Abstract
Migraine patients (Pts) show widespread structural and functional brain changes that are associated with symptoms and increased pain catastrophizing A, Migraine patients showed (i) increased gray matter volume (GMV) in the left (L) hippocampus and (ii) decreased cortical thickness in the L anterior midcingulate cortex (aMCC) compared to healthy control subjects. B, Pain catastrophizing correlated with GMV reductions in the (i) L primary somatosensory cortex (S1) and (ii) L medial prefrontal cortex (mPFC), and cortical thinning in the (iii) L dorsolateral prefrontal cortex (DLPFC) and middle temporal gyrus (MTG) in migraine patients. C, GMV reductions correlated with (i) disease duration (ii), attack frequency, and (iii) migraine pain intensity in patients. D, Whole-brain overlay maps for migraine patients and healthy controls for the (i) L PCC, (ii) L aINS, and (iii) aMCC seed regions rendered onto inflated brains. Red represents resting-state functional connectivity for healthy controls and green represents the same maps in migraine patients. Yellow represents areas showing overlap in functional connectivity in controls and migraineurs. Images are thresholded at T = 4.5 (cluster extent = 25) for visualization purposes. The schematic illustrates the relationship between disease severity measures and pain catastrophizing and disruptions in functional connectivity between the default mode network (DMN), central executive network (CEN), and salience network (SN) in migraine patients. In patients, pain catastrophizing correlated with increased coupling between DMN and CEN nodes (PCC-DLPFC), whereas disease duration and migraine pain intensity correlated with SN-DMN network decoupling (aINS/aMCC-mPFC), and increased SN-CEN (aMCC-aINS) network coupling, respectively.
To investigate the neuroanatomical and functional brain changes in migraine patients relative to healthy controls, we used a combined analytical approach including voxel- and surface-based morphometry along with resting-state functional connectivity to determine whether areas showing structural alterations in patients also showed abnormal functional connectivity. Additionally, we wanted to assess whether these structural and functional changes were associated with group differences in pain catastrophizing and migraine-related disease variables in patients. We acquired T1-weighted anatomical and functional magnetic resonance imaging scans during rest in human subjects with a diagnosis of migraine and healthy controls. Structural analyses revealed greater left hippocampal gray matter volume and reduced cortical thickness in the left anterior midcingulate in patients compared with controls. We also observed negative associations between pain catastrophizing and migraine disease variables and gray matter in areas implicated in processing the sensory, affective, and cognitive aspects of pain in patients. Functional connectivity analyses showed that migraine patients displayed disrupted connectivity between default mode, salience, cognitive, visuospatial, and sensorimotor networks, which was associated with group differences in pain catastrophizing and migraine-related disease variables in patients. Together, our findings show widespread morphological and functional brain abnormalities in migraineurs in affective, cognitive, visual, and pain-related brain areas, which are associated with increased pain catastrophizing, disease chronicity, and severity of symptoms, suggesting that these structural and functional changes may be a consequence of repeated, long-term nociceptive signaling leading to increased pain sensitivity, mood disturbances, and maladaptive coping strategies to deal with unrelenting pain.
Significance Statement
Our study provides a new and comprehensive look at how migraine affects brain structure, how these changes in structure are related to functional brain networks, and how coping and disease severity influence both structure and functional networks. Specifically, we demonstrate concomitant functional and structural brain changes related to pain catastrophizing and disease severity in migraine patients. These findings will have important implications for our understanding of altered brain circuitry associated with the development and progression of migraine and could lead to better treatment options for this patient population.
Introduction
Migraine is a debilitating pain condition associated with substantial personal and societal disability (Lipton et al., 2007). Recent neuroimaging studies have demonstrated that migraine patients show widespread functional and structural brain abnormalities relative to healthy controls, and these abnormalities have been associated with migraine-related disease variables, including disease duration and attack frequency, indicating a possible link between the observed anatomical and functional brain changes, symptom severity, and migraine disease progression (Bashir et al., 2013; Maniyar and Goadsby, 2013). Moreover, patients suffering from migraine headaches are more likely to display higher levels of anxiety and maladaptive coping strategies, scoring higher on measures of pain catastrophizing compared with migraine-free individuals, a finding that has been shown to predict impairments in daily functioning and quality of life (Lantéri-Minet et al., 2005; Holroyd et al., 2007; Pires et al., 2013).
To quantify brain structural changes, the two common approaches include voxel-based morphometry (VBM) and surface-based analysis (SBA). VBM is a voxelwise approach that provides an estimate of regional gray matter volume (GMV) (Ashburner and Friston, 2000, 2001). SBA can be used to examine differences in cortical thickness between migraineurs and healthy controls. The benefit of SBA is that it utilizes gyral and sulcal geometry to account for anatomical variability of the cortical surface and therefore provides a direct measure of cortical thickness with subvoxel precision (Fischl and Dale, 2000; Hinds et al., 2008). VBM studies have reported that migraine patients have altered cortical and subcortical GMV, including areas involved in processing the sensory-discriminative, affective, and cognitive-evaluative aspects of pain, as well as increased GMV in brainstem structures such as the periaqueductal gray (PAG) and dorsolateral pons, known to play a critical role in descending pain modulation (Rocca et al., 2006; Kim et al., 2008; Schmidt-Wilcke et al., 2008; Schmitz et al., 2008; Valfre et al., 2008). Findings from the few studies conducted using SBA are mixed, with some showing increased (Granziera et al., 2006; DaSilva et al., 2007) and others reporting decreased (Messina et al., 2013) cortical thickness in migraine, and still others finding no group differences (Datta et al., 2011). Thus, in the current study, we use both VBM and SBA approaches and test for the association of gray matter (GM) changes with clinical variables to fully characterize structural brain changes in migraine.
Resting-state functional connectivity (RS-FC) is a functional magnetic resonance imaging (fMRI) method used to detect temporal correlations in spontaneous, low-frequency oscillations across functionally related and structurally distinct brain regions in the absence of an explicit task. This technique is also well-suited for examining the functional reorganization that occurs within intrinsic brain network circuitry in pathological disease states such as migraine. A common finding in chronic pain is that the resting-state default mode network (DMN) is altered (Baliki et al., 2008), and possibly attributable to increased baseline activity of other cognitive, salience, or sensorimotor networks. Combining structural and functional neuroimaging approaches in migraineurs allows us to assess how brain structural abnormalities and disrupted intrinsic network connectivity are related.
