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Page 1: Running Head: PAIN AND PSYCHOLOGICAL AROUSAL Murdoch ... · Running Head: PAIN AND PSYCHOLOGICAL AROUSAL . Murdoch University . Honours Thesis in Psychology . The Relationship between

Running Head: PAIN AND PSYCHOLOGICAL AROUSAL

Murdoch University

Honours Thesis in Psychology

The Relationship between Pain and Arousal:

The Modulation of Noxious Sensation by the Brain’s Alerting Network

This thesis is presented in partial fulfilment of the requirements for the degree of

Bachelor of Psychology (Honours), Murdoch University, 2017.

Amber L. English

Word Count: 9,587

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Declaration

I declare that this thesis is my own account of my research and contains as its main

content work that has not previously been submitted for a degree at any tertiary

educational institution.

Name: Amber L. English

Signature:

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Copyright Acknowledgement

I acknowledge that a copy of this thesis will be held at the Murdoch University Library.

I understand that, under the provisions of s51.2 of the Copyright Act 1968, all or part of

this thesis may be copied without infringement of copyright where such a reproduction is

for the purpose of study and research.

This statement does not signal any transfer of copyright away from the author.

Full Name of Degree: Bachelor of Psychology with Honours

Thesis Title: The Relationship between Psychological Arousal and

Pain in Healthy Adults

Author: Amber Lee English

Year: 2017

Signed:

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Table of Contents

Cover Page ..................................................................................................................... i

Declaration .................................................................................................................... ii

Table of Contents ......................................................................................................... iv

List of Figures .............................................................................................................. vi

List of Tables............................................................................................................... vii

Acknowledgements ................................................................................................... viii

Abstract ........................................................................................................................ ix

Introduction ................................................................................................................... 1

Psychological Arousal ........................................................................................... 2

Pain ........................................................................................................................ 4

Nociception ........................................................................................................... 5

The Dorsal Horn .................................................................................................... 6

Bidirectional Spinal Modulation ........................................................................... 6

The Noradrenergic System .................................................................................... 9

Pain Catastrophizing ........................................................................................... 12

Nociceptive Flexion Reflex................................................................................. 13

Pupillary Dilation Reflex .................................................................................... 15

The Present Study ............................................................................................... 16

Hypotheses .......................................................................................................... 17

Methods ....................................................................................................................... 18

Participants .......................................................................................................... 19

Design ................................................................................................................. 20

Measures and Apparatus ..................................................................................... 20

Procedure............................................................................................................. 22

Data Filtering and Reduction .............................................................................. 25

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Data Analysis ...................................................................................................... 26

Results ......................................................................................................................... 28

Assumption Testing for MANOVAR ................................................................. 28

Pain Catastrophizing ........................................................................................... 29

Self-report Variables ........................................................................................... 29

Nociceptive Flexion Reflex Responses ............................................................... 32

Pupillary Responses ............................................................................................ 36

Discussion .................................................................................................................. 37

Hypothesis One: Pain Ratings and Arousal ........................................................ 38

Hypothesis Two: Nociceptive Reflex and Arousal ............................................. 39

Hypothesis Three: Pupillary Responses .............................................................. 42

Hypothesis Four: Pain Catastrophizing ............................................................... 43

Limitations .......................................................................................................... 44

Conclusions and Future Directions ..................................................................... 45

References .................................................................................................................. 46

Appendices ................................................................................................................. 66

Appendix A – Ethics Approval Letter ................................................................ 66

Appendix B – Sequence Order of Stimulus Presentation ................................... 67

Appendix C – Pain Catastrophizing Scale ......................................................... 68

Appendix D – Information Letter and Consent Form ......................................... 69

Appendix E – Univariate Normality and Violations ........................................... 72

Appendix F – Pupillary Response Means over Trials ......................................... 81

Appendix G – Summary of Project ..................................................................... 82

Appendix H – SPSS Output ................................................................................ 84

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List of Figures

Figure 1. Supra-spinal noradrenergic pathways ............................................................ 4

Figure 2. Brainstem mechanisms of pain modulation ................................................... 8

Figure 3. Measurement of the Nociceptive Flexion Reflex ........................................ 14

Figure 4. Electrode placement..................................................................................... 20

Figure 5. Staircase method for the Nociceptive Flexion Reflex ................................. 22

Figure 6. Experimental design .................................................................................... 23

Figure 7. Stimulus timing in experimental conditions ................................................ 24

Figure 8. Measurement of pupil size ........................................................................... 25

Figure 9. Mean pain ratings over trials ....................................................................... 29

Figure 10. Means for subjective self-ratings ............................................................... 31

Figure 11. Mean response rate over trials ................................................................... 33

Figure 12. Means for response rate and magnitude. ................................................... 34

Figure 13. Means for pupil size................................................................................... 36

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List of Tables

Table 1. Descriptives for Reflex Response Rate ......................................................... 33

Table 2. Descriptives for Reflex Response Magnitude ............................................... 35

Table 3. Descriptives for R3 Response Latency ......................................................... 36

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Acknowledgements

Firstly, I would like to acknowledge those who directly facilitated this thesis

project. Thank you to my supervisor, Professor Peter Drummond, for your wealth of

knowledge and for always making time for me. Thank you to Paul Mckay for all your

insight and help with my pupillometry data. Additionally, a big thanks to Mann Trac,

without you I don’t think most of the equipment would exist, let alone work!

Secondly, I would like to express my appreciation to all those who participated

in my study, for their time and ‘pain’. Thank you also to my fellow pain researchers,

especially the lovely Jessica Wright.

Thirdly, I would like to thank all my friends and family, who put up with the

eternally grumpy thesis-Amber. Thank you to my partner Shane Murphy for the late

nights at the lab, for being my guinea-pig, and for supporting me through this intense

year. A shout out to my psych squad, for the solidarity and sporadic good humour. And

all my love for the English family: Mama Kitty, Papa Bo and my little brother Jay.

Lastly, I would like to dedicate this thesis to those who departed from my life

this year: David English, Lilly, and Caitlyn Pickles. May you all rest in peace.

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Abstract

The literature indicates that pain is decreased by arousal in healthy individuals.

Conversely, arousal has been observed to increase pain in those with chronic pain. The

present study explored the relationship between psychological arousal and pain in healthy

adults (N=30). To elucidate this interaction, this study utilised an acoustic startle stimulus

and electrically-induced pain, while also manipulating stimulus timing. The acoustic

startle was presented prior to electrical stimulation, to act as the arousal induction. The

reverse stimulus timing, the acoustic startle presented after electrical stimulation, acted

as the experimental control. Using a repeated-measures design, timing effects were

evaluated according to physiological responses and subjective self-ratings. The main

hypothesis was that the presentation of the acoustic startle before electrical stimulation

would result in significantly lower pain ratings, in comparison to electrical stimulation

alone. Not only was this inhibitory effect supported but it extended to both pain and

sharpness ratings, in comparison to the reverse stimulus timing. In line with predictions,

pupillary responses supported that there was adequate physiological arousal in all

conditions. Contradictory to predictions, stimulus timing did not significantly alter

pupillary responses or spinal nociceptive reflexes. These physiological outcomes were

inconsistent with the interaction found between stimulus timing and participant ratings.

Additionally, Pain Catastrophizing did not correlate with the other pain measures and thus

was not included in the other analyses. Together, these findings suggest that prior

activation of arousal significantly inhibits the experience of pain in healthy individuals’,

at a purely supra-spinal level.

Keywords: pain, nociception, arousal, descending inhibition, spinal reflex, pupillometry

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The Relationship between Pain and Arousal:

The Modulation of Noxious Sensation by the Brain’s Alerting Network

There are stories of individuals achieving great feats while in severe pain, a

wounded soldier continues to run through the battlefield, a frostbitten climber continuing

to climb after hearing the rumble of an approaching avalanche. It is well known that a

state of arousal can greatly inhibit the intensity of pain in a healthy person (Vo, 2014).

Psychological arousal refers to the heightened alertness of brain areas involved in how

we perceive such experiences. Descending arousal pathways, from the brain to body, have

been implicated in both the reduction and amplification of pain (Millan, 2002; Pertovaara,

2006). Some theorists have cast arousal as an overarching mechanism which orients the

body to the most significant stimuli (Berridge & Waterhouse, 2003; Young et al., 2017).

For pain and arousal, a relationship is presumed but poorly understood (Dowman, Ritz,

& Fowler, 2016).

Where arousal reduces perceived pain intensity (Millan, 2002), it increases

physiological signs of pain (Kyle & McNeil, 2014). The literature demonstrates that it

broadly increases both autonomic activities (Chapman, Bradshaw, Donaldson, Jacobson,

& Nakamura, 2014) and pain withdrawal reflexes (Bradley, Moulder, & Lang, 2005; Koh

& Drummond, 2006; Kyle & McNeil, 2014). Further, while reducing pain in healthy

people, arousal has been shown to do the opposite in those with chronic pain (Drummond,

Finch, Skipworth, & Blockey, 2001; Drummond & Willox, 2013; Knudsen, Finch, &

Drummond, 2011).

Chronic pain affects nearly 20% of adults (Henderson, Harrison, Britt, Bayram,

& Miller, 2013). Living with persistent pain is associated with myriad challenges. It is

accompanied by both poorer mental health (Dersh, Polatin, & Gatchel, 2002; Forgeron et

al., 2010; Geisser, 2000; Snelling, 1994) and physical function (Henderson et al., 2013).

