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Abstract

Background

Migraine is a disorder of periodic disabling headache. Facilitated cortical responsivity has been suggested as one predisposing factor. Although the underlying mechanisms of migraine attack onsets are not fully understood, facilitated cortical responsivity has been suggested as one predisposing factor. Here, we investigate if enhanced cortical responsivity is reflected in altered event-related potentials during processing of complex pictures.

Method

Altogether, 16 migraine patients and 16 healthy volunteers participated in this study. Each patient had a diagnosed migraine and was headache- and medication-free for the study. Participants watched positive, negative and neutral pictures from the international affective picture system. An electroencephalogram was recorded during picture presentation. Afterwards, participants were asked to rate the pictures for valence and arousal.

Results

Migraine patients showed significantly more negative-going early event-related potential components from 100 ms to 180 ms to all picture categories over occipital regions as well as more positive-going late potentials over central regions. Patients and controls did not differ in valence and arousal ratings for the international-affective picture system.

Discussion

Patients with migraine seem to react cortically more intensely to all kinds of pictorial stimuli, regardless of emotional content. This facilitated processing may be related to the high cortical responsivity shown in various other event-related potential studies and might contribute to the recurring intense headache attacks.

Keywords

Migraine event-related potentials late-positive-potential international affective picture system

Introduction

Although a much more common excuse, about 12% of the Western population actually suffer from migraine (1). The complete underlying pathophysiology of this disabling headache disorder is still unknown. This may be a result of migraine phenotypes being very heterogeneous (2). In spite of the heterogeneity, altered cortical responsivity in migraine patients has been repeatedly suggested to contribute to the disorder (3 –6). Various electroencephalogram (EEG) studies support the idea of a hyper-responsivity of cortical neurons by increased amplitudes and reduced habituation of event-related potentials (ERPs) (4,7 –9). For a more detailed review on the matter of altered responsivity, see also Tommaso et al. (10).

Most of these studies investigated automatic cortical components (up to 200 ms) with meaningless stimuli (e.g. flash-evoked visual potentials, pattern-reversed evoked potentials or sinus tones) (11 –13). Only a few studies investigated the cortical reactions of migraine patients to meaningful ‘real world’ stimuli, such as painful stimuli (14) or emotional faces (4).

Face stimuli elicit distinct ERP responses in healthy participants. For example, the N170 (or face N1, the first negative deflection in the processing stream) is commonly thought to reflect the processing of structural features of a face prior to real face recognition (15). Usually, the N170 is not altered by the emotion expressed in the displayed face. However, for instance, people with social anxiety waiting to give a public speech, show N170 enhancements for angry faces, suggesting disorder-related sensitising effects (16). Andreatta and colleagues (4) lately demonstrated that migraine patients also showed larger N170 amplitudes toward angry faces compared to neutral ones. This shows that migraine patients process angry faces more intensely than controls do. This result raises the question if migraine patients are generally more sensitive to emotional stimuli and if the hyper-responsivity of their cortex might also lead to intensified perceptions of emotional stimuli.

Results from Buodo et al. seem to point to a broader kind of alteration. She conducted a preliminary study with six migraine children (17). She presented pictures from the international affective picture system (IAPS) and found a larger late ERP component for all picture categories, commonly correlated with enhanced intrinsically motivated attention.

In adults, the processing of emotional stimuli is associated with at least two distinct ERPs: the early-posterior-negativity (EPN) and the late-positive potential (LPP). The EPN peaks around 200 ms and its amplitude is enhanced during processing of stimuli with emotional content (18). The EPN is believed to be an automatic reaction to emotional contents in stimuli. It occurs robustly during passive picture viewing and even when participants’ attention is occupied (19).

The LPP is a slow positive wave, peaking around 400–600 ms (19). Like the EPN, it is modulated by the intensity (or arousal) of emotional stimuli. Both, positive and negative stimuli result in an enhancement of EPN and LPP (20).