The integration of multimodal imaging techniques to investigate morphological and functional differences in the brains of migraineurs versus healthy controls allows for complementary information to be garnered with regard to structure−function relationships and the underlying pathophysiology of migraine to be further elucidated. The current study is novel in that we employed voxel- and surface-based morphometric techniques such as VBM and SBA, with resting-state fMRI, to quantify whole-brain structural differences in cortical and subcortical pain-related brain regions in migraine patients and healthy controls and ascertain whether these structural differences also showed corresponding abnormalities in functional connectivity. Specifically, we hypothesized that patients would show reductions in GMV and cortical thickness in circuits known to be involved in processing the affective [anterior cingulate cortex, anterior insula (aINS)], sensory-discriminative [somatosensory cortices, posterior cingulate cortex (PCC)], and cognitive-evaluative aspects of pain [dorsolateral prefrontal cortex (DLPFC), anterior midcingulate (aMCC), medial prefrontal cortex (mPFC)] and that these regions would also display aberrant functional connectivity. We also hypothesized that patients would show increased GMV in regions known to be important for pain transmission and its modulation (i.e., thalamus and PAG). Furthermore, in light of previous findings demonstrating higher levels of catastrophizing in migraine, we tested the hypothesis that pain catastrophizing would be related to structural and functional abnormalities in pain-related brain areas in patients. In addition, we sought to determine whether structural and functional abnormalities in patients were linked to measures of disease duration, attack frequency, and migraine pain intensity. We expected disease duration and symptom severity measures to be correlated with structural measures and abnormal functional connectivity.
Materials and Methods
Participants
Seventeen migraine patients [13 females; mean age = 41.71 years (12.20)] and 18 healthy controls [14 females; mean age = 38.89 years (11.25)] were recruited from campuses, local headache clinics, and through community advertisements. Patients were recruited as part of a larger treatment study to determine the long-term effects of meditation training on alleviating migraine-related symptoms and the efficacy of this intervention toward ameliorating abnormalities in brain structure and function. Diagnosis of migraine was made by a physician using the International Classification of Headache Disorders-II (ICHD-II) criteria (Headache Classification Subcommittee of the International Headache Society, 2004). Inclusion criteria required that all patients had a history of recurring headaches for at least 3 months and a headache frequency greater than four headache days per month (4-15 headaches/month classified as episodic migraine; ≥15 headaches/month classified as chronic migraine). The majority of patients (14/17; 82.4%) reported taking some type of prophylactic medication to prevent migraine attacks, whereas a little over a third (6/17; 35.3%) of these patients also reported taking abortive medications (i.e., triptans). Patients were never asked to refrain from taking any medications used to treat or prevent their headaches. At the clinical visit, which occurred prior to the imaging session, patients were given a 60-item general health questionnaire (GHQ-60; Goldberg, 1978) to assess the presence of mood disorders and insomnia. Informed consent was obtained from each participant prior to commencement of study procedures according to the Declaration of Helsinki and per Institutional Review Board guidelines set forth by the Human Research Protections Office.
Behavioral and clinical measures
Each participant completed a series of self-report questionnaires including the Profile of Mood States (POMS; McNair et al., 1971), the Pain Catastrophizing Scale (PCS; Sullivan et al., 1995), the Short-Form McGill Pain Questionnaire (SFMPQ; Melzack, 1987), and the Migraine Disability Assessment Scale (MIDAS; Stewart et al., 2000). In addition, migraine disease characteristics including retrospective self-report measures of disease duration (years), attack frequency (number of migraines over the past month, six months, and year), and ratings of migraine pain intensity using a 0 to 10 numerical rating scale (NRS; 0 = no pain and 10 = worst pain imaginable) for the past 24 h, past week, and past month were determined. Patients were also asked to rate their current migraine pain intensity using the NRS immediately before and after each scan session.
MRI data acquisition
All participants underwent a single scan session consisting of a high-resolution T1-weighted MP-RAGE anatomical scan [144 slices, FOV = 230 mm, echo time (TE) = 3.44 ms, repetition time (TR) = 2500 ms, flip angle = 9.0°, resolution = 0.9 × 0.9 mm, matrix size = 256 × 256 mm, slice thickness = 1 mm, no gap] and a resting-state T2-weighted echo-planar imaging volume functional scan in which the participant was instructed to relax with eyes open (spin-echo, 194 volumes, 36 slices, FOV = 230 mm, TE = 30 ms, TR = 2500 ms, flip angle = 90°, matrix size = 128 × 128 mm, resolution = 1.8 × 1.8 mm, slice thickness = 4 mm, no gap, oblique slices). All images were acquired with a Siemens 3T Tim Trio MRI scanner equipped with a 12-channel head coil. Two 10 min functional scans (during a cognitive and pain-related task) followed by a diffusion tensor imaging scan were also acquired after the resting-state scan (data to be presented in a separate report). Total scan time was approximately 50 min.
Voxel-based morphometry
We performed VBM to determine whether patients differed from controls in regional GMV in cortical and subcortical brain regions. All data preprocessing was accomplished using the VBM8 toolbox (version r435; http://dbm.neuro.uni-jena.de/vbm/). T1-weighted structural images were first segmented into GM, white matter (WM) and CSF, and then spatially normalized to MNI space (Ashburner and Friston, 2000; Mechelli et al., 2005) with DARTEL (Ashburner, 2007). Normalized images were resampled to a voxel size of 1.5 × 1.5 × 1.5 mm3, the default resolution used in VBM8. Segmented tissue maps were modulated with Jacobian determinants using the deformation fields obtained during spatial normalization and then smoothed with an 8 mm Gaussian kernel. Whole-brain GMV was calculated for each subject and averaged across each group. An absolute threshold mask of 0.1 was specified in the analyses.
Surface-based analysis
To determine whether patients differed from controls in cortical thickness, SBA was performed. The cortical thickness measure was obtained from T1-weighted images for each participant using FreeSurfer (version 5.3; http://surfer.nmr.mgh.harvard.edu) (Dale et al., 1999; Fischl et al., 1999; Fischl and Dale, 2000). The processing pipeline consisted of affine registration of the T1-weighted volume to Talairach space, skull stripping, followed by WM segmentation and tessellation of the gray/white matter boundary. At each step, visual inspection and manual correction of topological errors was performed. Following cortical reconstruction, brains were inflated, averaged across participants, and smoothed using a 10 mm FWHM Gaussian kernel. The cortical surface was then parcellated into 34 distinct regions (Desikan−Killiany atlas) for each hemisphere from which mean cortical thickness was derived (Desikan et al., 2006). A direct measure of cortical thickness was calculated by FreeSurfer using the distance (mm) between the pial and gray−white matter boundary at each vertex.
