) for values greater than 1.5 box- lengths from the edge of the box, one of them being an extreme outlier with a value greater than 3.0 box-lengths from the edge of the box, thus these participants were excluded from this test. The studentized residuals for week 0 and 4 then produced no values <-3 or >3. All response times were normally distributed in all data cells, as assessed by Shapiro-Wilk’s test (p

> 0.05). Levene’s Test of Equality of Error Variances was used to determine if there was homogeneity of variance and the assumption of homogeneity of variances was not violated (p >

0.05). Box’s test of equality of covariance matrices was used to test for homogeneity of covariances, where there was no homogeneity of covariances (p = 0.004). Since this test failed,

56 the interaction effect between baseline and 4 weeks and stimulus condition was no longer

assessed in this test.

The two-way mixed ANOVA for the visual stimulus showed no statistically significant difference

in mean visual response time at the different test days [SCNP week 0 (444±69 ms) vs week 4

(433±42 ms) and control week 0 (396±35 ms) vs week 4 (396±49 ms)], F(1, 21) = 0.760, p =

0.393, partial η2 = 0.035. The main effect of group showed that there was a statistically significant difference in mean visual response time between the two participant groups F(1, 21)

= 4.490, p = 0.046, partial η2 = 0.176, a large effect size.

Multisensory Stimulus

Using the boxplot outlier feature in SPSS, the descriptive statistics identified one outlier (1 control participant) for values greater than 1.5 box-lengths from the edge of the box, thus this participant was excluded from this test. The studentized residuals for week 0 and 4 then produced no values <-3 or >3. All response times were normally distributed in all data cells, as assessed by Shapiro-Wilk’s test (p > 0.05). Levene’s Test of Equality of Error Variances was used to determine if there was homogeneity of variance and the assumption of homogeneity of variances was not violated (p > 0.05). Box’s test of equality of covariance matrices was used to test for homogeneity of covariances, where there was no homogeneity of covariances (p =

0.004). Since this test failed, the interaction effect between baseline and 4 weeks and stimulus

condition was no longer assessed in this test.

The two-way mixed ANOVA for the multisensory stimulus showed no statistically significant

difference in mean multisensory response time at the different test days [SCNP week 0 (450±70

57 ms) vs week 4 (443±55 ms) and control week 0 (396±35 ms) vs week 4 (392±51 ms)], F(1, 22) =

0.647, p = 0.430, partial η2 = 0.029. The main effect of group showed that there was a

statistically significant difference in mean multisensory response time between the two

participant groups, where the healthy group was faster F(1, 22) = 6.340, p = 0.020, partial η2 =

0.224, a large effect size.

Multisensory Gain

The fastest mean response time for the unisensory stimuli for both groups was for the visual stimulus, almost matching the multisensory stimulus. The mean response time for visual was faster than multisensory for the group with SCNP. An independent t-test was conducted to

compare multisensory gain between the two groups. Since the visual and multisensory stimuli

showed no significant change over time, the two values were averaged and the difference

calculated. Outliers were recalculated separate from those of the ANOVA, since the average of

week 0 and 4 created new response time values. Boxplots identified one participant (control) as an outlier and was thus removed. The comparison between the fastest unisensory response time mean to the multisensory response time mean (visual minus multisensory) between the control and the participants with SCNP yielded values of 2.5 ms (±2.5) and 4.2 ms (±6.4) respectively for the average of week 0 and week 4 measurements. Outliers were present as indicated by the boxplot, and one participant was removed. Shapiro-Wilk’s test for normality yielded no significance for both the control (p = 0.753) and SCNP (p = 0.717) groups. The assumption of homogeneity of variances was violated, as assessed by Levene’s test for equality of variances (p = 0.009), and thus a modified t-test, Welch t-test was used. There was no statistically significant difference in mean multisensory gain between SCNP and control, with

58 SCNP multisensory gain mean difference score was 1.78 (95% CI, -16.4 to 12.8), t(14.373) =

0.261, p = 0.797 higher than control multisensory gain.

Redundancy Control

The race model was compared with the multisensory condition in order to determine if there was a gain in multisensory integration beyond what can be predicted due to the redundancy effect (Miller, 1982). Even though no significant difference was seen in the weak multisensory gain between the groups in the earlier t-test, a CDF to compare with the race model was conducted, to determine if there were gain changes in some time bins, that could not have been reflected when simply comparing the means using a t-test. See Figure 8 for a graphical representation of the CDFs.

