Microstructural alterations of white matter in juvenile myoclonic epilepsy

MRI-Based Radiomics Approach for Differentiating Juvenile Myoclonic Epilepsy from Epilepsy with Generalized Tonic-Clonic Seizures Alone

BACKGROUND

The clinical presentation of juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic-clonic seizures alone (GTCA) is similar, and MRI scans are often perceptually normal in both conditions making them challenging to differentiate.

PURPOSE

To develop and validate an MRI-based radiomics model to accurately diagnose JME and GTCA, as well as to classify prognostic groups.

STUDY TYPE

Retrospective.

POPULATION

164 patients (127 with JME and 37 with GTCA) patients (age 24.0 ± 9.6; 50% male), divided into training (n = 114) and test (n = 50) sets in a 7:3 ratio with the same proportion of JME and GTCA patients kept in both sets.

FIELD STRENGTH/SEQUENCE

3T; 3D T1-weighted spoiled gradient-echo.

ASSESSMENT

A total of 17 region-of-interest in the brain were identified as having clinical evidence of association with JME and GTCA, from where 1581 radiomics features were extracted for each subject. Forty-eight machine-learning combinations of oversampling, feature selection, and classification algorithms were explored to develop an optimal radiomics model. The performance of the best radiomics models for diagnosis and for classification of the favorable outcome group were evaluated in the test set.

STATISTICAL TESTS

Model performance measured using area under the curve (AUC) of receiver operating characteristic (ROC) curve. Shapley additive explanations (SHAP) analysis to estimate the contribution of each radiomics feature.

RESULTS

The AUC (95% confidence interval) of the best radiomics models for diagnosis and for classification of favorable outcome group were 0.767 (0.591-0.943) and 0.717 (0.563-0.871), respectively. SHAP analysis revealed that the first-order and textural features of the caudate, cerebral white matter, thalamus proper, and putamen had the highest importance in the best radiomics model.

CONCLUSION

The proposed MRI-based radiomics model demonstrated the potential to diagnose JME and GTCA, as well as to classify prognostic groups. MRI regions associated with JME, such as the basal ganglia, thalamus, and cerebral white matter, appeared to be important for constructing radiomics models.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 3.

Diffusion tensor imaging in photosensitive and nonphotosensitive juvenile myoclonic epilepsy

INTRODUCTION/BACKGROUND

Juvenile myoclonic epilepsy (JME) syndrome is known to cause alterations in brain structure and white matter integrity. The study aimed to determine structural white matter changes in patients with JME and to reveal the differences between the photosensitive (PS) and nonphotosensitive (NPS) subgroups by diffusion tensor imaging (DTI) using the tract-based spatial statistics (TBSS) method.

METHODS

This study included data from 16 PS, 15 NPS patients with JME, and 41 healthy participants. The mean fractional anisotropy (FA) values of these groups were calculated, and comparisons were made via the TBSS method over FA values in the whole-brain and 81 regions of interest (ROI) obtained from the John Hopkins University White Matter Atlas.

RESULTS

In the whole-brain TBSS analysis, no significant differences in FA values were observed in pairwise comparisons of JME patient group and subgroups with healthy controls (HCs) and in comparison between JME subgroups. In ROI-based TBSS analysis, an increase in FA values of right anterior corona radiata and left corticospinal pathways was found in JME patient group compared with HC group. When comparing JME-PS patients with HCs, an FA increase was observed in the bilateral anterior corona radiata region, whereas when comparing JME-NPS patients with HCs, an FA increase was observed in bilateral corticospinal pathway. Moreover, in subgroup comparison, an increase in FA values was noted in corpus callosum genu region in JME-PS compared with JME-NPS.

CONCLUSIONS

Our results support the disruption in thalamofrontal white matter integrity in JME, and subgroups and highlight the importance of using different analysis methods to show the underlying microstructural changes.

