Aberrant modulations of static functional connectivity and dynamic functional network connectivity in chronic migraine

Association between brain resting-state functional activities and migraine: a bidirectional mendelian randomization study

Researchers have conducted extensive research on the correlation between brain resting-state functional activities (RSFA) and migraine. However, we still do not fully understand the exact nature of the causal relationship between these RSFA and migraine. We conducted a bidirectional two-sample Mendelian randomization (MR) study to investigate the causal association between migraine and RSFA. We gathered summary statistics from genome-wide association studies for 191 resting-state functional magnetic resonance imaging phenotypes. We employed various analytical methods for bidirectional two-sample MR analyses. This included inverse variance weighted, weighted median, MR Egger, and the constrained maximum likelihood approaches. We also conducted pleiotropy and heterogeneity analyses to evaluate the robustness and reliability. We found the functional connectivity between the default mode and the central executive network (OR = 1.39, p = 4.77 × 10-4, FDR corrected p value = 0.040) and the intensity of spontaneous brain activity in the calcarine or lingual gyrus within the visual network (OR = 0.74, p = 5.94 × 10-4, FDR corrected p value = 0.040) having a causal effect on the risk of migraine. Our MR analysis provided genetic support for these networks, which may play an important role in influencing migraine susceptibility.

Multimodal transformer graph convolution attention isomorphism network (MTCGAIN): a novel deep network for detection of insomnia disorder

Background

In clinic, the subjectivity of diagnosing insomnia disorder (ID) often leads to misdiagnosis or missed diagnosis, as ID may have the same symptoms as those of other health problems.

Methods

A novel deep network, the multimodal transformer graph convolution attention isomorphism network (MTGCAIN) is proposed in this study. In this network, graph convolution attention (GCA) is first employed to extract the graph features of brain connectivity and achieve good spatial interpretability. Second, the MTGCAIN comprehensively utilizes multiple brain network atlases and a multimodal transformer (MT) to facilitate coded information exchange between the atlases. In this way, MTGCAIN can be used to more effectively identify biomarkers and arrive at accurate diagnoses.

Results

The experimental results demonstrated that more accurate and objective diagnosis of ID can be achieved using the MTGCAIN. According to fivefold cross-validation, the accuracy reached 81.29% and the area under the receiver operating characteristic curve (AUC) reached 0.8760. A total of nine brain regions were detected as abnormal, namely right supplementary motor area (SMA.R), right temporal pole: superior temporal gyrus (TPOsup.R), left temporal pole: superior temporal gyrus (TPOsup.L), right superior frontal gyrus, dorsolateral (SFGdor.R), right middle temporal gyrus (MTG.R), left middle temporal gyrus (MTG.L), right inferior temporal gyrus (ITG.R), right median cingulate and paracingulate gyri (DCG.R), left median cingulate and paracingulate gyri (DCG.L).

Conclusions

The brain regions in the default mode network (DMN) of patients with ID show significant impairment (occupies four-ninths). In addition, the functional connectivity (FC) between the right middle occipital gyrus and inferior temporal gyrus (ITG) has an obvious correlation with comorbid anxiety (P=0.008) and depression (P=0.005) among patients with ID.

Altered static and dynamic functional brain network in knee osteoarthritis: A resting-state functional magnetic resonance imaging study: Static and dynamic FNC in KOA

This study aimed to investigate altered static and dynamic functional network connectivity (FNC) and its correlation with clinical symptoms in patients with knee osteoarthritis (KOA). One hundred and fifty-nine patients with KOA and 73 age- and gender-matched healthy subjects (HS) underwent resting-state functional magnetic resonance imaging (rs-fMRI) and clinical evaluations. Group independent component analysis (GICA) was applied, and seven resting-state networks were identified. Patients with KOA had decreased static FNC within the default mode network (DM), visual network (VS), and cerebellar network (CB) and increased static FNC between the subcortical network (SC) and VS (p < 0.05, FDR corrected). Four reoccurring FNC states were identified using k-means clustering analysis. Although abnormalities in dynamic FNCs of KOA patients have been found using the common window size (22 TR, 44 s), but the results of the clustering analysis were inconsistent when using different window sizes, suggesting dynamic FNCs might be an unstable method to compare brain function between KOA patients and HS. These recent findings illustrate that patients with KOA have a wide range of abnormalities in the static and dynamic FNCs, which provided a reference for the identification of potential central nervous therapeutic targets for KOA treatment and might shed light on the other musculoskeletal pain neuroimaging studies.

Integration of temporal & spatial properties of dynamic functional connectivity based on two-directional two-dimensional principal component analysis for disease analysis

Dynamic functional connectivity, derived from resting-state functional magnetic resonance imaging (rs-fMRI), has emerged as a crucial instrument for investigating and supporting the diagnosis of neurological disorders. However, prevalent features of dynamic functional connectivity predominantly capture either temporal or spatial properties, such as mean and global efficiency, neglecting the significant information embedded in the fusion of spatial and temporal attributes. In addition, dynamic functional connectivity suffers from the problem of temporal mismatch, i.e., the functional connectivity of different subjects at the same time point cannot be matched. To address these problems, this article introduces a novel feature extraction framework grounded in two-directional two-dimensional principal component analysis. This framework is designed to extract features that integrate both spatial and temporal properties of dynamic functional connectivity. Additionally, we propose to use Fourier transform to extract temporal-invariance properties contained in dynamic functional connectivity. Experimental findings underscore the superior performance of features extracted by this framework in classification experiments compared to features capturing individual properties.