Resting-state functional connectivity
All resting-state fMRI data were preprocessed using SPM8. Resting-state fMRI preprocessing steps included slice timing correction, motion correction, coregistration of the anatomical image to the mean functional image, segmentation of the anatomical image into GM, WM, and CSF, and normalization of anatomical and functional images to the standard MNI brain template. Normalized images were smoothed with an 8 mm isotropic FWHM Gaussian kernel. Single-subject connectivity analysis was performed with the Conn toolbox (Whitfield-Gabrieli and Nieto-Castanon, 2012). Resting-state fMRI was bandpass filtered (0.008 to 0.09 Hz), signal associated with the six motion parameters and those extracted from four WM and three CSF seed regions were removed. We performed a seed-based, voxelwise analysis using three regions of interest. All seeds were 8 mm spheres generated in the MarsBar toolbox (http://marsbar.sourceforge.net). Two of the three seed regions were created using MNI coordinates from peak voxels obtained from the VBM analysis showing significant negative correlations between GMV and migraine pain intensity (past month). These seed regions were all lateralized to the left (L) hemisphere and included the PCC (−8, −46, 27) and aINS (−36, 14, −23). In addition, we also chose the aMCC (−3, 29, 20) as a seed for the connectivity analysis based on the finding of significant group differences in cortical thickness obtained from the SBA results. We chose these seeds given our hypotheses that intrinsic connectivity within the DMN (i.e., PCC) would be altered due to enhanced engagement of the functionally competing salience network (SN) (i.e., aINS and aMCC) (Raichle et al., 2001; Seeley et al., 2007; Taylor et al., 2009; Napadow et al., 2010) resulting in migraine patients showing impaired ability to disengage attention from ongoing pain, as evidenced by higher pain catastrophizing scores compared with controls.
Statistical analysis
Behavioral analyses
One-way ANOVAs were conducted to determine whether groups differed in age, mood disturbance (POMS), pain catastrophizing (PCS), pain-related characteristics (i.e., quality and intensity), and associated disability (SFMPQ, MIDAS). In addition, Chi-square tests (χ2 statistic) were performed on frequency measures of handedness, gender, and education level. A repeated-measures ANOVA was also performed to determine if patients’ migraine pain intensity ratings differed prior to and following scanning.
Voxel-based morphometry and surface-based analyses
All voxel-based analyses were performed using SPM8. Voxelwise comparisons in GMV between groups were performed using a GLM analysis with group specified as the fixed factor, and age and mean centered total intracranial volume (calculated by summing each participant’s GM, WM, and CSF volumes) entered as nuisance variables. For the surface-based analyses, group comparisons for cortical thickness were conducted separately for each hemisphere using FreeSurfer’s Query, Design, Estimate, Contrast (QDEC) graphical interface (version 1.4). Cortical thickness analysis for the between-group comparisons was performed using a GLM model with group specified as the fixed factor and age designated as a nuisance variable. Results for each analysis were projected onto the averaged brain map using QDEC. For both the VBM and SBA analyses, we applied an initial cluster forming significance threshold of p ≤ 0.005 and a cluster extent of 100. Correction for multiple comparisons was performed using random-field-theory-based significant clusters at p < 0.05.
To assess interactions between group and pain catastrophizing for structural measures of GMV and cortical thickness, the same GLM analyses mentioned above were conducted, but with mean-centered PCS scores specified as a covariate of interest. To further examine the influence of pain catastrophizing on structural changes, the average values within each significant cluster were extracted and imported to SPSS, wherein scatterplots were generated and partial correlation analyses were conducted for each group separately, while controlling for nuisance variables.
To determine the extent to which migraine disease variables were associated with our structural measures, separate GLM analyses were performed with migraine disease characteristics (all mean centered), which included disease duration, attack frequency (past month), and migraine pain intensity (past month) identified as covariates of interest, while controlling for nuisance variables. For all analyses, we applied a cluster forming significance threshold of p ≤ 0.005 (minimum cluster extent = 100 voxels), and corrected for multiple comparisons using random-field-theory-based significant clusters at p < 0.05.
Functional connectivity analysis
Group-level analyses were performed on each seed using SPM8 to compare differences in functional connectivity in patients and controls, while controlling for age. Significance thresholds for all analyses were set to a p ≤ 0.005 (minimum initial cluster extent = 100 voxels) and cluster-level corrected for multiple comparisons. To determine if group differences in RS-FC varied depending upon the degree of pain catastrophizing, an additional GLM analysis was conducted specifying PCS scores (mean centered) as a covariate of interest. Separate GLM analyses were also performed in patients to determine if changes in RS-FC were related to migraine disease characteristics (mean centered). For these analyses, disease duration, attack frequency (past month), and migraine pain intensity (past month) were entered as covariates into the model.
Results
Behavioral and clinical measures
Descriptive and inferential statistics for group demographics and behavioral measures are presented in Table 1. No significant group differences were observed for age, gender, handedness, or education level. As expected, patients had significantly higher PCS scores than healthy controls. Patients also had significantly higher total POMS scores, indicating greater overall mood disturbance, and scored higher on the SFMPQ and MIDAS, reflecting greater pain intensity and associated headache-related disability relative to controls.
Descriptive and inferential statistics for demographic and behavioral measures in migraine patients and healthy controls
In the patient group, mean (SD) score for the GHQ-60 was 24.12 (±10.44). Patients reported an average disease duration of 12.53 (±8.41) years, and an attack frequency of 11.65 d (±10.07) over the past month, 76.12 d (±60.70) over the past 6 months, and 133.82 d (±106.11) over the past year. For migraine pain intensity, patients reported an average of 3.65 (±3.00) for the past 24 h, 4.92 (±2.33) for the past week, and 5.72 (± 2.16) for the past month. Although no patients reported having migraine headaches elicited by scanning per se, four of the 17 patients did report having a migraine headache just prior to the scan session, which lasted for the duration of the scan. Migraine pain intensity assessed just prior to scanning was 2.93 (±2.95) and 3.77 (±2.98) at the end of the scan session. A repeated-measures ANOVA revealed no significant difference between prescan and postscan migraine pain intensity ratings (F = 3.41, p = 0.086).
Group comparisons between patients and controls for structural measures
For the VBM analysis, significant group differences in regional GMV were observed for the L hippocampus with patients having greater GMV compared with controls (p = 0.011; Table 2, Fig. 1A). For the SBA analysis, migraineurs showed significant reductions in cortical thickness in the L aMCC relative to healthy controls (Table 2, Fig. 2A).
Summary of significant clusters for voxel- and surface-based morphometric group effects, group × pain catastrophizing interactions, and migraine disease characteristics
Statistical maps for the voxel-based morphometric analysis overlaid onto the averaged ch2bet brain template in MRIcron. A, Patients showed significant increased GMV in the left hippocampus, which extended into the parahippocampal gyrus, compared with controls. L, Left hemisphere; R, right hemisphere. B, Cortical areas showing significant group × pain catastrophizing interactions for GMV and corresponding scatter plots showing correlations between GMV and catastrophizing in migraine patients (orange circles) and healthy controls (blue circles). C−E, Regions showing significant reductions in GMV that correlated with longer disease durations (C), greater attack frequency (D), and migraine pain intensity in patients (E).
