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Attentional and cognitive consequences of migraine visual cortical hyperexcitability Mickleborough, Marla Joy Sanderson 2012

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Attentional and Cognitive Consequences of Migraine Visual Cortical Hyperexcitability by MARLA JOY SANDERSON MICKLEBOROUGH BA(Hons), University of Saskatchewan, 2002 MSc, University of Western Ontario, 2005  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Neuroscience) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2012  ! Marla Joy Sanderson Mickleborough, 2012  Abstract People with migraine have hyperexcitable visual cortical response to normal visual inputs between attacks. Given that our attentional and perceptual processing can be influenced by our sensory experience, we might expect migraine visual cortical hyperexcitability to have a forward cascade of effects on cognitive processing. With this in mind, this dissertation explored the functional consequences of migraine hyperexcitable visual cortices on attentional and cognitive processing between headache attacks. To begin with, given that topdown attentional control signals can affect excitability of sensory response in visual cortex, Chapter 2 assessed if this normal modulation is affected in migraineurs. Using a probabilistic spatial orienting task while measuring ERPs to attended vs. unattended foveal and parafoveal stimuli, Chapter 2 revealed that migraineurs manifest heightened sensory responses of to-be-ignored visual stimuli. Next, Chapter 3 examined the behavioral impact of hyperexcitability of migraine visual cortex in terms of its effect on bottom-up attentional processing, in this case reflexive attentional orienting.  Using three behavioral spatial  attention paradigms, this chapter provided evidence of heightened reflexive visual-spatial orienting specific to sudden-onset peripheral events.  Lastly,  Chapter 4 assessed post-spatial-selection consequences of visual cortical hyperexcitability in migraineurs. Participants viewed unfamiliar commercial logos in the context of a target identification task while brain responses were recorded via ERPs. Following this task, participants individually identified those logos that they most liked or disliked.  The results of this chapter suggested that ii  migraineurs were not only evaluating environmental stimuli more than controls over time, but also not adequately hedonically categorizing it for quick allocation of attention. Collectively, the research presented in this dissertation suggests that migraineurs have anomalies specifically pointing to increased allocation of attention to extraneous environmental stimuli.  The final concluding chapter  briefly recaps each research chapter and then critically examines the impact of these findings in the context of four outstanding questions exposed by this research. Specifically, are top-down attentional control signals in migraineurs intact?  How might anomalies found in this dissertation be a result of or  independent from known sensory cortical abnormalities? How do the findings fit with the migraineur experience?  Finally, what are the real-world clinical  implications for migraineurs?  iii  Preface I am the primary author on all work presented in this PhD dissertation.  A version of Chapter 2 has been published.  Mickleborough, M.J.S.,  Truong, G., & Handy, T. C. (2011). Top-down attentional control of visual cortex in migraine populations. Neuropsychologia, 49, 1006-1015. I am the primary author of this manuscript and conducted and/or supervised all data collection and statistical analyses with the assistance of G. Truong. T. Handy supervised the project and provided intellectual contributions.  A version of Chapter 3 has been accepted for publication. Mickleborough, M. J. S., Hayward, J., Chapman, C., Chung, J., & Handy, T. C. (in press). Reflexive attentional orienting in migraineurs: the cognitive implications of hyperexcitable visual cortex. Cephalalgia. I am the primary author of this manuscript and conducted and/or supervised all data collection and statistical analyses with the assistance of J. Hayward, C. Chapman, and J. Chung. T. Handy supervised the project and provided intellectual contributions.  A version of Chapter 4 has been submitted for publication. Mickleborough, M. J. S., Chapman, C., Toma, A. S., Chan, J. H. M., & Handy, T. C. Implicit Evaluative Analysis of Visual Images in Migraine Populations. I am the primary author of this manuscript and conducted and/or supervised all data collection and statistical analyses with the assistance of C. Chapman, A. Toma, and J. Chan. T. Handy supervised the project and provided intellectual contributions. iv  The experiments described herein were approved by the Clinical Research Ethics Board of the University of British Columbia. The Certificate Number of the Ethics Certificate obtained is: H07-00458.  v  Table of Contents Abstract ...................................................................................................... ii! Preface....................................................................................................... iv! Table of Contents ..................................................................................... vi! List of Tables ............................................................................................ ix! List of Figures............................................................................................ x! Acknowledgements.................................................................................. xi! Dedication ............................................................................................... xiii! Chapter 1: General Introduction .............................................................. 1! What is Migraine?.............................................................................................3! Epidemiology ..................................................................................................3! Symptoms and Classifications........................................................................4! Evidence of Hyperexcitable Sensory Cortices in Migraine ..........................7! Lack of Habituation in Migraineurs ...............................................................10! Visual Processing Impairments in Migraine..................................................12! From Hyperexcitable Cortex to Headache Pain ..........................................14! Evidence for a Genetic Predisposition..........................................................14! Cortical Spreading Depression .....................................................................15! Activation of the Trigeminovascular System.................................................16! Possible Cognitive Consequences of Hyperexcitability ............................18! Visual Spatial Attention.................................................................................18! Evaluative Processing ..................................................................................19! Research Question.........................................................................................20!  Chapter 2: Top-down Attentional Control of Visual Cortex in Migraineurs .............................................................................................. 23! Introduction ....................................................................................................24! Materials and Methods...................................................................................28! Participants ...................................................................................................28! Headache Classification ...............................................................................28! Stimuli ...........................................................................................................29! Electrophysiological Recording ....................................................................32! Results ............................................................................................................33! Behavior .......................................................................................................33! Electrophysiology .........................................................................................36! vi  Control Analyses ..........................................................................................44! Discussion ......................................................................................................46! Sensory Suppression in the Parafovea ........................................................47! Discriminative Processing at the Fovea .......................................................50! Migraine and Attentional Performance .........................................................52!  Chapter 3: Reflexive Attentional Orienting in Migraineurs.................. 54! Introduction ....................................................................................................55! Experiment 1...................................................................................................57! Materials and Methods...................................................................................57! Participants ...................................................................................................57! Headache Classification ...............................................................................57! Stimuli and Timing ........................................................................................58! Procedure .....................................................................................................60! Results ............................................................................................................60! Reaction Times.............................................................................................60! Control Analyses ..........................................................................................63! Discussion ......................................................................................................64! Experiment 2...................................................................................................65! Materials and Methods...................................................................................65! Participants ...................................................................................................65! Stimuli and Procedures ................................................................................66! Results ............................................................................................................68! Reaction Times.............................................................................................68! Accuracy .......................................................................................................69! Control Analyses ..........................................................................................70! Discussion ......................................................................................................71! Experiment 3...................................................................................................72! Materials and Methods...................................................................................72! Participants ...................................................................................................72! Stimuli and Timing ........................................................................................72! Procedure .....................................................................................................74! Results ............................................................................................................74! Reaction Times.............................................................................................74! Control Analyses ..........................................................................................76! Discussion ......................................................................................................76! Migraineurs Across Experiments ..................................................................76! General Discussion........................................................................................77! What are the Implications for Migraineurs? ..................................................77! What are the Implications for Attention?.......................................................80! vii  Chapter 4: Implicit Evaluative Analysis of Visual Images in Migraine Populations .............................................................................................. 82! Introduction ....................................................................................................83! Materials and Methods...................................................................................86! Participants ...................................................................................................86! Headache Classification ...............................................................................86! Stimuli ...........................................................................................................86! Procedures ...................................................................................................87! Electrophysiological Recording ....................................................................88! Results ............................................................................................................89! Habituation Analyses ....................................................................................89! Implicit Hedonic Analyses.............................................................................93! Discussion ......................................................................................................99! Increasing LPP Over Time ...........................................................................99! Absent Negativity Bias................................................................................101! Sensory Contributions to Altered Evaluative Analyses?.............................103!  Chapter 5: General Conclusions.......................................................... 104! Outstanding Questions................................................................................109! Impaired Top-Down Control Signals?.........................................................109! Problem of Suppression? ...........................................................................110! Consistent with the Migraineur Experience? ..............................................112! Clinical Implications? ..................................................................................113! Concluding Remarks ...................................................................................114!  References ............................................................................................. 115!  viii  List of Tables Table 1.1 Migraine Classification Summary 1 .......................................................5! Table 2.1 Reaction Times for Target Discrimination 2.........................................34! Table 2.2 Perceptual Sensitivity Rates 3.............................................................34! Table 2.3 Mean Target Duration 4.......................................................................34! Table 2.4 Mean Amplitudes of the Lateral Occipital Component 5 .....................38! Table 3.1 Mean Accuracies 6 ..............................................................................70! Table 4.1 Mean Amplitudes 7..............................................................................90! Table 4.2 Mean Amplitudes 8..............................................................................94! Table 4.3 Hedonic Preference Ratings 9 ............................................................98!  ix  List of Figures Figure 1.1 Pathophysiology of Migraine 1 ............................................................9! Figure 2.1 Basic Trial Conditions 2 .....................................................................30! Figure 2.2 P1 and N1 Component Responses to Foveal Targets 3....................39! Figure 2.3 P1 and N1 Component Responses to Parafoveal Targets 4 .............42! Figure 3.1 Basic Trial Conditions for Experiment 1 5..........................................59! Figure 3.2 Mean Reaction Times (RTs) to Targets 6...........................................62! Figure 3.3 Basic Trial Conditions for Experiment 2 7.........................................67! Figure 3.4 Mean Reaction Times (RTs) to Targets 8...........................................69! Figure 3.5 Basic Trial Conditions for Experiment 3 9..........................................73! Figure 3.6 Mean Reaction Times (RTs) to Targets 10.........................................75! Figure 4.1 Grand-averaged ERP Waveforms11 .................................................91! Figure 4.2 Grand-averaged ERP Waveforms 12 ................................................95! Figure 5.1 Research Findings 13 ......................................................................106!  x  Acknowledgements I would like to thank Todd Handy, for being an absolutely fantastic supervisor. He encouraged me to pursue my own research interests and has remained enthusiastic about my choice to research migraine.  More than a  supervisor, Todd has been both a mentor and a friend.  In addition, I have had the benefit of fantastic committee members, Alan Kingstone, Jason Barton, and Debbie Giaschi.  While I can’t speak for my  committee members, I really enjoyed the annual meetings and the conversations around my research. Importantly, my committee members were supportive of my choice to have family during my studies, and had good advice based on experience, like when Jason gently suggested that writing my thesis “when the baby is sleeping” is not as easy as it sounds!  Of course, he was right, and I could not have completed this dissertation without an outstanding support network.  At the lab I had outstanding  undergraduate research assistants to keep the research going. In particular, Grace Truong, Simi Toma, and Christine Chapman kept participants running and me informed so that I could focus my energy elsewhere. On the home-front, my family was amazingly generous with their time and support. Above all, Mom, Gail, Graham, and Christina – thank you for taking care of me and the boys! In addition, Dad and Jaime, thank you both for sharing mom and for believing in  xi  me. Finally, Ben, as always you have provided continuous support and kept me grounded.  This research was supported by a grant from the Migraine Trust, UK. I am also grateful for support from a UBC four-year scholarship.  xii  Dedication  For Ben, Reid, and Colton – for being my balance.  xiii  Chapter 1: General Introduction  1  “I can’t come in today, I’ve got a migraine.” While we have all heard of migraine headaches, for a sufferer what it is to be a migraineur often goes well beyond the headache itself. A migraineur may feel that he/she is impacted in daily activities, even when not suffering from an attack. Many migraineurs report that they feel sensitive to light, sounds, smells, and distractions in day-to-day life (e.g., Sacks, 1992). In fact, empirical evidence in the last decade supports this impression, and migraine is now considered a form of sensory processing disturbance (e.g., Goadsby, 2007), with substantial evidence implicating hyperexcitability of sensory cortices in migraine between attacks (e.g., Ambrosini & Schoenen, 2006; Aurora & Wilkinson, 2007; Brighina, Palermo, & Fierro, 2009; Pietrobon, 2005). Given that our attentional and perceptual processing can be influenced by our sensory experience, we might expect this hypersensitivity to normal sensory inputs to have a forward cascade of effects on cognitive processing in migraineurs. With this in mind, the purpose of this dissertation is to explore the functional consequences of migraine hyperexcitable visual cortices on cognitive processing between headache attacks.  This introductory chapter first covers basic background information about migraine, then reviews three key issues concerning sensory hyperexcitability in migraine populations: evidence for it, its role in the pathophysiological cascade of events in migraine, and the cognitive consequences in between headache events. The chapter closes with a brief review of the primary question of the dissertation and an outline of the particular investigations that follow in the three research chapters. 2  What is Migraine? Epidemiology Migraine affects people of all ages, all races, both sexes, and every occupation. Specifically, in Canada approximately 7.8% of men and 24.9% of women (Obrien, Goeree, & Streiner, 1994) and an estimated 3-10% of children (Barnes, 2011) suffer from migraine headache.  