Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI

Background

Previous studies have defined low-frequency, spatially consistent intrinsic connectivity networks (ICN) in resting functional magnetic resonance imaging (fMRI) data which reflect functional interactions among distinct brain areas. We sought to explore whether and how repeated migraine attacks influence intrinsic brain connectivity, as well as how activity in these networks correlates with clinical indicators of migraine.

Methods/Principal Findings

Resting-state fMRI data in twenty-three patients with migraines without aura (MwoA) and 23 age- and gender-matched healthy controls (HC) were analyzed using independent component analysis (ICA), in combination with a “dual-regression” technique to identify the group differences of three important pain-related networks [default mode network (DMN), bilateral central executive network (CEN), salience network (SN)] between the MwoA patients and HC. Compared with the HC, MwoA patients showed aberrant intrinsic connectivity within the bilateral CEN and SN, and greater connectivity between both the DMN and right CEN (rCEN) and the insula cortex - a critical region involving in pain processing. Furthermore, greater connectivity between both the DMN and rCEN and the insula correlated with duration of migraine.

Conclusions

Our findings may provide new insights into the characterization of migraine as a condition affecting brain activity in intrinsic connectivity networks. Moreover, the abnormalities may be the consequence of a persistent central neural system dysfunction, reflecting cumulative brain insults due to frequent ongoing migraine attacks.     

Abnormal Resting-State Activities and Functional Connectivities of the Anterior and the Posterior Cortexes in Medication-Na?ve Patients with Obsessive-Compulsive Disorder

Background

Obsessive-compulsive disorder (OCD) is a mental illness characterized by the loss of control. Because the cingulate cortex is believed to be important in executive functions, such as inhibition, we used functional magnetic resonance imaging (fMRI) techniques to examine whether and how activity and functional connectivity (FC) of the cingulate cortex were altered in drug-naïve OCD patients.

Methods

Twenty-three medication-naïve OCD patients and 23 well-matched healthy controls received fMRI scans in a resting state. Functional connectivities of the anterior cingulate (ACC) and the posterior cingulate (PCC) to the whole brain were analyzed using correlation analyses based on regions of interest (ROI) identified by the fractional amplitude of low-frequency fluctuation (fALFF). Independent Component Analysis (ICA) was used to identify the resting-state sub-networks.

Results

fALFF analysis found that regional activity was increased in the ACC and decreased in the PCC in OCD patients when compared to controls. FC of the ACC and the PCC also showed different patterns. The ACC and the PCC were found to belong to different resting-state sub-networks in ICA analysis and showed abnormal FC, as well as contrasting correlations with the severity of OCD symptoms.

Conclusions

Activity of the ACC and the PCC were increased and decreased, respectively, in the medication-naïve OCD patients compared to controls. Different patterns in FC were also found between the ACC and the PCC with respect to these two groups. These findings implied that the cardinal feature of OCD, the loss of control, may be attributed to abnormal activities and FC of the ACC and the PCC.     

偏头痛患者体感刺激下脑电信号的功能连接（英文）

目的 偏头痛是一种复杂的脑功能障碍性疾病,全球范围内患病率为14.4%。功能连接测量两个神经信号之间的统计学相互依赖性,不同的功能连接反映了大脑区域协同工作的不同模式。因此,研究不同脑区的功能连接对于理解偏头痛的病理生理机制具有十分重要的意义。以往基于脑电图对偏头痛患者脑功能连接的分析主要集中在视觉和疼痛刺激。本文尝试研究偏头痛患者在发作间期对体感刺激的皮质反应,以进一步了解偏头痛的神经功能障碍,为偏头痛的预防和治疗提供线索。方法 招募23例无先兆偏头痛患者,10例有先兆偏头痛患者,28名健康对照者。所有受试者均进行详细的基本资料和病史采集,完善量表评估,在正中神经体感刺激下进行脑电图记录。计算68个脑区的相干性作为功能连接,并评估功能连接与临床参数的相关性。结果 在正中神经体感刺激下,无先兆偏头痛和有先兆偏头痛患者的脑电功能连接与对照组相比存在差异,异常的脑电功能连接主要位于感觉辨别、疼痛调节、情绪认知和视觉处理等区域。无先兆偏头痛和有先兆偏头痛患者的大脑皮层对体感刺激可能具有相同的反应方式。偏头痛患者的功能连接异常与临床特征之间存在相关性,可以部分反映偏头痛的严重程度。结论 本研究...     