Statistical maps for the surface-based analysis rendered onto the inflated averaged brain template using Freesurfer’s QDEC graphical user interface software. A, Group differences in cortical thickness were found; migraine patients showed significant reductions in cortical thickness in the left aMCC compared with healthy controls. B, Cortical areas showing significant group × pain catastrophizing interactions for cortical thickness measures and corresponding scatter plots displaying correlations between cortical thickness and catastrophizing in migraine patients (orange circles) and healthy controls (blue circles). C−E, Cortical areas showing significant cortical thinning (blue) and thickening (red) in migraine patients that were associated with longer disease durations (C), greater migraine attack frequency (D), and migraine pain intensity in patients (E).
Association between structural measures and pain catastrophizing
There were significant group × catastrophizing interactions in several regions for both VBM and SBA in which patients showed negative correlations and controls showed positive correlations with pain catastrophizing. These results, as well as partial correlations for each group, are shown in Table 2. For GMV, there were significant group × catastrophizing interactions in the L primary somatosensory cortex (S1), L mPFC, and L aMCC (Fig. 1B). For cortical thickness, significant interactions were found in the L DLPFC, L middle temporal gyrus (MTG), and right (R) inferior frontal gyrus (IFG) (Fig. 2B).
Association between structural measures and migraine disease variables
For the patient group, significant relationships emerged between structural measures and migraine disease variables (Table 2). Analyses performed between VBM and SBA and disease severity measures yielded predominantly negative correlations in pain-related, affective−motivational, and visuospatial brain areas. For example, disease duration correlated negatively with GMV (Fig. 1C) for the bilateral posterior insula (pINS) and L IFG, and with cortical thickness for the bilateral DLPFC (Fig. 2C). Patients’ attack frequency scores also negatively correlated with GMV (Fig. 1D) and cortical thickness in the lingual gyrus and R S1 (Fig. 2D). Migraine pain intensity negatively correlated with GMV in the L aINS and L PCC (Fig. 1E) and cortical thickness in the L PCC, L IFG, L fusiform, R mPFC, and R lingual gyrus (Fig. 2E).
Resting-state functional connectivity analysis
Whole-brain overlay maps for each of the three seed regions are displayed in Figure 3 to show the brain networks represented in each analysis. Overall, the connectivity pattern for the PCC seed matched the DMN. The aINS and aMCC seed connectivity patterns were consistent with the SN. Statistical tests assessing group differences in connectivity patterns are described below.
Whole-brain overlay maps for patients and controls for the left PCC, left aINS, and aMCC seed regions, rendered onto inflated brains in SPM8. Teal represents RS-FC for healthy controls and purple represents the same maps in migraine patients. Light violet represents areas showing overlap in RS-FC in controls and patients. Images are thresholded at T = 4.5 (cluster extent = 25) for visualization purposes. The PCC seed showed a connectivity map consistent with the DMN, whereas the aINS and aMCC seeds connectivity patterns were consistent with the SN.
Group differences in resting-state functional connectivity
Compared with controls, patients showed increased connectivity between the aINS seed and the L cuneus and between the aMCC seed and the R lingual gyrus (Table 3, Fig. 4A). For the PCC seed, patients relative to controls showed reduced RS-FC with the bilateral DLPFC, bilateral S1, R mPFC, R PPC, R IFG, and R inferior temporal gyrus (ITG) (Table 3, Fig. 4B).
Brain regions showing significant resting-state functional connectivity patterns for the group effect, and group × pain catastrophizing interactions
Group differences in RS-FC for the aINS and aMCC seeds (SN) and PCC seed (DMN) overlaid onto the average ch2bet brain template in MRIcron. A, Patients showed significant enhancement in aINS and aMCC connectivity with the L cuneus and R lingual gyrus, respectively, and B, reduced connectivity between the PCC seed and bilateral DLPFC, S1, R PPC, R IFG, R ITG, and R mPFC. C, D, RS-FC group differences associated with pain catastrophizing for the aINS and PCC seeds. C, Patients high in catastrophizing showed enhanced RS-FC between the aINS and the L hippocampus, L SMA, and bilateral thalami. D, Significant increases in RS-FC were also identified between the PCC and the bilateral DLPFC in patients with greater pain catastrophizing scores. PAT, Patients; CTL, controls.
Relationship between pain catastrophizing and functional connectivity
Results for the group × catastrophizing interactions and partial correlations are displayed in Table 3. Partial correlation analysis revealed that in patients, catastrophizing correlated with RS-FC between the aINS seed and the L hippocampus, L SMA, and the bilateral thalamus (Fig. 4C). For the PCC seed, catastrophizing correlated with increased RS-FC with the bilateral DLPFC in patients (Fig. 4D), whereas in controls, catastrophizing negatively correlated with PCC and R DLPFC coupling, but not with the L DLPFC (Fig. 4D). Note that these DLPFC clusters were slightly more anterior and medial (deeper in the sulcus) than those identified in the above group analysis with PCC connectivity.
Relationship between migraine disease variables and functional connectivity
Results of the RS-FC analyses for the migraine-related disease variables are shown in Table 4. Disease duration positively correlated with RS-FC between the DMN-PCC seed and the R pons, whereas aINS and aMCC seeds belonging to the SN negatively correlated with DMN nodes. For attack frequency, significant negative correlations between the DMN-PCC seed and the PPC were found. For migraine pain intensity, patients had significant positive correlations between the DMN-PCC seed and nodes within the sensorimotor and visuospatial networks, including the L S1 and R secondary visual cortex (V2).
Summary of significant correlations between whole-brain resting-state functional connectivity and migraine disease characteristics
Discussion
We hypothesized that migraine patients would show concomitant structural and functional abnormalities in pain-related brain regions and that these structural−functional changes would be associated with higher levels of pain catastrophizing and measures of disease chronicity and symptom severity. Our VBM analysis showed that migraineurs had significantly larger GMV in the L hippocampus compared with controls. Results from our SBA analysis revealed significant reductions in cortical thickness in the L aMCC. Pain intensity in patients negatively correlated with GM in multiple areas, including the PCC and aINS. In addition, pain catastrophizing in patients correlated with reduced cortical GM in brain areas involved in processing the attentional, sensory, and affective aspects of pain, including the DLPFC, mPFC, IFG, MTG, and S1, with many of these same areas also showing disrupted RS-FC. The majority of these structural and functional brain abnormalities were negatively correlated with measures of disease duration, attack frequency, and migraine pain intensity, suggesting they may be a consequence of repeated, painful attacks over time.