Inflammation, brain connectivity, and neuromodulation in post-traumatic headache

Post-traumatic headache (PTH) is a debilitating condition that affects individuals with different levels of traumatic brain injury (TBI) severity. The difficulties in developing an effective treatment are related to a lack of understanding the complicated mechanisms and neurobiological changes in brain function after a brain injury. Preclinical studies have indicated that peripheral and central sensitization of the trigeminal nociceptive pathways contributes to PTH. While recent brain imaging studies have uncovered widespread changes in brain functional connectivity following trauma, understanding exactly how these networks contribute to PTH after injury remains unknown. Stimulation of peripheral (trigeminal or vagus) nerves show promising efficacies in PTH experimental animals, likely mediated by influencing TBI-induced pathological plasticity by decreasing neuroinflammation and neuronal apoptosis. Non-invasive brain stimulations, such as transcranial magnetic or direct current stimulations, show analgesia for multiple chronic pain conditions, including PTH. Better mechanistic understanding of analgesia achieved by neuromodulations can define peripheral and central mechanisms involved in the development, the resolution, and the management of PTH.

Hippocampal volume and resting-state functional connectivity on magnetic resonance imaging in patients with Parkinson and depression

Background

Recent structural and functional imaging studies of depression in Parkinson disease (DPD) have failed to reveal the relevant mechanism, and relatively few studies have been conducted on limbic systems such as the hippocampus. This study thus aimed to gain new insights into the pathogenesis of DPD by detecting the changes in the hippocampal structure and the resting-state functional connectivity (FC) of patients with DPD.

Methods

This study included 30 patients with DPD (DPD group), 30 patients with nondepressed Parkinson disease (NDPD; NDPD group), and 30 normal controls (NCs; NC group) with no significant age or gender differences with the DPD group. The Hamilton Depression Rating Scale (HAMD) and three-dimensional T1-weighted imaging and blood oxygen level-dependent imaging data of all patients were collected. The hippocampal volumes were measured using MATLAB software (MathWorks). The correlation between hippocampal volume and the HAMD score in the DPD group was analyzed with Pearson correlation coefficient. The bilateral hippocampi were used as the regions of interest and as the seed points for FC. FC analysis was performed between the preprocessed functional data of the whole brain and the two seed points with Data Processing Assistant for Resting-State and Statistical Parametric Mapping 8 software, respectively. The correlation between FC and HAMD scores in the patients with DPD was determined using partial correlation analysis.

Results

Compared with those in the NC group and the NDPD group, the bilateral hippocampal volumes in the DPD group were significantly decreased (P<0.05). There was a negative correlation between the bilateral hippocampal volume and the HAMD score in the DPD group (P<0.05). Compared with that of the NDPD group, the FC of the right hippocampus with the right occipital lobe and left precuneus was reduced in the DPD group. In the DPD group, the FC values of the right hippocampus, right occipital lobe, and left anterior cuneiform lobe were negatively correlated with HAMD scores.

Conclusions

The volume of bilateral hippocampi in patients with DPD is significantly decreased and negatively correlated with the severity of depressive disorder. The weakened FC of the right hippocampus to the right occipital lobe and the left precuneus may play an important role in the neurological basis of DPD.

Functional connectivity of the visual cortex in chronic migraine before and after medication withdrawal therapy

Acute withdrawal of headache medication in chronic migraine patients with medication overuse may lead to a dramatic reduction in headache frequency and severity. However, the brain networks underlying chronic migraine and a favorable response to acute withdrawal are still poorly understood. The goal of the present study was to characterize the pattern of intrinsic magnetic resonance imaging (MRI) functional connectivity (FC) specific to chronic migraine and to identify changes in FC that characterize subjects with CM reverting to less frequent headaches. Subjects with chronic migraine (N = 99) underwent a resting-state functional MRI scan before and after three months of medication withdrawal therapy. In addition, we included four control groups who were scanned once: healthy participants (N = 27), patients with episodic migraine (N = 25), patients with chronic back pain (N = 22), and patients with clinical depression (N = 17). Using dual regression analysis, we compared whole-brain voxel-level functional connectivity with ten well-known resting-state networks between chronic migraine and control groups, and between responders to treatment (≥50 % reduction in monthly headache days) and non-responders (<50 % reduction), before and after treatment. Subjects with chronic migraine showed differences in FC with a number of RS-networks, most of which involved the visual cortex, compared with healthy controls. A comparison with patients with episodic migraine, chronic pain and depression showed differences in the same direction, suggesting that altered patterns of functional connectivity in chronic migraine patients could to some extent be explained by shared symptomatology with other pain, depression, or migraine conditions. A comparison between responders and non-responders indicated that effective withdrawal reduced FC with the visual cortex for responders. Interestingly, responders already differed in functional connectivity of the visual cortex at baseline compared with non-responders. Altogether, we show that chronic migraine and successful medication withdrawal therapy are linked to changes in the functional connectivity of the visual cortex. These neuroimaging findings provide new insights into the pathways underlying migraine chronification and its reversibility.

Abnormal intrinsic brain functional network dynamics in patients with cervical spondylotic myelopathy

The specific topological changes in dynamic functional networks and their role in cervical spondylotic myelopathy (CSM) brain function reorganization remain unclear. This study aimed to investigate the dynamic functional connection (dFC) of patients with CSM, focusing on the temporal characteristics of the functional connection state patterns and the variability of network topological organization. Eighty-eight patients with CSM and 77 healthy controls (HCs) were recruited for resting-state functional magnetic resonance imaging. We applied the sliding time window analysis method and K-means clustering analysis to capture the dFC variability patterns of the two groups. The graph-theoretical approach was used to investigate the variance in the topological organization of whole-brain functional networks. All participants showed four types of dynamic functional connection states. The mean dwell time in state 2 was significantly different between the two groups. Particularly, the mean dwell time in state 2 was significantly longer in the CSM group than in the healthy control group. Among the four states, switching of relative brain networks mainly included the executive control network (ECN), salience network (SN), default mode network (DMN), language network (LN), visual network (VN), auditory network (AN), precuneus network (PN), and sensorimotor network (SMN). Additionally, the topological properties of the dynamic network were variable in patients with CSM. Dynamic functional connection states may offer new insights into intrinsic functional activities in CSM brain networks. The variance of topological organization may suggest instability of the brain networks in patients with CSM.

