Introduction Although migraine and persistent post-traumatic headache often share phenotypic characteristics, few studies have interrogated the pathophysiological differences underlying these headache types. While there is now some indication of differences in brain structure between migraine and persistent post-traumatic headache, differences in brain function have not been adequately investigated. The objective of this study was to compare static and dynamic functional connectivity patterns in migraine versus persistent post-traumatic headache using resting-state magnetic resonance imaging. Methods This case-control study interrogated the static functional connectivity and dynamic functional connectivity patterns of 59 a priori selected regions of interest involved in pain processing. Pairwise connectivity (region of interest to region of interest) differences between migraine (n = 33) and persistent post-traumatic headache (n = 44) were determined and compared to healthy controls (n = 36) with ANOVA and subsequent t-tests. Pearson partial correlations were used to explore the relationship between headache burden (headache frequency; years lived with headache) and functional connectivity and between pain intensity at the time of imaging and functional connectivity for migraine and persistent post-traumatic headache groups, separately. Results Significant differences in static functional connectivity between migraine and persistent post-traumatic headache were found for 17 region pairs that included the following regions of interest: Primary somatosensory, secondary somatosensory, posterior insula, hypothalamus, anterior cingulate, middle cingulate, temporal pole, supramarginal gyrus, superior parietal, middle occipital, lingual gyrus, pulvinar, precuneus, cuneus, somatomotor, ventromedial prefrontal cortex, and dorsolateral prefrontal cortex. Significant differences in dynamic functional connectivity between migraine and persistent post-traumatic headache were found for 10 region pairs that included the following regions of interest: Secondary somatosensory, hypothalamus, middle cingulate, temporal pole, supramarginal gyrus, superior parietal, lingual gyrus, somatomotor, precentral, posterior cingulate, middle frontal, fusiform gyrus, parieto-occiptal, and amygdala. Although there was overlap among the regions demonstrating static functional connectivity differences and those showing dynamic functional connectivity differences between persistent post-traumatic headache and migraine, there was no overlap in the region pair functional connections. After controlling for sex and age, there were significant correlations between years lived with headache with static functional connectivity of the right dorsolateral prefrontal cortex with the right ventromedial prefrontal cortex in the migraine group and with static functional connectivity of right primary somatosensory with left supramarginal gyrus in the persistent post-traumatic headache group. There were significant correlations between headache frequency with static functional connectivity of left secondary somatosensory with right cuneus in the migraine group and with static functional connectivity of left middle cingulate with right pulvinar and right posterior insula with left hypothalamus in the persistent post-traumatic headache group. Dynamic functional connectivity was significantly correlated with headache frequency, after controlling for sex and age, in the persistent post-traumatic headache group for one region pair (right middle cingulate with right supramarginal gyrus). Dynamic functional connectivity was correlated with pain intensity at the time of imaging for the migraine cohort for one region pair (right posterior cingulate with right amygdala). Conclusions Resting-state functional imaging revealed static functional connectivity and dynamic functional connectivity differences between migraine and persistent post-traumatic headache for regions involved in pain processing. These differences in functional connectivity might be indicative of distinctive pathophysiology associated with migraine versus persistent post-traumatic headache.

