Abnormal functional integration across core brain networks in migraine without aura

Chronic pain as an emergent property of a complex system and the potential roles of psychedelic therapies

Despite research advances and urgent calls by national and global health organizations, clinical outcomes for millions of people suffering with chronic pain remain poor. We suggest bringing the lens of complexity science to this problem, conceptualizing chronic pain as an emergent property of a complex biopsychosocial system. We frame pain-related physiology, neuroscience, developmental psychology, learning, and epigenetics as components and mini-systems that interact together and with changing socioenvironmental conditions, as an overarching complex system that gives rise to the emergent phenomenon of chronic pain. We postulate that the behavior of complex systems may help to explain persistence of chronic pain despite current treatments. From this perspective, chronic pain may benefit from therapies that can be both disruptive and adaptive at higher orders within the complex system. We explore psychedelic-assisted therapies and how these may overlap with and complement mindfulness-based approaches to this end. Both mindfulness and psychedelic therapies have been shown to have transdiagnostic value, due in part to disruptive effects on rigid cognitive, emotional, and behavioral patterns as well their ability to promote neuroplasticity. Psychedelic therapies may hold unique promise for the management of chronic pain.

Aberrant brain functional hubs and causal effective connectivity in menstrually-related and non-menstrually-related migraine without aura

Background

Menstrual migraine without aura (MRM) is common in female migraineurs and is closely related to cerebral functional abnormalities. However, whether the whole brain networks and directional functional connectivity of MRM patients are altered remains unclear. The purpose of this study was to detect the alterations of resting-state functional networks and directional functional connectivity between MRM and non-menstrual migraine without aura (NMM) patients using functional magnetic resonance imaging (fMRI) with degree centrality (DC) and Granger causality analysis (GCA) methods.

Methods

In this retrospective and cross-sectional study, 45 MRM and 40 NMM patients (matched in age, gender, and years of education) were recruited in the study between May 2018 and June 2022. All participants had undergone resting-state fMRI scanning at the Neurology and Pain Outpatient Department of Nanjing First Hospital. Their brain functions were analyzed in terms of DC and GCA, with the significant threshold at voxel level P<0.01 and cluster level P<0.05, Gaussian random field corrected. Correlation analysis was adopted to assess the relationships between the fMRI results and clinical features (P<0.05, Bonferroni corrected).

Results

Compared with those in the NMM group, MRM patients showed decreased DC in the right insula (T=-4.253). Using the right insula as the seed region, patients with MRM demonstrated enhanced effective connectivity from the right insula to the ipsilateral middle temporal gyrus (T=4.138) and contralateral superior temporal gyrus (T=3.523). Furthermore, the MRM group also showed decreased effective connectivity from several brain regions to the right insula, which included the right inferior occipital gyrus (T=-4.498), left middle frontal gyrus (T=-4.879), right precuneus (T=-4.644), and left inferior parietal gyrus (T=-4.113). The average Self-rating Anxiety Scale score of the MRM group was significantly higher than that of the NMM group [P=0.032, 95% confidence interval (CI): 0.363-7.761]. In the MRM group, disease duration was negatively correlated with the mean value of DC in right insula (r=-0.428, P=0.01).

Conclusions

The present research demonstrated that patients with MRM have disruption in insula resting-state functional networks. Disrupted networks contained regions associated with cognitive processes, emotional perception, and migraine attack in MRM patients. These results may improve our comprehension of the neuromechanism of menstrually-related migraine.

Arterial Spin Labeling in Migraine: A Review of Migraine Categories and Mimics

Migraine is a complex headache characterized by changes in functional connectivity and cerebral perfusion. The perfusion changes represent a valuable domain for targeted drug therapy. Arterial spin labeling is a noncontrast imaging technique of quantifying cerebral perfusion changes in the migraine setting. In this narrative review, we will discuss the pathophysiology of the different categories of migraine, as defined by the International Classification of Headache Disorders-3 and describe a category-based approach to delineating perfusion changes in migraine on arterial spin labeling images. We will also discuss the use of arterial spin labeling to differentiate migraine from stroke and/or seizures in the adult and pediatric populations. Our systematic approach will help improve the understanding of the complicated vascular changes that occur during migraines and identify potential areas of future research.

A state-of-the-art review of functional magnetic resonance imaging technique integrated with advanced statistical modeling and machine learning for primary headache diagnosis

Primary headache is a very common and burdensome functional headache worldwide, which can be classified as migraine, tension-type headache (TTH), trigeminal autonomic cephalalgia (TAC), and other primary headaches. Managing and treating these different categories require distinct approaches, and accurate diagnosis is crucial. Functional magnetic resonance imaging (fMRI) has become a research hotspot to explore primary headache. By examining the interrelationships between activated brain regions and improving temporal and spatial resolution, fMRI can distinguish between primary headaches and their subtypes. Currently the most commonly used is the cortical brain mapping technique, which is based on blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI). This review sheds light on the state-of-the-art advancements in data analysis based on fMRI technology for primary headaches along with their subtypes. It encompasses not only the conventional analysis methodologies employed to unravel pathophysiological mechanisms, but also deep-learning approaches that integrate these techniques with advanced statistical modeling and machine learning. The aim is to highlight cutting-edge fMRI technologies and provide new insights into the diagnosis of primary headaches.