We investigate cortical responses to complex emotionally arousing and neutral pictures. We test whether there is evidence for either a general or an emotion-specific facilitation of cortical processing and whether any alteration is related to differences in behavioural emotional stimulus appraisal. Our ERP analysis focuses on early sensory responses for which alterations have been reported in studies using simple perceptual stimuli (11 –13) and the emotion-sensitive EPN and LPP components (18,19).

Methods

Participants

Altogether, 19 patients with migraine responded to a study advertisement within the University of Bielefeld. To participate in this study, migraine must have been diagnosed by a neurologist/physician prior to this study. Within the study, a migraine questionnaire was used to assess data about migraine attacks and disease course (see Table 1). Exclusion criteria were acute headache, other neurological disorders and medication affecting the central nervous system (including migraine prophylactic medication) within the last 24 hours, as well as a Beck Depression Inventory (BDI) score above 12 points. No patient reported a migraine attack within the last 24 hours before data acquisition. Three patients had to be excluded – two for having no clinical but only self-diagnosed migraine and one for a BDI score of 20 points. Thus, we finally include 16 patients.

Table 1.

Summary data of migraine and control group.

	Migraine group	Control group
Sex (female/male)	13/3	13/3
Age (mean (range))	26 (18–35)	24.75 (20–30)
Age at first migraine attack (mean (range))	14.5 (1–23)
Years with migraine (range)	10 (3–17)
Days per month with migraine (range)	3.6 (0.5–10)
Days per month with none-migraine headache (range)	4 (0–22.5)	3 (0–10)
Pain location (left/right) in %	48/52
Duration of migraine attack (mean)	5–12 hours
Subjective painfulness of the migraine (0 – no pain; 10 – worst possible pain) (range)	7 (3–10)
Last migraine related medication (range)	36 (1–120 days)
BDI (mean (range))	4.4 (0–12)	3 (0–9)

BDI: Beck Depression Inventory, cut of value was set to above 12 points.

The 20 controls were also recruited from the University of Bielefeld. Four control participants had to be excluded from further analysis. Two for technical problems during data recording, one for excessive artefacts (blinks and drifts) within EEG data and one mentioned possible migraine attacks in childhood, communicated after data acquisition. Thus, we finally include 16 controls for further analysis. They match the patient group for age, gender, days with non-migraine headache and BDI scores (see Table 1). Controls reported no history of migraine in themselves and only two reported migraine within the family.

All participants were rewarded with €10 or credit points. The study was approved by the ethics committee of the University of Bielefeld.

Procedure

After arrival, participants received oral and written study information. Then, they signed an informed consent form. Participants were seated on a comfortable chair in front of a computer. While electrodes were applied, participants filled in two questionnaires, one for basic demographics and one addressing the migraine.

Presentation software (Presentation; Neurobehavioral Systems, Albany, CA, USA) was used to control picture presentation and trigger synchronisation with the EEG recording. ActiView (ActiveTwo, Version 3.2, Biosemi, Cortech Solutions, LLC) software recorded the EEG signal.

The experiment consisted of five EEG runs and a rating task. During the first five runs, 5 × 12 positive, negative and neutral pictures from the IAPS were presented in a randomised order. During these runs, participants were asked to passively view the pictures and avoid eye, face and body movements. For each participant, the run order was randomised. Each picture lasted for 1000 ms on the computer screen. The inter-stimulus interval (ISI) ranged from 2500 ms to 13,000 ms. Participants were told to blink during the ISI while the fixation cross was presented. The long ISI helped effectively to reduce blink artefacts for the epochs of picture presentation.

For the last task, the EEG cap was removed. Participants were then asked to rate each picture on valence (very unpleasant to very pleasant) and arousal (very quiet to very exciting), using the 1–7 self-assessment manikin scale (21).