Background.-The American Registry for Migraine Research (ARMR) is a multicenter, prospective, longitudinal patient registry, biorepository, and neuroimaging repository that collects clinical data, electronic health record (EHR) data, blood samples, and brain imaging data from individuals with migraine or other headache types. In this manuscript, we outline ARMR research methods and report baseline data describing an initial cohort of ARMR participants.Methods.-Adults with any International Classification of Headache Disorders (ICHD) diagnosis were prospectively enrolled from one of the 8 participating headache specialty centers. At baseline, ARMR participants complete web-based questionnaires, clinicians enter the participant's ICHD diagnoses, an optional blood specimen is collected, and neuroimaging data are uploaded to the ARMR neuroimaging repository. Participants maintain the ARMR daily headache diary longitudinally and follow-up questionnaires are completed by participants every 3 months. EHR data are integrated into the ARMR database from a subset of ARMR sites. Herein, we describe the ARMR methodology and report the summary data from ARMR participants who had, from February 2016 to May 2019, completed at least 1 baseline questionnaire from which data are reported in this manuscript. Descriptive statistics are used to provide an overview of patient's sociodemographics, headache diagnoses, headache characteristics, most bothersome symptoms other than headache, headache-related disability, comorbidities, and treatments.Results.-Data were available from 996 ARMR participants, enrolled from Mayo Clinic Arizona, Institute. Among ARMR participants, 86.7% (n = 864) were female and the mean age at the time of enrollment was 48.6 years (±13.9; range 18-84). The most common provider-reported diagnosis was chronic migraine (n = 622), followed by migraine without aura (n = 327), migraine with aura (n = 196), and medication overuse headache (n = 65). Average headache frequency was 19.1 ± 9.2 days per month (n = 751), with 68% reporting at least 15 headache days per month. Sensitivity to light was the most frequent (n = 222) most bothersome symptom overall, other than headache, but when present, cognitive dysfunction was most frequently (n = 157) the most bothersome symptom other than headache. Average migraine disability assessment (MIDAS) score was 52 ± 49 (n = 760), (very severe headache-related disability); however, 17% of the ARMR population had MIDAS scores suggesting "no" or "mild" disability. The most common non-headache health issues were allergies (n = 364), back pain (n = 296), neck pain (n = 296), depression (n = 292), and anxiety (n = 278). Nearly 85% (n = 695) of patients were using preventive medications and 24.7% were using non-medication preventive therapy (eg, vitamins and neuromodulation). The most common preventive medication classes were neurotoxins, anticonvulsants, antidepressants, vitamins/supplements, and anticalcitonin gene-related peptide ligand or receptor-targeted monoclonal antibodies. Nearl...

Objective: To evaluate whether the 15-day threshold of headache days per month adequately reflects substantial differences in disability across the full spectrum of migraine. Background:The monthly frequency of headache days defines migraine subtypes and has crucial implications for epidemiological and clinical research as well as access to care. Methods: The patients with migraine (N = 836) who participated in the American Registry for Migraine Research, which is a multicenter, longitudinal patient registry, between February 2016 and March 2020, were divided into four groups based on monthly headache frequency: Group 1 (0-7 headache days/month, n = 286), Group 2 (8-14 headache days/month, n = 180), Group 3 (15-23 headache days/month, n = 153), Group 4 (≥24 headache days/month, n = 217). Disability (MIDAS), Pain intensity (NRS), Work Productivity and Activity Impairment (WPAI), Pain Interference (PROMIS-PI), Patient Health Questionnaire-4 (PHQ-4), and General Anxiety Disorder-7 (GAD-7) scores were compared. Results: Mean (standard deviation [SD]) age was 46 (13) years (87.9% [735/836] female). The proportion of patients in each group was as follows: Group 1 (34.2% [286/836]), Group 2 (21.5% [180/836]), Group 3 (18.3% [153/836]), and Group 4 (26.0%[217/836]). There were significant relationships with increasing disability, lost productive time, and pain interference in higher headache frequency categories. There were no significant differences between Group 2 and Group 3 for most measures (NRS, all WPAI scores, PROMIS-PI, GAD-7, and PHQ-4), although MIDAS scores differed (median [interquartile range (IQR)]; 38 [20-58] vs. 55 [30-90], p < 0.001). Patients in Group 1 had significantly lower MIDAS (median [IQR];[16][17][18][19][20][21][22][23][24][25][26][27][28][29][30], p < 0.001), WPAI-% total active impairment (mean (SD): Group 1 [30.9 (26.8)] vs. Group 2 [39.2 (24.5), How to cite this article: Ishii R, Schwedt TJ, Dumkrieger G, et al. Chronic versus episodic migraine: The 15-day threshold does not adequately reflect substantial differences in disability across the full spectrum of headache frequency.

Symptoms of autonomic dysfunction were greatest among those with PPTH compared to migraine and healthy controls. Among individuals with PPTH, number of lifetime TBIs was associated with greater symptoms of autonomic dysfunction, while greater headache burden was associated with higher vasomotor domain autonomic dysfunction subscores, potentially indicating that PPTH patients with higher disease burden have an increased risk for having autonomic dysfunction. Symptoms of autonomic dysfunction should be ascertained during the clinical management of patients with PPTH and might be a characteristic that helps differentiate PPTH from migraine.