Functional magnetic resonance imaging in migraine: A systematic review

BACKGROUND

Migraine is a highly prevalent primary headache disorder. Despite a high burden of disease, key disease mechanisms are not entirely understood. Functional magnetic resonance imaging is an imaging method using the blood-oxygen-level-dependent signal, which has been increasingly used in migraine research over recent years. This systematic review summarizes recent findings employing functional magnetic resonance imaging for the investigation of migraine.

METHODS

We conducted a systematic search and selection of functional magnetic resonance imaging applications in migraine from April 2014 to December 2021 (PubMed and references of identified articles according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines). Methodological details and main findings were extracted and synthesized.

RESULTS

Out of 224 articles identified, 114 were included after selection. Repeatedly emerging structures of interest included the insula, brainstem, limbic system, hypothalamus, thalamus, and functional networks. Assessment of functional brain changes in response to treatment is emerging, and machine learning has been used to investigate potential functional magnetic resonance imaging-based markers of migraine.

CONCLUSIONS

A wide variety of functional magnetic resonance imaging-based metrics were found altered across the brain for heterogeneous migraine cohorts, partially correlating with clinical parameters and supporting the concept to conceive migraine as a brain state. However, a majority of findings from previous studies have not been replicated, and studies varied considerably regarding image acquisition and analyses techniques. Thus, while functional magnetic resonance imaging appears to have the potential to advance our understanding of migraine pathophysiology, replication of findings in large representative datasets and precise, standardized reporting of clinical data would likely benefit the field and further increase the value of observations.

Altered static functional network connectivity predicts the efficacy of non-steroidal anti-inflammatory drugs in migraineurs without aura

Brain networks have significant implications for the understanding of migraine pathophysiology and prognosis. This study aimed to investigate whether large-scale network dysfunction in patients with migraine without aura (MwoA) could predict the efficacy of non-steroidal anti-inflammatory drugs (NSAIDs). Seventy patients with episodic MwoA and 33 healthy controls (HCs) were recruited. Patients were divided into MwoA with effective NSAIDs (M-eNSAIDs) and with ineffective NSAIDs (M-ieNSAIDs). Group-level independent component analysis and functional network connectivity (FNC) analysis were used to extract intrinsic networks and detect dysfunction among these networks. The clinical characteristics and FNC abnormalities were considered as features, and a support vector machine (SVM) model with fivefold cross-validation was applied to distinguish the subjects at an individual level. Dysfunctional connections within seven networks were observed, including default mode network (DMN), executive control network (ECN), salience network (SN), sensorimotor network (SMN), dorsal attention network (DAN), visual network (VN), and auditory network (AN). Compared with M-ieNSAIDs and HCs, patients with M-eNSAIDs displayed reduced DMN-VN and SMN-VN, and enhanced VN-AN connections. Moreover, patients with M-eNSAIDs showed increased FNC patterns within ECN, DAN, and SN, relative to HCs. Higher ECN-SN connections than HCs were revealed in patients with M-ieNSAIDs. The SVM model demonstrated that the area under the curve, sensitivity, and specificity were 0.93, 0.88, and 0.89, respectively. The widespread FNC impairment existing in the modulation of medical treatment suggested FNC disruption as a biomarker for advancing the understanding of neurophysiological mechanisms and improving the decision-making of therapeutic strategy.

Top-down threat bias in pain perception is predicted by intrinsic structural and functional connections of the brain

Top-down processes such as expectations play a key role in pain perception. In specific contexts, inferred threat of impending pain can affect perceived pain more than the noxious intensity. This biasing effect of top-down threats can affect some individuals more strongly than others due to differences in fear of pain. The specific characteristics of intrinsic brain characteristics that mediate the effects of top-down threat bias are mainly unknown. In this study, we examined whether threat bias is associated with structural and functional brain connectivity. The variability in the top-down bias was mapped to the microstructure of white matter in diffusion weighted images (DWI) using MRTrix3. Mean functional connectivity of five canonical resting state networks was tested for association with bias scores and with the identified DWI metrics. We found that the fiber density of the splenium of the corpus callosum was significantly low in individuals with high top-down threat bias (FWE corrected with 5000 permutations, p < 0.05). The mean functional connectivity within the language/memory and between language/memory and default mode networks predicted the bias scores. Functional connectivity within language memory networks predicted the splenium fiber density, higher pain catastrophizing and lower mindful awareness. Probabilistic tractography showed that the identified region in the splenium connected several sensory regions and high-order parietal regions between the two hemispheres, indicating the splenium's role in sensory integration. These findings demonstrate that individuals who show more change in pain with changes in the threat of receiving a stronger noxious stimulus have lower structural connectivity in the pathway necessary for integrating top-down cue information with bottom-up sensory information. Conversely, systems involved in memory recall, semantic and self-referential processing are more strongly connected in people with top-down threat bias.