Impairments to the multisensory integration brain regions during migraine chronification: correlation with the vestibular dysfunction

Objectives

Migraine is often combined with vestibular dysfunction, particularly in patients with chronic migraine (CM). However, the pathogenesis of migraine chronification leading to vestibular dysfunction is not fully understood. The current study investigated whether structural or functional impairments to the brain during migraine chronification could be associated with vestibular dysfunction development.

Methods

The eligible participants underwent clinical assessment and magnetic resonance imaging (MRI) scans. Voxel-based morphometry (VBM) determined structural impairment by evaluating alterations in gray matter volume (GMV). Functional impairment was assessed by the mean amplitude of low-frequency fluctuation (mALFF). Furthermore, the resting-state functional connectivity (rsFC) of regions possessing impairment was examined with a seed-based approach. We also analyzed the correlations between altered neuroimaging features with clinical variables and performed multiple linear regression.

Results

Eighteen CM patients, 18 episodic migraine (EM) patients, and 18 healthy controls (HCs) were included in this study. A one-way ANOVA indicated the group differences in mALFF. These were located within right supramarginal gyrus (SMG), left angular gyrus (AG), middle frontal gyrus (MFG), left middle occipital gyrus (MOG), right rolandic operculum (Rol) and left superior parietal gyrus (SPG). During rsFC analysis, the CM group had more enhanced rsFC of left SPG with left MOG than the EM and HC groups. The EM group revealed enhanced rsFC of left SPG with left AG than the CM and HC groups. In multiple linear regression, after controlling for age, body mass index (BMI) and disease duration, the rsFC of left SPG with left MOG (β = 48.896, p = 0.021) was found to predict the total Dizziness Handicap Inventory (DHI) score with an explained variance of 25.1%. Moreover, the rsFC of left SPG with left MOG (β = 1.253, p = 0.003) and right SMG (β = -1.571, p = 0.049) were significant predictors of migraine frequency, accounting for a total explained variance of 73.8%.

Conclusion

The functional impairments due to migraine chronification are primarily concentrated in the multisensory integration-related brain regions. Additionally, the rsFC of SPG with MOG can predict the frequency of migraine and the degree of vestibular dysfunction. Therefore, these neuroimaging features could be potential mechanisms and therapeutic targets for developing vestibular dysfunction in migraine.

Classification of Migraine Using Static Functional Connectivity Strength and Dynamic Functional Connectome Patterns: A Resting-State fMRI Study

Migraine is a common, chronic dysfunctional disease with recurrent headaches. Its etiology and pathogenesis have not been fully understood and there is a lack of objective diagnostic criteria and biomarkers. Meanwhile, resting-state functional magnetic resonance imaging (RS-fMRI) is increasingly being used in migraine research to classify and diagnose brain disorders. However, the RS-fMRI data is characterized by a large amount of data information and the difficulty of extracting high-dimensional features, which brings great challenges to relevant studies. In this paper, we proposed an automatic recognition framework based on static functional connectivity (sFC) strength features and dynamic functional connectome pattern (DFCP) features of migraine sufferers and normal control subjects, in which we firstly extracted sFC strength and DFCP features and then selected the optimal features using the recursive feature elimination based on the support vector machine (SVM−RFE) algorithm and, finally, trained and tested a classifier with the support vector machine (SVM) algorithm. In addition, we compared the classification performance of only using sFC strength features and DFCP features, respectively. The results showed that the DFCP features significantly outperformed sFC strength features in performance, which indicated that DFCP features had a significant advantage over sFC strength features in classification. In addition, the combination of sFC strength and DFCP features had the optimal performance, which demonstrated that the combination of both features could make full use of their advantage. The experimental results suggested the method had good performance in differentiating migraineurs and our proposed classification framework might be applicable for other mental disorders.

Altered brain function in patients with vestibular migraine: a study on resting state functional connectivity

PURPOSE

To characterize the altered brain function in patients with vestibular migraine (VM) using resting-state functional magnetic resonance imaging (fMRI).

METHODS

In this prospective study, fMRI images as well as clinical characteristics and behavioral scales were collected from 40 VM patients and 40 healthy controls (HC). All patients received neurological, neuro-otological, and conventional MRI examinations to exclude peripheral vestibular lesions, focal lesions, and other neurological diseases. Seed-based (bilateral parietal operculum cortex 2, OP2) functional connectivity (FC) and independent component analysis (ICA)-based functional network connectivity (FNC) were performed to investigate the brain functional changes in patients with VM. Additionally, the correlations between the altered FC/FNC and behavioral results were analyzed.

RESULTS

Compared with HC, patients with VM showed increased FC between the left OP2 and right precuneus and exhibited decreased FC between the left OP2 and left anterior cingulate cortex. We also observed increased FC between the right OP2 and regions of the right middle frontal gyrus and bilateral precuneus, as well as decreased FC between the bilateral OP2. Furthermore, patients with VM showed decreased FNC between visual network (VN) and networks of auditory and default mode, and exhibited increased FNC between VN and executive control network. A correlation analysis found that FC between the left OP2 and right precuneus was positively correlated with scores of dizziness handicap inventory (DHI) in patients with VM.

CONCLUSION

The present study demonstrated altered brain function in patients with VM.

Exploration of static functional connectivity and dynamic functional connectivity alterations in the primary visual cortex among patients with high myopia via seed-based functional connectivity analysis

Aim

This study was conducted to explore differences in static functional connectivity (sFC) and dynamic functional connectivity (dFC) alteration patterns in the primary visual area (V1) among high myopia (HM) patients and healthy controls (HCs) via seed-based functional connectivity (FC) analysis.