A major finding in the present study was the significant GMV increase in the L hippocampus in migraineurs compared with controls. This finding is consistent with morphometric studies conducted in chronic pain patients, such as low-frequency migraine, chronic pelvic pain, and burning mouth syndrome (Schweinhardt et al., 2008; Maleki et al., 2013; Khan et al., 2014). The hippocampus is involved in learning and memory, decision making, regulation of the stress response, and affective processing. Although the role of the hippocampus in pain processing has received little attention until recently, previous animal studies using electrophysiological and neurohistochemical techniques provide strong support for hippocampal involvement in pain-related functions (Archer and Roth, 1997; Zheng and Khanna, 1999; Wei et al., 2000; Carter et al., 2011). Moreover, neuroimaging studies utilizing evoked pain paradigms in both healthy controls and irritable bowel syndrome (IBS) patients have demonstrated hippocampal activation in response to noxious stimuli, particularly when the stimulation is of an unpredictable nature (Ploghaus et al., 2000, 2001; Wilder-Smith et al., 2004). Although speculative, the hippocampal GMV increase in patients observed here may be indicative of activity-dependent neuroplastic changes resulting from chronic nociceptive signaling originating from trigeminal sensory afferents. Thus, neuroplastic changes, including neurogenesis, unmasking of silent synapses, morphological restructuring of synaptic connections, and/or dendritic arborization, may be related to LTP-like processes occurring within hippocampal neuronal ensembles, a mechanism by which memory for pain may be encoded (Bruel-Jungerman et al., 2006; Sandkuhler, 2007).
Our SBA analysis revealed significant cortical thinning in the L aMCC in patients compared with controls. The aMCC is involved in processing the affective−motivational dimensions of pain, as well as pain-related anticipatory, attentional, and cognitive inhibitory control functions (Shackman et al., 2011). Although previous VBM studies have reported GMV reductions in the aMCC and adjacent areas within the rostral cingulate in both migraineurs and chronic tension headache patients (Schmidt-Wilcke et al., 2005, 2008; Rocca et al., 2006; Kim et al., 2008), only one study has identified cortical volume differences in this region using SBA (Maleki et al., 2012) and no study has reported differences in cortical thickness. Our SBA results demonstrating reduced cortical thickness in the aMCC indicate that migraineurs show significant structural abnormalities in an area involved in processing the affective−motivational aspects of pain.
According to the attentional model, pain catastrophizing reflects a propensity to attend to painful events or experiences, whether real or imagined. This inability to shift attentional focus away from pain, in turn, leads to increased pain perception and sensitivity (Crombez et al., 1998; Sullivan et al., 2001; Goubert et al., 2004; Van Damme et al., 2004). To our knowledge, no study to date has examined the association between pain catastrophizing and structural GM abnormalities in migraine patients. Here, we show a strong association between catastrophizing and gray matter reductions in S1, mPFC, DLPFC, MTG, and IFG. These findings are in accord with functional and morphometric studies showing a strong relationship between catastrophizing and abnormalities in similar regions in IBS and fibromyalgia patients (Gracely et al., 2004; Blankstein et al., 2010). Taken together, our findings indicate that higher levels of catastrophizing in patients are linked with GM reductions in areas critically involved in the sensory-discriminative aspects, as well as the top-down, cognitive inhibitory control of pain. We suggest that these cortical alterations may lead to increased pain transmission and an inability to efficiently disengage attention from pain in migraine patients, which would account for some of the cognitive impairments reported in the literature (Martins de Araujo et al., 2012).
We found significant relationships between structural GM changes in areas involved in pain processing, cognitive inhibitory control, and visuospatial functions and migraine disease variables. GMV in the bilateral pINS and cortical thickness in the bilateral DLPFC correlated with longer disease duration, consistent with previous findings in migraine and chronic tension type headache (Schmidt-Wilcke et al., 2005; Rocca et al., 2006; Kim et al., 2008; Schmitz et al., 2008; Valfre et al., 2008). Attack frequency was associated with greater GMV and cortical thickness in regions within the frontal, parietal, and occipital-temporal regions. Many of these regions serve in processing attention and pain modulation, as well as processing visual information. We also observed strong associations between migraine pain intensity and lower GM in many of the same areas showing morphological abnormalities related to disease duration and attack frequency (i.e., PCC, IFG, lingual gyrus, and S1). Collectively, the observed structural abnormalities in pain-related and visuospatial brain areas may underlie the pathophysiology of migraine symptoms (e.g., blurred vision, sensitivity to light, visual disturbances) and, therefore, may serve as important indicators of disease severity.
Recent studies employing RS-FC have provided evidence of anatomically segregated and functionally dissociable intrinsic brain networks. These networks include the well known DMN and the central executive network (CEN), among others (Raichle et al., 2001; Seeley et al., 2007; Buckner et al., 2008; Spreng et al., 2009). It has recently been proposed that these spatially segregated networks play a critical role in internally and externally guided cognition, respectively. The DMN is said to be active during rest and has been termed a “task negative network”, since it shows reliable deactivation during cognitively demanding tasks (Buckner et al., 2008; Spreng et al., 2013). Conversely, the CEN, which is thought to play an important role in executive functions, guiding externally driven goal-directed attentional focus and cognition, is referred to as a “task positive network”, since it is primarily activated during tasks requiring allocation of attentional resources and higher-order cognition (Seeley et al., 2007; Dosenbach et al., 2008). This network includes, but is not limited to, areas such as the DLPFC and PPC. A third network, known as the SN, which includes core nodes aMCC and bilateral aINS, may be involved in modulating the activity within these two networks by regulating the switching between internal or externally generated cognitive demands of the functionally competing DMN and CEN networks, depending upon the saliency ascribed (Seeley et al., 2007; Taylor et al., 2009; Sridharan et al., 2008; Goulden et al., 2014). Thus, SN coupling with DMN may promote internally guided mentation by guarding against disruptive or competing stimuli arising from external sources and simultaneously dampening the CEN. Similarly, decoupling of the DMN with the SN may promote functional engagement with the CEN and facilitate the shifting of focus toward salient external events that demand immediate attention.
To examine how structural brain changes were related to functional connectivity changes in patients, we used areas identified in the structural analyses as seed regions in our RS-FC analyses, with a focus on DMN and SN, since those networks have been most reliably shown to have altered connectivity in chronic pain conditions. Overall, patients showed disrupted DMN and SN connectivity patterns compared with healthy controls. Specifically, patients had reduced RS-FC within the DMN (L PCC seed with IFG, ITG, and mPFC) and increased RS-FC of the SN to extrastriate visual areas. Patients also showed decreased connectivity between the DMN and regions of the CEN (bilateral DLPFC, PPC), as well as a somatosensory network (bilateral S1). These findings strongly indicate atypical connectivity patterns in patients associated with vigilance to visual stimuli and engagement of cognitive and somatosensory networks at baseline, which may reflect a general hypervigilance or enhanced attentional focus toward salient events, such as ongoing pain, as well as sensitivity to visual stimuli, which are common triggers for migraine headaches.