EEG recording and data analysis

The EEG was recorded with Ag/AgCl active electrodes (BioSemi ActiveTwo, Cortech Solutions, LLC). Altogether, 32 scalp electrodes were placed according to the international 10–20 system. Three additional electrodes were placed at the location of O9, Iz and O10 to have better coverage of visual areas. Reference and ground were placed left and right from Cz. Three electrodes were used to record vertical and horizontal eye movements (two at the left and right outer canthi of the eyes, one below the left eye). The EEG was continuously recorded with a sampling rate of 2048 Hz. No additional filters were applied for recording.

Offline pre-processing was performed with the software Brain Electrical Source Analysis (BESA Research 6.0). Data were re-referenced to average reference, re-sampled to 512 Hz and filtered between 0.16 Hz and 15 Hz for averaging. Epochs were defined from −100 to 1000 ms. Epochs with amplitudes above 120 microvolt were automatically rejected as artefacts. One participant, as mentioned above, had to be excluded due to a high rejection rate of epochs because of excessive blinking.

Each experimental condition was then averaged for every participant.

Within the averaged epochs, statistical analysis of group and emotion effects was performed with EMEGS (22) within the following time windows: We analysed early visual components between 100 and 180 ms after stimulus onset in a occipital electrode cluster (eight electrodes: PO3; PO4; O1; Oz; O2; O9; Iz; O10). We further tested for the EPN effects within a time window between 200 and 300 ms after picture presentation over the same occipital electrode cluster (eight electrodes: PO3; PO4; O1; Oz; O2; O9; Iz; O10). Finally, the LPP was analysed within the timeframe of 400–700 ms after picture onset over a centro-parietal electrode cluster (10 electrodes: FC1; FC2; C3; Cz; C4; CP1; CP2; P3; Pz; P4).

Analyses of variance (ANOVA) were performed for ERP components and valence/arousal ratings separately. Included were group (control/migraine) as between group factor and emotion (positive, negative and neutral) as within factor. If Mauchly’s test showed a violation of the assumption of sphericity, degrees of freedom were corrected according to Greenhouse–Geisser. For valence and arousal ratings, ANOVA was carried out with SPSS 19 (Statistical Package for the Social Sciences; SPSS Inc., Chicago, IL, USA). For the ERP components the ANOVA was performed with EMEGS and contained the additional within factors ‘electrode cluster’. The significance level was set at 0.05 for all analyses, effect sizes are reported as partial eta squared (η²).

Results

Valence and arousal ratings

For the ratings of valence and arousal, significant main effects were found for emotion (valence: F(2,29) = 318.46, p < 0.000; arousal: F(2,29) = 99.37, p < 0.000). Bonferroni correction comparisons between emotion categories confirmed significant rating differences between all three valence ratings (positive vs. negative: t(62) = 24.39, p < 0.0001; positive vs. neutral: t(62) = 10.43, p < 0.0001; neutral vs. negative: t(62) = 20.87, p < 0.0001) and all three arousal ratings (positive vs. negative: t(62) = 3.50, p < 0.0009; positive vs. neutral: t(62) = 7.03, p < 0.0001; negative vs. neutral: t(62) = 10.82, p < 0.0001). However, there was no main effect for group, migraine patients did not differ in their ratings from controls (valence: F(1,30) = 0.38, p = 0.11; arousal: F(1,30) = 0.24, p = 0.627). Finally, there was no significant interaction of emotion and group, neither for valence: F(2,29) = 0.06, p = 0.90; nor for arousal: F(2,29) = 0.18, p = 0.83. Means and SD are summarised in Table 2.

Table 2.

Means and SD for valence and arousal ratings for migraine patients and controls respectively.