Insular functional connectivity in migraine with aura

Introduction

Insula plays an integrating role in sensory, affective, emotional, cognitive and autonomic functions in migraine, especially in migraine with aura (MA). Insula is functionally divided into 3 subregions, the dorsoanterior, the ventroanterior and the posterior insula respectively related to cognition, emotion, and somatosensory functions. This study aimed at investigating functional connectivity of insula subregions in MA.

Methods

Twenty-one interictal patients with MA were compared to 18 healthy controls (HC) and 12 interictal patients with migraine without aura (MO) and were scanned with functional MRI during the resting state. Functional coupling of the insula was comprehensively tested with 12 seeds located in the right and left, dorsal, middle, ventral, anterior and posterior insula, by using a seed-to-voxel analysis.

Results

Seed-to-voxel analysis revealed, in MA, a strong functional coupling of the right and left antero-dorsal insula with clusters located in the upper cerebellum. The overlap of these cerebellar clusters corresponded to the vermis VI. These functional couplings were not correlated to duration of MA, frequency of MA attacks nor time since last MA attack, and were not found in MO.

Discussion

The anterior insula and superior cerebellum, including vermis VI, are components of the central Autonomic Nervous System (ANS) network. As these regions are involved in the control of cardiovascular parasympathetic tone, we hypothesize that this connectivity may reflect the cardiovascular features of MA.

Conclusion

The anterior dorsal insula is connected with vermis VI in MA patients in the resting state. This connectivity may reflect the cardiovascular features of MA.

Trial registration

NCT02708797.

Predicting response to tVNS in patients with migraine using functional MRI: A voxels-based machine learning analysis

Background

Migraine is a common disorder, affecting many patients. However, for one thing, lacking objective biomarkers, misdiagnosis, and missed diagnosis happen occasionally. For another, though transcutaneous vagus nerve stimulation (tVNS) could alleviate migraine symptoms, the individual difference of tVNS efficacy in migraineurs hamper the clinical application of tVNS. Therefore, it is necessary to identify biomarkers to discriminate migraineurs as well as select patients suitable for tVNS treatment.

Methods

A total of 70 patients diagnosed with migraine without aura (MWoA) and 70 matched healthy controls were recruited to complete fMRI scanning. In study 1, the fractional amplitude of low-frequency fluctuation (fALFF) of each voxel was calculated, and the differences between healthy controls and MWoA were compared. Meaningful voxels were extracted as features for discriminating model construction by a support vector machine. The performance of the discriminating model was assessed by accuracy, sensitivity, and specificity. In addition, a mask of these significant brain regions was generated for further analysis. Then, in study 2, 33 of the 70 patients with MWoA in study 1 receiving real tVNS were included to construct the predicting model in the generated mask. Discriminative features of the discriminating model in study 1 were used to predict the reduction of attack frequency after a 4-week tVNS treatment by support vector regression. A correlation coefficient between predicted value and actual value of the reduction of migraine attack frequency was conducted in 33 patients to assess the performance of predicting model after tVNS treatment. We vislized the distribution of the predictive voxels as well as investigated the association between fALFF change (post-per treatment) of predict weight brain regions and clinical outcomes (frequency of migraine attack) in the real group.

Results

A biomarker containing 3,650 features was identified with an accuracy of 79.3%, sensitivity of 78.6%, and specificity of 80.0% (p &lt; 0.002). The discriminative features were found in the trigeminal cervical complex/rostral ventromedial medulla (TCC/RVM), thalamus, medial prefrontal cortex (mPFC), and temporal gyrus. Then, 70 of 3,650 discriminative features were identified to predict the reduction of attack frequency after tVNS treatment with a correlation coefficient of 0.36 (p = 0.03). The 70 predictive features were involved in TCC/RVM, mPFC, temporal gyrus, middle cingulate cortex (MCC), and insula. The reduction of migraine attack frequency had a positive correlation with right TCC/RVM (r = 0.433, p = 0.021), left MCC (r = 0.451, p = 0.016), and bilateral mPFC (r = 0.416, p = 0.028), and negative with left insula (r = −0.473, p = 0.011) and right superior temporal gyrus/middle temporal gyrus (r = −0.684, p &lt; 0.001), respectively.

Conclusions

By machine learning, the study proposed two potential biomarkers that could discriminate patients with MWoA and predict the efficacy of tVNS in reducing migraine attack frequency. The pivotal features were mainly located in the TCC/RVM, thalamus, mPFC, and temporal gyrus.