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In turn, practical difficulties threaten financial and vocational stability (van Leeuwen,

Blyth, March, Nicholas, & Cousins, 2006). All of these pressures are compounded by

social isolation (Forgeron et al., 2010; Snelling, 1994), and inadequate pain control

(Breivik, Collett, Ventafridda, Cohen, & Gallacher, 2006). Effective pain management is

rare, and many pain conditions are resistant to commonly administered pharmaceutical

treatments (Arnér & Meyerson, 1988; Blackburn-Munro & Blackburn-Munro, 2003).

Psychological arousal pathways are broadly implicated in the upregulation of pain in

chronic pain conditions (Taylor & Westlund, 2017). Hence, these mechanisms are a

promising target for research and treatment (Pertovaara, 2013).

This study aimed to enhance the future study of pain and associated conditions,

by exploring the functional relationship between pain and arousal in healthy participants.

This study provides a methodological framework and baseline data, to enable future

research to make valid comparisons between healthy and clinical populations.

Psychological Arousal

Psychological arousal is a broad construct referring to the general alertness of

brain areas responsible for how sensory input is perceived (Pfaff, 2006). This energised

state is normally induced by salient or biologically significant stimuli (Young et al., 2017).

It can be challenging to differentiate psychological arousal from overlapping mental

functions, such as attention (Coull, 1998), and parallel processes, such as physiological

arousal (Young et al., 2017). Arousal occurs without attention, but attention cannot

increase without arousal (Coull, 1998). The same applies to intense sensations (Rhudy,

Williams, McCabe, Russell, & Maynard, 2008), which are accompanied by arousal but

characterised by the involuntary reactions which occur in conjunction with them

(Samuels, Hou, Langley, Szabadi, & Bradshaw, 2007). The startle response is one such

set of reactions, occurring due to an intense and unexpected stimuli (Bradley et al., 2005).

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The startle-induced arousal state orients mental resources toward the stimuli and

suppresses irrelevant information, in order to enhance defensive processes (Dowman et

al., 2016). Sympathetic processes then mobilise the body, resulting in heightened

physiological arousal and rapid motor responses (Goldstein, 2013). Simultaneously,

psychological arousal activates higher processes and stimulates the sympathetic nervous

system.

Psychological arousal is communicated by networks of neurotransmitters, with

catecholamine systems the primary mediators (Lundberg, 2005). The catecholamine

noradrenaline is particularly important to psychological arousal as it innervates an

overarching alerting system (see Figure 1), composed of the Locus Coeruleus and regions

of the parietal and frontal cortex (Posner, 2008). This high-level psychological arousal

is relayed primarily via the noradrenergic system (Samuels & Szabadi, 2008a; Young et

al., 2017), whereas low-level arousal is mainly dopamine-mediated (Floresco, 2015).

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Figure 1. Supra-spinal noradrenergic pathways. Adapted from Higgins and George

(2009).

Pain

Pain is a dominating and unpleasant experience (Montes-Sandoval, 1999). It is

defined not only by sensation but also by pervasive thoughts and emotions (Weissman-

Fogel, Sprecher, & Pud, 2008). It does, however, serve important biological functions. It

alerts the body to threat or injury, enabling both protective and defensive processes

(Dowman et al., 2016). The unpleasantness of pain helps to protect the body by

conditioning avoidance of danger. Further, it initiates defensive operations in the nervous,

endocrine and immune systems which cooperatively minimise harm from danger

(Chapman, Tuckett, & Song, 2008).

Scientific understanding of higher pain processing has been revolutionised by

contemporary neuroimaging techniques. Many theorists point to a "Pain Matrix" of key

structures, due to consistent activation in frontal, parietal, somatosensory, insular, and

cingulate areas (Davis & Moayedi, 2013; Garcia-Larrea & Peyron, 2013). The evidence,

however, suggests that this network of activation is not unique to pain (Iannetti &

Mouraux, 2010; Salomons, Iannetti, Liang, & Wood, 2016). As a consequence, some

have returned to the more general "Neuro-matrix" theory (Melzack, 1999), in which pain

processing depends on multi-sensory and multi-modal integration (Legrain, Iannetti,

Plaghkib, & Mouraux, 2011; Mouraux, Diukova, Lee, Wise, & Iannetti, 2011). This

perspective emphasises the importance of functional pathways and relationships rather

than localised structures (Apkarian, Hashmi, & Baliki, 2011).

Nociception

Nociception refers to the detection of stimuli causing or potentially causing

damage, commonly termed "noxious stimuli" (Wiech, Ploner, & Tracey, 2008).

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Cutaneous pain, activated by noxious stimulation of the skin, is detected by nerves and

receptors in the peripheral nervous system and relayed to processing areas of the central

nervous system (CNS), which encompasses the spinal cord and brain (van Griensven,

Strong, & Unruh, 2013). The nerve fibres, termed nociceptors, respond preferentially to

noxious stimuli. Many are poly-modal, responding to chemical, thermal and mechanical

stimuli. The transmission of pain signals occurs along Aδ-fibres and C-fibres. Aδ-fibres

are highly myelinated, fast-conducting, and signal sharp pain. C-fibres, on the other hand,

are slow-conducting and signal dull, prolonged pain (Basbaum, Bautista, Scherrer, &

Julius, 2009). These afferent nerve fibres terminate in the spinal dorsal horn (Almeida,

2004). From there, inter-neurons relay information to sensory nerves in the CNS, for

higher processing, and motor nerves in the peripheral nervous system, for reflex reactions

(Snell, 2010).

The Dorsal Horn

The Dorsal Horn of the spinal cord is the first place that sensory inputs are

integrated (Le Bars, 2002). It is a multi-functional and multi-synaptic structure that is

organised into layers, termed laminae. Aδ nociceptors project primarily onto laminae I

and V, C-fibers project to laminae II and VI (Cordero-Erausquin, Inquimbert, Schlichter,

& Hugel, 2016). Within these layers, pain signals are inhibited or facilitated, especially

within laminae II, according to neural influences stemming from information about the

external and internal environment (Basbaum et al., 2009). These nociceptive signals are

relayed, via laminae VI, to the periphery as a part of reflex pathways (Snell, 2010). They

are also sent to higher structures for further processing, mainly via laminae I and V

(Cordero-Erausquin et al., 2016). Before higher processing, these nociceptive signals are

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further integrated by brainstem structures (Chapman et al., 2008). Information is relayed

from the spinal dorsal horn to various brain structures via two ascending tracts: the

spinothalamic tract, terminating in structures enabling the discrimination of pain qualities,

and the spinoreticular tract, which relays to limbic structures responsible for emotional

and cognitive elements of pain (Almeida, 2004).

Bi-directional Spinal Modulation

The relationship between nociceptive signals sensed in the periphery, and pain,

experienced in the brain, is a bidirectional one (Drummond, 2012). Current understanding

indicates that pain arises from the interaction between various networks in the spinal cord

and brain (Mendell, 2014). The dorsal horn does not passively transmit sensory messages

to higher structures. Rather, peripheral pain pathways interact with complex modulatory

mechanisms throughout the CNS (Millan, 2002). The seminal Gate Control theory of

Melzack and Wall (1965), and Melzack’s (1999) subsequent neuro-matrix theory,

crystalised contemporary understanding of pain communication throughout the body.

Melzack and Wall proposed that pain is "gated" by non-nociceptive stimuli, due to

competition between different forms of sensory input at various points in the spinal cord.

This mechanism is often referred to as "segmental" inhibition, as the distribution of pain

inhibition corresponds, anatomically, to segments of the dorsal horn (Clark & Proudfit,

1992). In addition to segmental modulation, pain signals can change as they cross the

spinal cord, proprio-spinally, or due to higher structures, supra-spinally (Sandkühler,

1996). Supra-spinal modulation can occur purely at the cortical level, involving processes

of perceptual appraisal (Rhudy et al., 2009). At the mid-level, ascending pain signals can

also be influenced by activity in the brainstem nuclei (Heinricher, Tavares, Leith, & Lumb,

2009; Schlereth & Birklein, 2008).

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Descending inhibition when greater than descending facilitation, “gates” pain

signals, resulting in analgesia (Millan, 2002). This suppression of pain signals is

particularly dominant following the detection of a dangerous or stressful stimulus.

Stressful conditions are frequently observed to lead to a range of adaptive responses and

general anti-nociception, presumably due to the biological imperative that pain does not

interfere with "fight or flight" (Chapman et al., 2008). This effect, known as stress-

induced analgesia, originates in cortical fear networks and modulatory systems in the

brainstem (Vo, 2014), through overlapping networks of stress and arousal (Valentino &

Van Bockstaele, 2008). Research suggests that it is mediated primarily by endogenous

opioids (Butler & Finn, 2009; Vo, 2014). Opioids exert their influence through the Peri-

aqueductal Grey (PAG) and Rostroventral Medulla (RVM), which connect directly to the

DH (Millan, 2002). Electrical stimulation and microinjection of opioid agents, into the

PAG and RVM, demonstrate that stress-induced analgesia can be abolished by blocking

these pathways or induced by their stimulation (Gebhart, 2004; Vo, 2014). However, this

analgesic effect is not mediated by opioids alone and a plethora of neuro-modulatory

mechanisms are involved (Butler & Finn, 2009). In particular, parallel inputs from

serotonergic and noradrenergic mechanisms are likely to be necessary for the full

expression of stress-induced analgesia (Millan, 2002). Serotonin, produced in the medulla,

forms part of an excitatory link between the PAG and RVM (Pertovaara & Almeida,

2006). Noxious stimulation activates both pro- and anti-nociceptive serotonergic

pathways and their effects rely heavily on stimulus parameters (Millan, 2002).