Multi-spectral diffusion MRI mega-analysis in genetic generalized epilepsy: Relation to outcomes

BACKGROUND AND OBJECTIVES

Genetic generalized epilepsy (GGE) is the most common form of generalized epilepsy. Although individual patients with GGE typically present without structural alterations, group differences have been demonstrated in GGE and some GGE subtypes like juvenile myoclonic epilepsy (GGE-JME). Previous studies usually involved only small cohorts from single centers and therefore could not assess imaging markers of multiple GGE subtypes.

METHODS

We performed a diffusion MRI mega-analysis in 192 participants consisting of 126 controls and 66 patients with GGE from four different cohorts and two different epilepsy centers. We applied whole-brain multi-site harmonization and analyzed fractional anisotropy (FA), as well as mean, radial and axial diffusivity (MD/RD/AD) to assess differences between controls, patients with GGE and the common GGE subtypes, i.e. GGE with generalized tonic-clonic seizures only (GGE-GTCS), GGE-JME and absence epilepsy (GGE-AE). We also analyzed relationships with patients' response to anti-seizure-medication (ASM).

RESULTS

Relative to controls, we identified decreased anisotropy and increased RD in patients with GGE. We found no significant effects of disease duration, age of onset or seizure frequency on diffusion metrics. Patients with JME had increased MD and RD when compared to controls, while patients with GGE-GTCS showed decreased MD/AD when compared to controls. Compared to patients with GGE-AE, patients with GGE-GTCS had lower AD/MD. Compared to patients with GGE-GTCS, patients with GGE-JME had higher MD/RD and AD. Moreover, we found lower FA in patients with refractory when compared to patients with non-refractory GGE in the right cortico-spinal tract, but no significant differences in patients with active versus controlled epilepsy.

DISCUSSION

We provide evidence that clinically defined GGE as a whole and GGE-subtypes harbor marked microstructural differences detectable with diffusion MRI. Moreover, we found an association between microstructural changes and treatment resistance. Our findings have important implications for future full-resolution multi-site studies when assessing GGE, its subtypes and ASM refractoriness.

Altered Cerebellar Volumes and Intrinsic Cerebellar Network in Juvenile Myoclonic Epilepsy

Objectives. This study is aimed at investigating the alterations in cerebellar volumes and intrinsic cerebellar network in patients with juvenile myoclonic epilepsy (JME) in comparison with healthy controls. Methods. Patients newly diagnosed with JME and healthy controls were enrolled. Three-dimensional T1-weighted imaging was conducted, and no structural lesions were found on brain magnetic resonance imaging. Cerebellar volumes were obtained using the ACAPULCO program, while the intrinsic cerebellar network was evaluated by applying graph theory using the BRAPH program. The nodes were defined as individual cerebellar volumes and edges as partial correlations, controlling for the effects of age and sex. Cerebellar volumes and intrinsic cerebellar networks were compared between the two groups. Results. Forty-five patients with JME and 45 healthy controls were enrolled. Compared with the healthy controls, the patients with JME had significantly lower volumes of the right and left cerebellar white matter (3.33 vs. 3.48%, $p=0.009$ ; 3.35 vs. 3.49%, $p=0.009$ ), corpus medullare (0.99 vs. 1.03%, $p=0.04$ ), and left lobule V (0.19 vs. 0.22%, $p=0.002$ ). The intrinsic cerebellar networks also showed significant differences between the two groups. The small-worldness index in the patients with JME was significantly lower than that in the healthy controls (0.771 vs. 0.919, $p=0.04$ ). Conclusion. The cerebellar volumes and intrinsic cerebellar network demonstrated alterations in the patients with JME when compared with those of the healthy controls. Our study results provide evidence that the cerebellum may play a role in the pathogenesis of JME.