		Valence rating	Arousal rating
Migraine	Positive pictures	5.19 (SD = 0.66)	4.44 (SD = 0.89)
Migraine	Negative pictures	1.78 (SD = 0.41)	5.19 (SD = 0.81)
Neutral pictures	3.94 (SD = 0.44)	2.81 (SD = 1.03)
Controls	Positive pictures	5.31 (SD = 0.60)	4.59 (SD = 0.82)
Controls	Negative pictures	1.97 (SD = 0.53)	5.18 (SD = 0.54)
Neutral pictures	4.00 (SD = 0.00)	3.00 (SD = 0.95)

Notes: Pictures were rated on the 1–7 self-assessment manikin scale. Valence: rated with 1 = very negative picture, rated with 4 = neutral picture, rated with 7 = very positive picture. Arousal: rated with 1 = very calm picture, rated with 7 = very arousing picture.

ERP effects

Early effects

A significant group effect was found between 100 and 180 ms. Patients with migraine showed significant differences in processing of all picture categories with relatively more negative going waveforms F(1,30) = 4.79, p < 0.05, partial η²= 0.14 (see Figure 1). Within this early time window, no main effect for emotion F(2,60) = 1.20, p = 0.31, partial η²= 0.04 or group*emotion interaction F(2,60) = 0.65, p = 0.52, partial η²= 0.02 was found.

Figure 1.

Main effects of group and emotion in the early time windows. (a) Difference topographies for the main effect of group. Blue colour indicates more negativity and red colour more positivity in the ERPs of migraine patients compared to controls. (b) Electrode O1, displaying the time course of ERPs for migraine patients and controls over occipital sites. (c) Difference topographies for the main effect of emotion. Blue colour indicates more negativity and red colour more positivity in the ERPs of negative and positive pictures compared to neutral pictures. (d) Electrode O9, displaying the time course of ERPs for negative, neutral and positive pictures over occipital sites.

EPN

The analysis of the EPN time window (200–300 ms) revealed a significant main effect for emotion F(2,60) = 6.08, p < 0.01, partial η²= 0.17 (see Figure 1). A post hoc test showed significant differences for the negative pictures compared to neutral (p < 0.01) and positive pictures (p < 0.01) with negative pictures being relatively more negative in amplitude. There was no difference between positive and neutral pictures (p = 0.76) (see Figure 1).

For the EPN time window, there was only a trend for a group effect F(1,30) = 3.62, p = 0.07, partial η²= 0.11 (with patients having a more pronounced EPN than controls) and no group*emotion effect F(2,60) = 0.51, p = 0.60, partial η²= 0.02.

LPP

The LPP analysis revealed a significant main effect of group F(1,30) = 7.15, p < 0.05, partial η²= 0.19 and a significant main effect of emotion F(2,60) = 14.40, p < 0.001, η²= 0.32. Post hoc tests for the significant group effect showed a larger LPP for migraine patients over central sites with a broad distribution (see Figure 2(a)). For the emotion main effect, post hoc tests showed that both positive and negative pictures elicited more positive ERPs than neutral ones (both p < 0.001). Positive and negative pictures did not differ significantly from each other (p = 0.34). An example of the LPP at the electrode Pz can be seen in Figure 2(b,d). Using two separated electrode clusters (fronto-central and parietal) within the LPP time window led to similar results. The main effect of group was significant fronto-centrally (eight electrodes: F1; Fz; F2; FC1; FC2; C3; Cz; C4; F(1,30) = 7.99, p < 0.01), while the emotion effect disappeared (F(2,60) = 0.46, p = 0.64).

Figure 2.

Main effects in the late positive potential time window. (a) Difference topographies for the main effect of group. Blue colour indicates more negativity and red colour more positivity in the ERPs of migraine patients compared to controls. (b) Electrode Pz, displaying the time course of ERPs for migraine patients and controls over centro-parietal sites. (c) Difference topographies for the main effect of emotion. Blue colour indicates more negativity and red colour more positivity in the ERPs of negative and positive pictures compared to neutral pictures. (d) Electrode Pz, displaying the time course of ERPs for negative, neutral and positive pictures over centro-parietal sites.

For the LPP time window, no significant interaction of emotion and group F(2,60) = 2.15, p = 0.13, partial η²= 0.07 was found.