Noradrenaline shares a similar relationship with opioidergic pain modulation (see Figure

2), but unlike serotonin it is also demonstrated to exert independent effects on nociception

(Llorca-Torralba, Borges, Neto, Mico, & Berrocoso, 2016; Pertovaara, 2006, 2013).

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Figure 2. Brainstem mechanisms of pain modulation. Adapted from Brodin, Ernberg,

and Olgart (2016).

The Noradrenergic System

The Noradrenergic system is best known for its role in the initiation and regulation

of arousal (Berridge, 2008), though recent literature also emphasises its capacity for pain

modulation (Pertovaara, 2013). Through bi-directional transmission of noradrenaline in

the brain and spinal cord, this system coordinates general arousal, as well as specific

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responses to threat and reward (Young et al., 2017). Noradrenaline is a neurotransmitter

which enables rapid adaptive responses to stimulation (Bouret & Sara, 2005).

Noradrenaline acts directly on specific receptors, termed adrenoceptors, found throughout

the CNS. Physiological and pharmacological interventions demonstrate the arousal

effects of α1-adrenoceptor activation (Berridge, 2008; Berridge & Waterhouse, 2003).

The inhibitory influences of α2-adrenoceptors, on the other hand, are associated with

sedation and parasympathetic processes (Berridge & Waterhouse, 2003; Gyires, Zádori,

Török, & Mátyus, 2009). Similarly, central activation of α2-adrenoceptors usually exerts

an inhibitory influence over spinal nociception (Millan, 2002). To enable analgesia,

however, this inhibitory control must be greater than the pro-nociceptive influence of

spinal noradrenaline on α1-adrenoceptors (Drummond, 2012).

The Locus Coeruleus (LC) is a nucleus in the pons of the brainstem which directly

mediates psychological arousal (Carter et al., 2010) and indirectly regulates autonomic

arousal (Berridge, 2008). It is the primary source of noradrenaline in the brain (Wetzel,

Buttelmann, Schieler, & Widmann, 2016) and has projections throughout the cerebral

cortex, as well as directly to the dorsal horn (Szabadi, 2012). Noradrenaline directly

mediates arousal functions of the LC (Samuels & Szabadi, 2008b). The LC also exerts

indirect arousal modulation. Increased LC activity inhibits sedation-promoting GABA-

ergic neurons and excites alertness-promoting serotonergic and cholinergic systems

(Samuels & Szabadi, 2008a). The LC is robustly activated by specific stressors, such as

acoustic startle stimuli (Wetzel et al., 2016), and responds preferentially to noxious

stimulation (Irwin, Ahluwalia, & Anisman, 1986; Szabadi, 2012). Subsequently, LC-

mediated arousal directly controls reflex reactions such as the acoustic startle reflex and

pupillary reflex dilation (Szabadi, 2012). As these responses are also indicative of

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mechanisms involved in descending pain modulation, the LC-noradrenaline system is

broadly implicated in the intersection of arousal and pain (Chapman et al., 2014).

LC-mediated arousal contributes not only to analgesia, via inhibition of pain

signals, but also to hyperalgesia, due to pain facilitation (Millan, 2002). The timeframe

of activation binds the demonstrated effects of arousal on nociception. Arousal

inductions in healthy participants, such as body cooling, demonstrate the pro-nociceptive

influence of prolonged activation (Drummond, 2001). Similarly, prolonged pain appears

to activate unique mechanisms of the LC-noradrenaline system. While the injection of

spinal noradrenaline does little to alter basal pain in healthy people (Pertovaara, 2013), it

increases chronic pain (Ali et al., 2000). The LC-noradrenaline system is even referred

to as a "chronic pain generator", according to review of relevant neuro-chemical evidence

(Taylor & Westlund, 2017). Arousal is often investigated using neurochemical and

pharmacological interventions, but these often have wide-ranging limitations.

Pharmacological manipulation of arousal, for instance, has been argued to induce extra

effects that can produce false positives and compromise the validity of results

(Drummond et al., 2001). Functional research can provide the basic understanding of

these mechanisms that is needed before manipulation (Arendt-Nielsen, Curatolo, &

Drewes, 2007).

Recent studies have produced preliminary functional evidence for an inverse

relationship between LC-mediated arousal and chronic pain. Drummond and colleagues

(2001) demonstrated that various arousal stimuli decrease pain, to a subsequent thermal

pain induction, for healthy participants. A number of the same stimuli facilitated clinical

pain in those with Complex Regional Pain Syndrome. Acoustic startle stimuli, in

particular, have repeatedly been shown to increase pain ratings in those with chronic pain

(Drummond & Willox, 2013; Knudsen et al., 2011). Some have suggested that arousal

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can transform from analgesia to hyperalgesia, due to specific pathological changes in

noradrenergic mechanisms (Donello et al., 2011; Drummond, 2012; Rahman, D’Mello,

& Dickenson, 2008; Vanegas & Schaible, 2004). However, to explore and eventually

understand these relationships, further functional research is required.

Pain Catastrophizing

The interaction between arousal and pain intensity is not only bound by the temporal

properties of the activating stimuli (Schlereth & Birklein, 2008) but also the cognitive

and emotional state they are appraised in (Ploghaus et al., 1999). Emotional state

contributes up to 52% of the variance in perceived pain intensity, as indexed by both self-

report and physiological measures such as the Nociceptive Flexion Reflex (Rhudy et al.,

2008). While fear of an impending shock reduces pain intensity, anxiety has been shown

to amplify it (Ploghaus et al., 2001; Rhudy & Meagher, 2000). When this relationship

between stress and pain is pervasive, it likely indicates Pain Catastrophizing (Sullivan &

Neish, 1998).

Pain Catastrophizing is an exaggerated negative cognitive and affective state,

activated by nociceptive pain (Sullivan, Bishop, & Pivik, 1995). Many have highlighted

it as an important variable in the experimental measurement of pain (Edwards,

Haythornthwaite, Sullivan, & Fillingim, 2004; Quartana, Campbell, & Edwards, 2009;

Sullivan, Tripp, & Santor, 2000). It accounts for up to 31% of the variance in pain ratings

(Keefe, Rumble, Scipio, Giordano, & Perri, 2004), and is positively associated with

amplified pain responses in healthy (Seminowicz & Davis, 2006) and clinical populations

(Sullivan et al., 2001).

Sullivan and colleagues (Sullivan et al., 1995; 2001) proposed that catastrophizing

amplifies pain by altering spinal gating. This theory is supported by the negative

association between catastrophizing and diffuse noxious inhibition, a well-researched

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spinal pain modulating mechanism (Weissman-Fogel et al., 2008). On the other hand,

evidence suggests that it does not correlate with the Nociceptive Flexion Reflex (France,

France, al’Absi, Ring, & McIntyre, 2002; Rhudy et al., 2011; Terry, 2015). Hence, some

argue that catastrophizing is a purely supra-spinal mechanism (Rhudy et al., 2009; Rhudy,

Maynard, & Russell, 2007).

Nociceptive Flexion Reflex

Pain signals trigger many rapid bodily responses. While most autonomic

responses occur via relay stations in the brain, nociceptive input can also directly initiate

reflex movements via the dorsal horn (Benarroch, 2006). The nociceptive flexion reflex

of the lower limbs is one such response, often utilised as a measure of spinal nociception

(Dowman, 1991). It is consistently activated by painful nociceptive stimulation, acting to

withdraw the stimulated limb from a potentially harmful stimulus (Sandrini et al., 2005).

Withdrawal is accomplished by flexion at the ankle, knee and hip. The flexion reflex at

the knee, usually measured via the biceps femoris, is followed by a smaller reflex in the

hip, measured via the rectus femoris (Andersen, 2000; Arendt-Nielsen, Brennum, Sindrup,

& Bak, 1994; Hugon, 1973; Roby-Brami, & Brussels, 1987).

Electromyography (EMG) is the most common technique to measure this reflex,

which it does by recording the electrical signals that cause muscles to contract. The NFR

is characterised by three distinct phases of EMG activity; the tactile R2 component, the

nociceptive R3 component, and an involuntary movement response (Sandrini et al., 2005).

The latencies of the inconsistent R2 and more stable R3 correspond, respectively, to the

conduction velocities of the tactile Aβ fibres and the nociceptive Aδ fibres (Plaghki,

Bragard, Le Bars, Willer, & Godfraind, 1998). The R3 can only be invoked by stimulation

of Aδ fibres, though it recruits input from Aβ and C fibres (Skljarevski & Ramadan, 2002).

These signals are integrated proprio-spinally by wide dynamic range neurons in laminae

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V of the dorsal horn (Neziri et al., 2009). These neurons are multi-receptive to enable

rapid discrimination of the intensity and location of noxious stimuli to induce an effective

withdrawal reflex (Sandrini et al., 2005). Following the R2 and R3 is the associated startle

response, which is an involuntary movement response mediated by spinal and supra-

spinal pathways (Rhudy & France, 2007). The R3, on the other hand, is mediated

primarily at the spinal level (Cogiamanian et al., 2011; Rhudy et al., 2011).