There is an increase in the  occurrence of migraine in both males and females between the ages of 12 and 40 years, after which a decline occurs in overall prevalence (Lipton, Stewart, Reed, & Diamond, 2001). In short, migraine is widespread, and, furthermore, the impairment migraine causes is high, with the World Health Organization naming headache disorder among the 20 most disabling conditions (Diener, Steiner, & Tepper, 2006). The nature of migraine leads to much loss in productivity in society, with an estimated indirect cost of migraine to American employers of $2800 more annually for each employee with migraine compared to those without migraine, mostly due to absenteeism, which nationally totals approximately $12 billion dollars annually (Hawkins, Wang, & Rupnow, 2007). Moreover, for the migraineur the impact spreads well beyond work-productivity loss, affecting occupational, academic, social, leisure, and family life and responsibilities (e.g., Leonardi, Steiner, Scher, & Lipton, 2005) beyond what any dollar value can capture.  While it is well known that migraine headaches cause substantial  impairment during attacks, there is mounting evidence that migraineurs also have impairment between attacks (e.g., Dahlof & Dimenas, 1995).  3  Symptoms and Classifications While migraine has been identified for more than 4000 years, the systematic classification of migraine is a relatively recent phenomenon. In order to help clinicians and researchers identify migraine, the International Headache Society created a diagnostic criteria and classification system for primary headache disorders in 1997, and updated a second version in 2004 (Headache Classification Subcommittee of the International Headache Society, 2004). In Table 1.1, I have summarized the criterion for migraine without aura (formerly called common migraine), migraine with aura (formerly called classic migraine), and tension type headache.  4  Table 1.1 Migraine Classification Summary 1 Migraine Without Aura  Migraine With Aura  Tension Type  A. 5+ attacks fulfilling criteria B–D  A. 2+ attacks fulfilling criteria B–D for Migraine without aura begins during the aura or follows aura within 60 minutes  2.1 Infrequent episodic tension-type headache A. 10+ episodes occurring on <1 day/month on average (<12 days/year) and fulfilling criteria B–D B. 30 minutes to 7 days C. At least 2 of the following characteristics: 1. bilateral location 2. pressing/tightening (nonpulsating) quality 3. mild or moderate intensity 4. not aggravated by routine physical activity such as walking or climbing stairs D. Both of the following: 1. no nausea or vomiting (anorexia may occur) 2. no more than one of photophobia or phonophobia E. Not attributed to another disorder  B. Headache attacks lasting 472 hours (untreated or unsuccessfully treated) C. Headache has at least 2 of the following characteristics: 1. unilateral location 2. pulsating quality 3. moderate or severe pain intensity 4. aggravation by or causing avoidance of routine physical activity (eg, walking or climbing stairs) D. During headache at least 1 of the following: 1. nausea and/or vomiting 2. photophobia (extreme sensitivity to light) and phonophobia (extreme sensitivity to sound) E. Not attributed to another disorder  B. Aura consisting of at least 1 of the following, but no motor weakness: 1. fully reversible visual symptoms including positive features (eg, flickering lights, spots or lines) and/or negative features (ie, loss of vision) 2. fully reversible sensory symptoms including positive features (ie, pins and needles) and/or negative features (ie, numbness) 3. fully reversible dysphasic speech disturbance C. At least two of the following: 1. homonymous visual symptoms and/or unilateral sensory symptoms 2. at least one aura symptom develops gradually over >5 minutes and/or different aura symptoms occur in succession over >5 minutes 3. each symptom lasts >5 and <60 minutes E. Not attributed to another disorder  2.2 Frequent episodic tension-type headache As 2.1 except: A. At least 10 episodes occurring on >1 but <15 days/month for >3 months (>12 and <180 days/year) and fulfilling criteria B–D  2.3 Chronic tension-type headache As 2.1 except: A. Headache occurring on >15 days/month on average for >3 months (>180 days/year) and fulfilling criteria B–C B. Headache lasts hours or may be continuous C. Both of the following: 1. no more than one of photophobia, phonophobia or mild nausea 2. neither moderate or severe nausea nor vomiting .  5  Both migraineurs with aura (MA) and migraineurs without aura (MO) report similar triggers and are told by clinicians to avoid common migraine triggers to attempt to prevent headache attacks. Common triggers precipitating migraine attack include certain foods, alcohol, monosodium glutamate (MSG), weather changes, sleep irregularities, stress, and release from stress.  In addition,  sensory triggers include flashing or bright lights, certain smells, and loud noise. For many migraineurs, migraine attacks occur only when an intrinsic migraine threshold, which is set by genetic factors and altered by environmental changes, is reduced or when a combination of triggers are particularly strong or frequent (e.g., Ferrari, 1998).  While triggers are widely reported, the effectiveness of  preventing headache by avoiding triggers has been questioned in the literature, with the suggestion that mild-moderate exposure might decrease a migraineurs sensitivity to triggers (e.g., Martin, 2010). Nonetheless, elimination of triggers remains one of the first lines of defense suggested in migraine treatment, and many headache specialists recommend migraineurs keep a headache diary to help patients identify personal triggers. A headache diary also helps a patient recognize the phases of his/her migraine attack.  Typically, migraine attacks consist of four phases: prodrome, aura, headache, and postdrome (e.g., Capobianco, Cheshire, & Campbell, 1996). The prodrome, which occurs in about 80% of migraine patients in the hours or days before the headache, includes symptoms such as increased photophobia (extreme sensitivity to light), phonophobia (extreme sensitivity to sound), osmophobia (extreme sensitivity to odors), yawning, drowsiness, mood changes, 6  polydipsia (excessive thirst), food cravings, and a vague awareness that an attack is about to occur. Next, in the 20% of migraineurs who experience aura, the aura phase lasts up to 60 minutes and is characterized by focal neurological symptoms – 99% of which are visual (Eriksen, Thomsen, & Olesen, 2005). The headache itself starts during aura or 5-20 minutes after aura ends.  The  headache pain typically lasts 4-72 hours, and in addition to symptoms described in Table 1.1, patients often exhibit a strong inclination to avoid further stimulation by decreasing motion, light, and sound. Following the cessation of the headache is the postdrome, which consists of lingering symptoms where patients often feel fatigued and have limited food tolerances.  While headache is the major complaint of migraineurs, it is evident now that there is much more going on than the pain. Triggers of headaches and symptoms of migraine both before and after headache are strongly indicative of the involvement of sensory modalities in migraine.  The following section  expands on the sensory sensitivities in migraine, linking them to the underlying mechanisms of migraine.  Evidence of Hyperexcitable Sensory Cortices in Migraine Migraine is now considered to be a disorder of sensory processing where the central nervous system reacts abnormally to otherwise non-noxious sensory stimuli (e.g., Chakravarty, 2010; Goadsby, 2007; Goadsby, 2009). While sensory events can trigger an attack, diagnostic symptoms during an attack include hypersensitivity to light and sound, and migraineurs report sensitivities to sensory 7  stimuli (bright or flashing lights, patterns, smells, sounds) between migraine attacks (interictally). While these have long indicated the importance of sensory factors in migraine, mounting empirical evidence confirms that indeed hyperexcitable sensory cortices (occipital in particular) can trigger a series of events that leads to the headache itself (see Figure 1.1).  In fact, research  supports hyperexcitable sensory cortices as the underlying pathophysiology predisposing individuals to migraine.  8  Figure 1.1 Pathophysiology of Migraine 1 CSD = cortical spreading depression; TNC = trigeminal nucleus caudalis; TGS = trigeminal vascular system  9  Specifically, hyperexcitable visual cortex can trigger cortical spreading depression (CSD), which activates the trigeminal vascular system (TGS), and subsequently leads to a headache event. The following sections will first reveal evidence supporting hyperexcitability and then detail the elements of Figure 1.1, explaining how a genetic predisposition for hyperexcitable sensory cortices can lead to CSD, and headache itself. There are two key lines of evidence in which the literature I will detail which support that migraineurs have hyperexcitable visual cortex. First, migraineurs have interictal lack of habituation to repetitive sensory  stimulation,  and  second  migraineurs  have  visual  processing  impairments.  Lack of Habituation in Migraineurs What is habituation? After repeated non-harmful, non-beneficial repetition of a stimulus, there is a gradual decrease in the response to the stimulus (e.g., Groves & Thompson, 1970; Rankin et al., 2009; Thompson, 2009). While, the specific mechanisms underlying habituation are poorly understood, it is likely due to a decrease in the amount of neurotransmitter vesicles released from presynaptic terminals of sensory neurons (e.g., Thompson, 2009). Thus, there is no change in receptor sensitivity, only in neurotransmitters released to them. Habituation is thought to be a basic form of implicit learning, lasting minutes, and proposed to protect the cortex against sensory overload (e.g., Brighina et al., 2009; Groves & Thompson, 1970; Thompson, 2009).  10  It is precisely this protective mechanism of habituation that is found to be lacking in migraineurs, in this case indexed via strength of the cortical response to visual stimuli (e.g., Stankewitz & May, 2009). For example, when migraineurs watch visually repetitive stimuli such as a repeated flash or checkerboard reversal, they do not show the normal pattern of habituated visual sensory responses. Specifically, while electrophysiological studies in normal populations reveal a gradual and automatic attenuation in the strength of sensory-evoked cortical responses to repeated visual stimuli, migraineurs have either no change or even an increase in amplitude (e.g., Afra, Cecchini, De Pasqua, Albert, & Schoenen, 1998; Ambrosini & Schoenen, 2003; Brighina et al., 2009; Brinciotti, Guidetti, Matricardi, & Cortesi, 1986; Coppola, Pierelli, & Schoenen, 2009; Di Clemente et al., 2005; Giffin & Kaube, 2002; Judit, Sandor, & Schoenen, 2000; Schoenen, Wang, Albert, & Delwaide, 1995; Siniatchkin, Kropp, & Gerber, 2003). While this difference between migraineurs and controls has not been found in all conditions (e.g., Khalil, Legg, & Anderson, 2000; Oelkers et al., 1999; Oelkers-Ax, Parzer, Resch, & Weisbrod, 2005), decreased habituation is one of the most widely accepted findings in migraine and has been considered by some to be a neurophysiological hallmark of migraine (e.g., Brighina et al., 2009; Coppola et al., 2009).  This lack of normal habituation is a key line of evidence supporting hyperexcitability in migraine visual cortex. It has been proposed that migraineurs have a reduced pre-activation level of sensory cortex and do not readily reach the top (or ceiling) of response activity after which repeated sensory stimulation 11  normally habituates (e.g., Schoenen, 1996). The disturbance of habituation in migraineurs has been cited as playing a pivotal role in the pathophysiology of migraine by contributing to a general vulnerability of sensory overload. Accordingly, hyperexcitability in migraine can result from sensory overload which can underlie the initiation of a migraine event (e.g., Fumal et al., 2006).  Visual Processing Impairments in Migraine A second line of evidence pointing to hyperexcitability in migraine is heightened visual sensitivity between migraine attacks (e.g., Aurora & Wilkinson, 2007; Chronicle & Mulleners, 1996; Main, Dowson, & Gross, 1997; McKendrick, Vingrys, Badcock, & Heywood, 2001; Sacks, 1992; Shepherd, 2000; Vanagaite et al., 1997). Anecdotal reports from migraineurs suggest that visual inputs such as bright lights, glare and repetitive patterns can be sufficiently intense so as to cause discomfort in a manner akin to walking into bright light after extended dark adaptation, and peripheral visual information is often reported as particularly distracting or difficult to ignore (e.g., Sacks, 1992). Furthermore, photophobia is a  diagnostic  criterion  for  migraine  headache  (Headache  Classification  Subcommittee of the International Headache Society, 2004), and 20-30% of migraineurs suffer from visual aura symptoms.  In addition to the more subjective experiences of migraineurs, visual processing has been the focus of clinical investigations that support brain hyperexcitability. In general, migraineurs are found to have heightened visual sensitivities including overall increased sensitivity to light (e.g., Main et al., 1997; 12  Vanagaite et al., 1997), increased discomfort from stripes (e.g., Marcus & Soso, 1989), decreased critical flicker fusion rates (e.g., McKendrick & Badcock, 2004a), decreased detection of target on a noise grate (e.g., Chronicle, Wilkins, & Coleston, 1995), and contrast processing deficits (e.g., McKendrick & Badcock, 2003).  In addition, examining how visual cortical function is modulated via  external or exogenous signal sources by applying transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) to various visual cortical areas has revealed that the perception of phosphenes can be artificially induced at a lower stimulation threshold in migraineurs relative to nonheadache controls (e.g., Antal, Arlt, Nitsche, Chadaide, & Paulus, 2006; Aurora, Ahmad, Welch, Bhardhwaj, & Ramadan, 1998), and that the perception of visual stimuli is more difficult to suppress in migraineurs (e.g., Chronicle, Pearson, & Mulleners, 2006; Mulleners, Chronicle, Palmer, Koehler, & Vredeveld, 2001). Another interesting study linking visual stimulation directly to pain found that migraineurs (but not controls) experienced significant and enduring drops in pain thresholds after light stimulation, suggesting that visual information may play an influential role in trigeminal nociception in migraineurs (e.g., Kowacs et al., 2001). Such studies and others reveal that this abnormally sensitive low-level visual processing in migraineurs can be attributed to hyperexcitable visual cortex (e.g., Wray, Mijovicprelec, & Kosslyn, 1995).  Together, the altered visual sensitivities reported by the anecdotal and empirical reports from migraineurs precisely align with what one would predict from hyperexcitable occipital cortices.  These abnormal visual processing 13  examples are thought to indicate a general excitability of sensory cortical function rather than being specific to the occipital cortex, and it is this excitability that is thought to be an underlying mechanism in the pathophysiology of migraine.  From Hyperexcitable Cortex to Headache Pain While the pathophysiology of migraine is not yet wholly understood, recent evidence from areas of genetics, neuroimaging, and pharmacology have started to converge to support a theory that a genetic predisposition for hyperexcitability can lead to CSD, triggering TGS activation and ultimately leading to headache pain (see Figure 1.1).  Evidence for a Genetic Predisposition For years, clinicians have noted the tendency of migraine to run in families. Studies of twin pairs have provided support that migraine has a strong genetic component (Ulrich, Gervil, Kyvik, Olesen, & Russell, 1999). In addition, one rare type of migraine, familial hemiplegic migraine, has long been assigned a chromosomal link associated with calcium channel mutations and enhanced glutamate release. While these findings have allowed researchers to suggest a strong heritability of migraine, it is only very recently that a genome-wide association study confirmed the first robust genetic association for common migraine types (MA and MO; e.g., Anttila et al., 2010). The identified variant gene has been associated with glutamate regulation, leading to an excess of glutamate, which then increases susceptibility to cortical spreading depression (e.g., Anttila et al., 2010).  This glutamate increase could underlie both the 14  hyperexcitable sensory cortices and the CSD, which is considered to be the pathophysiological basis of migraine (e.g., Brighina et al., 2009).  Cortical Spreading Depression A link between CSD and migraine auras was suggested more than 50 years ago (Milner, 1958), and recent fMRI evidence has provided empirical support of the potential role for CSD in inducing both migraine aura and migraine pain. CSD is a slow propagating (2-6mm/min) wave of intense depolarization of neuronal and glial membranes that generates an intense spike of activity as it moves over the surface of the cortex (e.g., Leao, 1944). This wave is followed by a period of neural suppression. The depolarization phase is associated with an increase in regional cerebral blood flow, while the phase of reduced neural activity is associated with a reduction in regional cerebral blood flow. In humans, the aura phase of migraine correlates to an initial phase of increased regional cerebral blood flow followed by reduced regional cerebral blood flow, moving across the cortex at a rate of 2-3 mm/min, and this has been widely accepted as evidence for CSD underlying human migraine aura. In addition, migraine without aura is thought to be a result of CSD occurring in a clinically silent area of the cerebral cortex (e.g., Pietrobon, 2005).  CSD is a good candidate for the  mechanism leading to the TGS activation, which causes headache pain.  While it is unclear precisely how CSD begins in migraineurs, the threshold for the initiation of CSD is presumably lower in migraineurs than in the normal population and is likely due to a combination of increased excitation (i.e., 15  increased glutamate) and decreased inhibition (i.e., decreased gamma-amino butyric acid - GABA). Most factors that facilitate CSD are excitatory depolarizing events, and enhanced cerebral excitability with increased glutamate is the best candidate in migraine. Specifically, mutations associated with migraine genetics have implicated elevated extracellular glutamate as a critical modulator of both cortical hyperexcitability and CSD in the pathophysiology of migraine.  Activation of the Trigeminovascular System So how does CSD lead to migraine headache pain? Migraine pain is interesting because the brain itself does not have any pain sensors.  The  meninges and blood vessels of the brain, however, are pain sensitive. Painful stimulation in these regions is referred to the forehead, neck, or occipital skin areas. It is the trigeminocervical nerves that innervate the meninges that are thought to underlie migraine headache pain. This section outlines how the TGS is activated and implicated in headache pain in migraine.  While genetic mutations leading to excess glutamate and hyperexcitable cortex may lead to a susceptibility to CSD in migraineurs, another neuromodulator, calcitonin gene-related peptide (CGRP), that is released during CSD contributes to the activation of the TGS. CGRP has a strong vasodilatory effect on the cerebral blood vessels, and is thought to play a contributing part in peripheral sensitization.  In the cranial vasculature, CGRP is expressed in  sensory nerve fibers, which project to the trigeminal nucleus caudalis (TNC). In the periphery, the CGRP receptor is found in the smooth muscle layer of the dura 16  arteriol blood vessels. CGRP can activate trigeminal neurons during migraine, enhancing the sensitivity of the trigeminal system to pain, resulting in stronger and more sustained pain signaling in the brain, thus contributing to trigeminal sensitization and allodynia (perceiving pain from to a stimulus which does not normally provoke pain) and hyperalgesia (extreme sensitivity to pain) in migraine. These changes could lead to a sensitive migraine state in which normally innocuous inputs such as sensory sensations, lights, sounds, smells, and taste can pass through the normal brainstem filters and reach higher-level pain processing, thereby becoming bothersome migraine symptoms such as allodynia, pain, photophobia, phonophobia, and nausea.  In this way, a feedback loop is formed, where TGS activation leads to vasodilation and inflammation, which causes pain and further activation of TGS. Thus, as summarized in Figure 1.1, a genetic predisposition can lead to hyperexcitable sensory cortices, contributing to CSD, which activates the TGS, also initiating a feedback loop that further sensitizes the brain to future sensory inputs. Accordingly, it is easy to see that migraine can be thought of primarily as a problem with hyperexcitable reactions in sensory cortices to otherwise normal sensory stimulation. An understanding of this basic pathophysiology of migraine is important for understanding how hyperexcitability of cortex may have other functional consequences.  17  Possible Cognitive Consequences of Hyperexcitability As explained above, recent research suggests that migraine may be considered a form of sensory processing disturbance with wide implications in the CNS (e.g., Coppola et al., 2009) yet there is still little research towards understanding the extent of the sensory processing impairments and how they might permeate to everyday cognitive function.  