59 HEALTHY

Visual Auditory Multisensory RACE

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3

CUMULATIVE PROBABILITY CUMULATIVE 0.2 0.1 0 100 300 500 700 900 1100 RESPONSE TIME (MS)

SCNP

Visual Auditory Multisensory RACE

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3

CUMULATIVE PROBABILITY CUMULATIVE 0.2 0.1 0 100 300 500 700 900 1100 RESPONSE TIME (MS)

Figure 8 A comparison of CDFs for both healthy and SCNP groups. The race model is depicted in addition to the visual, auditory, and multisensory conditions.

60 A clear difference can be seen for all the curves, where the healthy group has their curves

shifted to the left in comparison to the SCNP group, indicating that the healthy group were

faster in all aspects. However, it is unclear from visual inspection of the graph if there are

significantly faster multisensory responses in comparison to either of the two unisensory

conditions. Further analysis from the one-sample t-test identified no significant difference (p >

0.05) in deviations of the multisensory condition from the race model in all time bins for the

healthy population. There was however a significant deviation (p ≤ 0.05) for the SCNP group in

time bins 290-320 ms in the positive direction (probability of multisensory integration >

probability of RACE) and 430-480 ms in the negative direction (probability of multisensory integration < probability of RACE). Thus, the SCNP group was the only group to show multisensory integration beyond the redundancy effect, and only for the 290-320ms time bins.

When the two groups were compared using the two-sample t-test to test for difference in

deviations, no significant differences (p > 0.05) were identified.

Discussion

The results shown are the first to reveal that there is a significant difference in response times for visual and multisensory stimuli in a two-alternative forced-choice discrimination task

between adults with SCNP and controls. These differences are not due to slower movement times in general, because previous studies of people with SCNP found no difference in simple response times in this population, although the SCNP group did have slower mental rotation response times in Baarbé et al.’s paper (2016).

61 Results from the SCNP group are similar to the slow unisensory response times seen in the elderly population in Laurienti et al.’s (2006) study. Though showing similar group differences between response times in the two groups, the actual response time values did not match

between the two studies. All of our mean values for response times for each stimulus condition

and the standard deviation were lower than Laurienti et al.’s (2006) study. We did not remove responses lower than 250 milliseconds, unlike Laurienti et al.’s (2006) study. The large differences in response times between the two studies (e.g. visual: 396 ±35 ms vs 538 ±117 ms) cannot solely be accounted for by the removal of outliers, as this would only account for a minor difference i.e. < 10 milliseconds. Another reason for this difference is that it is highly likely that we used equipment and drivers that produced a lower latency and variance than

Laurienti et al.’s (2006), however they did not provide these technical specifications in their article. It is important to note that our visual conditions mean response time for the healthy young adults (396 ±35 ms) was lower than their young adult controls for the multisensory condition (485 ±93 ms). There is a possibility that lower latency equipment is responsible for the weaker observed multisensory gain. The fact the our standard deviations were sometimes almost 1/3 of the values reported by Laurienti et al. (2006), coupled with our faster response times, suggests that our stimulus presentations were stronger and less “noisy” due to a combination of smaller delays and lower variability in timing of stimulus presentation and recording parameters of the equipment used to collect the data. For example, some sound cards have long latencies and substantial variability (>100 ms) within those latencies

(Psychology Software Tools, 2014) which could delay response times, independent of participant’s true response times, having the same effect as a “noiser” signal. The same effect

62 can be seen in graphic presentation, where we concentrated on lower display lag (5 ms).

Unfortunately, Laurienti et al. (2006) did not provide the technical specifications of their equipment so the latency response of their auditory and visual equipment is unknown. In

setting up this current experiment, great care was taken to ensure that there was minimal delay

in the stimulus presentation by: ensuring the graphic and sound card and their drivers were as

fast as possible, that the lag in the keyboard response time was as small as possible, and that

the next stimulus to be presented by the E-prime 2.0 software (Psychology Software Tools,

Sharpsburg, Pennsylvania) was stored in RAM, so that it was retrieved quickly upon trial onset.

All of these factors would explain the much faster response and lower standard deviations for

the healthy group data as compared to Laurienti et al. (2006).