At the parietal electrode cluster (seven electrodes: CP1; CP2; P3; Pz; P4; PO3; PO4), a large emotion effect F(2,60) = 25.55, p < 0.001, but no group effect (F(1,30) = 0.64, p = 0.43) is found. Interactions are far from significant.

Mean amplitudes with SD and statistics are shown in Table 3.

Table 3.

Statistical results and mean amplitudes per group and condition.

	Migraine patients			Controls			Statistics
ERPs	Negative	Neutral	Positive	Negative	Neutral	Positive	Emotion F_(2,60)	Group F_(1,30)
P1/N1	0.99 µV (2.77)	0.75 µV (2.81)	0.66 µV (2.80)	2.81 µV (2.45)	2.88 µV (2.25)	2.71 µV (2.60)	1.20	4.79^*
EPN	4.64 µV (2.39)	5.07 µV (1.88)	5.19 µV (3.23)	6.66 µV (4.11)	7.34 µV (3.65)	7.11 µV (3.80)	6.08^**	3.62^τ
LPP	1.10 µV (1.54)	0.24 µV (1.03)	0.71 µV (1.20)	−0.44 µV (1.74)	−0.91 µV (1.31)	−0.32 µV (1.34)	14.40^***	7.15^*

τ= p ≤ 0.1; *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001.

Note: SD appear in parentheses below means.

Discussion

This study investigates the neurological and behavioural responses of migraine patients to emotional pictures. We found expected emotion effects within the time frames of the EPN and the LPP. More interestingly, we also found enhanced early and more automatic cortical responses in patients compared to controls as well as an enhanced LPP. Between 100 and 180 ms, patients showed a significantly more negative going ERP for all three picture categories (positive, negative and neutral). Between 400 and 700 ms, patients exhibited significantly more pronounced LPPs, again for all three picture categories. Amplitude differences between patients and controls within the EPN time window only reached trend level, but the direction of this trend is, again, that patients have a more pronounced EPN than controls. It is worth noting, however, that, patients and controls showed clearly separated ERP waves throughout nearly the whole analysis epoch. By contrast, valence and arousal ratings did not differ between the two groups.

On the cortical level, patients exhibited pronounced early components, suggesting that they process all pictures more intensively than healthy individuals do. These results fit well with the previous literature, showing enhanced cortical reactions of migraine patients to visual stimuli in early components (9,23,24). Regarding emotional stimulation, Andreatta showed an enhanced reaction of migraine patients to angry faces. The same could not be found for the happy counterparts (4). In our study, patients showed enhanced reactions to all kinds of stimuli. In fact, the absence of any interaction between group and emotion clearly shows that migraine patients have equally facilitated processing of emotional and neutral pictures. Andreatta, on the other hand, argued for a focus on negative emotion in migraine patients, possibly resulting in enhanced social stress, which is discussed as a trigger for migraine attacks (4). Because our stimuli did not exclusively depict social scenes, they do not bear directly on the issue whether migraine patients may be more sensitive towards negative social stimuli. However, our results suggest a more generally enhanced sensitivity to all kinds of complex pictorial stimuli, both at early and late processing stages. Patients showed a much broader cortical reaction to all types of IAPS pictures, not exclusively for negative emotions. In the late analysis window, there is a small trend towards an interaction, suggesting that with more participants a somewhat greater sensitivity for negative contents in migraine might be found. However, the general amplitude differences are clearly the more robust phenomenon. At early stages, cortical reactions of migraine patients are relatively more negative, which is commonly related to more excitatory cerebral activity (for a review, see Ambrosine et al. (7)). Therefore, the processing of IAPS pictures can be described as more intense in migraine patients. Since this effect holds true for emotional as well as neutral pictures, migraine patients seem to allocate more perceptual and cognitive resources to all kinds of stimuli than controls do. Kropp et al. showed, in his experiment, that migraine patients allocate more cognitive resources (increased ‘post-imperative negative variation’) in order to avoid situations where they could experience a loss of control and fail in the experimental task (25). Along the same lines, Andreatta et al. showed that migraine patients react more sensitively to negative social feedback (angry faces leading to an enhanced N170), similar to what is seen in people with social phobia (4). Indeed, migraine patients self-report more social distress than healthy people (26). Taken together, the results suggest that migraine patients constantly allocate more cognitive resources in order to predict and subsequently avoid stressful situations of any kind (social or otherwise), which have often been described as migraine attack triggers.