This thesis explores the  attentional and evaluative consequences of migraine hyperexcitability. Following is an overview of the limited research on visuo-spatial attentional processing in migraineurs.  Visual Spatial Attention The limited research assessing attentional processes in migraineurs have used indirect measures of visual processing and have been both contradictory and inconclusive. For example, there have been a number of investigations of migraineur attention relying on visual search tasks, where participants look for a visual target embedded within an array of distracting elements. While one study of visual search found faster search time in migraineurs (Wray et al., 1995), three others reported no differences between migraineurs and controls (Conlon & Humphreys, 2001; Palmer & Chronicle, 1998; Shepherd, 2006). Other attempts have been made to assess attentional functioning in migraine using paper-andpencil or clinician-administered neuropsychological test batteries, where participants are given a series of psychological tests (such as the Weschler Adult Intelligence Scale - WAIS) and attention is just one of the many components being indirectly assessed (for example, via subtests of the WAIS in which 18  attention is required to repeat numbers and letters back in reverse or chronological order). Again, results from these studies are contradictory, with some finding attentional deficits (e.g., Calandre, Bembibre, Arnedo, & Becerra, 2002), while others find no attentional abnormalities in migraineurs (e.g., McKendrick, Badcock, Badcock, & Gurgone, 2006). Given these contradictory results and indirect testing, a primary objective of this thesis is to bring direct measures of visual processing to bear on the question of whether migraine hyperexcitability may lead to impairments in visual attentional function.  Evaluative Processing In addition to visual attentional function, this dissertation explores whether the abnormalities associated with migraine visual cortex permeate to how we cognitively process and evaluate stimuli at post-sensory stages.  Specifically,  recent evidence from ERPs in normal populations has shown that even for emotionally benign visual stimuli we automatically and implicitly evaluate visual stimuli at a hedonic level, indicating that implicit hedonic analysis is a natural and normal part of visual perception (Handy, Smilek, Geiger, Liu, & Schooler, 2010). Given this normal aspect of visual processing, we are interested in seeing if migraineurs show differences in this level of visual perceptual analysis. This type of perceptual processing in migraineurs has not yet been evaluated in the literature. These components of cognitive evaluative processing may be related to early impression formation (e.g., Hoefel & Jacobsen, 2007; Hoefel, Lange, & Jacobsen, 2007; Hofel & Jacobsen, 2003), so abnormalities here would indeed  19  suggest consequences of migraine hyperexcitability impacting day-to-day processing beyond low-level visual processing.  Research Question As has been outlined, the hyperexcitability of migraine visual cortex is a major pathophysiological factor in migraine. While extensive work has looked at the implications this hyperexcitability has in basic visual processing and habituation, there has been very little research to expand to consequences beyond the basic sensory response.  The purpose of this dissertation is to  explore the functional consequences of migraine hyperexcitability on attentional and evaluative cognitive processing in between headache attacks.  To test our question, can hyperexcitable visual cortex in migraine have consequences for attentional and evaluative processing, the three subsequent experimental chapters each ask a specific question. Chapter 2 begins by asking if hyperexcitable visual cortex may impact top-down attention in migraineurs, using ERP to evaluate an attentional paradigm while looking at foveal and parafoveal midline stimuli.  Chapter 3 follows with an exploration of reflexive  visual-spatial attention, using three reaction time experiments.  Chapter 4  focuses on implicit evaluative analysis in migraineurs, again using ERP to analyze visual cortical reactions.  It is important here to clarify the general terms used in this thesis concerning the stages of visual processing being examined in this collective set  20  of studies. While exactly how visual processing is parceled into stages and substages depends on the nature of what one is trying to model or understand, in terms of this dissertation, I distinguish between two very general, dichotomous stages of visual processing. In particular, Chapters 2 and 3 consider potential migraineur abnormalities in how attention affects relatively early, “sensory-level” visual processing stages in extrastriate visual cortex.  The intensity of visual  responses at this stage reflect two factors – the physical parameters of the visual stimulus driving the initial sensory-evoked response in cortex, and the degree to which attention may be either amplifying or dampening this sensory-evoked excitability. These attentional effects can be either top-down or bottom-up in origin, and this dissertation looks at migraineur abnormalities in these two forms of sensory-level attention in Chapters 2 and 3, respectively. On the other hand, Chapter 4 turns to the question of whether migraineurs may also show abnormalities in comparatively later, post-sensory or “cognitive” stages of visual processing. At these later stages of processing, activity is driven not by the physical properties of the stimulus itself, but by more cognitive factors like whether it was an expected event, something we were waiting for, and how we feel about the stimulus. As such, Chapter 4 concerns the question of whether migraineurs show altered levels of implicit hedonic analysis of complex, stylized visual images – in this case commercial branding images or logos.  The final conclusion chapter explains how my research shows that, indeed, migraine includes functional differences in attentional and evaluative cognitive processing as compared to controls and explores how this relates to 21  hyperexcitability.  It considers the practical implications this may have for  migraineurs, including suggestions for future studies.  22  Chapter 2: Top-down Attentional Control of Visual Cortex in Migraineurs 1  1  A version of this chapter has been published. Mickleborough, M.J.S., Truong, G., & Handy, T. C. (2011). Top-down attentional control of visual cortex in migraine populations. Neuropsychologia, 49, 1006-1015.  23  Introduction Although migraine is medically classified as a headache disorder, a key part of its pathophysiology is a heightened excitability of visual cortex that chronically persists in between headache events (e.g., Aurora & Wilkinson, 2007; Pietrobon 2009). Most notably, migraineurs show reduced sensory habituation to repetitive visual stimuli as measured via sensory-evoked potentials. Whereas the amplitude of sensory-evoked components to repeated stimuli normally diminish over time, migraineurs show no evidence of this sensory attenuation (e.g., Afra et al., 1998; Coppola et al., 2009; Di Clemente et al., 2005; Giffin & Kaube, 2002; Siniatchkin et al., 2003), an effect that has been linked to impaired inhibitory intracortical circuitry (Brighina et al., 2009; Chronicle et al., 2006; Mulleners et al., 2001).  In light of this inhibition-related visual cortical pathophysiology in  migraine, here we examined the hypothesis that migraine may also include an altered ability to modulate visuocortical sensory responses via the volitional orienting of visual spatial attention.  Our question followed from the common neuroanatomical locus of heightened cortical excitability and spatial attention effects in visuocortical processing.  In particular, combined ERP and functional neuroimaging have  demonstrated that the top-down control of visual spatial attention specifically modulates the sensory-evoked excitability of extrastriate visual cortex (e.g., Heinze et al., 1994; Woldorff et al., 1997), the same visuocortical region linked to several visual anomolies in migraineurs (e.g., Battelli, Black, & Wray, 2002; Ditchfield, McKendrick, & Badcock, 2006; Fierro et al., 2003). Moreover, a key 24  receptor-level mechanism underlying top-down attentional modulation of sensoryevoked activity in extrastriate cortex—GABAergic inhibition (e.g., Eickhoff, Rottschy, & Zilles, 2007)––has been implicated in both the normal modulatory effects of spatial attention (e.g., Houghton & Tipper, 1996) and hyperexcitability in migraineur cortex (e.g., Brighina et al., 2009; Chronicle & Mulleners, 1996). Taken together, this raises the possibility that attentional control of these visual cortical regions may also be altered in migraineurs.  Our question itself was of interest for two primary reasons.  First, in  studying the altered excitability of visual cortex in migraineurs, the dominant methodology has been to examine how visual cortical function is modulated via external or exogenous signal sources, such as TMS or tDCS. For instance, applying TMS/tDCS to various visual cortical areas has been used to show that the perception of phosphenes can be artificially induced at a lower stimulation threshold in migraineurs relative to non-headache controls (e.g., Antal et al., 2006; Aurora et al., 1998), and that the perception of distracting visual stimuli is more difficult to suppress in migraineurs (e.g., Chronicle et al., 2006; Mulleners et al., 2001). From this perspective, our goal here was to ask a very different but highly complimentary question—given the altered excitability of migraineurs’ visual cortex as revealed via the application of exogenous modulatory signals, are there differences between migraineurs and controls in terms of how sensoryevoked excitability in visual cortex is affected by endogenous or top-down modulatory signals?  25  Second, in terms of understanding the neurocognitive basis of visualspatial attention itself, the cortical pathophysiology of migraine offers a novel investigative opportunity. To the point, it has long been suggested that visualspatial attention operates in a bipartite manner, such that stimuli in attended visual locations are perceptually facilitated, while in tandem, stimuli in unattended visual locations are perceptually attenuated (e.g., Luck, 1995; Slotnick, Hopfinger, Klein, & Sutter, 2002; Slotnick, Schwarzbach, & Yantis, 2003).  If  migraineurs do in fact have altered intracortical inhibition (e.g., Brighina et al., 2009; Chronicle et al., 2006; Mulleners et al., 2001), then the potential contributions these inhibitory processes make to the attentional facilitation and/or attenuation of visual stimuli can be illuminated by examining if—and how— migraineurs might differ in their ability to attentionally modulate sensory-evoked activity in extrastriate cortex, relative to non-migraineurs.  To address these issues we tested migraineurs and non-migraine control participants in a canonical spatial orienting task (e.g., Posner, 1980) as we measured visual sensory cortical responses to attended and unattended stimuli via ERPs.  The paradigm itself was a direct replication of Handy and Khoe  (2005), where participants maintained fixation on a central location while on each trial being cued to orient their visual attention to either a parafoveal location several degrees above fixation along the vertical meridian, or to keep their visual attention aligned with their focus of gaze on the fixation point. A target stimulus was then briefly presented and immediately followed by a mask, with the target requiring a forced, two-choice discrimination. On 80% of the trials a target was 26  presented at the cued location, and on the remaining of the trials the target was presented at the uncued location, a probability manipulation designed to entice participants to volitionally orient their attention to the cued target location (e.g., Posner, 1980).  At issue in the paradigm is the extent to which the ERP  responses to targets vary as a function of target location (foveal vs. parafoveal) and whether or not the target was cued/attended.  Planned analyses focused on two ERP components of interest, the lateral occipital P1 and lateral occipitotemporal N1.  The P1 indexes the sensory-  evoked excitability of extrastriate visual cortex as modulated by attention (e.g., Heinze et al., 1994; Woldorff et al., 1997), such that the P1 amplitude positively covaries with the amount of attention allocated to the location of the ERP-eliciting stimulus (e.g., Handy & Mangun, 2000; Handy, Soltani, & Mangun, 2001). The N1 is also sensitive to top-down attentional modulation (e.g., Eimer, 1994; Handy & Mangun, 2000; Luck et al., 1994; Mangun & Hillyard, 1991) and indexes the kind of visual discriminative processes that might be altered in migraineurs (e.g., Hopf, Vogel, Woodman, Heinze, & Luck, 2002; Vogel & Luck, 2000). Because Handy and Khoe (2005) found that P1 attention effects were present for parafoveal stimuli but were absent for foveal stimuli (in participants not screened for migraine status), we thus adopted their paradigm here in order to examine whether migraineurs may likewise show effects of retinal eccentricity on attentional modulation of the P1 and/or N1 components.  27  Materials and Methods Participants 58 paid volunteers participated; 29 were in the non-migraine control group (19 women and 10 men; age 18-27 years, mean age 21.6, 2.5 SD) and 29 were in the migraine group (25 women and 4 men; age 18-54 years, mean age 29.3, 10.2 SD). The migraineurs had 14.9 (24.6 SD) headaches a year, with each headache lasting 22.3 (20.5 SD) hours. Because migraine hyperexcitability is thought to normalize prior to and during an attack (e.g., Schoenen, 2006) all migraineurs had not had a migraine within 48 hours prior and 48 hours after the testing period. All but one control participant were right-handed. All participants gave their informed consent and all testing procedures were approved by the University of British Columbia Clinical Review Ethics Board.  Headache Classification All migraine participants were required to meet the migraine criteria specified by the International Headache Society (Headache Classification Subcommittee, 2004) and as determined by an interview. Specifically, in order to be included in the migraine group, participants had to meet basic minimum criterion including 5 or more attacks with headache lasting 4-72 hours.  The  headache needed to include two of the following: unilateral pain; pulsating pain quality; moderate to severe pain; and pain aggravated by routine physical activity such as walking or climbing stairs. The headache also had to be accompanied by nausea and vomiting or photophobia and phonophobia. All our migraine  28  participants had not suffered from a migraine for at least 48 hours before testing nor did they have a migraine for at least 48 hours after testing.  Stimuli Our paradigm was designed to separately assess visual sensory gain control at the fovea and parafovea, and replicated the paradigm used by Handy & Khoe (2005). The sequence and timing of each trial type (foveal or parafoveal target) is presented in Figure 2.1. On each trial, a central fixation cross was presented on the centre of the screen. Next, a pair of attention-directing arrow cues (0.5° in length) were presented on either side of fixation, directing attention to where the targets would appear, at either fixation (on half of the trials) or 2.2° degrees above fixation on the vertical meridian (on the other half of the trials). An A or an H (0.5% probability) target letter (0.85° in width and 1.0° in height) then appeared in either of these locations, followed immediately by a mask (also 0.85° in width and 1.0° in height) consisting of an array of randomly oriented lines, with the target being presented to the attended location 80% of the time and in the unattended location 20% of the time. All stimuli were presented in dark grey (0.28 cd/m2) against a black background (0.02 cd/m2), providing a contrast ratio of 1.4.  29  Figure 2.1 Basic Trial Conditions 2 Shown are cued (or attended) trials for targets in the a) foveal and b) parafoveal locations, respectively. The relative ratio of target and mask durations are always summed to 102 msec, with the ratio varied within each participant on a run-to-run basis in order to avoid floor and/or ceiling effects in performance sensitivity. For uncued (or unattended) targets in the parafoveal location, the foveal location was cued; conversely, for uncued targets in the foveal location the parafoveal location was cued.  a) Foveal Target  Cue: 200 msec  ISI: 600-800 msec  Time  Target: 17/34/51 msec  b) Parafoveal Target  Mask: 85/68/51  30  Each participant performed 10 blocks of 32 validly-cued targets in each of the two target locations (i.e., the cue predicted the correct target location), and 8 invalidly-cued targets in each of the two target locations (i.e., the cue incorrectly predicted the target location). Between-blocks, the ratio of the target duration and mask duration (i.e., the target signal-to-noise ratio) was varied as necessary (51/51 ms, 34/68 ms, or 17/85 ms) within each target location in order to maintain the participant’s performance near 0.75 percent correct (e.g., Handy, Soltani, & Mangun, 1999; Handy & Mangun, 2000; Handy et al., 2001).  Specifically, if  participants were performing with 100% correct responses or performing near chance, the durations were adjusted accordingly so as to allow for an optimal measure of response accuracy (MacMillan & Creelman, 2005). In this manner, the duration of the target/mask complex always remained 102 ms, but depending on individual performance, the ratio could be different for foveal relative to parafoveal targets. At the beginning of the study, each participant was given one letter as the “go” target and one letter as the “no-go” target, with the order counterbalanced between participants.  As such, participants made a button  press only when they discriminated their specific target letter. The hit rate for calculating d’ was thus defined as the ratio of “target present” responses relative to the total number of “go” trials, and the false alarm rate was defined as the ratio of “target present” responses relative to the total number of “no-go” trials, averaged across all trial blocks for that participant. The reported RTs are for correct target responses only.  31  Electrophysiological Recording Scalp potentials were recorded from 32 Ag/AgCl active electrodes (Electro-Cap International) evenly distributed across the scalp based on a modified 10-20 layout, measured relative to the left mastoid. Actual electrode sites were FP1, FP2, F3, F4, F7, F8, FZ, CZ, C3, C4, T3, T4, P1, P2, P3, P4, P5, P6, P01, P02, PZ, OZ, T5, T6, OL, OR, O1, O2, LM, RM, HEOG, and VEOG. Electroencephalic activity was amplified with a bandpass of 0.1 to 30 Hz, with a gain of 50,000, and digitized on-line at a sampling rate of 256 samples-persecond.  To ensure proper eye fixation and allow for the correction and/or  removal of events associated with eye movements, vertical and horizontal electrooculograms (EOGs) monitored eye movements, with the vertical EOG measured via an electrode inferior to the right eye, and the horizontal EOG from an electrode on the right outer canthus. Electrode impedances were kept below 5 k" for the scalp electrodes and below 20 k" for the facial electrodes. Off-line computerized artifact rejection was used to eliminate trials during which detectable eye movements (>1 degree), blinks, muscle potentials, or amplifier blocking occurred. For each subject, the waveforms for “go” and “no-go” trials were collapsed within each cue-target condition, and the resulting ERPs were derived into 3000 ms epochs, beginning 1500 ms before stimulus onset. Subsequently, all ERPS were algebraically re-referenced to the average of the left and right mastoid signals, and filtered with a low-pass Gaussian filter (25.6 Hz half-amplitude cut-off) to eliminate residual high-frequency artifacts in the waveforms. The resulting single-subject ERPs were used to derive group-  32  averaged waveforms for display and analysis. Statistical quantification of ERP data were based on mean amplitude measures relative to a -200 to 0 prestimulus baseline.  Results To examine possible age- and gender-related effects in our primary findings reported below, we initially ran repeated measures ANCOVAs with headache category (migraine vs. control) as a between-subjects factor and attention (cued vs. uncued targets) as a within-subjects factor separately for each target location and with sigma-restricted coding of categorical predictors of sex and age covariates. As we found no significant effects of age or gender, either for behavioral (all Fs < 3.93; all ps > 0.075) or ERP measures (all Fs < 1.715; all ps > 0.196), we did not include these covariates in the main results.  Behavior Mean reaction times (RTs) and perceptual sensitivity (d’) for each group are reported in Table 2.1 and 2.2, respectively, as a function of headache classification, attention, and target location. We assessed these variables via repeated-measures ANOVAs that included headache category (migraine vs. control) as a between-subjects factor and attention (cued vs. uncued targets) as a within-subjects factor separately for each target location. Mean durations for foveal and parafoveal targets are reported in Table 2.3.  