The brainstem connections of the supplementary motor area and its relations to the corticospinal tract: Experimental rat and human 3-tesla tractography study

Although the supplementary motor area (SMA) is a large region on the medial surface of the frontal lobe of the brain, little is known about its function. The current study uses 3-tesla high-resolution diffusion tensor tractography (DTI) in healthy individuals and biotinylated dextran amine (BDA) and fluoro-gold (FG) tracer in rats to demonstrate the afferent and efferent connections of the SMA with brainstem structures. It also aims to clarify how SMA fibers relate to the corticospinal tract (CST). The BDA (n = 6) and FG (n = 8) tracers were pressure-injected into the SMA of 14 Wistar albino rats. Light and fluorescence microscopy was used to capture images of the FG and BDA-labeled cells and axons. High-resolution 3-tesla DTI data were acquired from the Human Connectome Project database. Tracts between the SMA and brainstem structures were analyzed using diffusion spectrum imaging (DSI) studio software. The FG injections into the SMA showed afferent projections from mesencephalic (periaqueductal gray matter, substantia nigra pars reticulata, ventral tegmental area, inferior colliculus, mesencephalic reticular, tegmental, and raphe nuclei), pontine (locus coeruleus, pontine reticular and vestibular nuclei), and medullary (area postrema, parabrachial, and medullary reticular nuclei) structures. The anterograde tracer BDA injections into the SMA showed efferent connections with mesencephalic (periaqueductal gray, substantia nigra pars compacta, dorsal raphe, trigeminal motor mesencephalic, and mesencephalic reticular nuclei), pontine (locus coeruleus, nucleus of the lateral lemniscus, vestibular, cochlear, and pontine reticular nuclei), and medullary (area postrema, medullary reticular, olivary, and parabrachial nuclei) structures. The SMA had efferent but no afferent connections with the cerebellar nuclei. The DTI results in healthy human subjects highly corresponded with the experimental results. Further, the DTI results showed a distinct bundle that descended to spinal levels closely related to the CST. Understanding SMA's afferent and efferent connections will enrich our knowledge of its contribution to various brainstem networks and may provide new perspectives for understanding its motor and non-motor functions.

Brain diffusion tensor imaging reveals altered connections and networks in epilepsy patients

Introduction

Accumulating evidence shows that epilepsy is a disease caused by brain network dysfunction. This study explored changes in brain network structure in epilepsy patients based on graph analysis of diffusion tensor imaging data.

Methods

The brain structure networks of 42 healthy control individuals and 26 epilepsy patients were constructed. Using graph theory analysis, global and local network topology parameters of the brain structure network were calculated, and changes in global and local characteristics of the brain network in epilepsy patients were quantitatively analyzed.

Results

Compared with the healthy control group, the epilepsy patient group showed lower global efficiency, local efficiency, clustering coefficient, and a longer shortest path length. Both healthy control individuals and epilepsy patients showed small-world attributes, with no significant difference between groups. The epilepsy patient group showed lower nodal local efficiency and nodal clustering coefficient in the right olfactory cortex and right rectus and lower nodal degree centrality in the right olfactory cortex and the left paracentral lobular compared with the healthy control group. In addition, the epilepsy patient group showed a smaller fiber number of edges in specific regions of the frontal lobe, temporal lobe, and default mode network, indicating reduced connection strength.

Discussion

Epilepsy patients exhibited lower global and local brain network properties as well as reduced white matter fiber connectivity in key brain regions. These findings further support the idea that epilepsy is a brain network disorder.

Altered neurovascular coupling in children with idiopathic generalized epilepsy

AIMS

Alterations in neuronal activity and cerebral hemodynamics have been reported in idiopathic generalized epilepsy (IGE) patients, possibly resulting in neurovascular decoupling; however, no neuroimaging evidence confirmed this disruption. This study aimed to investigate the possible presence of neurovascular decoupling and its clinical implications in childhood IGE using resting-state fMRI and arterial spin labeling imaging.

METHODS

IGE patients and healthy participants underwent resting-state fMRI and arterial spin labeling imaging to calculate degree centrality (DC) and cerebral blood flow (CBF), respectively. Across-voxel CBF-DC correlations were analyzed to evaluate the neurovascular coupling within the whole gray matter, and the regional coupling of brain region was assessed with the CBF/DC ratio.

RESULTS

The study included 26 children with IGE and 35 sex- and age-matched healthy controls (HCs). Compared with the HCs, the IGE group presented lower across-voxel CBF-DC correlations, higher CBF/DC ratio in the right posterior cingulate cortex/precuneus, middle frontal gyrus, and medial frontal gyrus (MFG), and lower ratio in the left inferior frontal gyrus. The increased CBF/DC ratio in the right MFG was correlated with lower performance intelligence quotient scores in the IGE group.