Objective To interrogate hippocampal morphology and structural co-variance patterns in migraine patients and to investigate whether structural co-variance patterns relate to migraine disease characteristics. Background Migraine is associated with structural alterations in widespread cortical and subcortical regions associated with the sensory, cognitive, and affective components of pain processing. Recent studies have shown that migraine patients have differences in hippocampal structure and function relative to healthy control subjects, but whether hippocampal structure relates to disease characteristics including frequency of attacks, years lived with migraine and symptoms of allodynia remains unknown. Furthermore, this study investigated hippocampal volume co-variance patterns in migraineurs, an indirect measure of brain network connectivity. Here, we explore differences in hippocampal volume and structural co-variance patterns in migraine patients relative to healthy controls and examine whether these hippocampal measures relate to migraine disease burden. Methods This study included 61 migraine patients and 57 healthy control subjects (healthy controls: median age=34.0, IQR=19.0; migraine patients: median age=35.0, IQR=17.5; p=0.65). Regional brain volumes were automatically calculated using FreeSurfer version 5.3. Symptoms of allodynia were determined using the Allodynia Symptom Checklist 12 (ASC-12). Structural covariance patterns were interrogated using pairwise correlations and group differences in correlation strength were estimated using Euclidian distance. A stepwise regression was used to investigate the relationship between structural co-variance patterns with migraine burden. Results Migraine patients had less left hippocampal volume (healthy controls: left hippocampal volume = 4276.8mm3, SD= 425.3mm3, migraine patients: left hippocampal volume= 4089.5mm3, SD= 453.9mm3, p= 0.02) and less total (right plus left) hippocampal volume (healthy controls: total hippocampal volume= 8690.8mm3, SD= 855.1mm3; migraine patients: total hippocampal volume= 8341.8mm3, SD=917.9mm3; p= 0.03) compared to healthy controls. Migraineurs had stronger structural covariance between the hippocampi and cortico-limbic regions in the frontal lobe (inferior opercular gyrus), temporal lobe (planum temporale, amygdala), parietal lobe (angular gyrus, precuneus,) and the cerebellar white matter. Results of a stepwise regression showed that hippocampal volumes and the interactions between hippocampal volumes with the volumes of other cortico-limbic regions associate with migraine-related allodynia but not with headache frequency or years lived with migraine. Conclusion Migraineurs have less hippocampal volume and stronger hippocampal-cortico-limbic connectivity compared to healthy controls. Hippocampal volumes and measures of hippocampal volume connectivity with other cortico-limbic network regions associate with symptoms of allodynia.

Background Persistent post-traumatic headache most commonly has symptoms that overlap those of migraine. In some cases, it can be clinically difficult to differentiate persistent post-traumatic headache with a migraine phenotype from migraine. The objective of this study was to develop a classification model based on questionnaire data and structural neuroimaging data that distinguishes individuals with migraine from those with persistent post-traumatic headache. Methods Questionnaires assessing headache characteristics, sensory hypersensitivities, cognitive functioning, and mood, as well as T1-weighted magnetic resonance imaging and diffusion tensor data from 34 patients with migraine and 48 patients with persistent post-traumatic headache attributed to mild traumatic brain injury were included for analysis. The majority of patients with persistent post-traumatic headache had a migraine/probable migraine phenotype (77%). A machine-learning leave-one-out cross-validation algorithm determined the average accuracy for distinguishing individual migraine patients from individual patients with persistent post-traumatic headache. Results Based on questionnaire data alone, the average classification accuracy for determining whether an individual person had migraine or persistent post-traumatic headache was 71.9%. Adding imaging data features to the model improved the classification accuracy to 78%, including an average accuracy of 97.1% for identifying individual migraine patients and an average accuracy of 64.6% for identifying individual patients with persistent post-traumatic headache. The most important clinical features that contributed to the classification accuracy included questions related to anxiety and decision making. Cortical brain features and fibertract data from the following regions or tracts most contributed to the classification accuracy: Bilateral superior temporal, inferior parietal and posterior cingulate; right lateral occipital, uncinate, and superior longitudinal fasciculus. A post-hoc analysis showed that compared to incorrectly classified persistent post-traumatic headache patients, those who were correctly classified as having persistent post-traumatic headache had more severe physical, autonomic, anxiety and depression symptoms, were more likely to have post-traumatic stress disorder, and were more likely to have had mild traumatic brain injury attributed to blasts. Discussion A classification model that included a combination of questionnaire data and structural imaging parameters classified individual patients as having migraine versus persistent post-traumatic headache with good accuracy. The most important clinical measures that contributed to the classification accuracy included questions on mood. Regional brain structures and fibertracts that play roles in pain processing and pain integration were important brain features that contributed to the classification accuracy. The lower classification accuracy for patients with persistent post-traumatic headache compared to migraine may be related to greater heterogeneity of patients in the persistent post-traumatic headache cohort regarding their traumatic brain injury mechanisms, and physical, emotional, and cognitive symptoms.