33  Table 2.1 Reaction Times for Target Discrimination 2 Reaction Times (msec) for Target Discrimination, as a Function of Headache Classification, Target Location, and Attention Condition, Averaged across Participants. Standard deviation in parentheses.  Group Control Migraine  Target Location Fovea 583.19 (144.67) 614.37 (131.27) 503.83 (99.45) 571.69 (107.22)  Attention Cued Uncued Cued Uncued  Parafovea 529.49 (125.07) 559.87 (107.02) 469.63 (96.91) 510.15 (99.43)  Table 2.2 Perceptual Sensitivity Rates 3 Hits, false alarms, and d’ for Target Discrimination, as a Function of Headache Classification, Target Location, and Attention Condition, Averaged across Participants. Standard deviation in parentheses.  Group  Attention  Control Migraine  Cued Uncued Cued Uncued  Target Location Fovea D’ Hits 2.09 (.70) 0.79 (.13) 2.22 (.78) 0.81(.13) 2.62 (.63) 0.87 (.08) 2.28 (.89) 0.77 (.16)  FA 0.14(.09) 0.14(.11) 0.11 (.07) 0.12 (.12)  Parafovea D’ 3.05 (.79) 2.74 .69) 3.54 (.98) 3.40 (1.00)  Hits 0.92(.07) 0.91(.08) 0.95 (.05) 0.94 (.05)  FA 0.12(.11) 0.16(.16) 0.08 (.06) 0.13 (.12)  Table 2.3 Mean Target Duration 4 Mean Target Duration (msec), as a function of Headache Classification and Target Location, Averaged across Participants.  Group Control Migraine  Target Location Fovea 37.93 37.78  Parafovea 26.82 28.72  34  Foveal Processing As is apparent in Table 2.1, each group showed faster RTs to cued than uncued targets, but the magnitude of the attention effect appeared to be greater in migraineurs than it was in controls.  This was confirmed statistically via a  significant interaction between group and attention (F(1,56) = 5.86; p < 0.05), driven by the cued condition. Follow-up statistics revealed that, indeed, both groups did show significant within-groups effect of attention (controls F(1,28) = 1.14, p < 0.01; migraineurs F(1,28) = 31.9, p < 0.001). There was also a trend for migraineurs to be faster than controls overall (F(1,56) = 3.578; p = .064).  For perceptual sensitivity as measured by d’, both groups appeared to show an effect of attention, as can be seen in Table 2.2. However, the direction of the effect appeared to differ between groups, with migraineurs having a higher d’ value for cued vs. uncued targets, but for controls having a higher value for uncued vs. cued targets. This was confirmed statistically, where there was a significant group by attention interaction (F(1,56) = 5.330; p < 0.05), driven by the cued condition.  Follow-up statistics confirmed that both groups showed  significant within-groups effects of attention (controls F(1,28) = 1.45, p < 0.01; migraineurs F(1,28) = 4.233, p < 0.05). As is apparent in the Tables 2.1 and 2.2, the controls showed a speed-accuracy trade-off, such that they are faster but less accurate for cued vs. uncued trials.  35  Parafoveal Processing As can be seen in Table 2.1, it appeared that responses to parafoveal targets were faster for cued than uncued targets, and that this effect did not differ between groups. This was confirmed statistically with a significant main effect of attention (F(1,56) = 7.04; p < 0.001), and no interaction with group (F(1,56) = 1.442; p = 0.235). There was also a trend for migraineurs to be faster than controls overall (F(1,56) = 3.852; p = .055).  For d’, it appeared that responses to parafoveal targets were more sensitive to cued than uncued targets, and that there were no group differences in the effect of attention on perceptual sensitivity, as can be seen in Table 2.2. This was confirmed statistically with a significant main effect of attention (F(1,56) = 9.872; p < 0.01), but again no group by attention interaction (F(1,56) = 1.44; p = 0.235).  In addition, migraineurs were more sensitive than controls overall  (F(1,56) = 6.974; p < 0.05).  Electrophysiology Statistical interrogation of each of these ERP components/phases included repeated measures ANOVAs separately for the foveal and parafoveal locations, with headache category (control vs migraine) as a between-subjects factor and attention (cued vs. uncued targets) as a within-subjects factor. Separate ANOVAs within each group were planned to follow-up any significant interactions between group and attention. All P1 measures were taken from lateral occipital electrode sites OL and OR, where this component is typically 36  maximal (Handy & Mangun, 2000; Handy & Khoe, 2005; Mangun & Hillyard, 1991) and all N1 measures were taken from lateral occipital-temporal sites T5 and T6, where the N1 is typically maximal (Hopf et al., 2002; Mangun & Hillyard, 1991; Vogel & Luck, 2000).  For the P1 component, it has been further subdivided into an “early phase” prior to the P1 peak that reflects the intensity of visual processing in dorsolateral extrastriate cortex of the middle occipital gyrus, and a “late phase” in the postpeak portion of the P1 tied to processing in ventral extrastriate cortex of the posterior fusiform gyrus (Di Russo, Martinez, Sereno, Pitzalis, & Hillyard, 2002). Given that the early and late phases of the P1 show differential sensitivity to various forms of visual attention (Fu, Caggiano, Greenwood, & Parasuraman, 2005; Hopfinger & Ries, 2005; Hopfinger & West, 2006), planned analysis of the P1 included a traditional mean amplitude measure centered on the P1 peak, as well as separate mean amplitude measures of the pre- and post-peak portions of the P1 component in order to independently examine the early and late P1 phases.  Foveal Processing Mean P1 Peak. Mean amplitude of the lateral occipital P1 was measured over a 110-140 ms post-stimulus time window centered on the approximate peak of the P1 in the grand-averaged waveforms and are reported in Table 2.4 as a function of headache classification, attention, and target location. As can be seen in Figure 2.2, the amplitude of the P1 appeared to be very similar for cued 37  relative to uncued targets at the fovea in both groups, and this was confirmed statistically. We found no main effect of attention (F(1,56) = 1.68; p = 0.20), or group (F(1,56) = 0.94; p = 0.34), and no group by attention interaction (F(1,56) = 0.31; p = 0.58).  Table 2.4 Mean Amplitudes of the Lateral Occipital Component 5 Mean Amplitudes (µV) of the Lateral Occipital Component, as a Function of Headache Classification, Target Location, Attention Condition, Component, and Electrode Location, Averaged across Participants. Standard error of the mean in parentheses.  ERP Scalp Component Location P1 OL OR Early P1 OL OR Late P1 OL OR N1 T5 T6 Migraine P1 OL OR Early P1 OL OR Late P1 OL OR N1 T5 T6  Group Control  Fovea Cued 1.85 (.35) 1.64 (.33) 1.29 (.26) 1.04 (.24) 0.96 (.46) 1.22 (.42) -0.61 (.52) 0.13 (.43) 2.16 (.29) 2.04 (34) 1.52 (.23) 1.38 (.27) 0.70 (.51) 0.87 (.50) -0.74 (.52) 0.33 (.49)  Uncued 1.59 (.41) 1.36 (.35) 1.27 (.36) 1.04 (.27) 0.63 (.51) 0.87 (.50) -0.81 (.47) -0.06 (.49) 2.06 (.35) 1.93 (.35) 1.42 (.28) 1.27 (.28) 0.30 (.53) 0.57 (.60) -1.81 (.52) -0.43 (.49)  Parafovea Cued 3.78 (.54) 3.94 (.57) 2.59 (.44) 2.57 (.41) 3.30 (.44) 3.80 (.50) 1.02 (.31) 1.50 (.38) 3.97 (.40) 4.78 (.48) 2.42 (.32) 2.87 (.32) 3.25 (.42) 4.34 (.50) 0.78 (.40) 1.86 (.40)  Uncued 2.96 (.49) 3.04 (.43) 1.91 (.40) 1.90 (.33) 2.47 (.46) 2.99 (.45) 0.34 (.37) 0.76 (.42) 3.64 (.37) 4.20 (.44) 2.46 (29) 2.64 (.29) 2.55 (.52) 3.56 (.50) 0.01 (.59) 0.82 (.47)  38  Figure 2.2 P1 and N1 Component Responses to Foveal Targets 3 All waveforms are displayed relative to a baseline of –200 to 0 msec prestimulus. Shown are the waveforms from lateral posterior electrode sites for Control Group.  39  Early Phase P1.  Mean amplitude of the early phase of the P1 were  measured over a 90-125 ms post-stimulus time window and is reported in Table 2.4 as a function of group and attention. As can be seen in Figure 2.2, the amplitude of the early phase P1 appeared to be very similar for cued relative to uncued targets at the fovea in both groups, and this was confirmed statistically. We found no main effect of attention (F(1,56) = 0.17; p = 0.68) or group (F(1,56) = 0.48; p = 0.49), and no group by attention interaction (F(1,56) = 0.13; p = 0.72).  Late Phase P1.  Mean amplitude of the late phase of the P1 was  measured from a 125-175 ms post-stimulus time window and is reported in Table 2.4 as a function of headache classification, attention, and target location. We found a main effect of attention (F(1,56) = 5.43; p < 0.05) such that the mean amplitude was larger for cued vs. uncued targets, but there was no main effect of group (F(1,56) = 0.21; p = 0.65) or group by attention interaction (F(1,56) = 0.01; p = 0.96).  N1 Amplitude. Mean amplitude of the lateral occipital N1 was measured over a 160-190 ms post-stimulus time window centered on the approximate N1 peak in the grand-averaged waveforms, and is reported in Table 2.4 as a function of headache classification, attention, and target location. As can be seen in Figure 2.2, the amplitude of the N1 appeared to be larger for uncued relative to cued targets at the fovea but more so in the migraine group, and this was confirmed statistically.  We found a significant group by attention interaction  (F(1,56) = 4.24; p < 0.05). The planned follow-up ANOVA revealed that controls 40  did not have an attention effect at the fovea (F(1,28) = 0.28; p = .60), while the migraineurs did (F(1,28) = 19.58; p < 0.001). Overall, this indicated that N1 amplitudes were larger for uncued relative to cued targets, and the main effect was driven by the migraine group.  Parafoveal Processing P1 Amplitude. Mean amplitude of the lateral occipital P1 was measured over a 120-150 ms post-stimulus time window centered on the approximate peak of the P1 in the grand-averaged waveforms and is reported in Table 2.4 as a function of headache classification and attention. As can be seen in Figure 2.3, the amplitude of the P1 appeared to be larger for cued relative to uncued targets at the parafovea in both groups, and this was confirmed statistically. We found significant main effects of attention (F(1,56) = 13.78; p < 0.001), but no main effect of group (F(1,56) = 1.47; p = 0.23) or group by attention interaction (F(1,56) = 1.28; p = 0.26). This indicated that overall P1 amplitudes were consistently larger for cued relative to uncued targets regardless of group.  41  Figure 2.3 P1 and N1 Component Responses to Parafoveal Targets 4 All waveforms are displayed relative to a baseline of –200 to 0 ms prestimulus. Shown are the waveforms from lateral posterior electrode sites for Control Group.  42  Early Phase P1. Mean amplitude of the early phase P1 was measured over a 90-135 ms post-stimulus time leading up to the peak of the P1 in the grand-averaged waveforms and is reported in Table 2.4 as a function of headache classification, attention, and target location. As can be seen in Figure 2.3, the amplitude of this early phase of the P1 appeared to be different for cued relative to uncued targets at the parafovea between groups, such that there was an effect of attention for controls but not migraineurs, and this was confirmed statistically. We found a group by attention interaction (F(1,56) = 3.82; p = 0.05). ANOVAs within each group revealed that controls had a main effect of attention in the early phase P1 (F(1,28) = 8.69; p < 0.01) but migraineurs did not (F(1,28) = 0.27; p = 0.61).  Late Phase P1. Mean amplitudes of the late phase of the lateral occipital P1 was measured over a 135-175ms post-stimulus time window leading away from the peak of the P1 in the grand-averaged waveforms and is reported in Table 2.4 as a function of headache classification and attention and target location. As can be seen in Figure 2.3, the amplitude of the late phase P1 appeared to be greater for cued relative to uncued targets at the parafovea in both groups, and this was confirmed statistically. We found a main effect of attention (F(1,56) = 16.43; p < 0.001), but no main effect of group (F(1,56) = 0.25; p = 0.62) or group by attention interaction (F(1,56) = 0.05; p = 0.825).  43  N1 Amplitude. Mean amplitude of the lateral occipital N1 was measured over a 160-190 ms post-stimulus time window centered on the approximate N1 peak in the grand-averaged waveforms and is reported in Table 2.4 as a function of headache classification and attention and target location. As can be seen in Figure 2.3, the amplitude of the N1 appeared to be larger for uncued relative to cued targets in both groups, and this was confirmed statistically.  We found  significant main effects of attention (F(1,56) = 20.12; p < 0.001), but no main effect of group (F(1,56) = 0.01; p = 0.94) or group by attention interaction (F(1,56) = 0.31; p = 0.58). This indicated that overall N1 amplitudes were larger for uncued relative to cued targets, and that this did not differ between groups.  Control Analyses In addition to the above analyses directly relating to our study’s question of interest, we also wanted to examine two control issues associated with our migraine group. In particular, we wanted to determine whether the pattern of results we report for migraineurs varied as a function of (1) migraine sub-types in our migraine group (aura vs. non-aura), and (2) the age of migraineur participants, which included a broader range of older participants than our control group.  Migraine Subtypes In people presenting with migraine headaches, approximately 20% have visual auras as part of their constellation of migraine symptoms. Our migraine group comprised 13 individuals who could be classified as migraine with aura 44  and 16 participants who had migraine without aura. We compared these two groups to determine whether this sub-population of migraineurs manifest any differences in d’ perceptual sensitivity, reaction time, P1 mean peak, early-phase P1, or late-phase P1 or N1 attention effects at the fovea or parafovea. Our reason for this comparison in the sub-populations of migraineurs was that, in assessments of neural and cognitive function, migraineurs with and without aura tend to show the same qualitative differences relative to controls, but in some experimental studies quantitative differences are more apparent or only found in migraineurs with aura (Chronicle et al., 1995). Statistical interrogation of each of the ERP components/phases included repeated measures ANOVAs with migraine subtype (13 migraine with aura vs. 16 migraine without aura) as a between-subjects factor, and location (fovea and parafovea) and attention (cued vs. uncued targets) as within-subjects factors. There were no differences in attention effects between the two migraine groups for early-phase P1, late-phase P1, mean peak P1, or N1 at either location (all Fs(1,27) < 0.82; all ps > 0.374). There were also no behavioral differences (reaction times or perceptual sensitivity) between the two migraine groups (all Fs(1,27) < 0.903; ps >0.350).  Effect of Age Distribution In addition to the ANCOVAs reported above for age as a covariate, to further demonstrate the group results were not affected by age in our migraine results, we divided the migraine group into two equal groups at the median age, dropping the median participant. Thus, the “younger” migraine group had 14 participants aged 18-25 and the “older” migraine group had 14 participants aged 45  25-54. We then ran repeated measures ANOVAs for each of the behavioral and ERP components of interest, comparing the two migraine age groups  (14  “younger” migraineurs vs. 14 “older” migraineurs) as a between-subjects factor and attention (cued vs. uncued targets) as within-subjects factors at each location (fovea and parafovea).  We found that neither of the behavioral  measures differed between these two migraine age groups (all Fs(1,27) < 2.413; all ps > 0.13). We found that the N1 attention effect for foveal targets differed between these two migraine age groups (F(1,27) = 4.67; p < .05), whereas all the remaining components did not differ in attention effects between the two migraine groups (all Fs(1,27) < 0.7056; all ps > .15). Comparison of the means showed that both groups had an N1 greater for uncued than cued, but the magnitude was greater for the younger migraineurs. This suggests that, if anything, inclusion of older migraineurs actually attenuated the difference that we found between the migraineurs (n=29) and controls (n=29).  Discussion Our study assessed the hypothesis that migraineurs may have an altered ability to modulate the sensory-evoked excitability of visual cortex in a goaldirected, top-down manner via visual-spatial attention. Towards answering this question, we found two significant differences between migraineurs relative to non-migraine controls.  First, in the parafovea, migraineurs showed no early-  phase attention effect in the P1 ERP component. Instead, attention effects were only found in the late phase of the P1, following the P1 peak. In comparison, control participants showed significant attention-related effects in both the early 46  and late phase of the P1 component. Second, at the fovea, migraineurs had an increased N1 for unattended relative to attended targets, a data pattern that was present but not statistically significant in the control group. Taken together, our findings thus suggest that the altered excitability of visual cortex in migraineurs is not limited to external modulatory signal sources (e.g., Antal et al., 2006; Aurora et al., 1998; Mulleners et al., 2001), but extends to endogenously-generated modulatory signal sources as well. In the following sections, we discuss the functional implications of our ERP findings, as well as the broader consequences for attention and migraine in general.  Sensory Suppression in the Parafovea The hypothesis for our study—migraineurs may have an altered ability to modulate extrastriate visual cortex via visual spatial attention—was predicated on the common neuroanatomical locus of migraine visual anomalies and spatial attention effects in visuocortical processing—extrastriate cortex.  Given the  deficits in extrastriate cortex observed in migraineurs (e.g., Battelli et al., 2002; Ditchfield et al., 2006; Fierro et al., 2003), it is thus perhaps not surprising that we found migraineurs to have an absent attentional response in the early phase of the P1 ERP component, which has been shown to index the intensity of sensoryevoked activity in dorsolateral extrastriate cortex (e.g., Di Russo et al., 2002). Importantly, however, the effect itself was limited to parafoveal targets, such that the early-phase P1 response for these targets was equivalent in amplitude for both attended and unattended conditions.  47  How should this be interpreted functionally? Three lines of converging evidence suggest that it reflects a decreased level of “normal” suppression for unattended events outside the fovea. First, visual spatial attention is known to modulate sensory-evoked visual cortical activity by a combination of amplifying sensory-evoked activity in attended locations while simultaneously suppressing or inhibiting sensory-evoked activity in unattended locations in a manner analogous to the classic center-surround response properties of retinal ganglion cells (e.g., Slotnick et al., 2002; Slotnick et al., 2003).  Within this context,  attention effects in the P1––that is, amplitude differences in the P1s elicited by attended vs. unattended stimuli—are believed to reflect the active suppression of sensory-evoked activity for unattended stimuli (e.g., Hillyard, Vogel, & Luck, 1998; Luck, 1995). In this model, the absence of an early-phase P1 attention effect in migraineurs for parafoveal targets would thus be explained by a lack of attention-related suppression of sensory-evoked activity for unattended targets, rather than an absence of facilitation for attended targets.  Second, that migraineurs have an altered ability to suppress sensoryevoked activity for unattended stimuli also aligns with the inhibition-based model of migraine visual cortical pathophysiology. Briefly put, this theory holds that cortical hyperexcitability found in striate (e.g., Chronicle et al., 2006; Mulleners et al., 2001) and extrastriate (e.g., Battelli et al., 2002) cortex in migraineurs, arises in part from a lack of GABA-ergic inhibitory control (e.g., Brighina et al., 2009; Chronicle & Mulleners, 1996). To be sure, migraineurs likely also have altered excitatory neurotransmitter activity in visual cortex, such as increased 48  presynaptic glutamate release and/or decreased glutamate reuptake relative to non-migraine populations (e.g., Aurora & Wilkinson, 2007; Bussone, 2004). Nevertheless, models linking P1 attention effects to an active suppression of unattended visual-sensory inputs (e.g., Hillyard et al., 1998; Luck, 1995) predict exactly what was observed here for migraineurs: if there is reduced inhibitory control in visual cortex, there should be a corresponding reduction in the magnitude and extent of P1 attention effects.  