Aberrant Functional Connectivity of Resting State Networks in Transient Ischemic Attack

Background

Transient ischemic attack (TIA) is usually defined as a neurologic ischemic disorder without permanent cerebral infarction. Studies have showed that patients with TIA can have lasting cognitive functional impairment. Inherent brain activity in the resting state is spatially organized in a set of specific coherent patterns named resting state networks (RSNs), which epitomize the functional architecture of memory, language, attention, visual, auditory and somato-motor networks. Here, we aimed to detect differences in RSNs between TIA patients and healthy controls (HCs).

Methods

Twenty one TIA patients suffered an ischemic event and 21 matched HCs were enrolled in the study. All subjects were investigated using cognitive tests, psychiatric tests and functional magnetic resonance imaging (fMRI). Independent component analysis (ICA) was adopted to acquire the eight brain RSNs. Then one-sample t-tests were calculated in each group to gather the spatial maps of each RSNs, followed by second level analysis to investigate statistical differences on RSNs between twenty one TIA patients and 21 controls. Furthermore, a correlation analysis was performed to explore the relationship between functional connectivity (FC) and cognitive and psychiatric scales in TIA group.

Results

Compared with the controls, TIA patients exhibited both decreased and increased functional connectivity in default mode network (DMN) and self-referential network (SRN), and decreased functional connectivity in dorsal attention network (DAN), central-executive network (CEN), core network (CN), somato-motor network (SMN), visual network (VN) and auditory network (AN). There was no correlation between neuropsychological scores and functional connectivity in regions of RSNs.

Conclusions

We observed selective impairments of RSN intrinsic FC in TIA patients, whose all eight RSNs had aberrant functional connectivity. These changes indicate that TIA is a disease with widely abnormal brain networks. Our results might put forward a novel way to look into neuro-pathophysiological mechanisms in TIA patients.     

Functional Connectivity in the Brain Estimated by Analysis of Gamma Events

It is known that gamma activity is generated by local networks. In this paper we introduced a new approach for estimation of functional connectivity between neuronal networks by measuring temporal relations between peaks of gamma event amplitudes. We have shown in freely moving rats that gamma events recorded between electrodes 1.5 mm apart in the majority of cases, are generated by different neuronal modules interfering with each other. The map of functional connectivity between brain areas during the resting state, created based on gamma event temporal relationships is in agreement with anatomical connections and with maps described by fMRI methods during the resting state. The transition from the resting state to exploratory activity is accompanied by decreased functional connectivity between most brain areas. Our data suggest that functional connectivity between interhemispheric areas depends on GABAergic transmission, while intrahemispheric functional connectivity is kainate receptor dependent. This approach presents opportunities for merging electrographic and fMRI data on brain functional connectivity in normal and pathological conditions.     

Stability of Whole Brain and Regional Network Topology within and between Resting and Cognitive States

Background

Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI) data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well.

Methodology/Principal Findings

fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state.

Conclusions/Significance

These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.     