In our group, this also leads to a significantly increased LPP for migraine patients.

Previous literature showed that the LPP amplitude varies with subjective stimuli-induced arousal (20). Thus, more arousing stimuli produce a more pronounced LPP. Concordant to that, we found a significant main effect for emotion categories across all participants: the highest LPP for negative pictures (which were judged as the most arousing by migraine patients and controls) and the lowest for neutral ones. Across groups, the LPPs for all picture categories for the migraine patient group showed higher amplitudes than those for controls.

This result fits well with Buodo at al. She conducted a preliminary study with six children and adolescents with migraine, targeting the negative central component (NCC) of children’s ERPs. While she failed to show the predicted enhancement of the NCC, she, too, found a larger positivity between 400 and 800 ms in response to all picture contents (positive, negative and neutral IAPS pictures). She concluded that ‘in children with migraine, the faster maturation of attentional circuits could be reflected in the allocation of greater attentional resources toward visual stimuli in general and not only emotionally relevant contents' (pp. 1513–1514) (17). Our data resemble the results from Buodo regarding the LPP. Our data further show that this is an age independent effect, apparently correlated with the migrainous brain.

It can be assumed that this ‘allocation of greater attentional resources' would lead to a constantly enhanced processing of all kinds of visual stimuli since psychophysical studies convincingly established that visual processing, on the neuronal basis, gets enhanced with attention (mainly in V1, V2 and V4) (27 –29). This continuously enhanced cortical activation would further amplify if many stimuli have to be processed in a short time. As it is, patients describe rapid stimuli (such as flicker boards or TV shows with rapid picture changes) as migraine attack triggers. It is noteworthy that we found the described migraine control differences even with a very slow stimulation rate.

Given previous literature, it is reasonable to believe that the amount of alterations in cortical excitability plays a role in triggering migraine attacks and therefore in migraine attack frequency. Diener et al., for example, has shown that effective migraine-prevention medication sets cognitive excitability back to normal (23). We would therefore assume that, in reverse, a more severe and disabling migraine is associated with greater cortical disturbances. This assumption receives some support by the fact that mean amplitudes of our migraine patients were negatively correlated with ‘days with migraine per month' (Pearson’s r = −0.576; p = 0.019) within the EPN time window. This shows that patients experiencing a higher number of days with migraine in a month tend to exhibit more negative going EPNs or, in other words, a more pronounced cortical alteration. There is also a trend for the correlation of ‘years with migraine' and the mean amplitude of the effects within the early time window (Pearson’s r − 0.510; p = 0.075). This negative correlation again shows a more pronounced cortical alteration with years of ongoing migraine. On the other hand, none of the other clinical features (like ‘subjective painfulness' or ‘migraine offset') showed correlations with patients' cortical responses in any time window (see Table 1 in Supplementary Material). However, this could be a result of the small sample size of this study. A future study with more patients and an expanded range in migraine severity is needed to clarify possible correlations of patients' clinical features with cortical alterations.

It would also be very interesting to see whether, in a more affected group of patients, reported valence and arousal ratings would differ from controls.