Finally, our conclusion here also fits well with both anecdotal and empirical reports from migraineurs, who frequently remark on the distracting nature of extraneous visual inputs (e.g., Sacks, 1992). Indeed, recent laboratory evidence suggests that migraineurs’ visual abnormalities may be considered signal-tonoise issues, where the ability to hone in on visual signals of interest is impaired by increased distraction from extraneous noise (e.g., Antal et al., 2006; Aurora & Wilkinson, 2007; Wagner, Manahilov, Loffler, Gordon, & Dutton, 2010). Moreover, not only did Wagner et al. (2010) find that migraineurs have difficulties in excluding external noise sources, but they attributed this difficulty to decreased GABA-mediated suppression in cortex. Notably, our data here directly parallel these reports and findings. Specifically, the apparent decreased suppression for unattended stimuli outside the fovea in migraineurs and increased reaction times could be symptomatic of their increased sensitivity to visual noise.  49  Discriminative Processing at the Fovea The second group difference we found in the ERP data was that migraineurs showed a significantly larger N1 for unattended vs. attended targets at the fovea, but controls did not. What does this reveal about visual processing in migraineurs?  Whereas attention effects in the P1 have been tied to the  suppression of sensory-evoked activity for stimuli outside the focus of attention, attentional modulation of the N1 has been linked to the active facilitation of sensory-evoked activity for stimuli falling within the attended region of space (e.g., Hillyard et al., 1998; Luck, 1995). While at first pass it may be tempting to conclude that migraineurs simply show a heightened degree of facilitation for attended events at the fovea relative to non-migraineurs, two factors make this direct interpretation difficult.  First, the cortical locus of the visual N1 has not been well-characterized. Thus, unlike the P1, there is no clear mapping of the N1 effect we report here to known functional pathologies in migraine cortex. Second, the actual pattern of attention effects we observed here—the N1 amplitude for foveal targets in migraineurs was greater on unattended relative to attended trials—is reverse to the more typical finding of an increased N1 for attended events in the upper and lower visual field quadrants (e.g., Handy & Mangun, 2000; Handy, Green, Klein, & Mangun, 2001; Luck et al., 1994; Mangun & Hillyard, 1991). To be sure, our N1 pattern was not necessarily unexpected, in that not only did Handy and Khoe (2005) find the same “reversed” N1 effect using the identical paradigm, but other ERP studies have also reported similar N1 data patterns when using stimuli 50  presented at the fovea or on the vertical meridian (e.g., Fu et al., 2005; Handy et al., 2001). Moreover, functional changes in the amplitude of sensory-evoked visual ERP components can vary depending on the retinotopic location of the ERP-eliciting stimulus. In particular, changing the location of a visual stimulus changes the orientation of the component-generating dipole in retinotopicallymapped cortex relative to the scalp surface, which can in turn affect the amplitude of the component, it’s polarity, and how it changes with attention (e.g., Clark & Hillyard, 1996; Mangun, Hillyard, & Luck, 1993). As such, it is possible that what appears to be a larger N1 for unattended targets at the fovea may actually reflect enhanced processing for attended targets, as ERP-based models of attention would predict (e.g., Hillyard et al., 1998; Luck, 1995). However, in the absence of further evidence, such a proposal would be speculative at best.  Instead, the firmest statement that can be made regarding our N1 finding in migraineurs is that it reflects an altered level of visual discriminative processing in cortex, relative to the non-migraine population. This conclusion stems from the canonical view of the N1 as indexing the degree or intensity of visual discrimination afforded to sensory inputs (e.g., Vogel & Luck, 2000).  And  notably, as we discuss in the next section, it would appear that based on between-group differences in response performance, migraineurs actually show heightened discriminative functioning.  51  Migraine and Attentional Performance Although ERPs were the primary dependent measure in our study, we were also able to compare behavioral performance between migraineurs and controls, in terms of both RTs and perceptual sensitivity (as indexed by d’). this regard, migraineurs actually out-performed controls in two key ways.  In  First,  in the parafovea, while both groups showed greater perceptual sensitivity for attended relative to unattended targets, migraineurs also showed an overall greater perceptual sensitivity relative to controls, regardless of the attention condition.  That this co-occurred with a trend towards faster overall RTs for  migraineurs indicates that their increased level of perceptual sensitivity in the parafovea can’t be dismissed as a simple speed-accuracy tradeoff. Rather, the d’ data in this case converge on the subjective reports of migraineurs outlined above, reports also suggesting that migraine is associated with an increased perceptual sensitivity to non-central visual inputs.  Second, at the fovea, whereas the controls and the participants in the study by Handy and Khoe (2005) showed greater perceptual sensitivity for unattended relative to attended targets, migraineurs showed the opposite pattern here, such that their perceptual sensitivity was greater for attended relative to unattended targets. In the context of the specific perceptual task here—identify a letter that is presented briefly and then rapidly masked—this indicates that in non-migraineurs (or in populations not screened for migraine status, as in the case of Handy and Khoe, 2005), whatever functional impact visual attention has on foveal processing leads to performance decrements in target discrimination. 52  Conversely, however, migraineurs’ attentional functioning at the fovea puts them at a perceptual advantage in our discrimination task. Although the underlying basis for this performance difference between migraineurs and controls remains unclear, migraineurs show the more beneficial attentional outcome.  In conclusion, whether or not migraine is consistently associated with perceptual advantages has been somewhat equivocal across studies, with some finding enhanced performance for migraineurs (e.g., Wray et al., 1995)  and  others not (e.g., Conlon & Humphreys, 2001; Palmer & Chronicle, 1998; Shepherd, 2006).  Although our study was not designed to resolve these  differences, the data here nevertheless suggest that migraineurs do have altered top-down attentional modulation of visual cortex, and that it does not necessarily come with perceptual costs. If anything, quite the opposite.  53  Chapter 3: Reflexive Attentional Orienting in Migraineurs2  2  A version of this chapter has been accepted for publication. Mickleborough, M. J. S., Hayward, J., Chapman, C., Chung, J., & Handy, T. C. (in press). Reflexive attentional orienting in migraineurs: the cognitive implications of hyperexcitable visual cortex. Cephalalgia.  54  Introduction Although migraine is classified as a headache disorder, a key part of migraine pathophysiology is a heightened excitability of sensory cortices in between headache events.  In vision for example, migraineurs are more  susceptible to visual illusions (e.g., Shepherd, 2006), have more discomfort in the presence of intense or repetitive patterns of visual stimulation (e.g., Marcus & Soso, 1989), and show reduced sensory habituation to repetitive visual stimuli (e.g., Afra et al., 1998; Coppola et al., 2009; Di Clemente et al., 2005; Giffin & Kaube, 2002; Siniatchkin et al., 2003). Given these visual sensory issues in migraine, the goal of our study here was to examine their possible impact on reflexive visual attentional orienting.  At issue in our study is whether visual cortical hyperexcitability in migraineurs may have functional consequences beyond the initial sensory responses themselves.  In particular, visual spatial attention is automatically  drawn to the location of sudden-onset, non-foveal visual stimuli in an automatic, bottom-up manner (e.g., Hopfinger & Mangun, 1998; McDonald, Ward, & Kiehl, 1999; Posner & Cohen, 1984). On the possibility that the magnitude of reflexive orienting may increase with the intensity of the sensory-evoked response to a visual stimulus, this suggests that migraineurs may not just be affected by an exaggerated sensory response itself, but as well, from the subsequent effect this has on reflexive attentional orienting.  In other words, does visuocortical  hyperexcitability in migraine lead to heightened reflexive orienting to suddenonset events in the visual periphery? 55  That it might is consistent with several lines of converging evidence. For one, at a subjective level, migraineurs frequently report having difficulty ignoring distracting visual stimuli (e.g., Sacks, 1992). Likewise, in the laboratory, migraineurs have been shown to have a reduced ability to suppress extraneous visual noise (e.g., Wagner et al., 2010). Indeed, even when migraineurs consciously orient their attention to a discrete location in visual space, they nevertheless manifest heightened sensory responses to visual events outside their zone of attentional focus, relative to non-migraine controls (Mickleborough, Truong, & Handy, 2011). Collectively, this suggests that migraineurs have systematic impairments in attenuating attentional responses to non-foveal visual stimuli, and precisely aligns with what would be predicted if they showed heightened reflexive visual-spatial orienting to sudden-onset non-foveal events.  Towards testing this prediction, we examined migraineurs reflexive visual spatial orienting in Experiment 1 using a canonical peripheral attentional cuing paradigm.  On each trial participants made speeded detection responses to  small, brief targets presented in either the upper left or upper right visual field quadrant.  The target locations themselves were demarcated by boxes that  remained onscreen throughout each trial block. Prior to each target presentation, one of the two box outlines brightened briefly, serving as the sudden-onset, sensory-driven attentional cue. On half the trials the target was presented at the "cued" location, and the other half of the trials the target was presented at the opposite––or "uncued"––location. In these paradigms, people are faster and more accurate in their responses when the target is presented at the cued 56  location within 200-300 ms after cue onset, relative to targets presented at the uncued location, the behavioral signature of attention being reflexively oriented to the cued location (e.g., Handy, Jha, & Mangun, 1999; Posner & Cohen, 1984). If migraineurs do in fact have heightened reflexive visual spatial orienting to sudden-onset non-foveal events, then it is predicted that they should have a larger effect of attention in RT performance, relative to non-migraine controls.  Experiment 1 Materials and Methods Participants A total of 40 paid volunteers participated, 20 in the non-migraine control group (15 women and 5 men) and 20 in the migraine group (17 women and 3 men). The control group mean age was 22.2 (SD 5.1) years and the migraineurs were 23.9 (SD 4.1) years, with no significant difference between group age (F(1,38) = 1.344; p = .254). The migraineurs had 15.4 (SD 22.6) headaches a year, while the controls had 3.0 (SD 3.1) headaches a year (non-classified as migraine; see below).  Headache Classification All migraine participants were required to meet the migraine criteria specified by the International Headache Society (Headache Classification Subcommittee of the International Headache Society, 2004) and as determined by an interview.  Specifically, in order to be included in the migraine group,  57  participants had to meet basic minimum criterion including 5 or more attacks with headache lasting 4-72 hours. In turn, the headaches needed to include two of the following: unilateral pain; pulsating pain quality; moderate to severe pain; and pain aggravated by routine physical activity such as walking or climbing stairs. The headache also had to be accompanied by nausea and vomiting or photophobia and phonophobia. All our migraine participants had not suffered from a migraine for at least 48 hours before testing nor did they have a migraine for at least 48 hours after testing. In addition to our headache classification criterion, migraineurs were excluded if they were taking any form of migraine prophylactics.  Stimuli and Timing Stimulus timing and sequence are shown in Figure 3.1. Each trial started with the presentation of a nonfoveal (peripheral) cue to the left or right of fixation. Following the cue, a small target dot was presented in one of the two peripheral locations. On half the trials the target was presented at the cued location, and on the other half of the trials the target was presented at the uncued location. As such, the cue was unpredictive as to the location of the pending target. As well, reflexive visual attentional orienting to sudden-onset peripheral events at short cue-target delays gives way to inhibition of return (or IOR; faster RTs for uncued vs. cued targets) at longer cue-target delays (e.g., Handy et al., 1999; Posner & Cohen, 1984). Accordingly, we randomly varied the onset of cue to the onset of target between trials (170 ms vs. 960 ms) to confirm this normative pattern of reflexive attentional orienting. As such, following a 2250-2650 fixation period, the 58  cue remained onscreen for 150 ms. Then, after a 20 or 810 ms cue-target delay, the target would appear for 50 ms. The target locations, one in each upper visual-field quadrant, were demarcated by the outlines of 1.0° white square boxes. These boxes were located 3.2° (to center) from fixation and 1.3° (to center) above the horizontal meridian. The nonfoveal cue was a brief brightening of one of the two boxes. The fixation point was a 0.2° fixation cross; the target dot was 0.1°.  Figure 3.1 Basic Trial Conditions for Experiment 1 5 Shown are cued and uncued trials.  59  Procedure Participants were required to press a button as quickly as possible after the appearance of the target dot on the screen. A cued trial was defined as a target at the cued peripheral location and an uncued trial was defined as a target at the uncued peripheral location. On 20% of the trials (catch trials), only a cue was presented, in order to eliminate anticipatory responses. Each participant completed 12 blocks of 50 trials (20 cued, 20 uncued and 10 catch trials per block), with the target trials equally split (but randomly varying) between short and long cue-target delays, so as to decrease expectation effects. No feedback was given on hit or miss rates.  Results Reaction Times To examine possible age- and gender-related effects in our primary findings reported below, we initially ran repeated measures ANCOVAS with sigma-restricted coding of categorical predictors for sex and age covariates. As we found no significant effects of age or gender (all F’s < 2.773; all p’s > 0.105), we did not include these covariates in the main results.  Target-Present Trials Mean reaction times to targets are presented in Figure 3.2 as a function of group, attention, and cue-target delay.  As can be seen, it appeared that  migraineurs had a greater attention effect at short cue-target delays, relative to 60  controls. To confirm this data pattern we assessed RTs via repeated-measures analyses of variance that included headache category (migraine vs. control) as a between-subjects factor and attention (cued vs. uncued targets) and cue-target delay (short vs. long delay) as within-subjects factors. We found a significant interaction between group, cue and cue-target delay, (F(1,38) = 4.178; p < 0.05). Performing separate follow-up t-tests within each group, both groups did indeed show a significant cuing effect at the short cue-target delay (for controls, t(19) = 2.891; p < 0.01; for migraineurs, t(19) = -3.853; p < 0.001) and a significant IOR effect at the long cue-target delay (for controls, t(19) = 7.477; p < 0.001; for migraineurs, t(19) = 8.592; p < 0.001). Importantly, however, separate follow-up between-groups ANOVA within each cue-target delay condition revealed a significant group x cue interaction at the short cue-target delay (F(1,38) = 5.892; p < 0.05), indicating a greater cuing effect for migraineurs vs. controls, but no such interaction was found at the long cue-target delay (F(1,38) = 0.955; p = 0.335).  61  Figure 3.2 Mean Reaction Times (RTs) to Targets 6 RTs to targets as a function of group, attention, and cue-target delay.  Catch Trials On 20% of the trials (catch trials), only a cue was presented, in order to eliminate anticipatory responses. The proportion of catch trials in which participants had a button press did not differ between groups (F(1,38) = 0.008; p = 0.931) with both groups responding on about 2% of catch trials (migraineurs mean 2.0%, SD 2.7%; controls mean 1.9%, SD 2.5%).  62  Control Analyses Proportional Analysis In addition, one may notice that migraineurs appear to respond slower overall to targets than controls, and this was confirmed statistically (F(1,38) = 6.429; p < 0.05). Although our RT findings suggest that migraineurs show greater cuing effects than non-migraineurs, an alternative explanation is that the apparent effect may be an artifact of this overall slower RTs in migraineurs. For example, if migraineurs simply respond at some constant rate slower than controls, we would expect to see an equal proportional increase in RTs between cued vs. uncued conditions in both groups. This would suggest that both groups are equally affected by the cue. To address this possibility that the increased magnitude in effects found may be a consequence of this overall speeded difference, we ran an additional analyses comparing the proportional difference between the cued and uncued targets. The proportional analyses revealed that indeed, the difference between groups held for the short cue-target delay (F(1,38) = 5.918; p < 0.05), but not for the long cue-target interval (F(1,38) = 0.027; p = 0.870), which demonstrates that the difference is not simply due to a slower overall response time by migraineurs.  Migraine Subgroups Some studies report that there are differences between MA vs MO groups. Accordingly, we divided the migraine group into more specific headache categories, with 8 Migraine with Aura and 12 Migraine without Aura. There were  63  no interactions between subgroup and attention (all Fs(1,18) < 1.01; ps > 0.328) and no overall differences in reaction speeds between subgroups (F(1,18) = 0.05; p = 0.836).  Discussion The results of Experiment 1 suggest that migraineurs do in fact have heightened reflexive visual-spatial orienting to sudden onset non-foveal events, an effect on attention consistent with known visual cortical hyperexcitability in migraine populations (e.g., Aurora & Wilkinson, 2007; Pietrobon, 2005). However, an alternative possibility is that migraineurs may simply have greater reflexive attentional orienting responses in general, the byproduct of a learned response to visual hypersensitivities rather than a direct result of heightened sensory responses per se. To test this possibility, we performed a second experiment that triggered reflexive visual spatial orienting via so-called "feature singletons."  In particular, in attentional capture paradigms, participants are asked to respond to targets that are not presented in isolation, but rather, in the context of multiple surrounding distractors that are presented simultaneously. On some trials the distractors are identical in terms of features like shape and color, and only the target is unique among the array of items. On other trials however, one of the distractors is uniquely different from the others (e.g., a different color or shape), a manipulation designed to reflexively draw attention to this "feature singleton." The extent to which attention is actually "captured" by the singleton is 64  determined by comparing target RTs on singleton present vs. absent trials–– longer RTs on singleton-present trials indicate "capture", or reflexive attentional orienting (e.g., Theeuwes, 1992). If the results of Experiment 1 were really tied to overall greater attentional sensitivities in migraineurs rather than visual cortical hyperexcitability, then they should show similar evidence of increased reflexive orienting in attentional capture paradigms.  Conversely, if the results of  Experiment 1 were due to sensory cortical hyperexcitability, migraineurs should show no difference from controls.  Experiment 2 Materials and Methods Participants A total of 56 paid volunteers participated in our study, 28 in the nonmigraine control group (20 women and 8 men) and 28 in the migraine group (21 women and 7 men). Of the 28 migraine participants, 5 had also participated in Experiment 1. The control group mean age was 22.8 (SD 3.3) years and the migraineurs were 25.5 (SD 7.1) years, with no significant difference between group age (F(1,55) = 3.491; p = .067). The migraineurs had a mean of 22.7 (SD 32.9) migraine headaches a year, while the controls had a mean of 11.7 (SD 21.9) non-migraine headaches a year. Headache classification was performed in the same manner as in Experiment 1.  