Patients also showed altered RS-FC associated with pain catastrophizing and migraine disease characteristics. Patients with high catastrophizing showed greater disruptions in DMN connectivity, namely increased correlation between the PCC-DMN node and the CEN (i.e., bilateral DLPFC). Additionally, in patients, pain catastrophizing correlated with RS-FC between SN nodes to the hippocampus, posterior thalamus, and the bilateral precuneus (nodes of the DMN). These findings provide further support for the notion that migraine patients display enhanced brain activation in cognitive-control inhibitory networks and areas mediating affect-related responses to salient events, likely a result from hypervigilance to their pain, reflected by higher catastrophizing, at the expense of the DMN functioning at rest. Furthermore, disease duration was associated with SN and DMN (mPFC, MTG, and SFG) decoupling. Likewise, attack frequency was also associated with decreased SN-DMN and increased SN-hippocampus connectivity, whereas pain intensity was associated with enhanced coupling between SN-CEN nodes (V2, PPC, and aINS). Overall, these findings indicate patients have disrupted RS-FC associated with higher levels of pain catastrophizing and symptom severity, which may reflect impairments in the ability to disengage attention from pain, central pain amplification, and symptom chronification. Future studies will determine whether interventions that reduce pain catastrophizing and symptom severity can reverse some of these aberrant connectivity patterns.
Some limitations should be considered when interpreting the results of the current study. First, our sample of migraine patients was heterogeneous. Although all patients reported a high frequency of attacks (≥8 headache days/month), four patients reported fewer than 15 headache days per month, which would make them episodic rather than chronic migraine sufferers according to ICHD-II criteria. A second limitation was that we did not control for medication use and the majority of patients in this study were taking prophylactic and/or abortive medications to control their symptoms. For ethical reasons, we did not ask patients to refrain from their typical medication usage patterns and therefore the effect of medication on the present study findings cannot be determined. Third, a potential drawback of RS-FC is that this technique provides no information with regard to the direction or strength of connectivity and thus, interpretation of results obtained using this approach is limited (Buckner et al., 2013). Fourth, our sample of migraine patients was relatively small. Further work is needed in a larger sample of migraine patients to generalize the current findings to a broader clinical population. Finally, the present study was cross-sectional, and therefore we are unable to address whether the morphological and functional brain abnormalities observed here were a cause or an effect of repeated migraine attacks over time. Future studies employing a longitudinal design are needed to address these questions.
Conclusion
The integration of multimodal techniques represent a promising approach that may lead to a better understanding of the etiological factors underlying migraine pathophysiology. In the present study, we provide evidence that migraine patients have concurrent structural and functional abnormalities in default mode, salience, visuospatial, cognitive control, and pain-related brain networks, which were associated with disease-related symptomology and the degree of pain catastrophizing. Altered structure and functional connectivity of areas critically involved in processing salient events and subserving cognitive inhibitory control functions may reflect neuroplastic brain changes that lead to the impaired ability to self-regulate and disengage attention away from pain, which over time might further reinforce maladaptive behaviors and coping strategies in these patients. Whether the observed functional abnormalities in connectivity result from structural changes that are causal or a consequence of repeated migraine attacks, and how these structural changes are related to altered brain functioning, remains unclear. Future work is needed to determine the extent to which certain interventions are capable of reversing these structural−functional alterations and the impact treatment has on ameliorating migraine-related symptoms.
Acknowledgments
This research was supported by NIH NCCAM 5R01AT007176 (to D.A.S.), K23 1KL2RR025006-01 (to M.G.), Society of General Internal Medicine Founders Award (to M.G.), and generous funds provided by the Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore, MD (to D.A.S.).
Footnotes
↵2 We thank the University of Maryland Magnetic Resonance Research Center, Dr. Rao Gullapalli and George Makris for their assistance with data collection. We would also like to express our gratitude to all the participants who took part in this study. The authors declare no competing financial interests.
This is an open-access article distributed under the terms of the Creative Commons Attribution License Attribution-Noncommercial 4.0 International which permits noncommercial reuse provided that the original work is properly attributed.
References
Author Response Letter:
Editorial Comments:
Synthesis of Reviews: The authors investigated patients with migraine and healthy controls to determine whether there are difference in brain structure and/or brain function and how they are related to the disease. Authors concluded that these structural and functional changes may be a consequence of repeated, long-term nociceptive signaling leading to increased pain sensitivity, mood disturbances, and maladaptive coping strategies to deal with unrelenting pain. Overall the manuscript is well written and the methods were correctly applied. The reviewers are, however, concerned that the authors apply a variety of methods, i.e. VBM, CT and resting state fMRI) that produced a large number of results (group comparisons, correlation, interactions, etc.) reported as a list of statistical tests and results more so than a coherent story. The authors should go a deeper concerning the interpretation of their data, perhaps reducing the number of imaging methods/results reported to draw a picture that is clearer to the reader. For example, the authors should offer an interpretations why VBM changes are associated with changes in functional connectivity. How much do the CT findings really add to the manuscript (in addition to the VBM findings)? Response: We thank the Editor and Reviewers for the favorable response to our manuscript. In the current revision, we have reduced the number of analyses/results by removing the surface-based measure of cortical volume from the manuscript, figures, and tables. We have also removed Figure 4E from the resting state connectivity results. In addition to the requested revisions, we have consolidated the results and the discussion sections and feel this has improved our manuscript significantly.
Specific concerns and comments by the two reviewers:
Reviewer 1
Comment 1: Abstract - Line 8: Explain the abbreviation MRI.
Response: The abbreviation “MRI” is now defined in full within the abstract.
Comment 2:
Abstract - Line 13/14: To be more comprehensive, please write: “We also observed negative associations between pain catastrophizing and migraine disease variables and gray matter in areas implicated in processing the sensory, affective, and cognitive aspects of pain in patients”.
Response: We thank the reviewer for the suggestion and have revised lines 13-15 as specified above.
Comment 3: Introduction - Page 4, line 76: Add the abbreviation “GM” after “gray matter”.
Response: The abbreviation “(GM)” has been added to pg. 4, line 76, of the manuscript.
Comment 4:
Materials and methods - Why Authors studied only patients with a quite high frequency of migraine attacks?
Response: Given that the present report was part of a larger treatment study investigating the effects of Vipassana meditation on migraine (data presented herein represents the baseline time point, prior to any treatment), we aimed to recruit patients who reported more headache days than headache free days in order to adequately assess the effect of this intervention on migraine related symptoms and functional/structural brain and behavioral changes.