颞叶癫痫脑“默认模式”的fMRI研究

功能磁共振成像(functional magnetic resonance imaging,fMRI)被用于检测静息时脑功能神经网络.作者运用静息fMRI检测海马硬化颞叶癫痫(temporal lobe epilepsy,TLE)脑"默认模式",采用感兴趣区域功能连接分析检测16例TLE患者和16名正常对照静息时脑的"默认模式",并进行组内和组间分析.研究发现,与正常对照相比,TLE静息时海马、颞极、额叶、颞叶、壳核及楔前叶等脑区与后扣带回的功能连接增强.研究结果表明TLE患者的固有脑功能组织模式有可能出现紊乱.这一研究将有助于从脑功能的角度了解癫痫患者某些临床症状的发病机理,为今后癫痫诊治的发展提供一定的帮助.     

Decreased Functional Connectivity of Homotopic Brain Regions in Chronic Stroke Patients: A Resting State fMRI Study

The recovery of motor functions is accompanied by brain reorganization, and identifying the inter-hemispheric interaction post stroke will conduce to more targeted treatments. However, the alterations of bi-hemispheric coordination pattern between homologous areas in the whole brain for chronic stroke patients were still unclear. The present study focuses on the functional connectivity (FC) of mirror regions of the whole brain to investigate the inter-hemispheric interaction using a new fMRI method named voxel-mirrored homotopic connectivity (VMHC). Thirty left subcortical chronic stroke patients with pure motor deficits and 37 well-matched healthy controls (HCs) underwent resting-state fMRI scans. We employed a VMHC analysis to determine the brain areas showed significant differences between groups in FC between homologous regions, and we explored the relationships between the mean VMHC of each survived area and clinical tests within patient group using Pearson correlation. In addition, the brain areas showed significant correlations between the mean VMHC and clinical tests were defined as the seed regions for whole brain FC analysis. Relative to HCs, patients group displayed lower VMHC in the precentral gyrus, postcentral gyrus, inferior frontal gyrus, middle temporal gyrus, calcarine gyrus, thalamus, cerebellum anterior lobe, and cerebellum posterior lobe (CPL). Moreover, the VMHC of CPL was positively correlated with the Fugl–Meyer Score of hand (FMA-H), while a negative correlation between illness duration and the VMHC of this region was also detected. Furthermore, we found that when compared with HCs, the right CPL exhibited reduced FC with the left precentral gyrus, inferior frontal gyrus, inferior parietal lobule, middle temporal gyrus, thalamus and hippocampus. Our results suggest that the functional coordination across hemispheres is impaired in chronic stroke patients, and increased VMHC of the CPL is significantly associated with higher FMA-H scores. These findings may be helpful in understanding the mechanism of hand deficit after stroke, and the CPL may serve as a target region for hand rehabilitation following stroke.     

Default Mode Network Connectivity in Stroke Patients

The pathophysiology of episodic memory dysfunction after infarction is not completely understood. It has been suggested that infarctions located anywhere in the brain can induce widespread effects causing disruption of functional networks of the cortical regions. The default mode network, which includes the medial temporal lobe, is a functional network that is associated with episodic memory processing. We investigated whether the default mode network activity is reduced in stroke patients compared to healthy control subjects in the resting state condition. We assessed the whole brain network properties during resting state functional MRI in 21 control subjects and 20 ‘first-ever’ stroke patients. Patients were scanned 9–12 weeks after stroke onset. Stroke lesions were located in various parts of the brain. Independent component analyses were conducted to identify the default mode network and to compare the group differences of the default mode network. Furthermore, region-of-interest based analysis was performed to explore the functional connectivity between the regions of the default mode network. Stroke patients performed significantly worse than control subjects on the delayed recall score on California verbal learning test. We found decreased functional connectivity in the left medial temporal lobe, posterior cingulate and medial prefrontal cortical areas within the default mode network and reduced functional connectivity between these regions in stroke patients compared with controls. There were no significant volumetric differences between the groups. These results demonstrate that connectivity within the default mode network is reduced in ‘first-ever’ stroke patients compared to control subjects. This phenomenon might explain the occurrence of post-stroke cognitive dysfunction in stroke patients.     