The R3 has attracted significant interest in research as an "objective" measure of

pain processing (Sandrini et al., 2005). Usually measured via the ipsilateral brevis head

of the biceps femoris (see Figure 3), the magnitude of this response has been linearly

correlated with participant-rated pain intensity (Chan & Dallaire, 1989; Micalos,

Drinkwater, Cannon, Arendt-Nielsen, & Marino, 2008). The intensity of the activating

stimulus not only corresponds to the participants' subjective pain threshold, but the

maximum reflex response is associated with the level of "intolerable" pain intensity

(Skljarevski & Ramadan, 2002).

Figure 3. Measurement of the Nociceptive Flexion Reflex. Adapted from Baars et al.

(2009).

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This reflex highlights the complexity of spinal and supra-spinal pain mechanisms.

Supra-spinal mediators, such as Pain Catastrophizing, have been shown to disassociate

the flexion reflex from pain ratings (France et al., 2002). Further, the magnitude of this

reflex is mostly unaffected by cognitive influences strongly correlated with perceived

pain intensity (Jurth, Rehberg, & von Dincklage, 2014; Terkelsen, Andersen, Mølgaard,

Hansen, & Jensen, 2004). On the other hand, specific affective influences, such as fear,

are consistent with changes in both the flexion reflex and self-rated pain (Rhudy et al.,

2008).

There is some evidence that psychological arousal, via supra-spinal pathways,

may increase pain withdrawal reflexes (Bradley et al., 2005), even when it decreases self-

rated pain (Koh & Drummond, 2006; Szabadi, 2012). This has thus far only been

examined with the nociceptive blink reflex, however, and further study is required to

verify these findings.

Pupillary Dilation Reflex

The study of pupil size has been of increasing psychometric interest since its

emergence in the 1960’s. It provides a consistent method for verifying the interaction

between physiological arousal and wide-ranging mental activities (Laeng, Sirois, &

Gredebäck, 2012). Pupillary reflex dilation is an arousal response mediated by the

sympathetic nervous system (Diamond, 2001), described by some as an autonomous

orienting response (Einhäuser, Stout, Koch, & Carter, 2008; Gilzenrat, Nieuwenhuis,

Jepma, & Cohen, 2010).

Pupillary reflex dilation is controlled mainly by the noradrenergic system (Larson,

2001; Neuhuber & Schrödl, 2011). Noradrenaline, is understood to inhibit the

parasympathetic pathways responsible for pupillary light reflexes (Koss, 1986), and

excite the responsible sympathetic pathways (Szabadi, 2012). Research shows tight

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correlation between pupil dilation and increased activity in the LC. This has been

evidenced both in animals (Bouret & Sara, 2005; Rajkowski, Kubiak, & Aston-Jones,

1993; Rajkowski, Majczynski, Clayton, & Aston-Jones, 2004) and humans (Aston-Jones

& Cohen, 2005a, 2005b; Murphy, O'Connell, O'Sullivan, Robertson, & Balsters, 2014).

Pharmacological inductions of noradrenergic excitation have been shown to induce

parallel increases in pupil diameter and LC activity (Phillips, Szabadi, & Bradshaw, 2000),

while inhibitory drugs are shown to reduce them (Chapman et al., 2014). Functional

studies of pupillary reflex dilation demonstrate that it is highly responsive to both startling

(Wetzel et al., 2016) and noxious stimulation (Chapman, 1999; Chapman et al., 2014;

Kyle & McNeil, 2014).

The Present Study

This study aimed to explore the interaction of psychological arousal and pain

intensity. Specifically, this was tested using experimentally-induced arousal, evoked by

an acoustic startle, and unilateral limb pain, evoked by electrical stimulation.

Differing response types were assessed for each stimulus condition, to explore the

level of interaction. Each stimulus intensity was subjectively measured, to illuminate the

supra-spinal experience of each, including self-rated pain. The nociceptive flexion reflex

was used to index spinal processing, as it is considered a reliable indicator of spinal

nociception (Rhudy & France, 2007). Pupillary responses were used to provide a

methodological check of physiological arousal by each stimulus. Additionally, they were

indexed the intensity of processing at the level of the brainstem.

In this study, we intended not only to measure the outcomes of startle-induced

arousal and electro-cutaneous pain but also to discern the effect of their timing. The time

span of arousal has a pronounced effect on nociception (Drummond, 2001; Schlereth &

Birklein, 2008) but previous behavioural interventions fail to manipulate stimulus timing

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to elucidate them (Kyle & McNeil, 2014). Due to this, the present study included an

arousal induction followed by painful stimulation and an experimental control: an arousal

induction following painful stimulation.

The effect of a startle stimulus on pain perception is bound not only by stimulus

timing but also how it is perceived. Perceptual factors determine whether supra-spinal

arousal induces stress-induced analgesia or anxiety-induced hyperalgesia (Ploghaus et al.,

2001; Rhudy & Meagher, 2000). Due to this, the pain catastrophizing scale was included

as a measure of individual variability in pain perception.

Hypotheses

Hypothesis one: pain ratings and arousal. The primary hypothesis of was that

pain ratings would decrease when the acoustic startle was presented before the pain

stimulus, due to descending inhibition by supra-spinal arousal. These ratings were

predicted to be lower than those for painful stimulation alone. The control condition, of

pain followed by an acoustic startle, was expected to differ from painful stimulation alone.

However, due to the absence of such a control in the literature, the investigation of

responses was purely exploratory.

Hypothesis two: nociceptive reflex and arousal. The combination of the arousal

induction with painful stimulation was predicted to increase nociceptive reflex responses.

This increase was predicted due to the spinal summation of the sensory inputs, compared

to painful stimulation alone. The presentation of the startle, in the control condition, was

later than the expected response time of the R3, so an increase was anticipated only for

the involuntary movement response.

Hypothesis three: pupillary response. Pupil size was predicted to increase due

to both stimulus types. This methodological check was intended to demonstrate that the

stimuli were increasing arousal. The combination of the startle and pain stimulus was

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predicted to induce greater physiological arousal, as indexed by pupil dilation, compared

to either on their own.

Hypothesis four: pain catastrophizing. In line with prior studies, Pain

Catastrophizing was predicted to correlate positively with pain ratings but not with the

nociceptive reflex.

Methods

Participants

This study recruited 43 participants, 30.23% of whom failed to exhibit a reliable

Nociceptive Flexion Reflex response, within tolerable stimulation levels. Jensen, Biurrun

Manresa, and Andersen (2015) reported a failure rate of 29% for the present procedures.

While not consistently reported, this difficulty is evident in healthy volunteers (Biurrun

Manresa et al.) and chronic pain sufferers (Sterling, Hodkinson, Pettiford, Souvlis, &

Curatolo, 2008).

Of those recruited, 11 males and 19 females were successfully tested (N= 30).

Participants were aged between 18 and 36 years (M=23.53, SD=4.79). Volunteers were

primarily recruited through the Psychology Research Participant Portal. The remainder

were recruited via convenience sampling. Students were reimbursed with two hours of

research credit for their time. Participants recruited from the general populace were

compensated with a free coffee voucher.

The recruited sample was of physically and psychologically healthy participants,

between 18-60 years of age. It excluded those with chronic pain conditions, impaired

hearing, psychiatric conditions, or any illness for which analgesic medication is

prescribed. Additionally, pregnant women were excluded.

All participants gave informed written consent, according to procedures approved

by the Murdoch University Human Research Ethics Committee (see Appendix A).

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Design

This study had a repeated-measures design, in which experimental conditions

were presented in a pseudo-randomised predetermined order (see Appendix B). A within-

subjects single-session design was chosen due to the wide variability in nociceptive reflex

responses between participants and sessions (Sandrini et al., 2005).

Measures and Apparatus

Pain Catastrophizing Scale. This 13-item measure (see Appendix C) determines

individual levels of pain catastrophizing according to 3 factors; magnification, rumination,

and helplessness. It requires reflection on an earlier painful experience to rate the presence

and intensity of associated thoughts and feelings; from 0 (not at all) to 4 (all the time).

Scores were calculated by summing the individual responses to all thirteen items. The

total score ranges from 0-52.

The validity of this scale has been supported by comparison with convergent and

divergent measures (Osman, 1997; Osman et al. 2000). It demonstrates high internal

consistency (α = .87-.95), and test-retest reliability (r =.7- .75) (Osman et al., 2000;

Sullivan et al., 1995). Additionally, it has been validated in both healthy and chronic pain

populations (Osman et al., 2000; Van Damme, Crombez, Bijttebier, Goubert, & Van

Houdenhove, 2002)

Nociceptive Flexion Reflex. A Grass SD9 was used to deliver electrical

stimulation to invoke the flexion reflex. Stimulation was delivered using a custom-built

concentric electrode, composed of a ring-shaped stainless steel anode with a copper wire

cathode at its centre, with an outer anode diameter of 20mm and an inner diameter of

10mm. This stimulation was presented to one leg, with half of the participants tested on

their right and the other half on their left. The electrode was secured to the skin, behind

the lateral malleolus, over the sural nerve. The stimulus consisted of 10 square-waves, of

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1 ms duration, with 2 ms intervals, lasting a total of 30 ms. This stimulus format was

chosen to reliably invoke the flexion reflex at a reduced stimulus intensity (Arendt-

Nielsen, Brennum, Sindrup, & Bak, 1994; Khatibi, Vachon-Presseau, Schrooten, Vlaeyen,

& Rainville, 2014). The incremental duration was chosen to produce the perception of a

single stimulus (Skljarevski & Ramadan, 2002).