Alterations in Functional and Structural Connectivity of Basal Ganglia Network in Patients with Obesity

Obesity is related to overconsumption of high-calorie (HiCal) food, which is modulated by brain reward and inhibitory control circuitries. The basal ganglia (BG) are a key set of nuclei within the reward circuitry, but obesity-associated functional and structural abnormalities of BG have not been well studied. Resting-state functional MRI with independent component analysis (ICA) and probabilistic tractography were employed to investigate differences in BG-related functional-(FC) and structural connectivity (SC) between 32 patients with obesity (OB) and 35 normal-weight (NW) participants. Compared to NW, OB showed significantly lower FC strength in the caudate nucleus within the BG network, and seed-based FC analysis showed lower FC between caudate and dorsolateral prefrontal cortex (DLPFC), which was negatively correlated with craving for HiCal food cues. Further SC analysis revealed that OB showed lower SC than NW between left caudate and left DLPFC as measured with fractional anisotropy (FA). Alterations in FC and SC between caudate and DLPFC in obese patients, which highlights the role of BG network in modulating the balance between reward and inhibitory-control.

Abnormalities in resting-state EEG microstates are a vulnerability marker of migraine

Background

Resting-state EEG microstates are thought to reflect brief activations of several interacting components of resting-state brain networks. Surprisingly, we still know little about the role of these microstates in migraine. In the present study, we attempted to address this issue by examining EEG microstates in patients with migraine without aura (MwoA) during the interictal period and comparing them with those of a group of healthy controls (HC).

Methods

Resting-state EEG was recorded in 61 MwoA patients (50 females) and 66 HC (50 females). Microstate parameters were compared between the two groups. We computed four widely identified canonical microstate classes A-D.

Results

Microstate classes B and D displayed higher time coverage and occurrence in the MwoA patient group than in the HC group, while microstate class C exhibited significantly lower time coverage and occurrence in the MwoA patient group. Meanwhile, the mean duration of microstate class C was significantly shorter in the MwoA patient group than in the HC group. Moreover, among the MwoA patient group, the duration of microstate class C correlated negatively with clinical measures of headache-related disability as assessed by the six-item Headache Impact Test (HIT-6). Finally, microstate syntax analysis showed significant differences in transition probabilities between the two groups, primarily involving microstate classes B, C, and D.

Conclusions

By exploring EEG microstate characteristics at baseline we were able to explore the neurobiological mechanisms underlying altered cortical excitability and aberrant sensory, affective, and cognitive processing, thus deepening our understanding of migraine pathophysiology.

Pain and the Triple Network Model

Acute pain is a physiological response that causes an unpleasant sensory and emotional experience in the presence of actual or potential tissue injury. Anatomically and symptomatically, chronic pathological pain can be divided into three distinct but interconnected pathways, a lateral “painfulness” pathway, a medial “suffering” pathway and a descending pain inhibitory circuit. Pain (fullness) can exist without suffering and suffering can exist without pain (fullness). The triple network model is offering a generic unifying framework that may be used to understand a variety of neuropsychiatric illnesses. It claims that brain disorders are caused by aberrant interactions within and between three cardinal brain networks: the self-representational default mode network, the behavioral relevance encoding salience network and the goal oriented central executive network. A painful stimulus usually leads to a negative cognitive, emotional, and autonomic response, phenomenologically expressed as pain related suffering, processed by the medial pathway. This anatomically overlaps with the salience network, which encodes behavioral relevance of the painful stimuli and the central sympathetic control network. When pain lasts longer than the healing time and becomes chronic, the pain- associated somatosensory cortex activity may become functionally connected to the self-representational default mode network, i.e., it becomes an intrinsic part of the self-percept. This is most likely an evolutionary adaptation to save energy, by separating pain from sympathetic energy-consuming action. By interacting with the frontoparietal central executive network, this can eventually lead to functional impairment. In conclusion, the three well-known pain pathways can be combined into the triple network model explaining the whole range of pain related co-morbidities. This paves the path for the creation of new customized and personalized treatment methods.

The anatomy of pain and suffering in the brain and its clinical implications

Pain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage. Chronic pain, with a prevalence of 20-30 % is the major cause of human suffering worldwide, because effective, specific and safe therapies have yet to be developed. It is unevenly distributed among sexes, with women experiencing more pain and suffering. Chronic pain can be anatomically and phenomenologically dissected into three separable but interacting pathways, a lateral 'painfulness' pathway, a medial 'suffering' pathway and a descending pain inhibitory pathway. One may have pain(fullness) without suffering and suffering without pain(fullness). Pain sensation leads to suffering via a cognitive, emotional and autonomic processing, and is expressed as anger, fear, frustration, anxiety and depression. The medial pathway overlaps with the salience and stress networks, explaining that behavioural relevance or meaning determines the suffering associated with painfulness. Genetic and epigenetic influences trigger chronic neuroinflammatory changes which are involved in transitioning from acute to chronic pain. Based on the concept of the Bayesian brain, pain (and suffering) can be regarded as the consequence of an imbalance between the two ascending and the descending pain inhibitory pathways under control of the reward system. The therapeutic clinical implications of this simple pain model are obvious. After categorizing the working mechanisms of each of the available treatments (pain killers, psychopharmacology, psychotherapy, neuromodulation, psychosurgery, spinal cord stimulation) to 1 or more of the 3 pathways, a rational combination can be proposed of activating the descending pain inhibitory pathway in combination with inhibition of the medial and lateral pathway, so as to rebalance the pain (and suffering) pathways.