Altered Functional Connectivity between Emotional and Cognitive Resting State Networks in Euthymic Bipolar I Disorder Patients

Bipolar disorder is characterized by a functional imbalance between hyperactive ventral/limbic areas and hypoactive dorsal/cognitive brain regions potentially contributing to affective and cognitive symptoms. Resting-state studies in bipolar disorder have identified abnormal functional connectivity between these brain regions. However, most of these studies used a seed-based approach, thus restricting the number of regions that were analyzed. Using data-driven approaches, researchers identified resting state networks whose spatial maps overlap with frontolimbic areas such as the default mode network, the frontoparietal networks, the salient network, and the meso/paralimbic network. These networks are specifically engaged during affective and cognitive tasks and preliminary evidence suggests that functional connectivity within and between some of these networks is impaired in bipolar disorder. The present study used independent component analysis and functional network connectivity approaches to investigate functional connectivity within and between these resting state networks in bipolar disorder. We compared 30 euthymic bipolar I disorder patients and 35 age- and gender-matched healthy controls. Inter-network connectivity analysis revealed increased functional connectivity between the meso/paralimbic and the right frontoparietal network in bipolar disorder. This abnormal connectivity pattern did not correlate with variables related to the clinical course of the disease. The present finding may reflect abnormal integration of affective and cognitive information in ventral-emotional and dorsal-cognitive networks in euthymic bipolar patients. Furthermore, the results provide novel insights into the role of the meso/paralimbic network in bipolar disorder.     

Structural integrity of the uncinate fasciculus and resting state functional connectivity of the ventral prefrontal cortex in late life depression

Background

Neuroimaging studies in late life depression have reported decreased structural integrity of white matter tracts in the prefrontal cortex. Functional studies have identified changes in functional connectivity among several key areas involved in mood regulation. Few studies have combined structural and functional imaging. In this study we sought to examine the relationship between the uncinate fasciculus, a key fronto-temporal tract and resting state functional connectivity between the ventral prefrontal cortex ((PFC) and limbic and striatal areas.

Methods

The sample consisted of 24 older patients remitted from unipolar major depression. Each participant had a magnetic resonance imaging brain scan using standardized protocols to obtain both diffusion tensor imaging and resting state functional connectivity data. Our statistical approach compared structural integrity of the uncinate fasciculus and functional connectivity data.

Results

We found positive correlations between left uncinate fasciculus (UF) fractional anisotropy (FA) and resting state functional connectivity (rsFC) between the left ventrolateral PFC and left amygdala and between the left ventrolateral PFC and the left hippocampus. In addition, we found a significant negative correlation between left ventromedial PFC-caudate rsFC and left UF FA. The right UF FA did not correlate with any of the seed region based connectivity.

Conclusions

These results support the notion that resting state functional connectivity reflects structural integrity, since the ventral PFC is structurally connected to temporal regions by the UF. Future studies should include larger samples of patients and healthy comparison subjects in which both resting state and task-based functional connectivity are examined.     

Enhanced Functional Connectivity between Putamen and Supplementary Motor Area in Parkinson’s Disease Patients

Parkinson’s disease (PD) is a surprisingly heterogeneous disorder with symptoms including resting tremor, bradykinesia and rigidity. PD has been associated with abnormal task related brain activation in sensory and motor regions as well as reward related network. Although corticostriatal skeletomotor circuit dysfunction is implicated in the neurobiology of Parkinson’s disease, the functional connectivity within this circuit at the resting state is still unclear for PD. Here we utilized resting state functional magnetic resonance imaging to measure the functional connectivity of striatum and motor cortex in 19 patients with PD and 20 healthy controls. We found that the putamen, but not the caudate, exhibited enhanced connectivity with supplementary motor area (SMA), using either the putamen or the SMA as the “seed region”. Enhanced SMA-amygdala functional connectivity was also found in the PD group, compared with normal controls. Our findings highlight the key role of hyper-connected putamen-SMC circuit in the pathophysiology of PD.     