The reflex was detected via Electromyography (EMG), using two disposable

Cleartrode electrodes (ConMed Corporation, NY, USA) on each muscle group (see

Figure 4). For the rectus femoris, electrodes were placed 15 cm superior to the patella.

For the biceps femoris, they were placed 10 cm above the popliteal fossa. An inter-

electrode distance of 2 cm was used for both. Additionally, a ground electrode was placed

below the knee, to filter out electrical noise. Signals were amplified using an EMG

biopotential amplifier (Biopac Systems, Inc., USA). An MP 100 Biopac Systems

Analogue/Digital Channel receptor digitised the data at 2,000 Hz (Biopac Systems, Inc.,

USA).

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Figure 4. Electrode placement. Adapted from Herman (2016).

Visual Analogue Scale. Participants reported the intensity of perceived pain and

sharpness, verbally, according to a visual analogue scale, ranging from 0 (indicating no

pain/no sharpness) to 10 (indicating extreme pain/extreme sharpness).

The visual analogue scale has good convergent (r=.72- .95) and concurrent

validity (r=.71–.92), when compared with other pain scales (Good et al., 2001; Kelly,

2001; Ohnhaus & Adler, 1975). It also has good test-retest reliability (r= .71–.99) (Good

et al., 2001; Price, 1983).

Acoustic Startle Stimulus. Tone bursts were administered to both ears for all

participants. These were generated using a Biopac STM 100 module (Biopac Systems,

Inc., USA), at 110 dB for 50 ms. This intensity and duration consistently initiates a strong

startle response (Blumenthal, 1996). Loudness and discomfort were verbally rated on a

scale ranging from 0 (no loudness/discomfort) to 10 (extreme loudness/discomfort).

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Pupil Dilation Response. Pupillary responses were monitored in each trial.

Changes were captured using a pupillometer, with a macro lens and infrared attachment,

via an external trigger. Each trigger initiated a photo sequence, as well as the electrical

stimulus and/or the acoustic stimulus. Images were captured every 0.2 s, over 5 s duration,

with a total of 750 photos per participant. For each trial, 25 photos were directly uploaded

to a tethered computer. The pupillary response was defined as the difference between

mean pupil area (mm2), pre-stimulus, and maximum pupil area (mm2), post-stimulus.

Procedure

All testing was conducted by the student researcher (AE), in controlled laboratory

settings, at a constant temperature of 20 ± 1°c. Upon arrival at the laboratory, the

participant was presented with an information letter, explaining the nature and scope of

the study, with an attached consent form (see Appendix D). This was followed by the

Pain Catastrophizing Scale. Once these had been filled out, the participant was prepared

for the experiment. Due to the natural electrical resistance of human skin, which can be

compounded by dead skin and other debris (Fish & Geddes, 2009), the electrode sites

were shaved and cleaned using an abrasive soap and alcohol wipes.

The impedances, for both stimulating and output electrodes, were always below 15 kΩ.

Participants were seated for the remainder of the study, with their position adjusted so

that their knees were at an angle of 130° and ankles at an angle of 90°.

Nociceptive Reflex Calibration. Before data was collected, each participant was

tested for the level at which the nociceptive flexion reflex could be reliably induced. Once

seated, participants were administered three electrical stimuli to accustom them to

noxious sensations (Rhudy & France, 2007). To determine the participants’ threshold for

reflex activation, Willers’ staircase method was used (Willer, 1977). The electrical

stimuli were administered in pseudo-randomised intervals of 10-20 s, to avoid habituation

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(Lim, Sterling, Stone, & Vicenzino, 2011; von Dincklage, Olbrich, Baars, & Rehberg,

2013). Pain ratings were recorded after each administration. The stimulus intensity started

at 1 mA and was incrementally increased and decreased until the response was detectable

in 80% of trials (see Figure 5). The reflex was considered present if the mean peaks

exceeded 1.5 SD above the mean 60 ms pre-stimulus (Rhudy & France, 2007). The

experiment was discontinued if the intensity reached 10 mA, or the pain was rated

intolerable by the participant. The intensity of the last two peaks and troughs was

averaged, to get the threshold level, which was multiplied by 120%. The subsequent

supra-threshold level was employed for the remainder of the study.

Figure 5. Staircase method for the Nociceptive Flexion Reflex. Adapted from Hubbard

et al. (2011).

Experimental phase. For the experiment, each participant was directed to apply

headphones, for the acoustic stimulus. A sticker (5 mm) was placed below the right eye,

used as an absolute reference for pupil measurement. A forehead rest and chin rest were

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then adjusted to frame the participant’s pupils with the camera. They were directed to

lean forward and focus their sight on a label affixed to the wall behind the camera.

The participants were then administered the trials of stimulation (see Figure 6).

Figure 6. Experimental design.

Each of these conditions was initiated by the trigger, at varying delays following

the initiation of photo capture (see Figure 7). After each trial, the participant rated the

pain, sharpness, loudness and discomfort associated with the stimuli. There were 30 trials

in total with pseudo-randomised intervals of 30-60 seconds.

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Figure 7. Stimulus timing in experimental conditions.

Data Filtering and Reduction

Stimulus outputs, barring the changes in pupil size, were interpreted via the

Biopac System (Biopac Systems, Inc., USA), and filtered using the AcqKnowledge

software (Biopac Systems, Inc., USA). To remove electrical noise, EMG data were

filtered with a high pass filter, using a cut-off frequency of 20 Hz. Additionally, a band-

stop filter, ranging from 49 to 51 Hz, was applied to these waveforms.

A customised program was used to extract the response amplitude (i.e. area under

the curve (AUC)) for each component of the flexion reflex. The measured timeframe for

each component was 50 ms. There was 50 ms between measures of the R2 and R3, and

100 ms between the R3 and the involuntary movement response. The timeframes were

set manually per participant, around the highest peak for the R3. In keeping with the

findings of France, Rhudy, and McGlone (2009) responses were determined according to

normalized EMG scores; with reflex magnitude expressed as a percentage of the

participants’ maximum voluntary contraction (AUC).

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Additionally, the response latency of the R3 component was measured for each trial.

Responses were too variable for accurate latency measurements of each component.

Pupillary response data was first processed using customised software developed

by Paul McKay. This algorithm was designed to identify the height and width of each

pupil, per frame. Simultaneously, it identified the height and width of the comparison

sticker which served as an index, against which the absolute area (mm2) within each pupil

was quantified. For the purposes of this study, analyses were focused on the

measurements from left pupil. This side was chosen because it produced more exact

measurements, due to the positioning of the comparison sticker (see Figure 8).

Figure 8. Measurement of pupil size.

Data Analysis

Multivariate analysis of variance with repeated measures (MANOVAR) was run,

using an alpha level of .05, using the Statistical Package for the Social Science (V.240,

Chicago, USA) for each of the main dependent variables: self-report ratings, reflex

responses and pupillary responses. A number of authors recommend the use of

multivariate over the univariate approach, for repeated measures analysis (Gueorguieva

& Krystal, 2004; Keselman, Algina, & Kowalchuk, 2001). With due consideration to the

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trade-off of statistical power (Park, Cho, & Ki, 2009), this approach was chosen to

prioritise test validity (Stevens, 2012). The within-subject factors were: the conditions,

for stimulus timing, and the trials, over time. A small number of planned contrasts were

then used for each of these variables to confirm or deny specific hypotheses about the

relationship among the conditions. In keeping with the recommendations of Keppel and

Wickens (2004) the number of comparisons never exceeded 1 + ((3a - 1) / 2) – 2a (where

a=levels), to ensure an acceptable level of family-wise error. Lastly, a small number of

correlations were run to analyse pain catastrophizing.

Self-report variables. MANOVAR was run for each of the four self-report

variables: pain, sharpness, loudness and discomfort. First, analyses were conducted for

the experimental manipulation; for 10 trials of acoustic then electrical and 10 trials of

electrical then acoustic. Means for pain and sharpness were analysed for the electrical

only, acoustic-before and acoustic-after, conditions. Means for loudness and discomfort

were analysed for the acoustic only, acoustic-before and acoustic-after conditions.

Reflex responses. MANOVAR was conducted for each of the three reflex

components: the R2, the R3 and the involuntary movement response. First, due to the

inconsistency of the reflex response, the data was coded according to responses and non-

responses. Non-responses were determined when reflex AUC was below 10% of

maximum voluntary contraction. MANOVAR was conducted for the number of

responses, response magnitude and latency. The means were compared for the electrical

only, acoustic-before, and acoustic-after conditions.

Pupillary Responses. Pupillary responses were compared across conditions

using MANOVAR. Average pupil size was compared between baseline pre-stimulus and

maximum post-stimulus. These were also compared across stimulus conditions. Due to

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missing data, there were insufficient degrees of freedom to analyse the response across

trials.

Pain Catastrophizing. Catastrophizing was compared to the pain-specific R3

reflex response and self-rated pain scores. Pearson’s product-moment correlation

coefficient (r) was calculated for each of the conditions that satisfied normality.

Results

Assumption Testing for MANOVAR

The following analyses were completed to ensure the data satisfied the normality

assumptions underlying MANOVAR.