65  Stimuli and Procedures Stimulus sequence and timing are shown in Figure 3.3. A black central circular fixation point (0.5 cm diam.) was located in the centre of the computer screen and remained on-screen for the duration of each trial block. On each trial, four stimulus elements––consisting of three squares and one diamond––were presented, spaced randomly at equal intervals above, below, left, or right of fixation around the boundary of an imaginary circle surrounding fixation (0.57 º radius). The open black squares had a line weight of 0.5 pt (0.38 º sides) and served as the distractors on each trial. The target shape singleton was an open black diamond shape with similar dimensions and luminance to the squares except for being oriented at a 90 º angle to create the diamond shape. Presented within each stimulus element was a small black bar oriented either vertically or horizontally (0.19º in length). The task required participants to signal on each trial the orientation of the bar within the diamond (vertical vs. horizontal). In the singleton distracter condition, which occurred in half the presentations, one of the three distractor squares was red in colour, rather than black. All variables in the paradigm––diamond location, target bar orientation, orientation of bars within the distractors, and location of the singleton distractor (when present)–– were randomly varied within each block of trials.  In terms of responding,  horizontal vs. vertical line was indicated using button presses on a hand-held response device with the left vs. right thumb, with the orientation/thumb mapping counterbalanced between participants.  Participants were told to ignore the  singleton distracter, to maintain fixation at all times and to respond as quickly and  66  as accurately as possible during the task. No feedback was given on accuracy rates. Stimuli were viewed at a distance of 150 cm. Stimuli were presented in 24 blocks of 24 trials. Each session was completed in approximately 1 hour.  Figure 3.3 Basic Trial Conditions for Experiment 2 7 Shown are no distractor and distractor singleton trials.  67  Results To examine possible age- and gender-related effects in our primary findings reported below, we initially ran repeated measures ANCOVAS with sigma-restricted coding of categorical predictors of sex and age covariates. As we found no significant effects of either age or gender (all F’s < 2.201, all p’s > 0.144), we did not include these covariates in the main results.  Reaction Times Mean RTs are presented in Figure 3.4 as a function of group and attention. Both groups appeared to show attentional capture effects in RT, such that the RTs were slower when a singleton distracter was present vs. absent, but this effect did not appear to differ in magnitude between groups.  This was  confirmed via an omnibus ANOVA that included group (migraine vs. control) as a between-group factor and capture condition (singleton present vs. absent) as a within-groups factor. This analysis, revealed a main effect of capture (F(1,54) = 27.144; p < 0.001), but no interaction between capture and group (F(1,54) = 0.078; p = .781). As well, there was no significant main effect of group (F(1,54) = 0.009; p = .926), indicating overall RTs were comparable between groups.  68  Figure 3.4 Mean Reaction Times (RTs) to Targets 8 RTs as a function of group and capture.  Accuracy Mean accuracies are presented in Table 3.1 as a function of group and capture condition. As with RTs, we assessed accuracy via repeated-measures ANOVAs that included group (migraine vs. control) as a between-subjects factor and capture condition (singleton present vs. absent) as a within-subjects factor. Looking at Table 3.1, it appeared that there is an effect of capture condition 69  (singleton present vs. absent) on accuracy, but there was no difference between groups in terms of effect magnitude. This was confirmed statistically, with a main effect of capture condition (F(1,54) = 6.820; p < 0.05), but no interaction between capture and group (F(1,54) = 1.377; p = .246).  In addition, there was no  significant difference in overall accuracy between groups (F(1,54) = 0.785; p = 0.380).  Table 3.1 Mean Accuracies 6 Mean accuracies as a function of Group and Singleton Condition. Standard deviation in parentheses.  No Distractor  Distractor  Controls  0.90 (.07)  0.89 (.07)  Migraineurs  0.88 (.12)  0.86 (.14)  Control Analyses Subgroups To examine whether the type of headache affected task performance, we divided the participants into more specific headache categories, with 6 Migraine with Aura, 22 Migraine without Aura, 21 Controls with Tension Type headache, and 7 controls with no headache history.  There were no interactions between  subgroup and capture condition (for reaction times F(3,52) = 0.276; p = 0.843; for accuracy F(3,52) = 1.440, p = 0.242) and no overall differences in reaction  70  speeds between subgroups (for reaction times F(3,52) = 1.457; p = 0.237; for accuracy F(3,52) = 0.557; p = 0.646).  Discussion In Experiment 2 we found no difference between migraineurs and controls in terms of reflexive attentional orienting as captured by color feature singletons. This suggests that migraineurs don't necessarily have heightened reflexive attentional orienting in general, but rather, they have heightened reflexive orienting linked to hyperexcitable visual cortical responses to sudden-onset peripheral events. However, with respect to this conclusion, it could also be the case that the need to attend peripherally––which was present in Experiment 1 but not Experiment 2––may drive the cuing effects seen in Experiment 1, and not visual cortical hyperexcitability per se. In other words, migraineurs might show heightened reflexive orienting to the visual periphery regardless of the attentional trigger, something the paradigm in Experiment 2 could not assess due to the relatively close spatial proximity all the stimuli had to fixation.  To test this possibility, we thus ran a third experiment, using non-foveal targets as in Experiment 1 but that triggered reflexive visual orienting via eye gaze cues presented at fixation. The notion that people orient their attention to where someone else is looking has been confirmed in studies revealing that eye gaze cues trigger reflexive shifts in attention (Friesen & Kingstone, 1998; Friesen, Ristic, & Kingstone, 2004). If migraineurs show heightened reflexive orienting to the visual periphery in general, then it is predicted that they should have a 71  greater attentional cuing effect in this paradigm, relative to controls. Conversely, if heightened reflexive orienting in migraineurs is really driven by hyperexcitable responses to peripheral visual stimuli, then it is predicted that migraineurs should have comparable attentional responses in this paradigm, relative to controls.  Experiment 3 Materials and Methods Participants A total of 34 paid volunteers participated in our study, 17 in the nonmigraine control group (14 women and 3 men) and 17 in the migraine group (14 women and 3 men). Of the 17 migraine participants, 1 had also participated in Experiments 1 and 2. The control group mean age was 20.2 (SD 1.6) years and the migraineurs were 21.7 (SD 3.1) years, with no significant difference between group age (F(1,32) = 3.314; p = .078). The migraineurs had a mean of 26.8 (SD 26.6) headaches per year while the controls had a mean of 16.2 (SD 13.8) nonmigraine headaches a year. Headache classification was performed in the same manner as in Experiment 1.  Stimuli and Timing Stimulus timing and sequence are shown in Figure 3.5. Each trial started with the foveal presentation of an image of eyes cuing either the left or the right visual field.  Following the cue, a target X was presented in one of the two  peripheral locations. On half the trials the target was presented at the cued  72  location, and on the other half of the trials the target was presented at the uncued location. As such, the cue was unpredictive as to the location of the pending target.  The target locations, one in each upper visual-field quadrant, were  located 3.1° (to center) from fixation and 0.4° (to center) above the horizontal meridian. The foveal cue was an image of eyes 2.1° x 1.1°, with pupils directing attention to either the left or right visual field. The fixation point was a 0.3° fixation cross; the target X was 0.3° x 0.5°.  Figure 3.5 Basic Trial Conditions for Experiment 3 9 Shown are cued and uncued trials.  73  Procedure Participants were required to press a button as quickly as possible after the appearance of the target on the screen. A cued trial was defined as a target at the cued peripheral location and an uncued trial was defined as a target at the uncued peripheral location. Each participant completed an average 30 blocks of 20 trials (50% cued and 50% uncued) per block. The time cue is on screen before the target appears was varied to decrease anticipatory responses. No feedback was given on hit or miss rates.  Results To examine possible age- and gender-related effects in our primary findings reported below, we initially ran repeated measures ANCOVAS with sigma-restricted coding of categorical predictors of sex and age covariates. As we found no significant effects of either age or gender (all F’s < 1.460, all p’s > 0.236), we did not include these covariates in the main results.  Reaction Times Mean RTs are presented in Figure 3.6 as a function of group and attention. Both groups appeared to show an attention effect in RT, such that the RTs were faster for cued than uncued targets, but this effect did not appear to differ in magnitude between groups. This was confirmed via an omnibus ANOVA that included group (migraine vs. control) as a between-group factor and attention (cued vs. uncued) as a within-groups factor. This analysis revealed a main effect of attention (F(1,32) = 24.172; p < 0.001), but no interaction between 74  attention and group (F(1,32) = 0.110; p = .742). As well, there was no significant main effect of group (F(1,32) = 0.724; p = .401), indicating overall RTs were comparable between-groups.  Figure 3.6 Mean Reaction Times (RTs) to Targets 10 Mean RTs to targets as a function of group and attention.  75  Control Analyses Subgroups To examine whether the type of headache affected task performance, we divided the participants into more specific headache categories, with 6 Migraine with Aura, 11 Migraine without Aura, and 17 Controls with no migraine history. There were no interactions between subgroup and attention (for reaction times F(2,31) = 0.066; p = 0.936) and no overall differences in reaction speeds between subgroups (for reaction times F(2,31) = 0.780; p = 0.467.  Discussion In Experiment 3 we found no difference between migraineurs and controls in terms of reflexive attentional orienting as triggered by a central eye gaze cue. This confirms that migraineurs do not have heightened reflexive attentional orienting to the visual periphery in general.  Rather, we can conclude that  migraineurs have heightened reflexive orienting linked to hyperexcitable visual cortical responses specific to sudden-onset peripheral events.  Migraineurs Across Experiments Notably, in all three of our experiments we found no significant differences between headache classifications (aura vs. non-aura) within migraineurs. One possibility is that we may not have had sufficient power within each experiment to find significant differences between headache groups. Accordingly, to investigate  76  this possibility, we conducted an additional analysis within the migraineurs only, pooled across all three experiments, using a normalized “attentional effect score”. To create a normalized score, within each experiment we calculated a difference score for attended vs. unattended stimuli (or the equivalent) and then based on the migraineur group mean within each experiment, calculated a z-score for each migraine participant. Then, for the cross-experiment comparison, we compared the z-scores in an ANOVA with factors of headache classification (migraine with aura vs. migraine without aura) and Experiment (Experiment 1 Short SOA, Experiment 1 Long SOA, Experiment 2, and Experiment 3).  There were no  significant main effects or interactions ((all Fs(1,77) < 1.235; ps > .303).  General Discussion We asked if migraine hyperexcitability in visual cortex leads to heightened visual attentional orienting responses. Experiment 1, which triggered attention via sudden-onset peripheral events, confirmed that indeed migraineurs do have heightened reflexive orienting. The two follow-up experiments revealed that this heightened orienting is not due to overall increased reflexive attentional responses (Experiment 2 & 3) or simply to attending to peripheral stimuli (Experiment 3), but specifically to attentional orienting in response to suddenonset peripheral events. Given our conclusions, several critical questions follow.  What are the Implications for Migraineurs? Overall, our study reveals that migraineurs have heightened reflexive visual attentional orienting as a result of a hyperexcitable response to sudden77  onset peripheral events. What is the impact of this finding for migraineurs? First, it is important to consider the proposed function of reflexive orienting. Reflexive orienting allows one’s attention to be drawn to new stimuli or salient changes in the environment to aid in our survival in a complex world.  With enhanced  orienting response, one would expect to be more aware of sudden changes in environmental stimuli, and in fact, migraineurs often report their attention is drawn to unwanted peripheral distractions (e.g., Sacks, 1992). It is important to note that this is the first study looking at inhibition of return in migraineurs, and it is found to be normal in migraineurs. The function of IOR is thought to be to encourage proper search of the environment (e.g., Klein & MacInnes, 1999). That this is intact in migraineurs means that while their attention is more drawn to locations of sudden-onset stimuli in the environment, their attention is just as able as controls to then block-out that already-checked area to the advantage of searching new areas in the environment.  Interestingly, our findings are also consistent with the recent result of Boulloche et al. 2010. In their study they found that during visual stimulation, migraineurs showed increased activity in regions of parietal cortex associated with  volitional  attentional  orienting,  whereas  controls  did  not.  These  neuroimaging results paralleled prior behavioral studies suggesting migraineurs have slowed response performance relative to controls due to their attention getting grabbed by visual stimuli (Conlon et al., 1998; Conlon & Hine, 2000). Not only do our data replicate this latter result––we found overall slowed RTs in migraineurs––but we also provide direct evidence of the hypothesized attentional 78  grabbing in migraineurs, in the form of heightened reflexive orienting. At the same time, this heightened reflexive orienting could also explain the increased activity in migraineurs’ posterior parietal cortex reported by Boulloche et al. (2010), in that if attention was reflexively grabbed by visual stimuli, controlled attentional processes would need to be invoked to countermand these automatic effects.  Acknowledging that enhanced orienting fits with the migraine profile, are there any advantages to having enhanced orienting and to knowing that this is an issue in migraine?  Regarding perceptual advantages, one can imagine many  tasks, such as driving, where heightened reflexive orienting could mean vital seconds. On the other hand, to the extent that such heightened orienting may be contributing to triggering migraine events, one could potentially use this information therapeutically to reduce headache frequency. While one can think of very simple adjustments a migraineur could do to limit distracting stimuli, such as sitting so a flashing television is behind them in a restaurant, we would also use attention literature to envision clinical therapeutic possibilities. For example, recent evidence suggests that action video-game playing leads to enhanced ability to suppress distracting irrelevant information (Mishra, Zinni, Bavelier, & Hillyard, 2011).  Given migraineurs’ heightened orienting to sudden-onset  peripheral events, and the potential for video-gaming to suppress this heightened orienting, future research could assess the therapeutic option of using videogaming to reduce sensory-triggered migraine events. This is just one example of  79  how a growing understanding of the cognitive consequences of hyperexcitable sensory cortices may be used to improve daily life in migraineurs.  What are the Implications for Attention? In Experiment 1, we found that migraineurs had increased attentional orienting at short cue-target intervals, but normal inhibition of return for long cuetarget intervals. Why might we find heightened facilitation but intact inhibition of return (IOR)? Facilitation effects from reflexive orienting are known to reflect the earliest sensory-level enhancement of visual processing, modulating the early posterior P1 ERP component occurring around 100 msec post-target (e.g., Hopfinger & Ries, 2005). Indeed, that migraineurs have a heightened response specific to early-sensory level processing fits well with our previous findings that migraineurs have altered voluntary attentional modulation of sensory-level visual processing (Mickleborough et al., 2011), as both of these effects are driven by early modulation of extrastriate cortex (Di Russo et al., 2002; Hopfinger & Ries, 2005). On the other hand, IOR and attentional capture are both thought to reflect later processing, modulating slightly later ERPs, such as the posterior N2pc ERP component, around 175-300 msec poststimulus (e.g., Hickey, McDonald, & Theeuwes, 2006; Hopfinger & Ries, 2005).  This suggests that these  hyperexcitable cortical implications of migraine are specific to the earliest sensory processing.  This finding is also an example of how migraineurs can provide neuropsychological evidence for dissociating reflexive attentional paradigms. 80  Essentially, a sensory model of reflexive orienting would suggest that the sensory response to a peripheral flash (i.e., cue) draws attention to a location, producing the heightened sensory cortical response (e.g., Hopfinger & Mangun, 1998) and faster RTs (e.g., Jonides & Irwin, 1981) to the subsequent target.  Because  migraineurs have heightened excitability of sensory cortices, that they show altered reflexive orienting only to sudden-onset peripheral targets supports a dissociation between this type of early sensory response reflexive orienting and other types of reflexive orienting in which attention is reflexively cued to the periphery (e.g., eye gaze) or when attention is captured by a salient object (attentional capture).  Thus, migraineurs provide novel neuropsychological  evidence to support the theory that there are multiple reflexive mechanisms acting in the brain to bias different stages of sensory information processing and that these mechanisms are triggered by different stimulus attributes (Hopfinger & Ries, 2005).  81  Chapter 4: Implicit Evaluative Analysis of Visual Images in Migraine Populations3  3  A version of this chapter has been submitted for publication. Mickleborough, M. J. S., Chapman, C., Toma, A. S., Chan, J. H. M., & Handy, T. C. Implicit Evaluative Analysis of Visual Images in Migraine Populations.  82  Introduction Although migraine is medically classified as a headache disorder, a key part of its pathophysiology is heightened excitability of visual cortex characterized by lack of visual sensory habituation in between headache events. Specifically, electrophysiological studies in normal populations reveal a gradual and automatic attenuation in the strength of sensory-evoked cortical responses to checkerboard reversals, while migraineurs have either no change or even an increase in amplitude (e.g., Afra et al., 1998; Ambrosini & Schoenen, 2003; Brighina et al., 2009; Coppola et al., 2009; Giffin & Kaube, 2002; Judit et al., 2000; Siniatchkin et al., 2003). Given the altered visual sensory functioning in migraineurs, here we examined the extent to which the abnormalities associated with migraine visual cortex permeate to how we cognitively process and evaluate stimuli at postsensory stages.  To date, the electrophysiological evidence speaking to post-sensory visual anomalies in migraineurs has come from ERP studies using visual “oddball” paradigms, which assess the generation of implicit visual expectancies (Evers, Bauer, Suhr, Husstedt, & Grotemeyer, 1997; Evers, Bauer, Grotemeyer, Kurlemann, & Husstedt, 1998; Evers, Quibeldey, Grotemeyer, Suhr, & Husstedt, 1999). In these "oddball" paradigms, participants are asked to watch a serial stream of stimuli that contains a small number of targets (or "oddballs") that require a manual response, and a large number of "standard" stimuli that can be ignored. What Evers and colleagues found is that while healthy controls showed a decrease in the P300 amplitude elicited by targets in the second half as 83  compared to the first half of trials, migraineurs actually showed the reverse, such that there was an increase in P300 amplitude in the second half as compared to first half of trials during the interictal period. This suggests that whereas controls show a decrease in implicit post-sensory visual expectancies over time, migraineurs show an increase.  