Hierarchical Alteration of Brain Structural and Functional Networks in Female Migraine Sufferers

Background

Little is known about the changes of brain structural and functional connectivity networks underlying the pathophysiology in migraine. We aimed to investigate how the cortical network reorganization is altered by frequent cortical overstimulation associated with migraine.

Methodology/Principal Findings

Gray matter volumes and resting-state functional magnetic resonance imaging signal correlations were employed to construct structural and functional networks between brain regions in 43 female patients with migraine (PM) and 43 gender-matched healthy controls (HC) by using graph theory-based approaches. Compared with the HC group, the patients showed abnormal global topology in both structural and functional networks, characterized by higher mean clustering coefficients without significant change in the shortest absolute path length, which indicated that the PM lost optimal topological organization in their cortical networks. Brain hubs related to pain-processing revealed abnormal nodal centrality in both structural and functional networks, including the precentral gyrus, orbital part of the inferior frontal gyrus, parahippocampal gyrus, anterior cingulate gyrus, thalamus, temporal pole of the middle temporal gyrus and the inferior parietal gyrus. Negative correlations were found between migraine duration and regions with abnormal centrality. Furthermore, the dysfunctional connections in patients'' cortical networks formed into a connected component and three dysregulated modules were identified involving pain-related information processing and motion-processing visual networks.

Conclusions

Our results may reflect brain alteration dynamics resulting from migraine and suggest that long-term and high-frequency headache attacks may cause both structural and functional connectivity network reorganization. The disrupted information exchange between brain areas in migraine may be reshaped into a hierarchical modular structure progressively.     

Abnormal Brain Functional Connectivity of the Hypothalamus in Cluster Headaches

The aim of this study was to detect the abnormality of the brain functional connectivity of the hypothalamus during acute spontaneous cluster headache (CH) attacks (‘in attack’) and headache-free intervals (‘out of attack’) using resting-state functional magnetic resonance imaging (RS-fMRI) technique. The RS-fMRI data from twelve male CH patients during ‘in attack’ and ‘out of attack’ periods and twelve age- and sex-matched normal controls were analyzed by the region-of-interest -based functional connectivity method using SPM5 software. Abnormal brain functional connectivity of the hypothalamus is present in CH, which is located mainly in the pain system during the spontaneous CH attacks. It extends beyond the pain system during CH attack intervals.     

Reduced Fractional Anisotropy of Corpus Callosum Modulates Inter-Hemispheric Resting State Functional Connectivity in Migraine Patients without Aura

Background

Diffusion tensor imaging (DTI) study revealed reduced fractional anisotropy (FA) values in the corpus callosum (CC) in migraine patients without aura. Abnormalities in white matter integrity, particularly in the CC, may affect inter-hemispheric resting state functional connectivity (RSFC). Unfortunately, relatively little is known about the alterations in functional interactions between the cerebral hemispheres during resting state in migraine patients without aura, and even less about how the inter-hemispheric RSFC are affected by the abnormalities of the CC.

Methods and findings

Twenty-one migraine patients without aura and 21 healthy controls participated in this study, age-, sex-, and education-matched. Tract-based spatial statistics (TBSS) was employed to investigate the white matter alterations of the CC. Meanwhile, voxel-mirrored homotopic connectivity (VMHC) was used to compare the inter-hemispheric RSFC differences between the patients and controls. TBSS analysis revealed reduced FA values in the genu and the splenium of CC in patient group. VMHC analysis showed decreased inter-hemispheric RSFC of anterior cingulate cortex (ACC) in migraine patients without aura relative to that of the controls. Furthermore, in migraine patients without aura, the reduced FA values of the genu of CC correlated with the decreased inter-hemispheric RSFC of the ACC.