The multisensory gain was not as we hypothesized, as the difference between the visual and

multisensory stimulus was extremely small for the control group and SCNP group, and there

was no significant difference in the multisensory gain between the two groups for both the

standard t-test and CDF analysis. This is dissimilar to other papers (Laurienti et al., 2006;

Laurienti et al., 2004), as they found a large difference between their visual and multisensory

stimulus for all their groups. The multisensory response times were similar to what the race

model had predicted as being simply due to redundancy gain. Most of the time bins revealed

that the multisensory gain seen was solely based on the redundancy effect, as most bins did not

violate the race model. However, the CDF from the SCNP group did show multisensory

integration beyond what was predicted by the race model between 290-320 ms, possibly

reflecting the increased gain that we hypothesized in the SCNP group. However, a significant

deviation below the race model prediction (e.g. decreased multisensory gain) was seen

63 between 430-480 ms, making it hard to draw definitive conclusions about differences in multisensory gain between the two groups. Additionally, the longer response times in

Laurienti’s et al.’s study (2006) suggest that the equipment they used may have had longer lag

times in stimulus presentation and recording, which would have effectively acted as “noise”.

Noise would have the effect of obscuring the strength of the stimulus signal, which

paradoxically could have enhanced multisensory gain, which is strongest when the unisensory

stimuli are weaker (Meredith & Stein, 1986b).

Another factor that may have led to weak multisensory integration was that the spatial,

temporal, and intensity factors of the stimulus that influence multisensory neurons were not

strong enough in this study to lead to significantly faster processing. Researchers have pointed to the importance of spatial and temporal factors in the stimulus presentation required to create multisensory integration (Meredith & Stein, 1986a; Nemitz et al., 1984), which may not have been effective enough in this experiment. Though the multisensory gain was not seen, and thus the integration of the multisensory stimulus may not have been effective, it is important to note that the separate unisensory stimulus, the visual stimulus, still provided a significant difference in response times. In other words, regardless of whether the integration was

“effective” for the multisensory stimulus, the visual alone stimulus cannot be disregarded as there were no possible integrative issues.

Some of the equipment may be seen as possible limitations to the study. This study utilized a

monitor that had an average of 5 milliseconds gray-to-gray latency, which may not have

allowed it to synchronize well with an auditory stimulus. Additionally, the monitor’s refresh rate

was 60 Hz, which could have added up to an additional 16.7 ms latency. The visual output could

64 be further improved by 1 millisecond latency and 144 Hz refresh rate monitors. The equipment

utilized in this study was not tested for accuracy, and latency values reported are based on the

specifications provided by the manufacturers. In multisensory integration, temporal factors are

important in determining when multisensory neurons may fire. For future studies, in order to strengthen a multisensory response, temporal, spatial, and intensity factors must all be considered. Bringing the auditory stimulus as close to the visual stimulus and making it as simultaneous as possible may increase multisensory integration.

Another possibility for the differences in our results to previous animal studies may relate to differences in upper level cortical processing. Felines possess efferent projections from the superior colliculus that were enhanced with multisensory input in behaviours involved with attention and orientation (Meredith & Stein, 1986b). Our study suggests that additional factors,

such as changes in projections from neck afferents, may interfere with upper-level cortical

processing, affecting the initially quick response times of multisensory neurons. As mentioned in the introduction, the superior colliculus integrates sensory inputs that involve movement and orientation behaviours (e.g. eye saccade, neck movement towards stimulus) (Meredith & Stein,

1986b). The altered sensory feedback from the neck in the SCNP group would have projected with other modalities onto these bimodal neurons, or through crossmodal projections onto

other sensory sites, potentially affecting multisensory processing. Our initial hypothesis was based on the concept that neck pain, like aging, would create a noisier system and longer unisensory response times, which we did find in the current study. However, we presumed that similar to Laurienti et al.’s study (2006) the multisensory neurons would show inverse effectiveness and greater gain to compensate. However, we failed to consider that neck pain is

65 different than aging in that some neck afferents project directly to these same multisensory

neurons, possibly altering their capacity to increase their gain to compensate for the slower

unisensory processing.

Even though there was no significant difference in multisensory gain, it is nevertheless

interesting to see the differences in the two groups for multisensory and visual response times.

In Taylor and Murphy’s study (2007a), they found that spinal manipulation improved SMI in

participants with SCNP. It would be interesting to see whether spinal manipulation or other

neck treatments would play a role in improving unisensory and multisensory response times.

Additionally, improving the temporal and spatial aspects of the multisensory stimulus

presentation might also improve multisensory gain. Future work should explore the impact of treatment while carefully addressing technical issues related to stimulus presentation.

66 Summary & Conclusions

Rationale & Purpose

The purpose of this thesis was to determine if adults with SCNP had altered multisensory

integration. Subclinical neck pain (SCNP) is defined as a category of chronic recurring neck pain

in which the individual has not yet sought regular treatment. In this thesis it was hypothesized

that participants with SCNP would have altered multisensory integration. This was based on the

research that showed SCNP had altered SMI and other populations possessing altered multisensory integration.