Another limitation, besides the small sample size of this study, is the fact that we did not control for the occurrence of a migraine attack shortly after the experiment. This would have been interesting, because it is known that cortical responsivity varies in temporal relation to the attack. While most cortical variations that can be found between attacks (like reduced habituation or altered latencies/amplitudes) normalise during attacks (30,31), at least for some components it has been shown that the alterations tend to increase 1 or 2 days before the attack (32,33). To the best of our knowledge, there is no study showing the temporal relation of EPN and LPP amplitudes to migraine attack proximity. It is, however, possible that they increase before attacks. If that were the case, and if some of our patients experienced an attack within the following 2 days, our results might overestimate the differences that can be found between patients and controls strictly between attacks. Still, we think it is unlikely that most of our patients experienced an attack on the following 2 days, assuming that attack onset is randomly distributed. Nevertheless, from our data, no conclusion about the temporal relationship of early and late ERP differences to attack proximity can be drawn. To summarise, our study showed altered cortical mechanisms in the processing of emotional and neutral pictures. Enhanced activation was found for early automatic reactions and for late indices of motivated attention. It seems that all kind of pictures induce more cortical activity in migrainous patients. We argue that the high cortical excitability may result in higher motivated attention even to neutral stimuli. Given lots of incoming stimuli, this may result in constantly enhanced neural activity and in perceived stress, which in turn may trigger migraine attacks.

Clinical implications

Migraine patients show enhanced early but also late cortical event related potentials.

Migraine patients seem to allocate more motivated attention to all kinds of complex pictures (IAPS).

We argue for a constantly enhanced neuronal activity while processing all kinds of visual stimuli, which might be correlated with migraine attack frequencies.

Footnotes

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-profit sectors.

Conflict of interest

None declared.

Acknowledgement

We would like to thank Diana Schlösser, Maleen Fiddicke and Liane Harlfinger for their help with data acquisition and all patients and students for participation.

References

Dahlöf

Dimenäs

. Migraine patients experience poorer subjective well-being/quality of life even between attacks. Cephalalgia 1995; 15: 31–36.

Ferrari

Klever

Terwindt

, et al. Migraine pathophysiology: lessons from mouse models and human genetics. Lancet Neurol 2015; 14: 65–80.

Schwedt

Dodick

. Advanced neuroimaging of migraine. Lancet Neurol 2009; 8: 560–568.

Andreatta

Puschmann

Sommer

, et al. Altered processing of emotional stimuli in migraine: An event-related potential study. Cephalalgia 2012; 32: 1101–1108.

Ghadiri

Kozian

Ghaffarian

, et al. Sequential changes in neuronal activity in single neocortical neurons after spreading depression. Cephalalgia 2012; 32: 116–124.

Brigo

Storti

Tezzon

, et al. Primary visual cortex excitability in migraine: a systematic review with meta-analysis. Neurol Sci 2013; 34: 819–830.

Ambrosini

de Noordhout

Sándor

, et al. Electrophysiological studies in migraine: A comprehensive review of their interest and limitations. Cephalalgia 2003; 23(Suppl. 1): 13–31.

Coppola

Parisi

Di Lorenzo

, et al. Lateral inhibition in visual cortex of migraine patients between attacks. J Headache Pain 2013; 14: 20–20.

Gantenbein

Sandor

Fritschy

, et al. Sensory information processing may be neuroenergetically more demanding in migraine patients. NeuroReport 2013; 24: 202–205.

10.

Tommaso

de Ambrosini

Brighina

, et al. Altered processing of sensory stimuli in patients with migraine. Nat Rev Neurol 2014; 10: 144–155.

11.

Connolly

Gawel

Rose

. Migraine patients exhibit abnormalities in the visual evoked potential. J. Neurol. Neurosurg. Psychiatr 1982; 45: 464–467.

12.

Afra

Proietti Cecchini

Sándor

, et al. Comparison of visual and auditory evoked cortical potentials in migraine patients between attacks. Clin Neurophysiol 2000; 111: 1124–1129.

13.

Dixon

. Measuring event-related potentials. Cephalalgia 1999; 19: 29–31.

14.

De Tommaso

Baumgartner

Sardaro

, et al. Effects of distraction versus spatial discrimination on laser-evoked potentials in migraine. Headache 2008; 48: 408–416.