Given this background, we wanted to advance our understanding of potential post-sensory anomalies in how migraineurs implicitly process visual images, and in particular, more evaluative aspects of neurocognitive processing. Our methodological approach was based on a recent ERP study in normal populations examining implicit aesthetic evaluative analysis of common everyday visual images, and in this case, commercial branding logos (Handy et al., 2010). Specifically, we recorded ERPs from both migraineurs and non-migraine controls as they viewed a serial stream of unfamiliar visual objects (232 distinct, different logos) in the context of a target identification task. In each trial block, each of these 232 logos was presented once.  After completing 10 trial blocks,  participants were then asked to identify the 15 logos they liked most and which 15 they disliked most. Importantly, they were not explicitly asked to think about or evaluate the logos in any way prior to this point of the study.  Using this paradigm, our first goal was to assess the evaluative-based cognitive habituation of non-repetitive images.  Specifically, the late positive  potential (LPP) is an ERP component associated with the depth of cognitive analysis afforded to the ERP-eliciting stimulus (e.g., Cacioppo, Crites, & Gardner, 84  1996; Crites, Cacioppo, Gardner, & Bernstson, 1995; Cuthbert, Schupp, Bradley, Birbaumer, & Lang, 2000). When Handy et al. (2010) compared the amplitude of the LPP elicited by logos across the different trial blocks, they found that participants quickly maxed-out in terms of how much cognitive analysis they gave the logos––from the second trial block on, there was no change in LPP amplitude. In light of this result, here, our aim was to see if migraineurs would show a similar rapid habituation of the LPP response, or alternatively, if they might continue to show changes in LPP amplitude over time.  Second, we wanted to examine whether migraineurs might show altered implicit hedonic analysis of visual images. In particular, making a like or dislike judgment of visual images is such a normal part of human behavior that it can be generated without conscious intent (e.g., Chen & Bargh, 1999; Dijksterhuis & Aarts, 2003) and even emotionally neutral images such as logos are implicitly evaluated at a hedonic level (e.g. Handy et al., 2010). Moreover, Handy et al. (2011) found a bias in visuocortical processing for disliked logos such that that when participants viewed emotionally neutral logos, their cortical response to disliked logos stood out from the cortical response to other logos. Again, our question was whether migraineurs might show an altered pattern of implicit evaluative analysis at the hedonic level, and in particular, whether they might show anomalies in either their responses to liked logos, disliked logos, or both, as compared to controls.  85  Materials and Methods Participants 58 paid volunteers participated; 29 were in the non-migraine control group (19 women and 10 men; age 25.9, SD 11.4) and 29 were in the migraine group (18 women and 11 men; age 26.1, SD 8.6). The migraineurs had 25.1 (SD 33.0) headaches a year, with each headache lasting 16.4 hrs (SD 33.0). Because migraine hyperexcitability is thought to normalize prior to and during an attack (Ambrosini & Schoenen, 2006), all migraineurs had not had a migraine within 48 hours prior and 48 hours after the testing period.  All participants gave their  informed consent and all testing procedures were approved by the University of British Columbia Clinical Review Ethics Board.  Headache Classification All migraine participants were required to meet the migraine criteria specified by the International Headache Society (Headache Classification Subcommittee of the International Headache Society, 2004) and as determined by an interview. All our migraine participants had not suffered from a migraine for at least 48 hours before testing nor did they have a migraine for at least 48 hours after testing.  In addition to our headache classification criterion, migraineurs  were excluded if they were taking any form of migraine prophylactics.  Stimuli This stimulus set was adapted from Handy et al. (2010). A total of 232 non-target logos were used as the primary stimulus set; the logos were drawn 86  from sources publicly available on the Internet. Criteria for inclusion in this set included that the logo contained no verbal/lexical information (i.e., no words or letters) and that it was not a widely known or familiar image (e.g., such as the Nike "swoosh").  Procedures Each trial block began with the presentation of the target logo for 2 s as a reminder of which logo required a manual response to be made; the same logo was used as the target across all trial blocks and participants. Within each trial block, this target was presented 20 times and each of the 232 non-target logos was presented once, with the order of presentation randomly varied between 10 trial blocks. The duration of each stimulus was 200 ms, and the inter-stimulus interval was randomly varied between 1300-1500 ms. Stimuli were presented on a VGA monitor controlled by a Pentium PC using the VAPP stimulus presentation system (http://nilab.psychiatry.ubc.ca/vapp/), and manual responses to the target were made by pressing a button on a hand-held joystick, with the thumb of response (left vs. right) counterbalanced between participants.  Initial instructions to the participants asked them to simply observe the logos on the screen and make a manual response as fast as possible whenever the target logo was presented. No instructions were given to think about or explicitly evaluate the non-target logos. After completing the task and removal of the recording equipment, each participant was asked to identify 30 non-target  87  logos based on hedonic preference (15 most liked, 15 most disliked), from one of four sheets of paper randomly displaying all 232 non-target logos.  Electrophysiological Recording Scalp potentials were recorded from 64 Ag/AgCl active electrodes via a Biosemi Active-Two ERP amplifier system. To ensure proper eye fixation and allow for the removal of events associated with eye movement artifacts, vertical and horizontal electro-oculograms (EOGs) were also recorded – the vertical EOG from an electrode inferior to the right eye, and the horizontal EOG from an electrode on the right outer canthus. Two additional electrodes were used to record from the left and right mastoids. Data were recorded relative to ActiveTwo's CMS/DRL feedback loop (Common Mode Sense [CMS] and Driven Right Leg [DRL]), using a second order low-pass filter of 0.05 Hz with a gain of 0.5 and with a digitized on-line sampling rate of 256 samples-per-second. Offline, all scalp electrodes were referenced to the average of the left and right mastoid signals.  Automated artifact rejection was then used to eliminate trials with  detectable eye movements, blinks, muscle potentials or amplifier blocking. For each participant, time-locked to the remaining events of interest was epoched into 800 ms segments, beginning 200 ms before stimulus onset until 600ms poststimulus.  These single-subject waveforms were then used to generate the  group-averaged waveforms for display and analysis. A -200 to 0 ms pre-stimulus baseline was used for all ERP waveform measurements and displays.  88  Results Habituation Analyses The ERP components measured for assessing cognitive habituation were the frontal/central N2 (200-400 ms) and the frontal/central LPP (400-600 ms). These components are consistent with the time-ranges found to be sensitive to visual cognitive habituation in previous migraine studies (Evers et al., 1997; Evers et al., 1998; Evers et al., 1999). Grand-averaged ERP waveforms for each block of ‘all’ logos are shown in Figure 4.1 as a function of group and scalp location. Statistical analyses were based on repeated measures ANOVAs with a between-subjects factor of group (control vs. migraine), and within-subjects factors of block (10 trial blocks), time window (200-400 ms vs. 400-600 ms), and electrode (frontal electrodes F3, FZ, & F4 and central electrodes C3, CZ, & C4). Any interactions that did not include group or block were not reported here, as they are tangential to the focus of our study. ANOVAs within each group were planned to follow-up any significant interactions. Mean amplitudes for each time window are reported in Table 4.1 as a function of group and block.  Four  participants from each group were dropped due to insufficient data for trial block analyses, such that each group is n=25 for the habituation analyses.  89  Table 4.1 Mean Amplitudes 7 Mean Amplitudes (!V) of grand-averaged ERP Frontal-Central components N2 and LPP for the Control and Migraineur Group as a function of Block. Standard deviation in parentheses; N = 25; data are collapsed across hemisphere and electrode.  N2 (200-400 ms) Controls Migraineurs Block 1 -1.16 (5.98) 0.15 (3.93) Block 2 -0.27 (5.98) 0.95 (4.94) Block 3 -0.32 (5.99) 1.10 (4.59) Block 4 -0.47 (4.87) 1.80 (5.62) Block 5 -0.05 (4.90) 2.47 (7.09) Block 6 0.11 (5.18) 2.43 (6.96) Block 7 0.24 (7.07) 3.37 (8.15) Block 8 0.51 (6.27) 3.07 (8.49) Block 9 0.77 (6.63) 3.51 (8.24) Block 10 0.46 (6.42) 3.95 (9.51)  LPP (400-600 ms) Controls Migraineurs 3.38 (6.31) 2.92 (4.83) 4.13 (5.83) 3.84 (5.60) 4.17 (6.34) 3.89 (4.67) 4.30 (5.74) 4.95 (5.59) 4.07 (5.37) 5.28 (6.46) 4.35 (5.73) 5.40 (6.08) 4.34 (6.16) 5.78 (6.11) 4.91 (6.81) 5.39 (6.24) 4.26 (6.75) 5.48 (5.98) 4.66 (6.48) 5.21 (6.16)  90  Figure 4.1 Grand-averaged ERP Waveforms11 Grand-averaged ERP Waveforms as a function of group, block, and scalp location. Control Group (N=25). Migraine Group (N=25). Shown are frontal-central electrodes F3, FZ, F4, C3, CZ, C4 and left and right mastoids (LM, RM) for ALL logos with first block (black line) through to 10th block (red line).  91  Frontal/Central N2 & LPP Looking at Figure 4.1, the prominent feature is that the post-sensory waveforms in migraineurs segregate by block.  The initial omnibus ANOVA  revealed an interaction of group and block (F(2,48) = 2.93; p < 0.01), qualified by an interaction of group, block, and time (F(2,48) = 1.44; p < .05). Follow-up ANOVAs confirmed that migraineurs have an effect of block in the N2 (200-400 ms) window (F(1,24) = 3.94; p < 0.001) and the LPP (400-600 ms) window (F(1,24) = 4.03, p < 0.001), while controls had no significant effect of run for either N2 or LPP (200-400 ms, F(1,24) = 1.66; p = 0.10; 400-600 ms, F(1,24) = 0.89; p = 54).  As is apparent by looking at the waveform, the effect on  migraineurs was such that the amplitude increased (on the positive) across blocks of presentation, reflecting a significant potentiation across time. Specifically, in the migraineurs the mean amplitude in the 200-400 ms window of block 1 is significantly different than block 10 (F(1,24) = 5.18; p < .05), and block 9 (F(1,24) = 5.53; p < .05), but not block 8 or any earlier blocks (all Fs < 3.93, all p’s > .055).  For the 400-600 ms window, the migraineurs’ mean amplitude of  block 1 is significantly different than block 9 (F(1,24) = 4.67; p < .05), but not for any of the other blocks (all F’s < 3.87, all p’s > .055).  The controls’ mean  amplitude of block 1 did not differ from any of the other blocks for either time window (all F’s < .280, all p’s > .60).  92  Implicit Hedonic Analyses The ERP components measured for assessing implicit hedonic processing were the lateral/occipital P1, the frontal/central N2, and the frontal/central LPP. The P1 was included because migraineurs are known to show altered sensory responses in the P1 component (Mickleborough et al., 2011a), and was measured at scalp electrodes OL & OR, using a 95-105 ms post-stimulus time window to capture the peak.  The N2 and LPP components were chosen  because they have been found to be sensitive to implicit hedonic analyses in previous studies (Handy et al., 2010), and were captured in a series of 50 ms windows from 225-575 ms designed to capture waveform variability, comprising electrodes F3, FZ, F4, C3, CZ, and C4. Statistical interrogation included two repeated measures ANOVAs with group (control vs. migraine) as a betweensubjects factor and preference (like vs. dislike vs. all non-target logos), and electrode location as within subjects factors, plus an additional factor of time window (50 ms windows from 225-575 ms) for the N2/LPP analyses. Separate ANOVAs within each group were planned to follow-up any significant interactions including group and preference. Grand-averaged ERP waveforms for ‘Liked’, ‘Disliked’, and ‘All’ logos are shown in Figure 4.2 as a function of headache classification and scalp location and in Table 4.2 as a function of group, preference and time window.  93  Table 4.2 Mean Amplitudes 8 Mean amplitudes (!V) of grand-averaged ERP components as a function of group, preference, and time-window. Standard deviation in parentheses; N=29; P1 data are collapsed across electrodes OL and OR. Frontal-central data are collapsed across electrodes F3, FZ, F4, C3, CZ, and C4.  Controls 95-105 ms (P1) 225-275 ms 275-325 ms 325-375 ms 375-425 ms 425-475 ms 475-525 ms 525-575 ms  Migraineurs  Like 3.44 (3.52)  Dislike 4.10 (3.64)  All 3.57(3.07)  Like 1.72 (3.28)  Dislike All 1.64 (3.31) 1.68 (3.24)  -1.57 (4.09) 0.51 (3.93) -0.98 (5.85) 1.59 (6.69) 0.47 (7.28) 1.95 (6.87) 2.33 (7.53)  -1.70 (3.90) 0.53 (4.48) -1.24 (5.70) 1.28 (6.60) 0.04 (7.48) 1.92 (7.16) 1.79 (7.78)  -1.25 (4.06) 1.16 (4.48) -0.28 (5.98) 2.71 (7.86) 1.38 (7.88) 3.55 (8.66) 3.24 (8.25)  2.42 (5.98) 3.61 (6.59) 3.43 (5.94) 4.55 (5.76) 4.41 (5.63) 4.95 (4.73) 4.64 (4.82)  2.59 (6.70) 3.15 (6.95) 4.05 (6.69) 3.57 (5.88) 4.92 (6.33) 4.14 (5.05) 5.12 (5.32)  4.16 (7.64) 4.44 (7.31) 5.03 (6.82) 4.84 (6.16) 5.60 (6.12) 5.17 (5.02) 5.82 (5.58)  94  Figure 4.2 Grand-averaged ERP Waveforms 12 Grand-averaged ERP waveforms as a function of group, preference, and scalp location. Control Group (N=29). Migraine Group (N=29). Shown are frontal-central electrodes F3, FZ, F4, C3, CZ, C4 and left and right mastoids (LM, RM) for LIKE, DISLIKE, and ALL logos.  95  Lateral Occipital P1 Peak As can be seen in Figure 4.2, it appeared that the amplitude of the P1 had a preference effect for controls but not migraineurs, and this was confirmed statistically. We found a group by preference interaction (F(1,56) = 3.11; p < 0.05). Planned ANOVAs within each group revealed that controls had a main effect of preference in the P1 (F(1,28) = 5.86; p < 0.01), such that the mean amplitude of the disliked logos was greater than the mean amplitude of liked logos (t(28) = -2.84, p < 0.01) and of all logos (t(28) = 2.69, p < 0.05), while there was no significant difference between liked logos and all logos (t(28) = -0.71, p = 0.48). Migraineurs showed no such effect of preference in the P1 ((F(1,28) = 0.06; p = 0.94).  Frontal/Central N2 & LPP As can be seen in Figure 4.2, it appeared that the post-sensory preference effects differed between groups across time windows, and this was confirmed statistically. We found a group by window by preference interaction (F(2,56) = 1.94; p < 0.05). Planned ANOVAs within each group revealed that controls had an interaction of preference and time window  (F(1,28) = 2.74; p < 0.01).  Specifically, within the control group the mean amplitude of the disliked logos was less than the mean amplitude of ‘all’ logos in all but the first time window (from 275-575 ms; all Fs(1,28) > 12.50; ps< 0.01) and the mean amplitude of the disliked logos was less than the mean amplitude of liked logos in the two last windows (from 475-575 ms; all Fs(1,28) = 4.43; ps < 0.05), while the mean  96  amplitude of liked logos was less than the mean amplitude of all logos only in two time windows (from 325-425 ms; all Fs(1,28) = 4.59; ps < 0.05). In contrast, migraineurs showed no such effect of preference (F(1,28) = 3.03; p = 0.06) or an interaction of preference by time window (F(1,28) = 1.81; p = 0.05). It is possible this lack of effect may be due to increased variability in the migraineurs.  Control Analyses In addition, as a possible control issue, we wanted to determine whether the pattern of results we report with migraineurs lacking preference effects could be due to a differing selection criterion as opposed to an actual abnormal early sensory response. Specifically, perhaps being a migraineur causes one to pick particular images that are different than non-migraineurs select, such that the logo properties (symmetry, complexity, contrast, etc.) do not produce the same sensory response as those that controls select.  The logos selected by each group are presented in Table 4.3, which demonstrates a relatively even distribution of logo choices across groups. Nonetheless, in order to directly address this question, we paired each migraineur with a control and exchanged their 15 liked and 15 disliked choices and reanalyzed these new data. In this way, if the logos chosen by migraineurs somehow differed from those chosen by controls and the results were a consequence of the selection criterion, then we would expect to see a reversal of the original results, such that the migraineurs would have a preference effect in early P1, but controls would not. 97  Table 4.3 Hedonic Preference Ratings 9 Hedonic Preference Ratings as a function of group and logo number. CN = Control Group; MG = Migraine Group; L = Liked Logos; D = Disliked Logos.  # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50  CN L 2 3 10 2 2 0 2 1 3 0 2 0 0 1 2 1 2 2 4 2 2 1 3 1 1 0 1 0 1 1 0 6 0 1 6 1 7 0 3 0 0 0 3 0 0 0 2 0 2 4  D 5 3 3 1 1 3 1 2 2 2 3 1 0 2 4 1 3 2 2 0 1 3 4 3 1 2 2 0 1 0 1 1 0 3 3 0 1 1 0 0 2 0 0 2 0 0 3 5 1 1  MG L 2 2 3 0 0 2 1 1 4 1 0 0 0 2 4 0 2 4 2 4 2 1 5 0 1 0 0 2 1 1 1 4 0 2 4 1 16 0 2 0 0 2 3 0 0 0 0 4 1 0  D 2 3 1 2 3 2 0 2 2 1 2 2 2 4 1 1 1 1 4 0 1 4 1 5 7 2 0 2 0 1 1 1 1 2 5 0 1 1 1 3 2 0 0 1 1 0 1 6 2 0  # 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100  CN L 1 4 5 2 2 5 4 0 0 7 5 1 2 3 0 6 3 0 4 1 0 2 2 1 0 4 0 4 1 1 4 5 3 1 4 3 2 0 1 2 0 8 0 0 2 5 1 1 1 2  D 1 0 1 3 3 2 0 2 0 2 0 2 2 4 0 0 1 4 1 0 2 1 6 3 7 3 3 1 2 0 0 2 4 1 2 1 5 3 1 1 3 0 6 2 2 1 0 3 2 0  MG L 0 3 7 1 0 2 6 10 0 8 2 0 1 2 3 8 3 1 2 1 0 1 6 2 0 0 1 3 0 0 4 4 4 3 3 5 1 0 0 0 0 5 0 0 1 1 0 0 3 0  D 1 2 3 1 3 2 0 1 0 3 2 5 0 4 0 1 1 3 3 1 1 1 5 0 4 1 0 1 2 1 1 1 0 2 1 3 1 6 4 2 1 0 2 0 2 2 1 0 3 1  # 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150  CN L 2 2 1 3 1 3 0 2 0 3 3 1 2 2 7 5 3 1 0 0 1 0 1 0 4 3 0 0 1 1 2 2 0 3 0 4 3 3 2 0 2 2 7 1 1 1 3 0 0 1  D 0 2 3 0 1 1 1 5 6 2 3 4 4 2 2 3 1 0 0 3 1 3 2 1 0 5 0 4 2 2 5 0 1 2 1 0 1 1 1 2 5 1 5 4 3 1 1 0 3 3  MG L 2 1 1 0 1 3 0 5 0 0 1 0 1 5 4 7 2 0 0 0 1 1 1 2 3 7 0 3 2 2 0 3 0 1 1 3 2 2 1 0 2 1 6 0 0 1 7 1 0 1  D 2 1 1 2 2 1 2 3 4 3 0 1 2 4 5 6 1 1 3 3 0 2 6 4 1 3 0 4 4 2 2 4 1 5 0 3 2 2 3 0 0 2 5 0 3 0 1 1 2 1  # 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200  CN L 0 0 0 0 4 4 4 1 0 4 0 1 7 3 0 0 6 0 2 2 2 2 0 0 1 1 3 5 2 2 0 5 3 0 3 2 0 3 1 1 0 0 0 0 0 2 1 1 0 3  D 3 2 3 3 0 1 2 3 0 1 2 2 2 0 2 2 1 0 1 6 3 3 6 2 3 5 1 3 0 4 1 2 0 3 5 5 0 0 1 6 4 0 1 0 0 1 2 1 1 1  MG L 2 0 0 0 2 2 3 2 0 5 4 0 11 4 0 0 5 0 0 7 1 0 4 1 1 0 2 3 0 5 0 2 3 2 3 0 0 0 2 0 0 0 0 0 0 3 0 2 1 4  D 3 0 2 3 3 6 4 1 1 1 2 2 0 1 0 2 1 1 2 4 1 0 3 2 2 2 0 0 2 3 1 1 1 5 3 4 1 0 3 0 3 0 1 0 0 0 1 0 4 0  # 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232  CN L 1 2 2 8 2 1 0 0 3 2 0 3 0 2 2 4 4 9 0 0 1 6 1 2 3 0 0 2 1 0 1 1  D 3 5 4 2 0 1 0 2 3 1 1 3 0 5 0 0 0 5 1 4 1 1 0 0 1 4 0 1 0 5 1 0  MG L 2 2 0 6 1 1 1 5 6 2 1 6 1 1 1 5 5 4 5 0 1 4 0 0 2 1 0 1 0 1 2 0  D 2 7 3 3 0 1 1 3 0 4 2 1 0 4 3 2 0 3 1 1 0 1 1 2 0 2 1 3 2 9 3 2  Statistical interrogation for the ERP components replicated the main hedonic analyses with the exception of using “swapped” logos (like and dislike logos of a paired participant from other group).  We found no significant  preference effects or interactions for P1, N2, or LPP time windows (all Fs(2,56) <  98  0.72; all ps > 0.49).  These null results are consistent with both groups  responding to “random” logos as opposed to their personal liked and disliked logos, and discredits the possibility that a group difference in logo selection bias could be producing the group by preference interactions.  Discussion Our study was designed to examine the extent to which migraineurs show altered implicit evaluative analysis of visual images. In this regard, we found two main results. First, whereas controls’ level of implicit cognitive analysis of visual images remains fairly stable over time, as measured via the LPP, migraineurs show an increasing level of analysis with each successive trial block. Second, controls showed a bias for disliked logos, as measured via amplitude at lateral occipital P1 and LPP components, a negativity bias that was absent in migraineurs. In the following sections, we discuss functional implications of each finding and the possible relationship of these findings to sensory abnormalities.  Increasing LPP Over Time First, our data suggest that migraineurs show increasing depth of implicit cognitive analysis of visual images over time.  As evidence of this, the LPP  amplitudes in migraineurs continued to increase across 10 blocks of logo presentation, while controls show no such effect. Previous research suggests such increasing LPP amplitudes reflect a deeper level of evaluative analyses (e.g., Cacioppo et al., 1996; Crites et al., 1995; Cuthbert et al., 2000).  