Altered thalamo-cortical functional connectivity in patients with vestibular migraine: a resting-state fMRI study

PURPOSE

To explore the functional connectivity (FC) between the bilateral thalamus and the other brain regions in patients with vestibular migraine (VM).

METHODS

Resting-state fMRI and 3D-T1 data were collected from 37 patients with VM during the interictal period and 44 age-, gender-, and years of education-matched healthy controls (HC). The FC of the bilateral thalamus was analyzed using a standard seed-based whole-brain correlation method. Furthermore, the correlations between thalamus FC and clinical characteristics of patients were investigated using Pearson's partial correlation.

RESULTS

Compared with HC, VM patients showed decreased FC between the left thalamus and the left anterior cingulate cortex (ACC), bilateral insular and right supplementary motor cortex. We also observed decreased FC between the right thalamus and the left insular and ACC in VM patients. Furthermore, patients with VM also exhibited increased FC between the left thalamus and the right precuneus and middle frontal gyrus, between the right thalamus and superior parietal lobule. FC between the right thalamus and the left insular was negatively correlated with disease duration (p = 0.019, r =  - 0.399), FC between the left thalamus and the left ACC was negatively correlated with HIT-6 score (p = 0.004, r =  - 0.484).

CONCLUSION

VM patients showed altered FC between thalamus and brain regions involved in pain, vestibular and visual processing, which are associated with specific clinical features. Specifically, VM patients showed reduced thalamo-pain and thallamo-vestibular pathways, while exhibited enhanced thalamo-visual pathway, which provided first insight into the underlying functional brain connectivity in VM patients.

Neuroprotection of sevoflurane against ischemia/reperfusion-induced brain injury through inhibiting GluN2A/GluN2B-PSD-95-MLK3 module

To investigate the role of GluN2A and GluN2B in neuroprotective effect of sevoflurane preconditioning against cerebral ischemia-reperfusion injury (CIRI). Rats were randomly divided into five groups as follows: control, ischemia-reperfusion (I/R) 6 h, sevoflurane preconditioning (SP), SP + amantadine, SP + NMDA. Immunoblot and immunoprecipitation were used to detect the tyrosine phosphorylation of GluN2A/GluN2B, the interaction of GluN2A/GluN2B-PSD-95-MLK3 and the expression of phosphorylation of MLK3, MKK7 and JNK3. Cresyl violet staining was employed to analyse neuronal injury in rat hippocampal CA1 subfields. Sevoflurane preconditioning inhibits the tyrosine phosphorylation of GluN2A/GluN2B, the interaction of GluN2A/GluN2B-PSD-95-MLK3 and the phosphorylation of MLK3, MKK7 and JNK3 in rat hippocampus. An N-methyl-D-aspartate receptor (NMDAR) antagonist amantadine reversed the MLK3-MKK7- JNK3 signal events. Such reversion was also realized by NMDA (60 and 80 nmol) and low doses of NMDA (0-40 nmol) could not change the inhibitory effect of sevoflurane preconditioning on MLK3-MKK7-JNK3 signal events. Finally, Cresyl violet staining also confirmed that low dose of NMDA reduced neuronal loss in rat hippocampal CA1 subfields. Sevoflurane preconditioning provides neuroprotection against CIRI by inhibiting NMDAR over-activation.

Temporal instability of salience network activity in migraine with aura

This study aims to investigate whether intranetwork dynamic functional connectivity and causal interactions of the salience network is altered in the interictal term of migraine. Thirty-two healthy controls, 37 migraineurs without aura, and 20 migraineurs with aura were recruited. Participants underwent a T1-weighted scan and resting-state fMRI protocol inside a 1.5T MR scanner. We obtained average spatial maps of resting-state networks using group independent component analysis, which yielded subject-specific time series through a dual regression approach. Salience network regions of interest (bilateral insulae and prefrontal cortices, dorsal anterior cingulate cortex) were obtained from the group average map through cluster-based thresholding. To describe intranetwork connectivity, average and dynamic conditional correlation was calculated. Causal interactions between the default-mode, dorsal attention, and salience network were characterised by spectral Granger's causality. Time-averaged correlation was lower between the right insula and prefrontal cortex in migraine without aura vs with aura and healthy controls (P < 0.038, P < 0.037). Variance of dynamic conditional correlation was higher in migraine with aura vs healthy controls and migraine with aura vs without aura between the right insula and dorsal anterior cingulate cortex (P < 0.011, P < 0.026), and in migraine with aura vs healthy controls between the dorsal anterior cingulate and left prefrontal cortex (P < 0.021). Causality was weaker in the <0.05 Hz frequency range between the salience and dorsal attention networks in migraine with aura (P < 0.032). Overall, migraineurs with aura exhibit more fluctuating connections in the salience network, which also affect network interactions, and could be connected to altered cortical excitability and increased sensory gain.