Methods

Resting-state functional magnetic resonance imaging (fMRI) scans were performed on 82 HM patients and 59 HCs who were closely matched for age, sex, and weight. Seed-based FC analysis was performed to identify alterations in the sFC and dFC patterns of the V1 in HM patients and HCs. Associations between mean sFC and dFC signal values and clinical symptoms in distinct brain areas among HM patients were identified via correlation analysis. Static and dynamic changes in brain activity in HM patients were investigated by assessments of sFC and dFC via calculation of the total time series mean and sliding-window analysis.

Results

In the left anterior cingulate gyrus (L-ACG)/left superior parietal gyrus (L-SPG) and left V1, sFC values were significantly greater in HM patients than in HCs. In the L-ACG and right V1, sFC values were also significantly greater in HM patients than in HCs [two-tailed, voxel-level P < 0.01, Gaussian random field (GRF) correction, cluster-level P < 0.05]. In the left calcarine cortex (L-CAL) and left V1, dFC values were significantly lower in HM patients than in HCs. In the right lingual gyrus (R-LING) and right V1, dFC values were also significantly lower in HM patients than in HCs (two-tailed, voxel-level P < 0.01, GRF correction, cluster-level P < 0.05).

Conclusion

Patients with HM exhibited significantly disturbed FC between the V1 and various brain regions, including L-ACG, L-SPG, L-CAL, and R-LING. This disturbance suggests that patients with HM could exhibit impaired cognitive and emotional processing functions, top-down control of visual attention, and visual information processing functions. HM patients and HCs could be distinguished from each other with high accuracy using sFC and dFC variabilities. These findings may help to identify the neural mechanism of decreased visual performance in HM patients.

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.

Changes in brain structure and related functional connectivity during menstruation in women with primary dysmenorrhea

Background

Neuroimaging studies have identified altered brain structures and functions in women with primary dysmenorrhea (PDM). However, previous studies focused on either structural or functional changes in specific brain regions rather than combining structural and functional analysis. Therefore, this prospective cross-sectional study aimed to investigate the changes in whole brain structure, and functional variation along with structural abnormalities in women with PDM during menstruation.

Methods

In all, 31 patients with PDM (PTs) and 31 healthy controls (HCs) were recruited. Voxel-based morphometry (VBM) and surface-based morphometry (SBM) analyses were applied to investigate structural changes based on high-resolution T1-weighted magnetic resonance images. Functional connectivity (FC) analysis was performed to evaluate functional variations related to the brain regions that showed structural group differences. Pearson correlation analysis was performed to assess the relationship between neuroimaging changes and clinical measures.

Results

Compared to HCs, PTs had reduced gray matter volume (GMV) in the right superior temporal gyrus (STG) and reduced thickness in the bilateral orbitofrontal cortex (OFC), left postcentral gyrus (PoCG), and left superior occipital gyrus (SOG). Among these areas, the STG and PoCG are responsible for altered resting-state FC patterns in PTs. Results showed decreased FC between the STG and the left cerebellar posterior lobe (poCb), the right dorsolateral prefrontal cortex (DLPFC), and the left precentral gyrus (PrCG). Results also showed decreased FC between the PoCG and the right precuneus and the right DLPFC. We also found greater FCs between the PoCG and the bilateral poCb, the left middle temporal gyrus (MTG), and the left angular gyrus. In addition, the FCs between the STG and poCb, and DLPFC in PTs were positively correlated with history and Cox menstrual symptom scale (CMSS) scores, respectively, while the FCs between STG and PrCG were negatively correlated with the onset age of PDM.

Conclusions

Our research found structural abnormalities and related FC changes in several brain regions that were mainly involved in the emotional and sensory aspects of menstrual pain in PDM. These findings could help us understand the occurrence of PDM from a neuroimaging perspective.

Aberrant dynamic functional network connectivity in vestibular migraine patients without peripheral vestibular lesion

PURPOSE

This study aimed to investigate changes in dynamic functional network connectivity (FNC) in patients with vestibular migraine (VM) and explore their relationship with clinical manifestations.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) data were scanned from 35 VM patients without peripheral vestibular lesion and 40 age-, sex- and education-matched healthy controls (HC). Independent component analysis (ICA), sliding window (SW) and k-means clustering analysis were performed to explore the difference in FNC and temporal characteristics between two groups. Additionally, Pearson's partial correlation analysis was adopted to investigate the relationship between clinical manifestations and rs-fMRI results in patients with VM.

RESULTS

Compared with HC, patients with VM showed increased FNC in pairs of extrastriate visual network (eVN)-ventral attention network (VAN), eVN-default mode network (DMN) and eVN-left frontoparietal network (lFPN), and exhibited decreased FNC in pairs of VAN-auditory network (AuN). The altered FNC was correlated with clinical manifestations of patients with VM. Additionally, we found increased mean dwell time and fractional windows in state 2 in VM patients compared with HC. Mean dwell time was positively correlated with headache impact test-6 (HIT-6) scores, fractional windows was positively associated with dizziness handicap inventory (DHI) scores.

CONCLUSION

Our results indicated that patients with VM showed altered FNC primarily between sensory networks and networks related to cognitive, emotional and attention implementation, with more time spent in a state characterized by positive FNC between sensor cortex system and dorsal attention network (DAN). These findings could help reinforce the understanding on the neural mechanisms of VM.

Alterations of degree centrality and functional connectivity in classic trigeminal neuralgia

Objectives

Recent neuroimaging studies have indicated a wide range of structural and regional functional alterations in patients with classic trigeminal neuralgia (CTN). However, few studies have focused on the intrinsic functional characteristics of network organization in the whole brain. Therefore, the present study aimed to characterize the potential intrinsic dysconnectivity pattern of the whole brain functional networks at the voxel level using the degree centrality (DC) analysis in CTN patients.