CONCLUSION

Children with IGE present altered neurovascular coupling, associated with lower performance intelligence quotient scores. The study shed a new insight into the pathophysiology of epilepsy and provided potential imaging biomarkers of cognitive performances in children with IGE.

Development and Validation of MRI-Based Radiomics Models for Diagnosing Juvenile Myoclonic Epilepsy

OBJECTIVE

Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME.

MATERIALS AND METHODS

A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified.

RESULTS

The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME.

CONCLUSION

Radiomic models using MRI were able to differentiate JME from HCs.

Relationship of white matter hyperintensities with clinical features of seizures in patients with epilepsy

BACKGROUND

Although epilepsy is primarily known as a cortical disorder, there is growing body of research demonstrating white matter alterations in patients with epilepsy.

OBJECTIVE

To investigate the prevalence of white matter hyperintensities (WMH) and its association with seizure characteristics in patients with epilepsy.

METHODS

The prevalence of WMH in 94 patients with epilepsy and 41 healthy controls were compared. Within the patient sample, the relationship between the presence of WMH and type of epilepsy, frequency of seizures, duration of disease and the number of antiepileptic medications were investigated.

RESULTS

The mean age and sex were not different between patients and healthy controls (p>0.2). WMH was present in 27.7% of patients and in 14.6% of healthy controls. Diagnosis of epilepsy was independently associated with the presence of WMH (ß=3.09, 95%CI 1.06-9.0, p=0.039). Patients with focal epilepsy had higher prevalence of WMH (35.5%) than patients with generalized epilepsy (14.7%). The presence of WMH was associated with older age but not with seizure characteristics.

CONCLUSIONS

WMH is more common in patients with focal epilepsy than healthy controls. The presence of WMH is associated with older age, but not with seizure characteristics.

Subtle Brain Developmental Abnormalities in the Pathogenesis of Juvenile Myoclonic Epilepsy

Juvenile myoclonic epilepsy (JME), a lifelong disorder that starts during adolescence, is the most common of genetic generalized epilepsy syndromes. JME is characterized by awakening myoclonic jerks and myoclonic-tonic-clonic (m-t-c) grand mal convulsions. Unfortunately, one third of JME patients have drug refractory m-t-c convulsions and these recur in 70-80% who attempt to stop antiepileptic drugs (AEDs). Behavioral studies documented impulsivity, but also impairment of executive functions relying on organization and feedback, which points to prefrontal lobe dysfunction. Quantitative voxel-based morphometry (VBM) revealed abnormalities of gray matter (GM) volumes in cortical (frontal and parietal) and subcortical structures (thalamus, putamen, and hippocampus). Proton magnetic resonance spectroscopy (MRS) found evidence of dysfunction of thalamic neurons. White matter (WM) integrity was disrupted in corpus callosum and frontal WM tracts. Magnetic resonance imaging (MRI) further unveiled anomalies in both GM and WM structures that were already present at the time of seizure onset. Aberrant growth trajectories of brain development occurred during the first 2 years of JME diagnosis. Because of genetic origin, disease causing variants were sought, first by positional cloning, and most recently, by next generation sequencing. To date, only six genes harboring pathogenic variants (GABRA1, GABRD, EFHC1, BRD2, CASR, and ICK) with Mendelian and complex inheritance and covering a limited proportion of the world population, are considered as major susceptibility alleles for JME. Evidence on the cellular role, developmental and cell-type expression profiles of these six diverse JME genes, point to their pathogenic variants driving the first steps of brain development when cell division, expansion, axial, and tangential migration of progenitor cells (including interneuron cortical progenitors) sculpture subtle alterations in brain networks and microcircuits during development. These alterations may explain "microdysgenesis" neuropathology, impulsivity, executive dysfunctions, EEG polyspike waves, and awakening m-t-c convulsions observed in JME patients.