In order to assess multisensory integration, this thesis found effective techniques on human participants to be the TOJ task and Laurienti et al.’s (2006) two-alternative forced-choice

discrimination task. Experiment one created a pilot study for the TOJ task and assessed the

results. In the next experiment, improvements were taken from the pilot in order to increase

the effectiveness of data.

Summary of Findings

The first experiment, titled “Study One: Pilot Measuring Intersensory Synchrony in Subclinical

Neck Pain” used a TOJ task to assess the intersensory synchrony aspect of multisensory

integration. It hypothesized that multisensory integration would be altered in SCNP

participants, which would be seen by a high range in JND values.

The results were inconclusive for several reasons. Many participants had high and variable JND values which either meant many participants did not understand the task or the task was not implemented effectively. The experiment later found that the equipment and the task designed

67 on E-prime 2.0 (Psychology Software Tools, Sharpsburg, Pennsylvania) was not up to par with experiments that require careful timing. Creating a TOJ task with careful consideration to the temporal aspect is very important. The latency on the monitor, keyboard, sound, and software was large and possessed high variance. The task implemented contained many bugs which would sometimes cut the stimulus short. There were also limitations to TOJ tasks as research has pointed to an experience factor that would allow participants to perform better.

With the information attained from the pilot experiment, a new task was designed under an experiment titled “Study Two: Multisensory Integration in Subclinical Neck Pain Using

Unisensory and Multisensory Response Times” with careful consideration to the temporal components. The study used a two-alternative forced-choice discrimination task similar to

Laurienti et al.’s (2006) to assess the response times in multisensory integration and the change in measurements over time. This study hypothesized that SCNP participants would have lower response times but better multisensory integration than the control group.

The results for the second study found that the groups significantly improved over time for the auditory component only. The response times for the auditory and visual components were significantly higher for the group with SCNP than the control. There was no significant difference in the gain from the fastest unisensory stimulus (visual) to the multisensory stimulus between the two groups.

Prospective Research Directions

These studies open doors to future work involving multisensory integration in adults with SCNP.

The fact that auditory response times showed improvement in both groups over four weeks,

68 suggests that participants may “learn” to attend more to auditory stimuli as a result of

participating in the first experiment. This means that auditory response times may not be a

useful measure for longitudinal designs investigating using a two-alternative forced-choice

discrimination task. Future work needs to determine if auditory integration can be stabilized

with more baseline practice to improve the robustness of multisensory designs.

Future work could also incorporate a redesigned TOJ task with careful consideration of temporal and experience factors, as well as improved technical specifications of the hardware and software used to deliver and record the stimuli. It would be interesting to effectively measure intersensory synchrony in adults with SCNP to test if this aspect is altered, since the

TOJ task can implement a tactile component in addition to an auditory and visual component. A possible design utilizing the TOJ task could include measurement of a tactile component from stimulating the hand versus the neck in adults with SCNP.

Conclusion

In conclusion, this thesis found that adults with SCNP have slower response times for visual and

multisensory stimuli than healthy controls, but differences in multisensory integration were

inconclusive. The auditory component was found to improve over time, suggesting a need to

perform multiple baseline tests to ensure that baseline performance has stabilized before

including auditory stimuli in a longitudinal study. Response times may be used as one of many

biomarkers to test for the impact of SCNP on multisensory processing. This study opens doors to future studies that may look at the effects of treatments such as chiropractic manipulation on changing response times. This knowledge, and future studies with interventions, is

69 important knowledge. If neck pain genuinely influences multisensory processing, it has important implications for performance at work and home of tasks requiring multisensory integration, such as computer work, driving, sports, and even crossing the road. It is important to further develop robust tools so that changes in multisensory integration and the effects of treatment can be accurately assessed.

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76

Appendix

77 Study One: JND Boxplots

JND is measured in milliseconds

78

79 Study Two: Sample Statistical Analysis Including Assumptions Two-Way Mixed ANOVA Auditory These series of tests assume that each stimulus condition is unrelated and thus a separate dependent variable. A repeated measure must then be done on each stimulus condition for different time points.

A two-way mixed ANOVA is performed for the auditory response time for baseline and week 4. Assumptions:

 There must be one dependent variable measured at the continuous level: auditory response time is a continuous measurement.  There must be one between-subject factor measured at the categorical level: presence of subclinical neck pain is at a nominal, categorical level.  There must be one within-subject factor measured at the categorical level: time at week 0 and 4 is categorical.  There must be no outlier. Using the boxplot outlier feature in SPSS, the descriptive statistics found two outliers for values greater than 1.5 box-lengths from the edge of the box. Participants #12 (control) had an outlier at baseline and participant #21 (SCNP) had an outlier at baseline as well.