For univariate repeated-measures analysis, sphericity is assumed where there are

three or more dependent variables. Mauchly’s test revealed that this assumption was

violated across nearly all of the variables. As the multivariate analysis does not assume

sphericity, this supports the appropriateness of this approach (Scheiner & Gurevitch,

2001).

Due to the small sample size (N = 30), univariate normality was assessed using

Shapiro-Wilk and visual inspection of boxplots. On a small number of variables these

assumptions were not satisfied (see Appendix E). As MANOVAR is robust against mild-

moderate violations of normality, these abnormalities were not considered to be a threat

to the interpretation of analyses (Park et al., 2009; Tabachnick & Fidell, 2007). Further,

multivariate normality was considered satisfied from inspection of multivariate outliers.

The absence of multicollinearity, usually assumed by multivariate analysis, is not of

concern to MANOVAR, which is intended to analyse related factors (Nimon, 2012).

Additionally, the relationships evident between variables were deemed roughly linear,

from visual inspection of scatterplots.

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The homogeneity of variance-covariance matrices, usually tested with Box’s M,

could not be verified due to the singular cell matrices of repeated measures data (Potvin,

Lechowicz, & Tardif, 1990). Due to this Pillai’s test was used for all multivariate effects

as it is robust against such violations (Nimon, 2012; Scheiner & Gurevitch, 2001).

Pain Catastrophizing

A small number of correlations were performed to ascertain whether pain

catastrophizing was a significant covariate for the other pain measures, specifically the

subjective self-ratings of pain and the nociceptive R3 reflex. Firstly, some analyses were

run to ascertain whether the data satisfied the assumptions underlying correlational

analysis. Normal distribution was assessed using Shapiro-Wilk (see Appendix E).

Linearity and Homoscedasticity were evaluated using visual inspection of scatterplots.

Pain catastrophizing scores and self-rated pain scores met the assumptions of normality.

Pearson’s (r) was not significant for all of the conditions (PCS x Pain for Electrical only:

r(28) = .22, p = .248, PCS x Pain for Electrical then Acoustic: r(28) = .28, p = .135, PCS

x Pain for Acoustic then Electrical: r(28) = .09, p = .650). As the nociceptive reflex scores

violated the assumption of normality, they were analysed using Spearman’s rho, as

recommended by Tabachnick and Fidell (2007). This revealed that the relationship was

not significant, PCS x R3: rs = .12, p = .561. Catastrophizing scores were not included in

the other analyses, as all correlations were not significant.

Self-report Variables

Pain. Subjective ratings for pain differed significantly among the experimental

conditions (main effect for Condition: F(1, 29) = 40.84, p = .000, η2=.59) and over trials

(main effect for Trial number: F(9, 21) = 2.94, p = .020, η2=.56). However, there was no

significant interaction effect (Condition x Trial: F(9, 21) = 1.23, p = .33). Planned

contrasts revealed that pain ratings were lower when the acoustic startle was presented

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prior to the electrical stimulus than they were for the electrical stimulus followed by the

acoustic stimulus: F(1, 29) = 40.84 , p = .000, η2=0.59, and the electrical stimulus alone:

F(1, 29) = 17.94 , p = .000, η2=0.38. Additionally, there was a quadratic change in ratings

over trials: F(1, 29) = 11.65, p = .002, η2=.29. For depiction of effects over trials see

Figure 9, for descriptives see Figure 10.

Figure 9. Mean pain ratings over trials. Error bars denote standard error.

Sharpness. There was a significant difference between experimental conditions

(main effect for Condition: F(1, 29) = 6.80, p = .014, η2= .19) but no significant effects

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over trials (main effect for Trial: F(9, 21) = .93, p = .522, interaction effect for Condition

x Trial: F(9, 21) = 1.72, p = .148).

Planned contrasts revealed that sharpness ratings were significantly lower for the

acoustic-before than for the acoustic-after condition: F(1, 29) = 6.80, p = .014, η2=0.19.

They did not, however, differ from the electrical stimulus alone: F(1, 29) = .00, p = .984.

For descriptives see Figure 10.

Loudness. There was a significant effect for the experimental condition: F(1, 29)

= 5.93, p = .021, η2= .17. There were, however, no significant effects for the trial number

(main effect for Trials: F(9, 21) = 1.04, p = .440), or for their interaction (Conditions x

Trials: F(9, 21) = .96, p = .500).

Planned contrasts showed that the acoustic stimulus was rated to be significantly

louder when presented before electrical stimulation than it was for acoustic-after: F(1, 29)

= 5.93, p = .021, η2= 0.17, though not from the acoustic stimulus alone: F(1,29) = 3.41,

p =.075. For descriptives see Figure 10.

Discomfort. The discomfort ratings differed significantly between the

experimental conditions (main effect for Conditions: F(1, 29) = 4.43, p =.044, η2=.13).

However, there were no significant effects for the trial number (main effect for Trials:

F(9, 21) = 2.09, p = .079, interaction effect for Conditions x Trials interaction: F(9, 21)

= 1.23, p = .329).

Planned contrasts showed that discomfort to the acoustic startle was greater when

presented before, compared to after, electrical stimulation; F(1, 29) = 4.43, p = .044,

η2=0.13. It did not, however, differ significantly from the discomfort to the acoustic

stimulus alone: F(1, 29) = 1.86, p = .184. For descriptives see Figure 10.

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Figure 10. Means for subjective self-ratings. Error bars denote standard deviation.

Nociceptive Reflex Responses

Response Rate. The number of responses did not differ significantly among

conditions for any of the reflex components. There were no significant differences across

the electrical only, acoustic-before or acoustic-after conditions, for the R2: F(1, 29) =

2.36, p = .136, R3: F(1, 29) = 1.41, p = .244, or involuntary movement response: F(1, 29)

= .44, p = .514). For descriptives see Table 1.

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Table 1

Descriptives for Reflex Response Rate (%)

Condition R2 R3 Involuntary

M (SD) M(SD) M(SD)

Electrical 40.00 (46.01) 65.67 (42.24) 70.67 (38.95)

Acoustic then Electrical 28.00 (40.21) 63.33 (39.33) 72.67 (34.63)

Electrical then Acoustic 27.00 (43.48) 56.33 (44.84) 75.00 (37.67)

The number of responses differed significantly between the three reflex

components (main effect for NFR: F(2, 28) = 18.33, p = .000, η2= .57) and over trials

(main effect for Trials: F(9, 21) = 9.52, p = .000, η2= .80). However, there was no

interaction between the levels (NFR x Trial: F(17, 13) = 2.15, p = .083).

Planned contrasts revealed that the response rate was significantly lower for the

R2 component than the other two components: F(1, 29) = 29.89, p = .000, η2= .51.

Additionally, the R3 component was significantly lower than the involuntary movement

response F(1, 29) = 8.14, p = .008, η2= .22. Further, there was a significant linear decline

response rates over trials: F(1, 29) = 53.47, p = .000, η2= .65. For the depiction over trials

see Figure 11.

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Figure 11. Mean response rate over trials. Error bars denote standard error.

Response Magnitude. The magnitude of responses also did not differ

significantly between conditions. Across the electrical only, acoustic-before and acoustic-

after conditions there were no significant effects for the R2: F(2, 16) = 1.08, p = .364, R3:

F(1, 7) = 1.66, p = .239), or the involuntary movement response: F(1, 7) = 1.66, p = .239.

For descriptives see Table 2.

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Table 2

Descriptives for Reflex Response Magnitude (%)

Condition R2 R3 Involuntary

M (SD) M(SD) M(SD)

Electrical 26.78 (13.09) 29.30 (16.00) 31.93 (17.88)

Acoustic then Electrical 27.63 (9.77) 33.67 (20.66) 38.72 (25.68)

Electrical then Acoustic 25.92 (8.90) 27.35 (15.77) 28.55 (18.44)

None of the reflex components varied significantly over trials (main effect for

Trials: F(2, 10) = .81, p = .649) but they did differ significantly from each other (main

effect for NFR: F(2, 10) = 16.43, p = .001, η2= .77). Planned contrasts revealed that the

R2 had a significantly lower magnitude than the other two components: F(1, 11) = 36.07,

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p = .000, η2= .77), though there was no significant difference between the latter: F(1, 11)

= .98, p = .345. For descriptives see Figure 12.

Figure 12. Means for response rate and magnitude. Error bars denote standard deviation.

Response Latency. The latency of the R3 response differed significantly between

conditions: F(2, 21) = 5.502, p = .012, η2=.119. Planned contrasts revealed that the

response latency was significantly shorter when the acoustic was presented before the

electrical stimulus, compared to the other conditions: F(2, 21) = 9.21, p = .006, η2=.30.

For descriptives see Table 3.

Table 3

Descriptives for the R3 Response Latency

Condition Mean SD

Electrical 140.55 ms 27.04 ms

Acoustic then Electrical 127.88 ms 22.06 ms

Electrical then Acoustic 141.81 ms 26.80 ms

Pupillary Response

Pupil measurements, at baseline and maximum, differed significantly: F(1, 26) =

191.76, p = .000, η2=.88. Additionally, there was a significant effect for the stimulus

condition: F(3, 24) = 3.48, p = .031, η2=.30. There was, however, no interaction effect:

F(3, 24) = 1.84, p = .167.

Post-hoc analyses revealed that there was significant dilation across conditions.

This response was greater following the acoustic stimulus than it was for the electrical

stimulus: F(1, 26) = 4.56, p = .042, η2=.15. There was, however, no significant difference

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between the experimental conditions: F(1, 28) = .71, p = .406. For descriptives see Figure

13.