Background and Objectives Migraine with aura (MwA) is associated with increased brain hyper‐responsiveness to visual stimuli and increased visual network connectivity relative to migraine without aura (MwoA). Despite this, prior studies have provided conflicting results regarding whether MwA is associated with higher photophobia symptom scores compared to MwoA. The relationships between MwA and other types of sensory hypersensitivity, such as phonophobia and cutaneous allodynia (CA), have not been previously investigated. The purpose of this cross‐sectional observational study was to investigate whether MwA is associated with greater symptoms of photophobia, phonophobia, and CA compared to MwoA. Methods This analysis included 321 migraine patients (146 MwA; 175 MwoA) who had been enrolled into the American Registry for Migraine Research. The diagnosis of either MwoA or MwA was determined by headache specialists using ICHD diagnostic criteria. Patients completed the Photosensitivity Assessment Questionnaire, the Hyperacusis Questionnaire, and the Allodynia Symptom Checklist. Mean or median values were compared between groups. Regression models were created to analyze the relationship between MwA with photophobia scores, hyperacusis scores, and the presence of interictal CA. Results Those with MwA had higher mean photophobia scores than those with MwoA (4.1 vs 3.0, P = .0003). MwA was positively associated with photophobia symptom severity (B = 0.50 [SE = 0.14], P = .0003), after controlling for age, patient sex, and headache frequency. Aura was not associated with hyperacusis symptom severity (B = 0.07 [SE = 0.08], P = .346) or the presence of interictal CA (OR 1.33 [95% CI 0.70‐2.53], P = .381). Conclusion MwA is associated with higher photophobia symptom scores compared to MwoA. Aura is not associated with greater hyperacusis or interictal allodynia scores. These findings complement prior imaging and neurophysiologic studies that demonstrated MwA to be associated with hyper‐responsiveness of brain visual processing regions. The findings suggest that MwA is associated specifically with visual hypersensitivity, as opposed to being associated with a general hypersensitivity to multiple types of sensory stimuli.

Objective: To evaluate the effect of migraine on women's pregnancy plans. Patients and Methods: Participants were enrolled in the American Registry for Migraine Research, an observational study that recruits patients from headache specialty clinics across the United States. Data for this analysis were collected via patient-completed questionnaires completed from February 1, 2016, through September 23, 2019. Participants were adult women with migraine who answered the American Registry for Migraine Research family planning questions. Results: Of 607 women, 19.9% (n¼121) avoided pregnancy because of migraine. Compared with women who did not avoid pregnancy, those who did were younger (37.5AE9.2 years vs 47.2AE13.3 years; P<.001), had fewer children (0.8AE1.1 vs 1.5AE1.5; P<.001), and were more likely to have chronic migraine (n¼99 [81.8%] vs n¼341 [70.2%]; P¼.012) and menstrually associated migraine (n¼5 [4.1%] vs n¼5[1.0%]; P¼.031). Women who avoided pregnancy believed that their migraine would be worse during pregnancy (n¼87[72.5%]), disability caused by migraine would make pregnancy difficult (n¼82[68.3%]), the migraine medications they take would negatively affect their child's development (n¼92[76.0%]), and migraine would cause the baby to have abnormalities at birth (n¼17[14.0%]). Conclusion: Migraine effects pregnancy plans of many women, especially of those who are younger and have menstrual migraine and chronic migraine. Women who avoid pregnancy because of migraine believe that migraine will worsen during pregnancy, make their pregnancy difficult, and have negative effects on their child. Study results highlight the importance of educating women with migraine about the relationships between migraine and pregnancy so that informed family planning decisions can be made.