Methods

Thirty-four patients with CTN and twenty-nine well-matched healthy controls (HCs) participated in this study. All subjects underwent resting-state functional magnetic resonance imaging (rs-MRI) examination and clinical and neuropsychologic assessments. DC is a graph theory-based measurement that represents the overall functional connectivity (FC) numbers between one voxel and other brain voxels. We first investigated brain regions exhibiting abnormal DC, and further identified their perturbation on FC with other brain regions using a seed-based FC analysis in patients with CTN. In addition, correlation analyses were performed to evaluate the relationship between the abnormal DC value and clinical variables in CTN patients.

Results

Compared with the HCs, the patients with CTN exhibited significantly greater DC values in the right pallidum and right putamen, and lower DC values in the right lingual gyrus, right calcarine sulcus, left paracentral lobule, and left midcingulate cortex. A further seed-based FC analysis revealed that the right lingual gyrus showed decreased FC within the visual network and with other core brain networks, including the sensorimotor network, default mode network, and salience network, relative to HCs. Additionally, the left midcingulate cortex exhibited decreased FC within the middle cingulate cortex and the visual network in CTN patients. Moreover, the DC value in the left midcingulate cortex was negatively correlated with the illness duration.

Conclusion

The present study shows that CTN patients exhibited specific functional connectivity network alterations in the basal ganglia, visual network, and salience network, which may reflect the aberrant neural network communication in pain processing and modulation. These findings may provide novel insight for understanding the mechanisms of pain chronicity in CTN patients.

Resting-state abnormalities in functional connectivity of the default mode network in migraine: A meta-analysis

Migraine-a disabling neurological disorder, imposes a tremendous burden on societies. To reduce the economic and health toll of the disease, insight into its pathophysiological mechanism is key to improving treatment and prevention. Resting-state functional magnetic resonance imaging (rs-fMRI) studies suggest abnormal functional connectivity (FC) within the default mode network (DMN) in migraine patients. This implies that DMN connectivity change may represent a biomarker for migraine. However, the FC abnormalities appear inconsistent which hinders our understanding of the potential neuropathology. Therefore, we performed a meta-analysis of the FC within the DMN in migraine patients in the resting state to identify the common FC abnormalities. With efficient search and selection strategies, nine studies (published before July, 2022) were retrieved, containing 204 migraine patients and 199 healthy subjects. We meta-analyzed the data using the Anisotropic Effect Size version of Signed Differential Mapping (AES-SDM) method. Compared with healthy subjects, migraine patients showed increased connectivity in the right calcarine gyrus, left inferior occipital gyrus, left postcentral gyrus, right cerebellum, right parahippocampal gyrus, and right posterior cingulate gyrus, while decreased connectivity in the right postcentral gyrus, left superior frontal gyrus, right superior occipital gyrus, right orbital inferior frontal gyrus, left middle occipital gyrus, left middle frontal gyrus and left inferior frontal gyrus. These results provide a new perspective for the study of the pathophysiology of migraine and facilitate a more targeted treatment of migraine in the future.

Altered functional connectivity of the right caudate nucleus in chronic migraine: a resting-state fMRI study

BACKGROUND

The definitive pathogenic mechanisms underlying chronic migraine (CM) remain unclear. Mounting evidence from functional and structural magnetic resonance imaging (MRI) studies suggests that the caudate nucleus (CN) plays a role in the cognitive, sensory, and emotional integration of pain information in patients with migraine. However, evidence concerning the role played by CN in CM patients is limited. Here, we used the CN as the seed to explore patterns of functional connectivity (FC) among healthy controls (HCs), patients with episodic migraine (EM), and patients with CM.

METHODS

We included 25 HCs, 23 EM patients, and 46 CM patients in this study. All participants underwent resting-state functional MRI scans on a GE 3.0T MRI system. We performed seed-based FC analyses among the three groups using the bilateral CNs as seeds. We also compared the subgroups of CM (with and without medication overuse headache, males and females) and performed Pearson's correlation analyses between FC values and the clinical features of CM patients.

RESULTS

FC values between the right CN and five clusters (mainly involved in emotion, cognition, and sensory-related brain regions) were higher in CM patients than in HCs. Compared to EM patients, enhanced FC values between the bilateral precuneus, left anterior cingulate gyrus, right middle cingulate cortex, right lingual gyrus, and right CN were shown in the CM patients. There were no significant differences between CM patients with and without MOH, males and females. FC values between the bilateral calcarine cortex, lingual gyrus, and right CN were positively correlated with body mass index. Moreover, right CN-related FC values in the left calcarine cortex and right lingual gyrus were inversely correlated with visual analogue scale scores for headaches.

CONCLUSION

Our results revealed abnormal right CN-based FC values in CM patients, suggesting dysfunction of brain networks associated with pain perception and multi-regulation (emotion, cognition, and sensory). Aberrant FC of the CN can provide potential neuroimaging markers for the diagnosis and treatment of CM.

Abnormal static and dynamic functional network connectivity in stable chronic obstructive pulmonary disease

Objective

Many studies have explored the neural mechanisms of cognitive impairment in chronic obstructive pulmonary disease (COPD) patients using the functional MRI. However, the dynamic properties of brain functional networks are still unclear. The purpose of this study was to explore the changes in dynamic functional network attributes and their relationship with cognitive impairment in stable COPD patients.

Materials and methods

The resting-state functional MRI and cognitive assessments were performed on 19 stable COPD patients and 19 age-, sex-, and education-matched healthy controls (HC). We conducted the independent component analysis (ICA) method on the resting-state fMRI data, and obtained seven resting-state networks (RSNs). After that, the static and dynamic functional network connectivity (sFNC and dFNC) were respectively constructed, and the differences of functional connectivity (FC) were compared between the COPD patients and the HC groups. In addition, the correlation between the dynamic functional network attributes and cognitive assessments was analyzed in COPD patients.