DECISION: Both participants were excluded from this analysis. A new participant then arises as an outlier but this is ignored, as this is from the new mean. The studentized residuals for week 0 and 4 produced no values <-3 or >3.  Data must be normally distributed. The test being performed is the Shapiro-Wilk test for normality. Reason: sample size is less than 50 participants and I am not confident in my visual

80 analysis skills using Q-Q Plots (not experienced with this). Response times were normally distributed in all data cells, as assessed by Shapiro-Wilk’s test (p > 0.05).

Kolmogorov-Smirnova Shapiro-Wilk Group Statistic df Sig. Statistic df Sig. Auditory Healthy .187 12 .200* .895 12 .138 reaction SCNP time .176 11 .200* .970 11 .886 baseline Auditory Healthy .162 12 .200* .955 12 .709 reaction time post SCNP .127 11 .200* .967 11 .856  Variance of dependent variable must be equal between the groups of the between-subjects factor. Levene’s Test of Equality of Error Variances was used to determine if there was homogeneity of variance. The assumption of homogeneity of variances was not violated (p > 0.05). F df1 df2 Sig. Auditory RT Week 0 1.354 1 21 0.258 Auditory RT Week 4 0.072 1 21 0.791  There must be homogeneity of covariances. Box’s test of equality of covariance matrices was used to test for homogeneity of covariances. There was homogeneity of covariances, as assessed by Box’s test of equality of covariance matrices (p = 0.256). Box’s M 4.523 F 1.352 df1 3 df2 111064.484 Sig. 0.256  The variance of the differences between groups should be equal. Mauchly’s test of sphericity is used to variance between groups. This test was not performed as the dependent variable is only measured at two levels, thus variance is assumed to be equal. Interpretation

1. Two-way interaction? There was no statistically significant interaction between learning time and presence of subclinical neck pain on auditory response time F(1, 21) = 0.082, p = 0.778, partial η2 = 0.004. 2. Any significant main effects? The main effect of learning time showed a statistically significant difference in mean auditory response time at the different time points, F(1, 21) = 4.306, p = 0.050, partial η2 = 0.170. The main effect of group showed that there was no statistically significant difference in mean auditory response time between the two groups F(1, 21) = 0.799, p = 0.382, partial η2 = 0.037.

81 Chronic Pain Grade Scale Pain intensity items 1. How would you rate your neck pain on a 0-10 scale at the present time, that is right now, where 0 is ‘no pain’ and 10 is ‘pain as bad as could be’? Pain as bad No pain as could be 0 1 2 3 4 5 6 7 8 9 10

2. In the past 6 months, how intense was your worse pain rated on a 0-10 scale where 0 is ‘no pain’ and 10 is ‘pain as bad as could be’? Pain as bad No pain as could be 0 1 2 3 4 5 6 7 8 9 10

3. In the past 6 months, on the average, how intense was your pain rated on a 0-10 scale where 0 is ‘no pain’ and 10 is ‘pain a bad as could be’? (That is, your usual pain at times you were experiencing pain.) Pain as bad No pain as could be 0 1 2 3 4 5 6 7 8 9 10

Disability items 4. About how many days in the last 6 months have you been kept from your usual activities (work, school or housework) because of neck pain? (# of days) ______

5. In the past 6 months, how much has neck pain interfered with your daily activities rated on a 0-10 scale where 0 is ‘no interference’ and 10 is ‘unable to carry on any activities’?

Unable to carry on No interference on any activities 0 1 2 3 4 5 6 7 8 9 10

6. In the past 6 months, how much has neck pain changed your ability to take part in recreational, social and family activities where 0 is ‘no change’ and 10 is ‘extreme change’?

No change Extreme change 0 1 2 3 4 5 6 7 8 9 10

7. In the past 6 months, how much has neck pain changed your ability to work (including schoolwork and housework) where 0 is ‘no change’ and 10 is ‘extreme change’?