Comment 5:
Materials and methods - Why cortical surface area abnormalities were not assessed? Together with cortical thickness and cortical volume evaluation, the cortical surface area assessment would provide additional information.
Response: We initially felt that cortical thickness and cortical volume would be sufficient to assess whether groups differed in surface-based measurements across the entire cortical mantle. However, upon further consideration we realize that since cortical volume is derived from thickness that the latter measure was somewhat redundant. Moreover, given the comment by the Editor and the desire to streamline the paper we have decided to remove the cortical surface volume data from the paper in its entirety. We agree with the Reviewer that a surface area measurement would have been an interesting addition to the paper. When we ran the group analysis for surface area, we found only one marginally significant cluster in left posterior parietal/occipital cortex. Because the paper is already dense with analyses, however, we have chosen not to report these findings. Nevertheless, if the Reviewer finds it essential to do so, we would be willing to add it.
Comment 6:
Materials and methods - Page 7, line 158: Write only the abbreviation “GM”. Response: On pg. 7, line 162, the term “gray matter” has now been removed.
Comment 7:
Materials and methods - Page 9, line 188: To be more comprehensive, please write: “Resting-state fMRI was bandpass filtered (0.008 to 0.09 Hz), signal associated with the six motion parameters and those extracted from four WM and three CSF seed regions were removed.”
Response: We have revised pg. 9, lines 194-195, as suggested by the Reviewer.
Comment 8:
Materials and methods - Page 9, line 208: “X2 statistic” should be written after “Chi-square tests”.
Response: On pg. 10, line 215, “χ2 statistic” has been moved to immediately follow “Chi-square tests”.
Comment 9:
Results - Since all patients had more than 4 attacks per month, probably most of them take preventive therapies. Authors should clarify this issue.
Response: To clarify, we have added the following sentence to pg. 6, lines 123-126, of the methods section:
“The majority of patients (14/17; 82.4%) reported taking some type of prophylactic medication to prevent migraine attacks, whereas a little over a third (6/17; 35.3%) of these patients also reported taking abortive medications (i.e., triptans). Patients were never asked to refrain from taking any medications used to treat or prevent their headaches.”
Comment 10:
Results - Were MRI scans acquired while patients had migraine attack? Authors should clarify this issue.
Response: No patients reported that the scan itself evoked a migraine headache. However, four out of 17 patients did report having a migraine headache just prior to scanning. Nevertheless, migraine pain intensity scores were not statistically different for pre- versus post-scan ratings, indicating that pain intensity associated with migraine headaches was similar across patients prior to and following scanning regardless of whether or not they had reported having a migraine. For clarification, the following statement was added to the results section on pg. 12, lines 274-276:
“Although no patients reported having migraine headaches elicited by scanning per se, four of the 17 patients did report having a migraine headache just prior to the scan session which lasted for the duration of the scan.”
Comment 11:
Results - The section where Authors described brain regions that had a significant association between structural/functional abnormalities and pain catastrophizing and disease variables in patients is quite dispersive and unclear. Authors should revised these sections. They may report synthetically the main findings and referred to tables and figures to list all brain regions. Moreover, they should highlight whether some of the regions that differed significantly between patients and controls were correlated with paitents’pain catastrophizing or disease variables.
Response: We agree with the Reviewer's concerns and have revised the Results section accordingly. Specifically, we have cut down these paragraphs substantially and refer to Table 2 for details.
Comment 12:
Results - RS analysis (page 14): Authors described qualitative group differences in RS FC, however this part is quite unnecessary.
Response: We agree with the Reviewer and have deleted parts of the paragraph that discuss qualitative group differences in RS-FC on pg. 15, lines 326-335.
Comment 13:
Discussion - Page 18, line 410: Write “patients’ migraine disease variables” instead of “our migraine disease variables”.
Response: We thank the Reviewer for pointing out this error and have corrected the text as suggested (pg. 20, line 450).
Comment 14:
Discussion - Page 19, line 427: Use only the abbreviation “DMN” and “CEN”.
Response: The terms “dorsal mode network” and “central executive network” have been replaced with the acronyms “DMN” and “CEN”, respectively, on pg. 21, line 468.
Comment 15:
Discussion - Page 20, line 439: Use only the abbreviation “SN”.
Response: The term “salience network” has now been replaced with the abbreviation “SN” on pg. 21, line 480.
Comment 16:
Discussion - Page 22: Authors should discuss structural abnormalities (both VBM and SBA results) at the same time, reporting the discussion concerning hippocampal volume abnormalities before the discussion about SBA results.
Response: We thank the Reviewer for the suggestion and have moved the paragraph discussing the VBM group differences in hippocampal volume to appear just prior to the section discussing the SBA results.
Comment 17:
Discussion - The discussion concerning the association between structural and functional abnormalities and pain catastrophizing and disease variables is quite rambling and unclear. Authors should revised this part.
Response: These sections have been revised to remove any extraneous or unnecessary information to provide a clearer and more concise discussion of the findings and their implications.
Comment 18:
Discussion - In addition, Authors should discuss which are the differences between VBM and SBA analysis, why they decided to use both of them to assess cortical volume abnormalities and why this two techniques revealed different results.
Response: Please see our response to the Editor's comment regarding this issue, as well as our reply in response to comment #5 given by the Reviewer.
Comment 19: Figure 1. A) please, specify left and right side. B) Authors should report whether images are referred to patients or controls.
Response: Abbreviations for left (L) and right (R) were added to Figure 1A and the corresponding figure legend was revised to reflect the change to the figure. In addition, we have corrected the color coding to depict the reduction in GMV in patients versus controls for the group x pain catastrophizing interaction in Figure 1B.
Comment 20:
Figure 2. A) In the text and in table 2 Authors reported reduced cortical thickness and volume of the aMCC and fusiform gyrus, however according to the colour-code they seemed to be increased. Please correct it. B) Authors should report whether images are referred to patients or controls.
Response: We thank the Reviewer for pointing out this discrepancy and have revised Figure 2A to show the significant decrease, represented by blue-green voxels, for cortical thickness in the aMCC in migraine patients. We have also corrected the color coding in Figure 2B to clarify that this figure is referring to reduced cortical thickness in patients compared to controls.
Comment 21:
Figure 4. Why Authors did not report also group differences in RS FC for the aMCC seed? B) In the text and in table 3 Authors reported reduced RS-FC for the PCC seed, however according to the colour-code it seemed that there is an increased RS-FC. Please correct it.