Results

Compared to HC, there were significant differences in sFNC among COPD patients between and within networks. COPD patients showed significantly longer mean dwell time and higher fractional windows in weaker connected State I than that in HC. Besides, in comparison to HC, COPD patients had more extensive abnormal FC in weaker connected State I and State IV, and less abnormal FC in stronger connected State II and State III, which were mainly located in the default mode network, executive control network, and visual network. In addition, the dFNC properties including mean dwell time and fractional windows, were significantly correlated with some essential clinical indicators such as FEV₁, FEV₁/FVC, and c-reactive protein (CRP) in COPD patients.

Conclusion

These findings emphasized the differences in sFNC and dFNC of COPD patients, which provided a new perspective for understanding the cognitive neural mechanisms, and these indexes may serve as neuroimaging biomarkers of cognitive performance in COPD patients.

Case report: The promising application of dynamic functional connectivity analysis on an individual with failed back surgery syndrome

Failed back surgery syndrome (FBSS), a chronic neuropathic pain condition, is a common indication for spinal cord stimulation (SCS). However, the mechanisms of SCS, especially its effects on supraspinal/brain functional connectivity, are still not fully understood. Resting state functional magnetic resonance imaging (rsfMRI) studies have shown characteristics in patients with chronic low back pain (cLBP). In this case study, we performed rsfMRI scanning (3.0 T) on an FBSS patient, who presented with chronic low back and leg pain following her previous lumbar microdiscectomy and had undergone permanent SCS. Appropriate MRI safety measures were undertaken to scan this subject. Seed-based functional connectivity (FC) was performed on the rsfMRI data acquired from the FBSS subject, and then compared to a group of 17 healthy controls. Seeds were identified by an atlas of resting state networks (RSNs), which is composed of 32 regions grouped into 8 networks. Sliding-window method and k-means clustering were used in dynamic FC analysis, which resulted in 4 brain states for each group. Our results demonstrated the safety and feasibility of 3T MRI scanning in a patient with implanted SCS system. Compared to the brain states of healthy controls, the FBSS subject presented very different FC patterns in less frequent brain states. The mean dwell time of brain states showed distinct distributions: the FBSS subject seemed to prefer a single state over the others. Although future studies with large sample sizes are needed to make statistical conclusions, our findings demonstrated the promising application of dynamic FC to provide more granularity with FC changes associated with different brain states in chronic pain.

Moxibustion for primary dysmenorrhea: A resting-state functional magnetic resonance imaging study exploring the alteration of functional connectivity strength and functional connectivity

Introduction

Primary dysmenorrhea (PDM) is a common gynecological disease and chronic pain disorder. Moxibustion, a form of traditional Chinese medicine therapy, has proven to be effective for PDM. However, the central mechanisms of PDM and moxibustion for PDM are still unclear. This study aims to explore the potential central mechanism of PDM and clarify the possible mechanism of moxibustion for relieving pain.

Materials and methods

A total of 23 PDM patients and 23 matched healthy controls (HCs) were enrolled. For PDM patients, resting-state functional magnetic resonance imaging (rs-fMRI) data were collected pre- and post-moxibustion treatment of 3 consecutive menstrual cycles, respectively. For HCs, rs-fMRI data were collected in the baseline. The resting-state functional connectivity strength (rs-FCS) analysis and the resting-state functional connectivity (rs-FC) analysis based on the region of interest (ROI) were combined to be conducted.

Results

Compared to HCs, PDM patients showed weaker rs-FCS in the left inferior frontal gyrus (IFG). After the moxibustion treatment, rs-FCS in the left IFG was increased with clinical improvement. Then, the left IFG was chosen as ROI, and the rs-FC analysis was conducted. It showed that the left IFG rs-FC in the bilateral anterior cingulate cortex (ACC)/middle cingulate cortex (MCC), the left posterior cingulate cortex (PCC)/precuneus (PCU), and the left parahippocampal gyrus (PHG) decreased after moxibustion treatment, most of which belong to the default mode network (DMN).

Conclusion

Our results highlight the role of the left IFG and the DMN in PDM. Specifically, the central mechanism of moxibustion for analgesia may be related to modulating the disorders of the reappraisal and processing of pain stimuli through influencing the cognition of pain.

Migraine and Posttraumatic Headache: Similarities and Differences in Brain Network Connectivity

Posttraumatic headache (PTH) is the most common symptom following mild traumatic brain injury (mTBI) (also known as concussion). Migraine and PTH have similar phenotypes, and a migraine-like phenotype is common in PTH. The similarities between both headache types are intriguing and challenge a better understanding of the pathophysiological commonalities involved in migraine and PTH due to mTBI. Here, we review the PTH resting-state functional connectivity literature and compare it to migraine to assess overlap and differences in brain network function between both headache types. Migraine and PTH due to mTBI have overlapping and disease-specific widespread alterations of static and dynamic functional networks involved in pain processing as well as dysfunctional network connections between frontal regions and areas of pain modulation and pain inhibition. Although the PTH functional network literature is still limited, there is some evidence that dysregulation of the top-down pain control system underlies both migraine and PTH. However, disease-specific differences in the functional circuitry are observed as well, which may reflect unique differences in brain architecture and pathophysiology underlying both headache disorders.

Abnormal Dynamics of Functional Connectivity Density Associated With Chronic Neck Pain

Background: Chronic neck pain (CNP) is highly prevalent and complicated, associated with limited movement, and accompanied by shoulder pain and other clinical manifestations such as dizziness, anxiety, and insomnia. Brain structural and functional abnormalities often occur in patients with CNP. However, knowledge of the brain’s functional organization and temporal dynamics in CNP patients is limited. Dynamic functional connectivity density (dFCD) can reflect the ability of brain areas or voxels to integrate information, and could become neuroimaging markers for objectively reflecting pain to a certain extent. Therefore, this study compared the dFCD between CNP patients and healthy controls (HCs) and investigated potential associations of the abnormal density variability in dynamic functional connectivity with pain characteristics in CNP patients.