Conclusions

Our findings demonstrated that the migraine patients without aura showed reduced FA values of the genu of CC and decreased inter-hemispheric RSFC of the ACC. The correlation between the above structural and functional changes suggested that the reduced fractional anisotropy (FA) of CC modulates inter-hemispheric VMHC in migraine patients without aura. Our results demonstrated that the VMHC alterations of ACC can reflect the FA changes of the genu of CC in migraine patients without aura.     

Evaluation of Resting State Networks in Patients with Gliomas: Connectivity Changes in the Unaffected Side and Its Relation to Cognitive Function

In this study, we investigated changes in resting state networks (RSNs) in patients with gliomas located in the left hemisphere and its relation to cognitive function. We hypothesized that long distance connection, especially between hemispheres, would be affected by the presence of the tumor. We further hypothesized that these changes would correlate with, or reflect cognitive changes observed in patients with gliomas. Resting state functional MRI datasets from 12 patients and 12 healthy controls were used in the analysis. The tumor’s effect on three well-known RSNs including the default mode network (DMN), executive control network (ECN), and salience network (SN) identified using independent component analysis were investigated using dual regression analysis. Scores of neuropsychometric testing (WAIS-III and WMS-R) were also compared. Compared to the healthy control group, the patient group showed significant decrease in functional connectivity in the right angular gyrus/inferior parietal lobe of the ventral DMN and in the dorsolateral prefrontal cortex of the left ECN, whereas a significant increase in connectivity in the right ECN was observed in the right parietal lobe. Changes in connectivity in the right ECN correlated with spatial memory, while that on the left ECN correlated with attention. Connectivity changes in the ventral DMN correlated with attention, working memory, full IQ, and verbal IQ measures. Although the tumors were localized in the left side of the brain, changes in connectivity were observed in the contralateral side. Moreover, these changes correlated with some aspects of cognitive function indicating that patients with gliomas may undergo cognitive changes even in the absence of or before the onset of major symptoms. Evaluation of resting state networks could be helpful in advancing our hodological understanding of brain function in glioma cases.     

Relations between BOLD fMRI-Derived Resting Brain Activity and Cerebral Blood Flow

Consistent resting brain activity patterns have been repeatedly demonstrated using measures derived from resting BOLD fMRI data. While those metrics are presumed to reflect underlying spontaneous brain activity (SBA), it is challenging to prove that association because resting BOLD fMRI metrics are purely model-free and scale-free variables. Cerebral blood flow (CBF) is typically closely coupled to brain metabolism and is used as a surrogate marker for quantifying regional brain function, including resting function. Assessing the correlations between resting BOLD fMRI measures and CBF correlation should provide a means of linking of those measures to the underlying SBA, and a means to quantify those scale-free measures. The purpose of this paper was to examine the CBF correlations of 3 widely used neuroimaging-based SBA measures, including seed-region based functional connectivity (FC), regional homogeneity (ReHo), and amplitude of low frequency fluctuation (ALFF). Test-retest data were acquired to check the stability of potential correlations across time. Reproducible posterior cingulate cortex (PCC) FC vs regional CBF correlations were found in much of the default mode network and visual cortex. Dorsal anterior cingulate cortex (ACC) FC vs CBF correlations were consistently found in bilateral prefrontal cortex. Both ReHo and ALFF were found to be reliably correlated with CBF in most of brain cortex. None of the assessed SBA measures was correlated with whole brain mean CBF. These findings suggest that resting BOLD fMRI-derived measures are coupled with regional CBF and are therefore linked to regional SBA.     