Aberrant activity within auditory network is associated with psychiatric comorbidities in interictal migraineurs without aura

The present study aimed to explore associations between brain activity in the auditory cortex and clinical and psychiatric characteristics in patients with migraine without aura (MwoA) during interictal periods. Resting-state data were acquired from patients with episodic MwoA (n = 34) and healthy controls (n = 30). Independent component analysis was used to extract and calculate the resting-state auditory network. Subsequently, we analyzed the correlations between spontaneous activity in the auditory cortex and clinical and psychiatric features in interictal MwoA. Compared with healthy controls, patients with MwoA showed increased activity in the left superior temporal gyrus (STG), postcentral gyrus (PoCG) and insula. Brain activity in the left STG was positively correlated with anxiety scores, and activity in the left PoCG was negatively correlated with anxiety and depression scores. No significant differences were found in intracranial volume between the two groups. This study indicated that functional impairment and altered integration linked to the auditory cortex existed in patients with MwoA in the interictal period, suggesting that auditory-associated cortex disruption as a biomarker may be implemented for the early diagnosis and prediction of neuropsychiatric impairment in interictal MwoA patients.

Functional Alterations in the Posterior Insula and Cerebellum in Migraine Without Aura: A Resting-State MRI Study

Background: Hypothesis-driven functional connectivity (FC) analyses have revealed abnormal functional interaction of regions or networks involved in pain processing in episodic migraine patients. We aimed to investigate the resting-state FC patterns in episodic migraine by combining data-driven voxel-wise degree centrality (DC) calculation and seed-based FC analysis.

Methods: Thirty-nine patients suffering from episodic migraine without aura and 35 healthy controls underwent clinical assessment and functional MRI. DC was analyzed voxel-wise and compared between groups, and FC of regions with DC differences were further examined using a seed-based approach.

Results: Compared with the control group, the migraine group showed increased and decreased DC in the right posterior insula and left crus I, respectively. Seed-based FC analyses revealed that migraine patients demonstrated increased right posterior insula connections with the postcentral gyrus, supplementary motor area/paracentral lobule, fusiform gyrus and temporal pole. The left crus I showed decreased FC with regions of the default mode network (DMN), including the medial prefrontal cortex (mPFC), angular gyrus, medial and lateral temporal cortex in patients with migraine. Furthermore, pain intensity positively correlated with DC in the right amygdala/parahippocampal gyrus, and migraine frequency negatively correlated with FC between the left crus I and mPFC.

Conclusion: Patients with episodic migraine without aura have increased FC with the right posterior insula and decreased FC within the DMN, which may underlie disturbed sensory integration and cognitive processing of pain. The left crus I-mPFC connectivity may be a useful biomarker for assessing migraine frequency.

Haemodynamic activity characterization of resting state networks by fractal analysis and thalamocortical morphofunctional integrity in chronic migraine

BACKGROUND

Chronic migraine (CM) can be associated with aberrant long-range connectivity of MRI-derived resting-state networks (RSNs). Here, we investigated how the fractal dimension (FD) of blood oxygenation level dependent (BOLD) activity may be used to estimate the complexity of RSNs, reflecting flexibility and/or efficiency in information processing in CM patients respect to healthy controls (HC).

METHODS

Resting-state MRI data were collected from 20 untreated CM without history of medication overuse and 20 HC. On both groups, we estimated the Higuchi's FD. On the same subjects, fractional anisotropy (FA) and mean diffusivity (MD) values of bilateral thalami were retrieved from diffusion tensor imaging and correlated with the FD values.

RESULTS

CM showed higher FD values within dorsal attention system (DAS) and the anterior part of default-mode network (DMN), and lower FD values within the posterior DMN compared to HC. Although FA and MD were within the range of normality, both correlated with the FD values of DAS.

CONCLUSIONS

FD of DAS and DMN may reflect disruption of cognitive control of pain in CM. Since the normal microstructure of the thalamus and its positive connectivity with the cortical networking found in our CM patients reminds similar results obtained assessing the same structures but with the methods of neurophysiology, in episodic migraine during an attack, this may be yet another evidence in supporting CM as a never-ending migraine attack.