82 No change Extreme change 0 1 2 3 4 5 6 7 8 9 10 Scoring guide characteristic pain intensity = (((response question 1) + (response question 2) + (response question 3)) / 3) * 10 disability score = (((response question 5) + (response question 6) + (response question 7)) / 3) * 10 disability points = (points for disability days) + (points for disability score) Disability points Disability days (0-180) Disability score (0-100) 0-6 Days 0 Points 0-29 0 Points 7-14 Days 1 Point 30-49 1 Point 15-30 Days 2 Points 50-69 2 Points 31 + Days 3 Points 70 + 3 Points

Classification

Grade 0 Pain free No pain problem (prior 6 months)

Grade I Low disability-low intensity Characteristic Pain Intensity Less than 50, and less than 3 disability points Grade II Low disability-high intensity Characteristic Pain Intensity of 50 or greater and less than 3 disability points Grade III High disability-moderately limiting 3-4 disability points, regardless of Characteristic Pain Intensity Grade IV High disability-severely limiting 5-6 disability points, regardless of Characteristic Pain Intensity

(Vonkorff et al., 1992)

83 Edinburgh Handedness Inventory

Please indicate your preferences in the use of hands in the following activities by putting a check in the appropriate column. Where the preference is so strong that you would never try to use the other hand, unless absolutely forced to, put 2 checks. If in any case you are really indifferent, put a check in both columns.

Some of the activities listed below require the use of both hands. In these cases, the part of the task, or object, for which hand preference is wanted is indicated in parentheses.

Please try and answer all of the questions, and only leave a blank if you have no experience at all with the object or task.

Task Left Right 1. Writing 2. Drawing 3. Throwing 4. Scissors 5. Toothbrush 6. Knife (without fork) 7. Spoon 8. Broom (upper hand) 9. Striking Match (match) 10. Opening box (lid) Total (count checks in both columns)

Difference Cumulative TOTAL Result

Scoring: Add up the number of checks in the “Left” and “Right” columns and enter in the “TOTAL” row for each column. Add the left total and the right total and enter in the “Cumulative TOTAL” cell. Subtract the left total from the right total and enter in the “Difference” cell. Divide the “Difference” cell by the “Cumulative TOTAL” cell (round to 2 digits if necessary) and multiply by 100; enter the result in the “Result” cell. Interpretation (based on Result): below -40 = left-handed between -40 and +40 = ambidextrous above +40 = right-handed

84 History of Neck Pain / Flare-ups How often do you experience neck pain (# days per month)? ______In what regions is your pain typically found? (mark areas with an X)

Adapted from “A new conceptual model of neck pain…`` by J. Guzman, E.L, Hurwitz, L.J. Carroll, S. Haldeman, P. Cote, E.J Carragee…J.D. Cassidy, 2008, Spine, 33, S14-S23

In the past six months, how would you rate your worse pain? (indicate with an X)

No Pain Extreme Pain

How would you rate your neck pain at the present time? (indicate with an X)

No Pain Extreme Pain

How long have you had this problem (i.e. two years)? ______Birthdate: ______Today’s date: ______Weight: ______Height: ______