Figure 13. Means for pupil size. Error bars denote standard deviation.

Discussion

The current study aimed to explore the relationship between psychological arousal

and the healthy individual's experience of pain. The relationship was tested using the

combination of an arousal induction and pain evoked by electrical stimulation of the sural

nerve. The arousal induction, an acoustic startle stimulus, was presented before or after

the painful stimulus to explore timing effects. The acoustic startle and electrical stimulus

were also presented alone, in separate trials, as comparative measures. Additionally,

physiological measures were taken as a methodological check and to index different

levels of stimulus processing.

The literature shows that arousal can have a substantial inhibitory effect on pain

perception in healthy individuals (Millan, 2002). Conversely, it can have the opposite

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effect on those with chronic pain (Drummond et al., 2001; Drummond & Willox, 2013;

Knudsen et al., 2011). By increasing understanding of the functional relationship between

pain and arousal in healthy participants, future studies will be better equipped to clarify

pathophysiological mechanisms in chronic pain.

Hypothesis One: Pain Ratings and Arousal

The central hypothesis of the present study was that the acoustic startle stimulus

would have an inhibitory effect on the electrically-induced pain, due to the descending

influences of psychological arousal. In line with predictions, the presentation of an

acoustic startle stimulus before the electrical stimulus significantly reduced subjective

ratings of pain. In accordance with existing research, this reduction was significant in

comparison to pain ratings to the electrical stimulus alone. The exploratory investigation

revealed that this inhibition was specific to the stimulus timing, with pain rated

significantly lower for the acoustic-before than the acoustic -after condition. These

findings were further supported by the significant reduction in the sharpness ratings to

the electrical stimulus in the acoustic-before condition, compared to acoustic -after.

In addition to the difference between pain ratings, between conditions, there was

also a significant change over trials. The results reveal that pain ratings initially increased

and then progressively decreased over the remaining trials. This quadratic change was

likely due to the competing influences of sensitisation and habituation. Repeated

exposure to a noxious stimulus will generally result in the pain dulling or intensifying.

These opposing influences are mainly mediated at the supra-spinal level (Bingel, Schoell,

Herken, Büchel, & May, 2007; Rhudy, Bartley, & Williams, 2010) and relate to the

prioritisation of resources for homeostasis. Due to the biological imperative to protect a

threatened area from damage, pain signals can be amplified by sensitisation. However,

when a painful stimulus fails to invoke damage, pain signals can be inhibited by

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habituation (Eisenstein, 2001). The rise and fall of pain ratings in this study may reflect

initial sensitisation and then, in the absence of any signs of damage, habituation.

Additionally, the results show that the inhibitory influence of the arousal induction may

have interacted with these competing influences. In the acoustic -before condition

sensitisation was less pronounced and the habituation effect more dramatic.

Interestingly, while pain and sharpness ratings were lower in the acoustic-before

condition, the loudness and discomfort to the acoustic stimulus were higher. There was,

however, no significant difference in comparison to the acoustic stimulus alone. The

likeliest explanation is that pain signals inhibited acoustic intensity. Whether this

inhibition occurred at a spinal or supra-spinal level is, however, unclear. It is widely

accepted that pain has a substantial capacity to re-orient attention (Eccleston & Crombez,

1999), and is preferentially processed by the brain’s alerting network (Dowman et al.,

2016). However, it is also possible that the difference occurred due to a spinal effect, such

as pre-pulse inhibition. Pre-pulse inhibition refers to the inhibition of a startle response

due to sensorimotor gating by a weaker stimulus, presented 30-500ms prior (Braff, Geyer,

& Swerdlow, 2001). The “pre-pulse” can be in the same or different sensory modality

(Blumenthal, 1996), and has been previously demonstrated with electrical stimulation

(Blumenthal, Burnett, & Swerdlow, 2001). The observed effect could be due to the

electrical stimulus acting as a weaker pre-pulse gating the subsequent acoustic. Equally,

it could be due to the greater salience of the pain signals re-directing attention. The main

implication is that stimulus timing intrinsically binds that perceived intensity of sensation.

Hypothesis Two: Nociceptive Reflex and Arousal

The spinal nociceptive flexion reflex was measured to better understand how

spinal processing was involved, in the interaction between arousal and pain. It was

predicted that reflex responses would be stronger for the two experimental conditions

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than for the electrical stimulus alone, due to the summation of the sensory inputs.

Contrary to predictions, no significant differences were found between conditions for the

response magnitude, in any of the reflex components. The only significant effect that the

stimulus timing had on spinal responses was their latency, which was significantly shorter

in the acoustic-before condition. This increased responsiveness implies that there was

some effect from the descending influence of the arousal, induced by the acoustic startle.

The results did not support any effects of the startle stimulus at the spinal level. However,

the variability of the reflex responses may have compromised findings.

In keeping with the research, the tactile R2 component was significantly smaller

and less consistent than the other two components. However, the nociceptive R3 and

involuntary movement response also had variable response rates. This inconsistency

directly contradicts comprehensive review by Sandrini et al. (2005), which attests to the

reliability of Willers’ staircase method in activating the R3 component of the flexion

reflex. The observed inconsistency may be partially attributable to habituation effects.

The significant linear decline observed supports the presence of habituation across reflex

components, for both response rates and response magnitude. Usually, however, this

reduction is observable only for response size (Sandrini et al., 2005). It is only severe

enough to significantly affect response consistency when the habituation effect is

magnified, for instance with weaker stimulus intensities (von Dincklage et al., 2013). The

SD9 stimulator stimulator that was used in the present study restricted the strength of the

electrical stimulation, as it could only emit a maximum of 100 volts. This study

compensated for the reduced voltage in a couple of ways. Firstly, a more substantial

electrical stimulus of 10-square waves was chosen rather than the usual five. Secondly, a

single concentric electrode was selected, rather than two bipolar electrodes, to administer

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more concentrated stimulation. However, as this stimulated a smaller surface area, it may

have impacted upon the reliability of stimulating the nociceptive receptive field.

Due to the inconsistency of the induction procedures, non-responses could have

impacted significantly upon statistical power (Schafer & Graham, 2002). To address this

the rate of responses (vs. non-responses) was analysed to discern any significant effects

that may have influenced findings. There were no significant differences in response rate

between any of the conditions, implying that it was unlikely to have systematically altered

effects. As there is already a reduction in statistical power intrinsic to MANOVAR,

however, this study is still at a heightened risk of committing a type II error. The findings

failed to support any spinal interaction between pain and arousal, other than the priming

of a swifter R3 response by the arousal induction. While the lack of significant findings

contradicts previous research (Bradley et al., 2005; Koh & Drummond, 2006; Szabadi,

2012) the literature on this topic is severely limited. Additionally, inspection of the

univariate output indicated that there were no significant findings that went undetected

due to the multivariate approach. The lack of meaningful relationship between this

response and startle-induced arousal is consistent with the hypothesis that the observed

interaction between arousal and pain is psychological. The lack of association between

this spinal response and the significant supra-spinal effects introduces the possibility that

the relationship may be purely supra-spinal. Due to the inconsistency of the reflex

induction methods, however, further research is required to substantiate these

interpretations.

Hypothesis Three: Pupillary Response

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Pupil size was predicted to increase in all conditions. The dilation was expected

to be greater for the combination of acoustic and electrical stimulation, compared to either

on their own. Pupillary responses fulfilled their role as a methodological check but failed

to support predicted differences. The results show that there was consistent pupil dilation

in each stimulus condition, supporting that the stimuli were inducing the intended

physiological outcomes. Contradictory to prediction, the experimental conditions were

not significantly different from baseline. Additionally, they did not differ significantly

between each other. As pupillary reflex dilation is under direct control of the brainstems

Locus Coeruleus (Larson, 2001; Neuhuber & Schrödl, 2011), the null results imply that

stimulus timing did not affect mid-level processing. This supports that the observed

effects for self-ratings were likely supra-spinal. However, the quantity of missing

response data limits this interpretation. Due to participants’ movement during the

experiment, many of the pupil photos were not of a high enough quality to make accurate

pupil measurements and thus were discarded. The subsequent reduction in power may

have contributed to the null result of experimental conditions. Due to this, future

researchers are advised to secure the participants’ head during pupillometry.

Due to missing data, this response could not be explored over trials, using

MANOVA. However, inspection of univariate output and response means (see Appendix

F) showed a roughly linear decline in pupil size. This may indicate a habituation effect,

akin to that found for reflex responses

The only significant difference was between the single stimulus conditions, with

the acoustic startle alone inducing a significantly greater response than the electrical

stimulus alone. This finding implies that the acoustic startle may have been the more

perceptually intense stimulus. Overall, these results support the induction of arousal, but

any interaction between pain and arousal was likely supra-spinal.

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Hypothesis Four: Pain Catastrophizing

Pain Catastrophizing was predicted to correlate positively with pain ratings.