Response: For consistency we have added the results displaying group differences in RS-FC for the aMCC seed to Figure 4A. In Figure 4B, we have corrected the color coding to depict the decreased RS-FC in patients versus controls for the PCC seed. In addition, the x coordinate for the right PPC and IFG clusters was corrected due to a typographical error, from a negative value to a positive value, and then adjusted slightly (from x = 40 to x = 35) to better illustrate the cluster extent of voxels in the PPC. The intensity bar was also re-oriented and values were adjusted to reflect threshold changes for the new images.
Reviewer 2 Comment 1:
Line 129 Were any of the migraineurs scanned within a migraine attack; if all were scanned outside a migraine attack, was there minimum temporal margine between last headache attack and day of scanning. Response: Please see above for our response to this same concern raised by Reviewer 1 (Comment #10).
Comment 2:
Line 159 What was the resampled voxelsize? Response: The resampled voxel size was 1.5 x 1.5 x 1.5 which is the default for VBM8. This information has now been added to the methods section on pg. 7, lines 164-165 as follows:
“Normalized images were resampled to a voxel size of 1.5 x 1.5 x 1.5 mm3, the default resolution used in VBM8.”
Comment 3:
Line 162 Did the authors apply a threshold, e.g. 0.1 or 0.2, to include only voxels with a certain gray matter intensity? Response: Yes, the Reviewer is correct. Thank you for making us aware of this omission. We used an absolute masking threshold of 0.1. The following statement has been added to pg. 8, lines 168-169, of the methods section:
“An absolute threshold mask of 0.1 was specified in the analyses.”
Comment 4:
Line 200 In this framework the following article should be cited: Intrinsic brain connectivity in fibromyalgia is associated with chronic pain intensity. Napadow V, LaCount L, Park K, As-Sanie S, Clauw DJ, Harris RE. Arthritis Rheum. 2010 Aug;62(8):2545-55. doi: 10.1002/art.27497. Response: We thank the Reviewer for this helpful suggestion and have cited the aforementioned article on pg. 9, line 207, and have added the corresponding reference to the reference section.
Comment 5:
Lines 223 - 226 Please specify how the correction for multiple comparisons was performed. It reads now, as if first a voxel based threshold of p < 0.005 was applied and clusters with > 100 contiguous voxels survived FEW correction (on the cluster level). With VBM that is normally not the case that clusters consisting of 100 voxels (< 0.005) survive FWE correction. Or was this second thresholding step performed after initial cluster formation? Please comment.
Response: We agree with the Reviewer that the phrasing for our procedure for thresholding and correction for multiple comparisons was slightly misleading. To clarify, we have revised the text as follows (pg. 10, lines 230-234):
“For both the VBM and SBA analyses, we applied an initial cluster forming significance threshold of p < 0.005 and a cluster extent of 100. Correction for multiple comparisons was performed using random field theory based significant clusters at p < 0.05.”
Comment 6:
Line 413 Which of the four citations refers to chronic tension type headache? Response: The citation referring to the study conducted with chronic tension type headache patients was missing. We have added the appropriate citation by Schmidt-Wilke et al., 2005 to the text. The reference for this citation was already contained within the reference section.
Comment 7:
Line 393 Indeed, recent evidence from functional neuroimaging studies in both patients with chronic pain (Gracely et al., 2004) and healthy, pain-free individuals (Seminowicz and Davis, 2006) support this contention. In this sentence it does not really become clear what the imaging studies added to the concept of catasptrohizing. Response: We agree that this sentence adds nothing toward supporting the concept of catastrophizing discussed in the previous sentence and therefore, have removed it from the manuscript.
Comment 8:
Line 500 The authors should add a limitation section; sample seize, draw backs of functional connectivity, etc..
Response: In accord with the Reviewer's request, we have added the following paragraph to the discussion section stating the limitations of this study.
“Some limitations should be considered when interpreting the results of the current study. First, our sample of migraine patients was heterogeneous. Although all patients reported a high frequency of attacks (≥ 8 headache days/month), four patients reported fewer than 15 headache days per month, which would make them episodic rather than chronic migraine sufferers according to ICHD-II criteria. A second limitation was that we did not control for medication use and the majority of patients in this study were taking prophylactic and/or abortive medications to control their symptoms. For ethical reasons, we did not ask patients to refrain from their typical medication usage patterns and therefore the effect of medication on the present study findings cannot be determined. Third, a potential drawback of RS-FC is that this technique provides no information with regard to the direction or strength of connectivity and thus, interpretation of results obtained using this approach is limited (Buckner et al., 2013). Fourth, our sample of migraine patients was relatively small. Further work is needed in a larger sample of migraine patients to generalize the current findings to a broader clinical population. Finally, the present study was cross-sectional, and therefore we are unable to address whether the morphological and functional brain abnormalities observed here were a cause or an effect of repeated migraine attacks over time. Future studies employing a longitudinal design are needed to address these questions.”
Additional Changes
In addition to the changes proposed by Reviewers 1 and 2, the following revisions to the manuscript, Figures, and Tables were made:
1) Per the request of the Editor and guidelines set forth by eNeuro we have revised the abstract (lines 9-10) to now contain the species name. The sentence has been revised and now reads as follows: “We acquired T1-weighted anatomical and functional magnetic resonance imaging (MRI) scans during rest in human subjects with a diagnosis of migraine and healthy controls”
2) On pg. 4, lines 78-79, the term “fMRI” was spelled out in full followed by the abbreviation since this was the first appearance of this term in the body of the manuscript.
3) On pg. 5, lines 96-97, “cortical volume” was replaced with “GMV”.
4) On pg. 6, line 121, “(4 > 15)” was changed to “(4 – 14)” for clarity.
5) On pg. 1, line 8, the phrase “in our migraine patient group” was changed to “in migraine patients”.
6) On pg. 8, lines 167-168, the sentence “Whole-brain GMV was calculated and averaged across each group” was revised for accuracy to “Whole-brain GMV was calculated for each subject and averaged across each group”.
7) On pg. 9, lines 202 and 203, “our” was changed to “the”.
8) On pg. 20, line 442, the citation Seminowicz et al., 2010 was incorrect and removed from the manuscript and reference section. The correct citation “Blankstein et al., 2010” was replaced within the text and the reference was added to the reference section.
9) On pg. 20, line 454, “Kim et al., 2008b” citation was corrected to “Kim et al., 2008”.
10) On pg. 21, line 484, the citation “Goulden N, 2010” was corrected for typographical errors to “Goulden et al., 2010”.
11) In Table 2, negative signs for the t-values were added for the correlational analyses conducted between GMV and migraine disease severity measures.
12) STG abbreviation was removed from Table 2 since it was no longer applicable.
13) In Table 4, the +/-corr was defined in the abbreviation list and the ordering of the abbreviations were correctly alphabetized.
14) In Figure 4, the headings were slightly modified to reflect changes requested by Reviewer 1. In addition, Figure 4E was removed as previously stated in the response to the Editor's comment.
In this issue