Structural and functional connectivity in newly diagnosed juvenile myoclonic epilepsy

OBJECTIVES

We aimed to evaluate structural and functional connectivity of patients with newly diagnosed juvenile myoclonic epilepsy (JME) compared to healthy subjects.

METHODS

We enrolled 36 patients with a diagnosis of JME, who were newly diagnosed and drug-naïve. They underwent T1-weighted imaging, and structural volumes were calculated using FreeSurfer software. In addition, EEG data were obtained from all of them. Structural and functional connectivity matrices were estimated by calculating the structural volumes and EEG amplitude correlation, respectively. Then, the connectivity measures were calculated using the BRAPH program. We also enrolled healthy subjects to compare its structural and functional connectivity with the patients with JME.

RESULTS

We observed that patients with JME exhibited significantly different functional and structural connectivity compared to healthy control subjects. In the global structural connectivity, global efficiency, and local efficiency, and small-worldness index were decreased, whereas characteristic path length was increased in patients with JME. Betweenness centrality of cingulate, precentral, superior parietal, and superior frontal cortex was increased in patients with JME whereas that of hippocampus was decreased. In the functional connectivity, the betweenness centrality of the fronto-central electrodes was significantly increased.

CONCLUSIONS

This study reports that the structural connectivity and functional connectivity in patients with JME are significantly different from those in healthy control subjects, even those with newly diagnosed drug-naive state. The patients with JME exhibited disrupted topological disorganization of the global brain network and hub reorganization in structural and functional connectivity. These alterations are implicated in the pathogenesis of JME and suggestive of network disease.

Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy

Patients with idiopathic generalised epilepsy (IGE) typically have normal conventional magnetic resonance imaging (MRI), hence diagnosis based on MRI is challenging. Anatomical abnormalities underlying brain dysfunctions in IGE are unclear and their relation to the pathomechanisms of epileptogenesis is poorly understood.

In this study, we applied connectometry, an advanced quantitative neuroimaging technique for investigating localised changes in white-matter tissues in vivo. Analysing white matter structures of 32 subjects we incorporated our in vivo findings in a computational model of seizure dynamics to suggest a plausible mechanism of epileptogenesis.

Patients with IGE have significant bilateral alterations in major white-matter fascicles. In the cingulum, fornix, and superior longitudinal fasciculus, tract integrity is compromised, whereas in specific parts of tracts between thalamus and the precentral gyrus, tract integrity is enhanced in patients. Combining these alterations in a logistic regression model, we computed the decision boundary that discriminated patients and controls. The computational model, informed with the findings on the tract abnormalities, specifically highlighted the importance of enhanced cortico-reticular connections along with impaired cortico-cortical connections in inducing pathological seizure-like dynamics.

We emphasise taking directionality of brain connectivity into consideration towards understanding the pathological mechanisms; this is possible by combining neuroimaging and computational modelling. Our imaging evidence of structural alterations suggest the loss of cortico-cortical and enhancement of cortico-thalamic fibre integrity in IGE. We further suggest that impaired connectivity from cortical regions to the thalamic reticular nucleus offers a therapeutic target for selectively modifying the brain circuit for reversing the mechanisms leading to epileptogenesis.

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Significant focal alterations along major white-matter fascicles in IGE patients are characterised.

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Increased white matter integrity found in thalamo-cortical connections.

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Decreased white matter integrity found in cortico-cortical connections.

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Disease mechanism is investigated by combining the neuroimaging findings with a dynamical model of seizure activity.

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Model implicates cortical projections to the thalamic reticular nucleus in IGE.

Disrupted Coupling Between the Spontaneous Fluctuation and Functional Connectivity in Idiopathic Generalized Epilepsy