Methods: Resting functional magnetic resonance imaging was performed for 89 CNP patients and 57 HCs. After preprocessing resting-state fMRI images by the Data Processing and Analysis of Brain Imaging toolbox, the sliding window method was applied to investigate dFCD changes in CNP patients and HCs using the DynamicBC toolbox. Then we quantified dFCD variability using their standard deviation. Based on the pain-associated factors collected from the case report form of CNP patients, the mean dFCD variability values of each dFCD from region of interest were extracted to calculate Pearson’s correlation coefficient to study the potential correlation between dFCD abnormal variability and pain.

Results: Compared with HCs, the dFCD values of the anterior cingulate cortex, occipital lobe, temporal lobe, and cerebellum were statistically different in patients with CNP. Subsequent correlation analysis showed that the variable dFCD in the related brain region was correlative with the course of the disease and clinical symptoms, such as pain and depression, in patients with CNP.

Conclusion: Dynamic functional alterations were observed in the brain regions of CNP patients, and the dFCD of these brain regions could become neuroimaging markers for objectively reflecting pain to a certain extent. This suggests that chronic pain may cause changes in pain processing and emotional feedback and highlights the link between dynamic neural communication in brain regions and disease conditions, deepening our understanding of chronic pain diseases, and guiding clinical practice.

Abnormal Large-Scale Neuronal Network in High Myopia

Aim

Resting state functional magnetic resonance imaging (rs-fMRI) was used to analyze changes in functional connectivity (FC) within various brain networks and functional network connectivity (FNC) among various brain regions in patients with high myopia (HM).

Methods

rs-fMRI was used to scan 82 patients with HM (HM group) and 59 healthy control volunteers (HC group) matched for age, sex, and education level. Fourteen resting state networks (RSNs) were extracted, of which 11 were positive. Then, the FCs and FNCs of RSNs in HM patients were examined by independent component analysis (ICA).

Results

Compared with the HC group, FC in visual network 1 (VN1), dorsal attention network (DAN), auditory network 2 (AN2), visual network 3 (VN3), and sensorimotor network (SMN) significantly increased in the HM group. FC in default mode network 1 (DMN1) significantly decreased. Furthermore, some brain regions in default mode network 2 (DMN2), default mode network 3 (DMN3), auditory network 1 (AN1), executive control network (ECN), and significance network (SN) increased while others decreased. FNC analysis also showed that the network connection between the default mode network (DMN) and cerebellar network (CER) was enhanced in the HM group.

Conclusion

Compared with HCs, HM patients showed neural activity dysfunction within and between specific brain networks, particularly in the DMN and CER. Thus, HM patients may have deficits in visual, cognitive, and motor balance functions.

Identifying functional brain abnormalities in migraine and depression comorbidity

BACKGROUND

Migraine and major depressive disorder (MDD) are both highly prevalent brain disorders and are often comorbid. However, the common and distinctive neural mechanisms underlying these disorders and the brain function alterations associated with their comorbidity are largely unknown. We aimed to explore the functional abnormalities of the brain associated with the co-occurrence of migraine and depression.

METHODS

High-resolution T1-weighted and resting-state functional magnetic resonance images (MRI) were acquired from 93 well-matched patients with comorbid migraine and depression, patients with migraine, patients with MDD, and healthy controls. Voxel-wise analysis of variance (ANOVA) and a two-sample t-test of multiple functional variables were performed among the groups. Furthermore, correlation analysis was conducted to detect the clinical significance of the altered functional regions in the brain.

RESULTS

Migraine patients with and without depression revealed widely shared regional networks of functional changes. Brain function changes in the right paracentral lobule and fusiform were specific to patients with comorbid migraine and depression [P<0.05, cluster-level familywise error (FWE)-corrected], while changes in the left thalamus, medial orbital of superior frontal gyrus and triangular part of the inferior frontal gyrus were specific to patients with migraine (P<0.05, cluster-level FWE-corrected). Importantly, the brain activity of the right paracentral lobule, left calcarine, and left dorsolateral superior frontal gyrus was associated with emotional symptoms in the pooled migraine data (P<0.05).

CONCLUSIONS

These findings help to identify the neural correlates underlying patients with migraine and those with comorbid migraine and depression. These shared and distinct brain changes could be used as potential image markers to decipher the comorbidity of the 2 disorders.

Altered brain functional network dynamics in classic trigeminal neuralgia: a resting-state functional magnetic resonance imaging study

Background

Accumulating studies have indicated a wide range of brain alterations with respect to the structure and function of classic trigeminal neuralgia (CTN). Given the dynamic nature of pain experience, the exploration of temporal fluctuations in interregional activity covariance may enhance the understanding of pain processes in the brain. The present study aimed to characterize the temporal features of functional connectivity (FC) states as well as topological alteration in CTN.

Methods

Resting-state functional magnetic resonance imaging and three-dimensional T1-weighted images were obtained from 41 CTN patients and 43 matched healthy controls (HCs). After group independent component analysis, sliding window based dynamic functional network connectivity (dFNC) analysis was applied to investigate specific FC states and related temporal properties. Then, the dynamics of the whole brain topological organization were estimated by calculating the coefficient of variation of graph-theoretical properties. Further correlation analyses were performed between all these measurements and clinical data.

Results

Two distinct states were identified. Of these, the state 2, characterized by complicated coupling between default mode network (DMN) and cognitive control network (CC) and tight connections within DMN, was expressed more in CTN patients and presented as increased fractional windows and dwell time. Moreover, patients switched less frequently between states than HCs. Regarding the dynamic topological analysis, disruptions in global graph-theoretical properties (including network efficiency and small-worldness) were observed in patients, coupled with decreased variability in nodal efficiency of anterior cingulate cortex (ACC) in the salience network (SN) and the thalamus and caudate nucleus in the subcortical network (SC). The variation of topological properties showed negative correlation with disease duration and attack frequency.