85 The Neck Disability Index This questionnaire has been designed to give your therapist information as to how your neck pain has affected your ability to manage in everyday life. Please answer every question by placing a mark in the ONE box which applies to you. We realize that 2 of the statements may describe your condition, but please mark only the ONE box that most closely describes your current condition. Neck Pain Intensity Concentration o I have no pain at the moment. o I can concentrate fully when I want to with no difficulty. o The pain is very mild at the moment. o I can concentrate fully when I want with slight difficulty. o The pain is moderate at the moment. o I have a fair degree of difficulty in concentrating when I want to. o The pain is fairly severe at the moment. o I have a lot of difficulty in concentrating when I want to. The pan is very severe at the moment. I have a great, great deal of difficulty in concentrating when I want o o to. o The pain is the worst imaginable at the moment. o I cannot concentrate at all. Personal Care (eg washing, dressing) Work o I can look after myself normally without causing extra pain. o I can do as much work as I want too. o I can look after myself normally but it causes extra pain. o I can only do my usual work, but no more. o It is painful to look after myself, and I am slow and careful o I can do most of my usual work, but no more. o I need some help, but manage most of my personal care. o I cannot do my usual work. o I need help every day in most aspects of self care. o I can hardly do any work at all. o I do not get dressed, I wash with difficulty, and stay in bed o I cannot do any work at all. Lifting Driving o I can lift heavy weights without extra neck pain o I can drive my car without any neck pain at all. o I can lift heavy weights, but it gives extra neck pain o I can drive my car as long as I want, with slight pain in my neck. Neck pain prevents me from lifting heavy weights off the floor, but I can drive my car as long as I want, with moderate pain in my o I can manage if they are conveniently positioned, for example on a o neck. table I cannot drive my car as long as I want, because of moderate pain in Neck pain prevents me from lifting heavy weights, but I can manage o my neck. o light to medium weights if they are conveniently positioned I can hardly drive at all because of severe pain in my neck. I can lift only very light weights o o o I cannot drive my car at all because of the pain in my neck. o I cannot lift or carry anything Reading Sleeping o I can read as much as I want, with no pain in my neck. o I have no trouble sleeping. o I can read as much as I want, with slight pain in my neck. o My sleep is barely disturbed (les than 1 hr, sleepless). o I can read as much as I want, with moderate pain in my neck. o My sleep is mildly disturbed (1-2 hrs, sleepless). I cannot read as much as I want, because of moderate pain in my My sleep is moderately disturbed (2-3 hrs, sleepless). o neck. o My sleep is greatly disturded (3-5 hrs, sleepless). I can hardly read at all because of severe pain in my neck. o o o My sleep is completely disturbed (5-7 hrs, sleepless). o I cannot read at all because of pain in my neck. Headaches Recreation I have no headaches at all. I am able to engage in all my recreational activities, with no neck o o pain at all. I have slight headaches which come infrequently. o I am able to engage in all my recreational activities, with some pain I have moderate headaches which come infrequently. o o in my neck. I have moderate headaches which come frequently. o o I am able to engage in most, but not all of my usual recreational o I have severe headaches which come frequently. activities, because of pain in my neck. I have headaches almost all the time. I am able to engage in few of my usual recreational activities, o o because of pain in my neck. I can hardly engage in any recreational activities because of pain in o my neck. I cannot engage in any recreational activities at all because of pain o in my neck. Vernon, H. and S. Mior, The Neck Disability Index: A Study of Reliability and Validity. Journal of Manipulative and Physiological Therapeutics, 1991. 14(7): p. 409-415.

86 Neck Pain Mini-Questionnaire Indicate which statement best describes your neck pain.

I have neck pain all the time.

I have neck pain most of the time.

My neck pain comes and goes. Sometimes I have neck pain and sometimes I don’t.

I have neck pain on the rare occasion.

I never have neck pain.

In your own words, please describe the location, onset, and type of pain you experience:

Approximately how long have you had this problem? ______Have you had previous care for this condition? Yes No If yes, please check one: chiropractic physiotherapist Other: ______Approximately when did you have these treatments:______Have these treatments helped? Please explain.______Can you think of an accident or other event that caused your pain or stiffness? Check one: Yes No Unsure If yes, please explain: ______Have you had previous trauma? Yes No Explain:______Have you had previous surgery? Yes No If applicable, explain:______On a scale of 1 to 10 how severe is your neck pain or stiffness? 1 indicates little or no pain. 5 indicates uncomfortable, but manageable. 10 indicates unbearable – seek help now!

How often does your neck pain or stiffness occur (ex. Every two weeks) ______

When is your birthdate? ______

87 Consent Professor Bernadette Murphy University of Ontario Institute of Technology Faculty of Health Sciences 2000 Simcoe St. North Oshawa, Ontario CANADA L0B 1J0 Email: [email protected] Phone: xxxxxxx Fax: xxxxxxxx

Title: Behavioural and multisensory integration in healthy and subclinical neck pain participants over four weeks - January, 2016 This study has received ethical approval from the UOIT ethics committee (REB# 07-072 & 07-073)

This study is being conducted by Dr. Bernadette Murphy in conjunction with MHSc candidate Bassim Farid and fourth year practicum research students from the Faculty of Health Sciences at the University of Ontario Institute of Technology (UOIT), in Oshawa, Ontario, Canada.

Rationale for Research: Research has found that neck pain is a significant burden and affects 30 to 50% of people every year. Research is also showing that neck pain affects the way that people move and their awareness of head and upper arm positioning.

The research we are doing is showing how the brain responds to neck pain. We want to show how neck pain affects the integration of other sensory modalities.

Information for participants: To do this research, we will ask you to complete questionnaires which will provide information regarding your current functional capacity, level of neck pain (if any), and general well-being. We will then ask you to perform a test on the computer with pictures and audio.

We are seeking people with no neck problems or subclinical neck pain who are between 18 and 50 years of age. To participate in this study you must complete an eligibility checklist in conjunction with one of the researchers to ensure you are eligible to participate. You will also be given a chance to review the details of the study and ask any questions you may have.