15.

Eimer

Holmes

. Event-related brain potential correlates of emotional face processing. Neuropsychologia 2007; 45: 15–31.

16.

Wieser

Pauli

Reicherts

, et al. Don't look at me in anger! Enhanced processing of angry faces in anticipation of public speaking. Psychophysiology 2010; 47: 271–280.

17.

Buodo

Sarlo

Battistella

, et al. Event-related potentials to emotional stimuli in migrainous children. J Child Neurol 2011; 26: 1508–1515.

18.

Junghöfer

Sabatinelli

Bradley

, et al. Fleeting images: rapid affect discrimination in the visual cortex. NeuroReport 2006; 17: 225–229.

19.

Schupp

Flaisch

Stockburger

, et al. Emotion and attention: Event-related brain potential studies. Prog Brain Res 2006; 156: 31–51.

20.

Cuthbert

Schupp

Bradley

, et al. Brain potentials in affective picture processing: covariation with autonomic arousal and affective report. Biol Psychol 2000; 52: 95–111.

21.

Bradley

Lang

. Measuring emotion: the self-assessment manikin and the semantic differential. J Behav Ther Exp Psychiatry 1994; 25: 49–59.

22.

Peyk

Cesarei

de Junghöfer

. ElectroMagnetoEncephalography software: overview and integration with other EEG/MEG toolboxes. Comput Intell Neurosci 2011; 2011: 861705–861705.

23.

Diener

Scholz

Dichgans

, et al. Central effects of drugs used in migraine prophylaxis evaluated by visual evoked potentials. Ann Neurol 1989; 25: 125–130.

24.

Shibata

Osawa

Iwata

. Simultaneous recording of pattern reversal electroretinograms and visual evoked potentials in migraine. Cephalalgia 1997; 17: 742–747.

25.

Kropp

Brecht

Niederberger

, et al. Time-dependent post-imperative negative variation indicates adaptation and problem solving in migraine patients. J Neural Transm 2012; 119: 1213–1221.

26.

Eskin

Akyol

Çelik

, et al. Social problem-solving, perceived stress, depression and life-satisfaction in patients suffering from tension type and migraine headaches. Scand J Psychol 2013; 54: 337–343.

27.

Motter

. Focal attention produces spatially selective processing in visual cortical areas V1, V2, and V4 in the presence of competing stimuli. J Neurophysiol 1993; 70: 909–919.

28.

Blaser

Sperling

. Measuring the amplification of attention. Proc Natl Acad Sci USA 1999; 96: 11681–11686.

29.

Moore

Armstrong

. Selective gating of visual signals by microstimulation of frontal cortex. Nature 2003; 421: 370–373.

30.

Kropp

Gerber

. Contingent negative variation during migraine attack and interval: evidence for normalization of slow cortical potentials during the attack. Cephalalgia 1995; 15: 123–128. discussion 78–79.

31.

Evers

Quibeldey

Grotemeyer

, et al. Dynamic changes of cognitive habituation and serotonin metabolism during the migraine interval. Cephalalgia 1999; 19: 485–491.

32.

Kropp

Gerber

. Prediction of migraine attacks using a slow cortical potential, the contingent negative variation. Neurosci Lett 1998; 257: 73–76.

33.

Judit

Sándor

Schoenen

. Habituation of visual and intensity dependence of auditory evoked cortical potentials tends to normalize just before and during the migraine attack. Cephalalgia 2000; 20: 714–719.

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Higher,faster,worse? An event-related potentials study of affective picture processing in migraine

Abstract

Background

Method

Results

Discussion

Keywords

Introduction

Methods

Participants

Procedure

EEG recording and data analysis

Results

Valence and arousal ratings

ERP effects

Early effects

EPN

LPP

Discussion

Clinical implications

Footnotes

Funding

Conflict of interest

Acknowledgement

References

Supplementary Material