Disrupted Functional Brain Connectivity and Its Association to Structural Connectivity in Amnestic Mild Cognitive Impairment and Alzheimer’s Disease

Although anomalies in the topological architecture of whole-brain connectivity have been found to be associated with Alzheimer’s disease (AD), our understanding about the progression of AD in a functional connectivity (FC) perspective is still rudimentary and few study has explored the function-structure relations in brain networks of AD patients. By using resting-state functional MRI (fMRI), this study firstly investigated organizational alternations in FC networks in 12 AD patients, 15 amnestic mild cognitive impairment (aMCI) patients, and 14 age-matched healthy aging subjects and found that all three groups exhibit economical small-world network properties. Nonetheless, we found a decline of the optimal architecture in the progression of AD, represented by a more localized modular organization with less efficient local information transfer. Our results also show that aMCI forms a boundary between normal aging and AD and represents a functional continuum between healthy aging and the earliest signs of dementia. Moreover, we revealed a dissociated relationship between the overall FC and structural connectivity (SC) in AD patients. In this study, diffusion tensor imaging tractography was used to map the structural network of the same individuals. The decreased FC-SC coupling may be indicative of more stringent and less dynamic brain function in AD patients. Our findings provided insightful implications for understanding the pathophysiological mechanisms of brain dysfunctions in aMCI and AD patients and demonstrated that functional disorders can be characterized by multimodal neuroimaging-based metrics.     

Disrupted functional brain connectivity in partial epilepsy: a resting-state fMRI study

Examining the spontaneous activity to understand the neural mechanism of brain disorder is a focus in recent resting-state fMRI. In the current study, to investigate the alteration of brain functional connectivity in partial epilepsy in a systematical way, two levels of analyses (functional connectivity analysis within resting state networks (RSNs) and functional network connectivity (FNC) analysis) were carried out on resting-state fMRI data acquired from the 30 participants including 14 healthy controls(HC) and 16 partial epilepsy patients. According to the etiology, all patients are subdivided into temporal lobe epilepsy group (TLE, included 7 patients) and mixed partial epilepsy group (MPE, 9 patients). Using group independent component analysis, eight RSNs were identified, and selected to evaluate functional connectivity and FNC between groups. Compared with the controls, decreased functional connectivity within all RSNs was found in both TLE and MPE. However, dissociating patterns were observed within the 8 RSNs between two patient groups, i.e, compared with TLE, we found decreased functional connectivity in 5 RSNs increased functional connectivity in 1 RSN, and no difference in the other 2 RSNs in MPE. Furthermore, the hierarchical disconnections of FNC was found in two patient groups, in which the intra-system connections were preserved for all three subsystems while the lost connections were confined to intersystem connections in patients with partial epilepsy. These findings may suggest that decreased resting state functional connectivity and disconnection of FNC are two remarkable characteristics of partial epilepsy. The selective impairment of FNC implicated that it is unsuitable to understand the partial epilepsy only from global or local perspective. We presumed that studying epilepsy in the multi-perspective based on RSNs may be a valuable means to assess the functional changes corresponding to specific RSN and may contribute to the understanding of the neuro-pathophysiological mechanism of epilepsy.     

Functional Connectivity Alterations in Epilepsy from Resting-State Functional MRI

The study of functional brain connectivity alterations induced by neurological disorders and their analysis from resting state functional Magnetic Resonance Imaging (rfMRI) is generally considered to be a challenging task. The main challenge lies in determining and interpreting the large-scale connectivity of brain regions when studying neurological disorders such as epilepsy. We tackle this challenging task by studying the cortical region connectivity using a novel approach for clustering the rfMRI time series signals and by identifying discriminant functional connections using a novel difference statistic measure. The proposed approach is then used in conjunction with the difference statistic to conduct automatic classification experiments for epileptic and healthy subjects using the rfMRI data. Our results show that the proposed difference statistic measure has the potential to extract promising discriminant neuroimaging markers. The extracted neuroimaging markers yield 93.08% classification accuracy on unseen data as compared to 80.20% accuracy on the same dataset by a recent state-of-the-art algorithm. The results demonstrate that for epilepsy the proposed approach confirms known functional connectivity alterations between cortical regions, reveals some new connectivity alterations, suggests potential neuroimaging markers, and predicts epilepsy with high accuracy from rfMRI scans.