Altered resting-state functional connectivity between subregions in the thalamus and cortex in migraine without aura

BACKGROUND AND PURPOSE

Migraine is a complex and disabling neurological disorder, the exact neurological mechanisms of which remain unclear. The thalamus is considered to be the hub of the central processing and integration of nociceptive information, as well as the modulation of these processes.

METHODS

A total of 48 migraineurs without aura (MWoAs) during the interictal phase and 48 age- and sex-matched healthy controls underwent resting-state functional magnetic resonance imaging scans. We utilized masked independent component analysis and seed-based functional connectivity (FC) to investigate whether MWoAs exhibited abnormal FC between subregions in the thalamus and the cortex regions.

RESULTS

The MWoAs showed significantly weaker FC between the anterior dorsal thalamic nucleus and left precuneus. Additionally, MWoAs exhibited significantly reduced FC between the ventral posterior nucleus (VPN) and left precuneus, right inferior parietal lobule (R-IPL) and right middle frontal gyrus. Furthermore, the FC Z-scores between the VPN and R-IPL were negatively correlated with pain intensity in MWoAs. The disease duration of patients was negatively correlated with the FC Z-scores between the VPN and R-IPL.

CONCLUSION

These altered thalamocortical connectivity patterns may contribute to multisensory integration abnormalities, deficits in pain attention, cognitive evaluation and pain modulation. Pain sensitivity and disease duration are closely tied to abnormal FC between the VPN and R-IPL. Remarkably, recurrent headache attacks might contribute to this maladaptive functional plasticity closely related to pain intensity.

Quantitative electroencephalogram analysis of frontal cortex functional changes in patients with migraine

The functional abnormality of brain areas accounting for the migraine remains to be elucidated. Most related studies have used functional magnetic resonance imaging to investigate brain areas involved in migraine. However, the results are heterogeneous. In this study, we used a convenient tool to explore the brain regions involved in migraine. In this study, 40 children with migraine and 40 sex- and age-matched health controls were enrolled, and electroencephalogram was used to explore the functional abnormal areas of migraine through electroencephalogram bands and low-resolution electromagnetic tomography analysis. The results revealed that spectrum edge frequency 50 in all electroencephalogram channels in patients with migraine were lower than those in controls. Significant differences were discovered over frontal areas. In addition, significantly higher current density over the frontopolar prefrontal cortex and orbitofrontal cortex and higher connectivity over the left prefrontal cortex were observed in patients with migraine. We suggest that functional disturbance of the prefrontal cortex may play a potential role in children with migraine, and that low-resolution electromagnetic tomography is a reliable and convenient tool for studying the functional disturbance of migraine.

Altered Interactions Among Resting-State Networks in Individuals with Obesity

OBJECTIVE

The aim of this study was to investigate alterations in functional connectivity (FC) within and interactions between resting-state networks involved in salience, executive control, and interoception in participants with obesity (OB).

METHODS

Using resting-state functional magnetic resonance imaging with independent component analysis and FC, alterations within and interactions between resting-state networks in 35 OB and 35 normal-weight controls (NW) were investigated.

RESULTS

Compared with NW, OB showed reduced FC strength in the ventromedial prefrontal cortex and posterior cingulate cortex/precuneus within the default-mode network, dorsal anterior cingulate cortex within the salience network (SN), bilateral dorsolateral prefrontal cortex-angular gyrus within the frontoparietal network (FPN), and increased FC strength in the insula (INS) (P_{familywise error}  < 0.0125). The dorsal anterior cingulate cortex FC strength was negatively correlated with craving for food cues, left dorsolateral prefrontal cortex FC strength was negatively correlated with Yale Food Addiction Scale scores, and right INS FC strength was positively correlated with craving for high-calorie food cues. Compared with NW, OB also showed increased FC between the SN and FPN driven by altered FC of bilateral INS and anterior cingulate cortex-angular gyrus.

CONCLUSIONS

Alterations in FC within and interactions between the SN, default-mode network, and FPN might contribute to the high incentive value of food (craving), lack of control of overeating (compulsive overeating), and increased awareness of hunger (impaired interoception) in OB.

Impaired intrinsic functional connectivity between the thalamus and visual cortex in migraine without aura

BACKGROUND

Resting-state functional magnetic resonance imaging (fMRI) has confirmed disrupted visual network connectivity in migraine without aura (MwoA). The thalamus plays a pivotal role in a number of pain conditions, including migraine. However, the significance of altered thalamo-visual functional connectivity (FC) in migraine remains unknown. The goal of this study was to explore thalamo-visual FC integrity in patients with MwoA and investigate its clinical significance.

METHODS

Resting-state fMRI data were acquired from 33 patients with MwoA and 22 well-matched healthy controls. After identifying the visual network by independent component analysis, we compared neural activation in the visual network and thalamo-visual FC and assessed whether these changes were linked to clinical characteristics. We used voxel-based morphometry to determine whether functional differences were dependent on structural differences.