Conclusions

The present study indicated disrupted flexibility of brain topological organization under persistent noxious stimulation and further highlighted the important role of “dynamic pain connectome” regions (including DMN/CC/SN) in the pathophysiology of CTN from the temporal fluctuation aspect. Additionally, the findings provided supplementary evidence for current knowledge about the aberrant cortical-subcortical interaction in pain development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10194-021-01354-z.

Altered static and dynamic functional network connectivity in post-traumatic headache

BACKGROUND

Post-traumatic headache (PTH) is a very common symptom following mild traumatic brain injury (mTBI), yet much remains unknown about the underlying pathophysiological mechanisms of PTH. Neuroimaging studies suggest that aberrant functional network connectivity (FNC) may be an important factor in pain disorders. The present study aimed to investigate the functional characteristics of static FNC (sFNC) and dynamic FNC (dFNC) in mTBI patients with PTH.

METHODS

With Institutional Review Board (IRB) approval, we prospectively recruited 50 mTBI patients with PTH, who were diagnosed with ICHD-3 beta diagnostic criteria and 39 mTBI without PTH who were well matched for age, gender and education. Resting-state functional magnetic resonance imaging (fMRI) scanning (3.0 T, Philips Medical Systems, Netherlands), Montreal Cognitive Assessment (MoCA) and headache symptom measurement (headache frequency and headache intensity) were performed. The resting-state fMRI sequence took 8 min and 10 s. Independent component analysis and sliding window method were applied to examine the FNC on the basis of nine resting-state networks, namely, default mode network (DMN), sensorimotor network (SMN), executive control network (ECN), auditory network (AuN), attention network (AN), salience network (SN), visual network (VN), and cerebellum network (CN). The differences in sFNC and dFNC were determined and correlated with clinical variables using Pearson rank correlation.

RESULTS

For sFNC, compared with mTBI patients without PTH, mTB with PTH group showed four altered interactions, including decreased interactions in SN-SMN and VN-DMN pairs, increased sFNC in SN-ECN and SMN-DMN pairs. For dFNC, significant group differences were found in State 2, including increased connectivity alteration in the DMN with CN, DMN with SMN, and AuN with CN. Significant reduced connectivity changes in the DMN with VN was found in State 4. Furthermore, the number of transitions (r=0.394, p=0.005) between states was positively associated with headache frequency. Additionally, dwell time (r=-0.320, p=0.025) in State 1 was negatively correlated with MoCA score.

CONCLUSIONS

MTBI patients with PTH are characterized with altered sFNC and dFNC, which could provide new perspective to understand the neuropathological mechanism underlying the PTH to determine more appropriate management, and may be a useful imaging biomarker for identifying and predicting mTBI with PTH.

Networks Are Associated With Acupuncture Treatment in Patients With Diarrhea-Predominant Irritable Bowel Syndrome: A Resting-State Imaging Study

Background: Irritable Bowel Syndrome (IBS), as a functional gastrointestinal disorder, is characterized by abdominal pain and distension. Recent studies have shown that acupuncture treatment improves symptoms of diarrhea-predominant irritable bowel syndrome (IBS-D) by altering networks in certain brain regions. However, few studies have used resting-state functional magnetic resonance imaging (fMRI) to compare altered resting-state inter-network functional connectivity in IBS-D patients before and after acupuncture treatment. Objective: To analyze altered resting-state inter-network functional connectivity in IBS-D patients before and after acupuncture treatment. Methods: A total of 74 patients with IBS-D and 31 healthy controls (HCs) were recruited for this study. fMRI examination was performed in patients with IBS-D before and after acupuncture treatment, but only at baseline in HCs. Data on the left frontoparietal network (LFPN), default mode network (DMN), salience network (SN), ventral attention network (VAN), auditory network (AN), visual network (VN), sensorimotor network (SMN), dorsal attention network (DAN), and right frontoparietal network (RFPN) were subjected to independent component analysis (ICA). The functional connectivity values of inter-network were explored. Results: Acupuncture decreased irritable bowel syndrome symptom severity score (IBS-SSS) and Hamilton Anxiety Scale (HAMA). It also ameliorated symptoms related to IBS-D. Notably, functional connectivity between AN and VAN, SMN and DMN, RFPN and VAN in IBS-D patients after acupuncture treatment was different from that in HCs. Furthermore, there were differences in functional connectivity between DMN and DAN, DAN and LFPN, DMN and VAN before and after acupuncture treatment. The inter-network changes in DMN-VAN were positively correlated with changes in HAMA, life influence degree, and IBS-SSS in IBS-D. Conclusion: Altered inter-network functional connectivity is involved in several important hubs in large-scale networks. These networks are altered by acupuncture stimulation in patients with IBS-D.

Differences in Frontal Lobe Dysfunction in Patients with Episodic and Chronic Migraine

Neuroimaging and neuropsychological investigations have indicated that migraineurs exhibit frontal lobe-related cognitive impairment. We investigated whether orbitofrontal and dorsolateral functioning differed between individuals with episodic migraine (EM) and chronic migraine (CM), focusing on orbitofrontal dysfunction because it is implicated in migraine chronification and medication overuse headache (MOH) in migraineurs. This cross-sectional study recruited women with CM with/without MOH (CM + MOH, CM − MOH), EM, and control participants who were matched in terms of age and education. We conducted neuropsychological assessments of frontal lobe function via the Trail Making Test (TMT) A and B, the Wisconsin Card Sorting Test (WCST), and the Iowa Gambling Task (IGT). We enrolled 36 CM (19 CM + MOH, 17 CM − MOH), 30 EM, and 30 control participants. The CM patients performed significantly (p < 0.01) worse on the TMT A and B than the EM patients and the control participants. The WCST also revealed significant differences, with poorer performance in the CM patients versus the EM patients and the control participants. However, the net scores on the IGT did not significantly differ among the three groups. Our findings suggest that the CM patients exhibited frontal lobe dysfunction, and, particularly, dorsolateral dysfunction. However, we found no differences in frontal lobe function according to the presence or absence of MOH.