Each evaluation session will take approximately 30 minutes and you will be given a chance to ask questions. It is recognized that research is fundamental to the university, and research experience allows one to grow intellectually, in support of the university tradition for creation of new knowledge. It is also recognized that volunteer work is an invaluable part of the undergraduate experience. Through participating in this study, you will be introduced, in some cases relatively early in your career, to the research tradition and be exposed to hand-on kinesiology work with state-of-the-art equipment. You will also be completing volunteer hours that could prove to be very useful for future job or graduate school applications. Participants who complete the cohort study can ask for a letter confirming they have completed these hours. Successful completion will also be recognized with two Tim Horton or Aramark cards of ten dollar ($10) value.

Your participation in this study is entirely voluntary (your choice), and you are free to decline taking part in this study. You may also withdraw from the study at any time without giving a reason. This will in no way affect your current or future chiropractic care, or your academic progress. Questions about your rights as a volunteer can be made to the Compliance Officer at xxxxxxxxxx ext. xxxx or [email protected] .

88 Measurement sessions: Should you agree to participate we will need you to attend two different sessions. These will be done over a four week period (on week one and week four).

Measurement procedures:

 We are looking at how neck pain affects how senses are perceived including vision and audition. To do this we will ask you to look at a series of events on a computer screen, as well as listen to a series of events. This experiment may take less than half an hour.

Risks and benefits The benefits of participating in this study is that you will learn more about neck pain and you will receive free treatment sessions with your preference. You will also be aiding our understanding of these costly and disabling conditions. Only safe conventional low amplitude spinal manipulation techniques will be employed in this study. These have been used by our research group in previous studies. Most participants have had very positive improvements in their outcome measures. On occasion, some participants may experience mild soreness the day after their first treatment, but this is only transient and is the first stage of the healing process.

If the information you provide is reported or published it is done in a way that does not identify you as its source. The data will be stored in a locked area at UOIT for seven years from the completion of the study after which it will be destroyed. You are free to withdraw from the data collection at any time up until the completion of your last data gathering session. Once you have completed the chiropractic care, your data cannot be withdrawn. Taking part in this study is voluntary and your decision to take part in this study (or not) will in no way influence your academic progress or relationship with your chiropractor and/or teacher.

Thank you very much for your time and help in making this study possible. If you have any queries or wish to know more please contact Dr. Bernadette Murphy, a Professor at the University of Ontario Institute of Technology, Faculty of Health Sciences, 2000 Simcoe St North, Oshawa, Ontario, L1H 7K4 Phone xxxxxxxxx Fax xxxxxxxxxx

For any queries regarding this study, please contact the UOIT Research and Ethics Committee Compliance Officer ([email protected] and xxxxxxxxxx ext xxxx).

The data from this research will be submitted to scientific conferences and peer reviewed journals. At the completion of the study, you will be sent a summary of the research findings and any place where the data has been published. All published data will be coded so that your data is not identifiable.

89 Please read the following before signing the consent form and remember to keep a copy for your own records.

• I understand that taking part in this study is voluntary (my choice) and that I am free to withdraw from the study at any time without giving a reason and that this will in no way affect my academic progress, irrespective of whether or not payment is involved.

• This consent form will be kept in a locked area at UOIT, Oshawa, Ontario for a period of seven years before being destroyed.

• The data collected in this study will be coded so that it is confidential from the consent form and stored in a locked area at UOIT, Oshawa, Ontario for a period of seven years before being destroyed.

I, …………………………………………...... agree to take part in this research.

• I understand that taking part in this study is voluntary (my choice) and that I am free to withdraw from the study at any time without giving a reason and that this will in no way affect my future chiropractic care and/or academic progress, irrespective of whether or not payment is involved.

• I have read and I understand the information sheet dated January 2016 for volunteers taking part in the study. I have had the opportunity to discuss this study. I am satisfied with the answers I have been given.

• I have completed an eligibility checklist to ensure I am eligible to participant in this research.

• I understand that I can withdraw any data I supply up to the completion of my last measurement session.

• I understand that my participation in this study is confidential and that no material which could identify me will be used in any reports on this study.

• I have had time to consider whether to take part.

• I know who to contact if I have any side effects to the study.

• I know who to contact if I have any questions about the chiropractic care portion of the study.

I give consent for the data from this study to be used in future research as long as there is no way that I can be identified in this research. YES NO (tick one)

I would like to receive a short report about the outcomes of this study (tick one) YES NO

Signed …………………………………… Date ……….....

Contact numbers of main researchers: Dr Bernadette Murphy, Phone: + xxxxxxxxxxxx

RESEARCHER TO COMPLETE

Project explained by: ______

Project role: ______

Signature: ______Date: ______

90