For  example, the LPP has been associated with increased evaluative categorization 99  (e.g., Cacioppo et al., 1996; Crites et al., 1995) and activation of motivational and affective systems (e.g., Cuthbert et al., 2000). But if migraineurs are showing increasing levels of evaluative cognitive analysis over time whereas controls are not, what is behind this effect and how might it impact migraineurs?  Two lines of evidence support the possibility that attention might be driving this effect at the cognitive level. First, the LPP has been shown to be enhanced by increased implicit attention due to motivationally relevant stimuli (e.g., Cuthbert et al., 2000; Dunning & Hajcak, 2009; Ito, Larsen, Smith, & Cacioppo, 1998).  This indicates that if migraineurs were increasing their motivational  attention to the logos over time, the LPP would be sensitive to such effects. Second, the collective evidence from a variety of paradigms suggests that interictally migraineurs show heightened attention to irrelevant visual stimuli (e.g., Antal et al., 2005; Aurora et al., 2007, McKendrick, 2004, Mickleborough, 2011a,b; Wagner, 2010). Specifically, migraineurs ability to hone in on salient visual signals seems to be affected by increased distraction from extraneous environmental stimuli. In light of these findings, it appears the present result of increased cognitive processing in migraineurs may be related to an increase in motivational attention towards logos across time where the controls show no such increase.  How might such an increase in cognitive processing over time influence migraineurs? In the same way that a lack of sensory habituation is considered to contribute to sensory overload in migraineurs leading to triggering of migraine 100  events (e.g., Ambrosini & Schoenen, 2006), this abnormal increase in cognitive processing could lead to inappropriate demand on cognitive resources. As the LPP is particularly noted for more contemplative aspects of emotional judgments (e.g., Cuthbert et al., 2000; Dunning & Hajcak, 2009; Ito et al., 1998), a cognitive rumination could be related to another very common trigger for migraineurs – emotional stress (e.g., Andress-Rothrock, King, & Rothrock, 2010).  In fact,  evidence indicates that migraineurs are more susceptible to stress (e.g., Hedborg, Anderberg, & Muhr, 2011; Sauro & Becker, 2009) and experience a diminished recovery from the thoughts and feelings associated with mental stress (e.g., Stronks et al., 1999). In this way, increased depth of evaluative cognitive processing over time may be contributing to the stress-related triggering of migraine events.  Absent Negativity Bias The second primary result of our study was that migraineurs showed a lack of a negativity bias for their implicit hedonic analyses, relative to what was observed in controls.  Specifically, we found a significant difference between  migraineurs relative to non-migraine controls for hedonic preference effects, such that controls had increased P1 and decreased LPP amplitude for disliked logos (as compared to either liked or all logos), while migraineurs lacked this bias of disliked images. This corresponds with previous research which reveals that, in normal visual processing, images we dislike appear to stand out to us at a neurocognitive level (Handy et al., 2010). An increased P1 has been linked to increased attention (e.g., Handy & Mangun, 2000; Handy et al., 2001), 101  suggesting that controls, but not migraineurs, show early increased attention to disliked logos. This is consistent with a negativity bias, in which more weight is given to negative than positive evaluations (e.g., Cacioppo & Berntson, 1994; Dijksterhuis & Aarts, 2003; Ito et al., 1998). In contrast, migraineurs lack this negativity bias in early visual cortex, as well as in later post-sensory processing in frontal/central cortex.  What might the impact of this be for migraineurs? An adaptive advantage of the negativity bias is that images can be assessed and attention can be quickly redirected to potentially threatening events (e.g., Cacioppo & Berntson, 1994; Ito et al., 1998). Controls show this bias as early as P1 processing, but then show decreased cognitive processing of dislike logos at the LPP. This suggests that while controls may initially put more emphasis on the disliked logos, this may allow for less evaluation at the cognitive level. Considering the negativity bias as an adaptation, migraineurs seem, to some degree, to be lacking this early motivational advantage of categorizing preference.  Generally speaking, this  again suggests an abnormality for migraineurs in how attentional resources are allocated to environmental stimuli. Collectively, our results show that migraineurs have increased LPP over time but no negativity bias, perhaps suggesting migraineurs are not only evaluating their environment more than controls, but also not adequately categorizing it for quick allocation of attention.  102  Sensory Contributions to Altered Evaluative Analyses? Given our two primary findings about visual post-sensory anomalies, to what extent, if at all, might they be driven by or independent of known sensory abnormalities? Two key concepts suggest that our findings of increasing LPPbased evaluative analysis and absence of negativity bias are not just a forwardcascade of the basic sensory abnormalities, but more likely another consequence of a more global cortical hyperexcitability in migraine. First, intercellular inhibitory processes are indicated in both the lack of habituation in migraineurs (e.g., Aurora, Barrodale, Chronicle, & Mulleners, 2005; Brighina et al., 2009), and in the modulatory effects of spatial attention which may be underlying our findings (e.g., Houghton & Tipper, 1996), so altered inhibition in migraine may be at the core of both effects. In addition, if it were a consequence of sensory abnormalities one would expect to see more evidence of these anomalies appearing earlier in our waveforms and continuing through, whereas they are distinct to specific components.  While our data suggests a common pathophysiological link  between our post-sensory effects and the sensory abnormalities in migraineurs, we can only surmise as it is beyond the scope of our paradigm. Either way, our study clearly suggests post-sensory consequences of migraine in between headache events, specifically increased cognitive evaluative processing over time and a lack of categorical hedonic evaluation.  103  Chapter 5: General Conclusions  104  The goal of this dissertation is to begin addressing the functional consequences of hyperexcitable cortex in migraineurs. Collectively, the research presented suggests that migraineurs have anomalies specifically pointing to increased allocation of attention to extraneous environmental stimuli. Namely, between attacks migraineurs manifest heightened sensory responses of to-beignored visual stimuli (Chapter 2), increased reflexive orienting to sudden-onset stimuli in the visual periphery (Chapter 3), and increased evaluative processing over time at a post-spatial-selection level of attention (Chapter 4).  This final chapter briefly recaps each research chapter, then critically examines the impact of these findings in the context of four outstanding questions exposed by this research. Specifically, what evidence is there that topdown attentional control signals in migraineurs are intact?  How might these  cognitive anomalies be a result of or independent from known sensory cortical abnormalities? How do our findings fit with the migraineur experience? Lastly, what are the real-world clinical implications for migraineurs?  105  Figure 5.1 Research Findings 13  The main issues in this thesis are depicted diagrammatically in Figure 5.1. Specifically, three questions regarding attentional and cognitive consequences of migraine hyperexcitable visual cortex were addressed.  To begin with, given that top-down attentional control signals can affect excitability of sensory response in visual cortex, in Chapter 2 we asked if this normal modulation is affected in migraineurs. Indeed, it is. Namely, when a migraineur consciously orients their attention to a discrete location in visual space, they nevertheless manifest heightened cortical responses to events 106  outside their zone of attentional focus. This is in contrast to the normal response in which the strength of sensory-evoked cortical activity engendered by a stimulus directly varies with the amount of attention someone is paying to the location of that stimulus and involves an active suppression of activity for unattended stimuli. Using a probabilistic spatial orienting task while measuring ERPs to attended vs. unattended foveal and parafoveal stimuli, the finding was manifested in two key ways. Specifically, relative to controls, migraineurs lacked the normal increased cortical activity to attended parafoveal events, and in contrast showed an increased response to unattended events at the fovea. In light of this finding of increased sensory responses of to-be-ignored visual stimuli, one would expect sudden-onset stimuli in a migraineur’s visual periphery might manifest heightened bottom-up attentional responses, which is precisely the outcome of Chapter 3.  Chapter 3 examined the behavioral impact of hyperexcitability of migraine visual cortex in terms of its effect on bottom-up attentional processing, in this case reflexive attentional orienting. To begin with, a non-predictive spatial cueing task that relied on stimulus-evoked responses in visual cortex for triggering attentional orienting revealed that migraineurs have greater attentional enhancement of manual target responses relative to non-migraine controls. Two control experiments confirmed that this heightened attention effect in migraineurs was not due to exaggerated reflexive orienting responses in general, but rather, it appeared to be specifically associated with stimulus-evoked attentional triggers. Taken together, this confirms that the functional consequences of hyperexcitable 107  visual cortex in migraineurs are not just purely sensory in nature, but directly impact at least some forms of reflexive attention. This provides evidence of an attentional implication of hyperexcitable visual cortical responses in migraineurs, namely heightened reflexive visual-spatial orienting specific to sudden-onset peripheral events.  Finally, as illustrated in Figure 5.1, Chapter 4 found post-spatial-selection consequences of visual cortical hyperexcitability in migraineurs.  Specifically,  while migraineurs showed increased evaluative processing over time consistent with an increase in motivational attention towards everyday logos, this coincided with decreased implicit evaluative categorization of visual stimuli. In this study, participants viewed a set of unfamiliar commercial logos in the context of a target identification task while brain responses were recorded via ERPs. Following this task, participants individually identified those logos that they most liked or disliked.  Two key results suggested migraineurs have abnormal implicit  evaluative processing of visual stimuli. First, our data suggested migraineurs had an increasing level of cognitive analysis over time. Second, migraineurs lacked a bias for disliked logos. Taken together, these results suggest that migraineurs are not only evaluating attended environmental stimuli more than controls over time, but also not adequately hedonically categorizing it for quick allocation of attention.  108  Outstanding Questions Collectively, while these studies reveal that migraineurs have altered allocation of attention to extraneous environmental stimuli, several new questions fall from this research.  Below this dissertation explores four outstanding  questions. The first addresses a key outstanding issue not addressed in Chapter 2. The remaining questions address broader issues surrounding the finding that migraineurs have altered allocation of extraneous attention in migraineurs.  Impaired Top-Down Control Signals? Chapter 2 provides evidence that migraineurs have an altered ability to modulate the sensory-evoked excitability of visual cortex in a top-down manner via visual-spatial attention, but it is important to note the underlying assumption that these executive control signals are normal in migraineurs. Executive control signals are the necessary precursors to the attention-related changes in visuocortical sensory response (e.g., Corbetta & Shulman, 2002; Hopfinger, Buonocore, & Mangun, 2000). While Chapter 2 did not provide direct evidence that these signals are functionally normal, future studies could look at this question using ERPs during a spatial orienting task with cues presented centrally predicting targets appearing in left or right visual fields.  Specifically, the neurocognitive processes underlying the control of attentional orienting can be examined via two ERP components: the early directing attentional negativity (EDAN) and the anterior directing attentional negativity (ADAN).  The EDAN is thought to reflect the evaluation and 109  interpretation of the attention-directing cue (e.g., Jongen, Smulders, & Van Der Heiden, 2007), while the ADAN is believed to reflect the act of actually orienting attention itself to the cued location. In both components, the electrode sites contralateral to the cued spatial location are expected to have increased ERP amplitudes as compared to the ipsilateral electrodes (e.g., Green & McDonald, 2006; Jongen et al., 2007; Seiss, Gherri, Eardley, & Eimer, 2007). In such a manner, future research could assess whether these executive control signals are in fact intact in migraineurs.  Problem of Suppression? Given that this dissertation reveals visual attentional anomalies in migraineurs, to what extent, if at all, can we presume they are driven by or independent of known hyperexcitable sensory cortices? Might these results be a forward-cascade of sensory habituation, or another consequence of a more global cortical hyperexcitability in migraine?  Before answering this question, it is important to note that while there is general agreement that the migraine visual system is hyperexcitable at the cortical level in the sense of responding more strongly to intense, repetitive or long-lasting stimulation, there is debate over the mechanisms underlying this hyperexcitability. On one hand, it has been proposed that the hyperexcitability is a direct consequence of lack of habituation due to an interictal reduction of the pre-activation level of sensory cortices, such that they do not readily reach the ceiling of response activity after which repeated sensory stimulation normally 110  habituate (e.g., Coppola et al., 2009; Schoenen, 1996). It is then suggested that the lack of habituation contributes to sensory overload, which can underlie the initiation of a migraine event (e.g., Fumal et al., 2006). On the other hand, other research points to the hyperexcitability being caused by actual neuronal hyperexcitability, due to either of decreased intracortical inhibition (likely via decreased GABA; Chronicle & Mulleners, 1994) or increased facilitation (for example via increased glutamate; Aurora & Wilkinson, 2007).  While these studies were not designed to directly test the underlying cause of hyperexcitability, the results presented in this dissertation are more consistent with hyperexcitability in migraine visual cortex rather than a direct consequence of habituation. In particular, these results fit best with decreased inhibitory mechanisms. Notably, GABA-based intercellular inhibitory processes are indicated in both hyperexcitability in migraineurs (e.g., Aurora et al., 2005; Brighina et al., 2009), and in the suppression of spatial attention (e.g., Houghton & Tipper, 1996).  As suppression of attention to extraneous visual stimuli is  precisely what seems to be altered in migraineurs, altered inhibition in migraine may be at the core of both effects. This is consistent with the conclusion Wagner and colleagues made, that the signal-to-noise issues they found in migraine may be a consequence of decreased GABA-mediated suppression (2010). Indeed, it is beyond the scope of this dissertation to conclude the long-running debate about the molecular underpinnings of migraine hyperexcitability. Nonetheless, it is important to note that the conclusion of this research - that migraineurs have  111  altered allocation of attention to extraneous visual stimuli - is not dependent on the particulars of the underlying mechanism of hyperexcitability.  Consistent with the Migraineur Experience? Do migraineurs report experiences that align with our conclusion? Indeed, anecdotally, migraineurs often report on the distracting nature of extraneous visual inputs (e.g., Sacks, 1992). In fact, it is one of the first things migraineurs will tell us as participants in our attentional studies. For example, one migraineur reported that he found himself overwhelmed in large crowds, feeling as if he was pulled to attend to all the faces passing by him. Another participant complained of being unable to ignore the constant distraction of the moving captions on TV news channels. While these anecdotal examples fit with our conclusion that migraineurs have altered attention to irrelevant stimuli, they also underscore the lack of an empirical study comparing perceived attentional experience of migraineurs to controls. To fill in this gap in the literature, a future research study could utilize a mass internet survey to assess perceived attentional implications of participants, and include a headache survey to categorize participants.  While there is a lack of research on the migraineur perceived experience, several lines of empirical research are consistent with the conclusion that migraineurs have altered allocation of attention to extraneous visual stimuli. First, evidence indicates that migraineurs have difficulty extracting relevant stimuli from noise. Specifically, when detecting luminance targets in visual noise resembling grainy photographs, Wagner et al. (2010) found that migraineurs 112  have impairments in noise exclusion.  In addition, it is well-established that  migraineurs have difficulty identifying the direction of coherent motion in an incoherent environment (Antal et al., 2005; Ditchfield et al., 2006; McKendrick et al., 2006; McKendrick & Badcock, 2004b; Webster, Dickinson, Battista, McKendrick, & Badcock, 2011).  Specifically, migraineurs require a higher  percentage of dots to be moving together than do controls in order to identify the global motion. Furthermore, migraineurs are found to be poorer at detecting a target when superimposed on a higher contrast mask (McColl & Wilkinson, 2000). Finally, the perception of visual stimuli is more difficult to suppress in migraineurs (e.g., Chronicle et al., 2006; Mulleners et al., 2001). For example, Chronicle and Mulleners (2006) used a TMS technique called magnetic suppression of perceptual accuracy and demonstrated that migraine cortex is less proficient at suppressing letter stimuli. Collectively, the research indicates migraineurs ability to hone in on visual signals of interest is affected by increased distraction from extraneous noise.  Clinical Implications? Perhaps the most important remaining question is whether this research has real-world implications for migraineurs. In particular, to what extent might such information hold therapeutic value, both for day-to-day comfort and decrease of actual migraine events? One can think of simple adjustments that a migraineur could make to limit distracting stimuli, such as sitting with a flashing television out of sight in a restaurant, studying with the door shut to avoid visual traffic, or sitting at the front of a classroom to avoid distractions from fellow 113  students. From a more clinical standpoint, potential therapeutic training may help migraineurs to compensate for or overcome these attentional anomalies. For example, recent evidence suggests that action video-game playing leads to enhanced ability to suppress the cortical processing of distracting irrelevant visual information (Mishra et al., 2011). Specifically, the video game players showed a greater suppression of cortical potentials to rapidly flashed sequences when attention was directed elsewhere. Given migraineurs increased attention to irrelevant information and the potential for video-gaming to suppress this, one could imagine repetitive video-gaming or similar clinical training involving attention may have potential for reducing sensory-triggered migraine events.  Concluding Remarks The research from this dissertation reveals that migraine hyperexcitable visual cortex is not just a sensory issue, but that the consequences reverberate to attentional and cognitive processing between attacks. In summary, we found that migraineurs manifest heightened sensory responses to unattended visual stimuli, increased reflexive orienting to sudden-onset stimuli in the visual periphery, and abnormal increased cognitive processing over time consistent with an increase in motivational attention towards everyday logos. Collectively, these findings suggest that migraineurs have altered allocation of attention to extraneous environmental stimuli.  114  References Afra, J., Cecchini, A. P., De Pasqua, V., Albert, A., & Schoenen, J. (1998). Visual evoked potentials during long periods of pattern-reversal stimulation in migraine. Brain, 121, 233-241. Ambrosini, A., & Schoenen, J. (2003). The electrophysiology of migraine. 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