Conversely, catastrophizing was predicted to have no significant associations with

nociceptive reflex responses. The analyses revealed that it was not associated with either

of the pain-specific measures. The absence of a relationship between catastrophizing and

the nociceptive flexion reflex was in line with predictions and supports the argument of

Rhudy, France and colleagues(2002; 2009; 2011; 2007) that catastrophizing exerts a

supra-spinal and not spinal effect on the experience of pain. The lack of association with

pain ratings, however, contradicts predictions and previous findings. The Pain

Catastrophizing Scale is consistently associated with subjectively rated pain, in healthy

participants (Sullivan & Neish, 1998; Sullivan, Rouse, Bishop, & Johnston, 1997;

Sullivan et al., 2001; Sullivan et al., 2000), across a range of electrical intensities

(Seminowicz & Davis, 2006). In the present study, catastrophizing did not correlate with

pain ratings in any of the conditions. One possible explanation is that catastrophizing was

not appropriately measured. There is some evidence that the catastrophizing only

correlates significantly with pain scores when administered closely after painful

stimulation (Dixon, Thorn, & Ward, 2004; Edwards, Campbell, & Fillingim, 2005;

Edwards et al., 2004). Dixon et al. (2004) found that pre- and post-test measurements of

catastrophizing did not correlate well (r=0.46) with those taken during an experimental

pain induction. This scale conceptualises catastrophizing as an underlying trait or

disposition activated by painful experiences. The measurement of catastrophizing, before

the experiment, relied on the participants’ recall of a potentially distant referent (Quartana

et al., 2009). Future researchers are advised to administer the scale during experimental

proceedings, to ensure accurate interpretation of this factor.

Limitations

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Several limitations need to be considered in the interpretation of results. The first

significant weakness was the generalizability of the findings. As the sample relied

primarily on young-adult students, it is unclear whether findings apply to the broader

population. Additionally, the reported violations of normality may aggravate this.

MANOVA is robust against moderate violations, but some of the more severe violations

may have reduced statistical power.

A second limitation was the reliance on self-report measures to evaluate the

perceived stimulus intensities. However, to minimise potential biases, the participants

were blind to all hypotheses.

A third major limitation was the high failure rate associated with the nociceptive

reflex induction procedures. As nearly a third of participants failed to exhibit a

measurable nociceptive flexion response, the failure rate presents a significant threat to

the generalizability of results. While this rate is within the normative range, this limitation

is one that is frequently overlooked and under-reported in the literature (Jensen et al.,

2015). One recommendation to reduce failure rates, is to stimulate the medial arch of the

foot rather than the sural nerve, behind the ankle. Stimulation of this area while

participants are standing, has been shown to result in lower failure rates and lower

subjective ratings of discomfort (Jensen et al., 2015; Lewis, Rice, Jourdain, & McNair,

2012). It should be taken into consideration that the medial arch of the foot has a

significantly smaller nociceptive receptive field (Neziri et al., 2009), which would require

a more diffuse stimulation than that used in this study, to ensure constant stimulation.

This reflex induction method was not viable in the present study due to the required

positioning of participants for pupillometry. Without these restrictions, however, this

approach provides a promising avenue for the improvement of future research.

Conclusions and Future Directions

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The main finding of this study was that the presentation of an acoustic startle

before electrical stimulation reduced subsequent pain perception. This inhibitory effect

was significant in comparison to both electrical stimulation alone and the reverse stimulus

timing. The difference between the arousal induction and electrical stimulation alone is

in line with previous research, supporting that an interaction occurred. The presence of

an inhibitory effect only for the prior arousal induction suggests that the relationship is

temporally bound. This interaction was not evident in pupillary responses or nociceptive

reflex results, implying that the inhibitory mechanisms involved may be purely supra-

spinal.

This study supports the effect of descending inhibition, due to prior activation of

arousal systems, on the healthy individuals’ experience of pain. Due to the limitations

and restricted scope of this study more research is needed to understand this relationship

entirely. Despite the acknowledged limitations, this study provides a strong indication of

how arousal interacts with pain. This interaction is not only crucial to the general

understanding of healthy populations but could also have significant functional

implications for chronic pain. Preliminary evidence has already emerged for an inverse

relationship, between pain and arousal, in those with chronic pain. Is this interaction

similarly bound by the temporal properties of the activating stimulus? Is it restricted by

individual factors such as pain catastrophizing? And does the interaction occur at a spinal

or supra-spinal level? These questions are essential, not only to greater understanding but

also to the development of effective treatments.

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Appendix A

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Ethics Approval Letter

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Appendix B

Scoring Sheet with Sequence Order of Stimulus Presentation

1) A 2) E 3) EA 4) AE 5) AE 6) A 7) EA 8) E 9) AE 10) EA Series 1 Pain, Sharp

Loud, Discomfort

NFR

11) AE 12) EA 13) AE 14) E 15) EA 16) AE 17) A 18) EA 19) AE 20) A Series 2 Pain, Sharp

Loud, Discomfort

NFR

21) E 22) EA 23) E 24) AE 25) A 26) EA 27) AE 28) EA 29) AE 30) EA Series 3 Pain, Sharp

Loud, Discomfort

NFR

Key: A denotes acoustic stimulus only; E denotes electrical stimulus only; AE denotes the acoustic followed by

electrical stimulus; EA denotes the electrical followed by the acoustic stimulus.

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Appendix C

Pain Catastrophizing Scale

Everyone experiences painful situations at some point in their lives. Such experiences may include headaches, tooth pain, joint or muscle pain. People are often exposed to situations that may cause pain such as illness, injury, dental procedures or surgery. Instructions: We are interested in the types of thoughts and feelings that you have when you are in pain. Listed below are thirteen statements describing different thoughts and feelings that may be associated with pain. Using the following scale, please indicate the degree to which you have these thoughts and feelings when you are experiencing pain.

RATING 0 1 2 3 4

MEANING Not at all To a slight degree

To a moderate degree

To a great degree

All the time

When I am in pain….

No Statement Rating

1 I worry all the time about whether the pain will end.

2 I feel I can’t go on.

3 It’s terrible and I think it’s never going to get any better.

4 It’s awful and I feel that it overwhelms me.

5 I feel I can’t stand it anymore.

6 I become afraid that the pain will get worse.

7 I keep thinking of other painful events.

8 I anxiously want the pain to go away.

9 I can’t seem to keep it out of my mind.

10 I keep thinking about how much it hurts.

11 I keep thinking about how badly I want the pain to stop.

12 There’s nothing I can do to reduce the intensity of the pain.

13 I wonder whether something serious may happen. Copyright 1995 Michael J. L. Sullivan. Reproduced with permission. Source: Sullivan MJL, Bishop S, Pivik J. (1995). The pain catastrophizing scale: Development and validation. Psychol Assess, 7(4), 524-532.

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Appendix D

Information Letter and Consent Form

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Appendix F

Pupillary Response Means over Trials

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Appendix G

Thesis Summary

There are stories of individuals achieving great feats while in severe pain, a

wounded soldier continues to run through the battlefield, a frostbitten climber

continuing to climb after hearing the rumble of an approaching avalanche. It is well

known that a state of arousal can greatly inhibit the intensity of pain in a healthy person.

Psychological arousal refers to the heightened alertness of brain areas involved in how

we perceive such experiences. The activation of the arousal system is generally

associated with the reduction of pain in healthy individuals (Millian, 2002).

Interestingly, there is increasing evidence that it can have the opposite effect on those

with chronic pain (Drummond et al., 2001; Drummond & Willox, 2013; Knudsen et al.,

2011). As psychological arousal pathways, from brain to body, have been broadly

associated with the facilitation of chronic pain (Taylor & Westlund, 2017) they provide

an promising target for future research and treatment.

To understand the relationship in chronic pain, however, there must first be a

good understanding of this relationship in healthy individuals. The current research

provides evidence for the presence of an interaction but not the nature of it. Previous

research fails to show how it is effected by the arousal timing, or whether the interaction

occurs as the pain signals travel to the brain or in the brain itself.

This study aims to enhance the future study of pain and associated conditions,

by exploring the functional relationship between pain and arousal in healthy

participants. The relationship was tested using the combination of an arousal induction

and pain evoked by a brief electrical shock. The arousal induction, a startling noise, was

presented before or after pain to explore the effect of timing. The acoustic startle and

electrical stimulus were also presented alone, in separate trials, to provide baseline

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measures. Self-report measures were used to assess the pain and sharpness of the

electrical stimulus, as well as the loudness and discomfort to the acoustic stimulus.

Additionally, physiological measures were taken to indicate spinal pain processing,

according to the knee jerk reflex, and provide a methodological check for arousal, via

changes in pupil size. Prior to the experiment itself, Pain Catastrophizing was assessed,

as a measure of individual variation in pain perception.

The main finding of this study was that presentation of the startling noise before

electrical stimulation reduced subsequent pain. This inhibitory effect was significant in

comparison to both electrical stimulation alone and the reverse stimulus timing. The

difference between the arousal induction and electrical stimulation alone supports

previous research. However, the inhibitory effect of the arousal induction was only

present when timed before electrical stimulation, supports that the relationship was

bound by timing. The involvement of arousal was confirmed by pupillary responses.

Further, as there were almost no significant differences, between the conditions, for

spinal reflex responses it is suggested that the interaction may have occurred purely in

the brain. Pain catastrophizing scores were not found to correlate with the other pain

measures. However, this was likely due to measurement issues.

Despite its limitations, this study provides a strong indication of how arousal

interacts with pain. This is not only important to the general understanding of healthy

populations but could have significant functional implications for chronic pain.

Preliminary evidence for an inverse relationship has already emerged. Is this interaction

similarly bound by the temporal properties of the activating stimulus? Does the

interaction occur at the level of the spine or brain? These questions are essential, not

only to greater understanding but also to the development of effective treatments.

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Appendix H

SPSS Output

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