RESULTS

The visual network exhibited significant differences in regions (bilateral cunei, right lingual gyrus and left calcarine sulcus) by inter-group comparison. The patients with MwoA showed significantly increased FC between the left thalami and bilateral cunei and between the right thalamus and the contralateral calcarine sulcus and right cuneus. Furthermore, the neural activation of the left calcarine sulcus was positively correlated with visual analogue scale scores (r = 0.319, p = 0.043), and enhanced FC between the left thalamus and right cuneus in migraine patients was negatively correlated with Generalized Anxiety Disorder scores (r = - 0.617, p = 0.005).

CONCLUSION

Our data suggest that migraine distress is exacerbated by aberrant feedback projections to the visual network, playing a crucial role in migraine physiological mechanisms. The current study provides further insights into the complex scenario of migraine mechanisms.

Large-Scale Granger Causal Brain Network based on Resting-State fMRI data

The causal connections among small-scale regions based on resting-state fMRI data have been extensively studied and a lot of achievements have been demonstrated. However, the causal connection among large-scale regions was seldom discussed. In this paper, we applied global Granger causality analysis to construct the causal connections in the whole-brain network among 103 healthy subjects (33 M/66F, ages 20-23) based on a resting-state fMRI dataset. We further explored four large-scale cognitive networks which have been widely known: central executive network (CEN), default mode network (DMN), dorsal attention network (DAN) and salience network (SN). These four cognitive networks are particularly important for understanding higher cognitive functions and dysfunction. Based on the above research, Out-In degree were introduced to identify the driving and driven hubs. Studying the driving and driven hub of brain network is of great significance for assessing the functional mechanism of the brain network. There were 817 directed edges identified as significant among the 8010 possible causal connections; seven driving hubs and ten driven hubs were identified in the whole-brain network. In CEN, dorsolateral prefrontal cortex (DlPFC) and superior parietal cortex (SPC) were the driven and driving hubs, respectively; in DMN, they were posterior cingulate cortex (PCC) and medial prefrontal cortex (MPFC); in DAN, they were frontal eye fields (FEF) and intraparietal sulcus (IPS); and in SN, they were frontoinsular cortex (FIC) and medial frontal cortex (MFC). These findings may provide insights into our understanding of human brain function mechanisms and the diagnosis of brain diseases.

Functional connectivity studies in migraine: what have we learned?

BACKGROUND

Resting-state functional connectivity (FC) MRI has widely been used to understand migraine pathophysiology and to identify an imaging marker of the disorder. Here, we review what we have learned from FC studies.

METHODS

We performed a literature search on the PubMed website for original articles reporting data obtained from conventional resting-state FC recording in migraine patients compared with healthy controls or during and outside of migraine attacks in the same patients.

RESULTS

We found 219 articles and included 28 in this review after screening for inclusion and exclusion criteria. Twenty-five studies compared migraine patients with healthy controls, whereas three studies investigated migraine patients during and outside of attacks. In the studies of interictal migraine more alterations of more than 20 FC networks (including amygdala, caudate nucleus, central executive, cerebellum, cuneus, dorsal attention network, default mode, executive control, fronto-parietal, hypothalamus, insula, neostriatum, nucleus accumbens, occipital lobe, periaqueductal grey, prefrontal cortex, salience, somatosensory cortex I, thalamus and visual) were reported. We found a poor level of reproducibility and no migraine specific pattern across these studies.

CONCLUSION

Based on the findings in the present review, it seems very difficult to extract knowledge of migraine pathophysiology or to identify a biomarker of migraine. There is an unmet need of guidelines for resting-state FC studies in migraine, which promote the use of homogenous terminology, public availability of protocol and the a priori hypothesis in line with for instance randomized clinical trial guidelines.

Structural and Functional Reorganization of the Brain in Migraine Without Aura

It remains unknown whether migraine headache has a progressive component in its pathophysiology. Quantitative MRI may provide valuable insight into abnormal changes in the migraine interictum and assist in identifying disrupted brain networks. We carried out a data-driven study of structural integrity and functional connectivity of the resting brain in migraine without aura. MRI scanning was performed in 36 patients suffering from episodic migraine without aura and 33 age-matched healthy subjects. Voxel-wise analysis of regional brain volume was performed by registration of the T1-weighted MRI scans into a common study brain template using the tensor-based morphometry (TBM) method. Changes in functional synchronicity of the brain networks were assessed using probabilistic independent component analysis (ICA). TBM revealed that migraine is associated with reduced volume of the medial prefrontal cortex (mPFC). Among 375 functional brain networks, resting-state connectivity was decreased between two components spanning the visual cortex, posterior insula, and parietal somatosensory cortex. Our study reveals structural and functional alterations of the brain in the migraine interictum that may stem from underlying disease risk factors and the "silent" aura phenomenon. Longitudinal studies will be needed to investigate whether interictal brain changes are progressive and associated with clinical disease trajectories.