Purpose: The purpose of this study was to comprehensively evaluate alterations of resting-state spontaneous brain activity in patients with idiopathic generalized epilepsy (IGE) and its subgroups [juvenile myoclonic epilepsy (JME) and generalized tonic-clonic seizures (GTCS)]. Methods: Resting state functional magnetic resonance imaging (fMRI) data were acquired from 60 patients with IGE and 60 healthy controls (HCs). Amplitude of low frequency fluctuation (ALFF), global functional connectivity density (gFCD), local FCD (lFCD), and long range FCD (lrFCD) were used to evaluate spontaneous brain activity in the whole brain. Moreover, the coupling between ALFF and FCDs (gFCD, lFCD, and lrFCD) was analyzed on both voxel-wise and subject-wise levels. Two-sample t-tests were used to analyze the difference in ALFF, FCDs and coupling on a subject-wise level between the two groups. Nonparametric permutation tests were used to evaluate differences in coupling on a voxel-wise level. Key findings: Patients with IGE and its subgroups showed reduced ALFF, gFCD and lrFCD in posterior regions of the default mode network (DMN). In addition, decreased ALFF and increased coupling with FCD were found in the cerebellum, while decreased coupling was observed in the bilateral pre- and postcentral gyrus in IGE compared with the coupling in HCs. Similar findings were found in the analysis between each of the two subgroups of IGE (JME and GTCS) and HCs, and JME patients had increased coupling in the cerebellum and bilateral middle occipital gyrus compared with coupling in the GTCS patients. Significance: This study demonstrated a multifactor abnormality of the DMN in IGE and emphasized that the abnormality in the cerebellum was associated with dysfunctional motor symptoms during seizures and might participate in the regulation of GSWDs in IGE.

Juvenile Myoclonic Epilepsy Shows Potential Structural White Matter Abnormalities: A TBSS Study

Background: Several studies on patients with juvenile myoclonic epilepsy (JME) showed widespread white matter (WM) abnormalities in the brain. The aim of this study was to investigate potential structural abnormalities in JME patients (1) compared to healthy controls, (2) among JME subgroups with or without photoparoxysmal responses (PPR), and (3) in correlation with clinical variables. Methods: A selection of 31 patients with JME (12 PPR positive) and 27 age and gender matched healthy controls (HC) were studied at a tertiary epilepsy center. Fractional anisotropy (FA) was calculated and intergroup differences analyzed using Tract Based Spatial Statistics (TBSS). Results: Compared to HC the JME group showed reduced FA widespread and bilateral in the longitudinal fasciculus, inferior fronto-occipital fasciculus, corticospinal tract, anterior and posterior thalamic radiation, corona radiata, corpus callosum, cingulate gyrus and external capsule (p < 0.01). Subgroup analysis revealed no significant differences of WM alterations between PPR positive and negative patients and with clinical and epilepsy-related factors. Conclusions: Widespread microstructural abnormalities among patients with JME have been identified.Prior findings of frontal and thalamofrontal microstructural abnormalities have been confirmed. Additionally, microstructural abnormalities were found in widespread extra-frontal regions that may help to validate pathophysiological concepts of JME.

Aberrant Thalamocortical Connectivity in Juvenile Myoclonic Epilepsy

The purpose of this study was to investigate the functional connectivity (FC) of thalamic subdivisions in patients with juvenile myoclonic epilepsy (JME). Resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data were acquired from 22 JME and 25 healthy controls. We first divided the thalamus into eight subdivisions by performing independent component analysis on tracking fibers and clustering thalamus-related FC maps. We then analyzed abnormal FC in each subdivision in JME compared with healthy controls, and we investigated their associations with clinical features. Eight thalamic sub-regions identified in the current study showed unbalanced thalamic FC in JME: decreased FC with the superior frontal gyrus and enhanced FC with the supplementary motor area in the posterior thalamus increased thalamic FC with the salience network (SN) and reduced FC with the default mode network (DMN). Abnormalities in thalamo-prefrontocortical networks might be related to the propagation of generalized spikes with frontocentral predominance in JME, and the network connectivity differences with the SN and DMN might be implicated in emotional and cognitive defects in JME. JME was also associated with enhanced FC among thalamic sub-regions and with the basal ganglia and cerebellum, suggesting the regulatory role of subcortical nuclei and the cerebellum on the thalamo-cortical circuit. Additionally, increased FC with the pallidum was positive related with the duration of disease. The present study provides emerging evidence of FC to understand that specific thalamic subdivisions contribute to the abnormalities of thalamic-cortical networks in JME. Moreover, the posterior thalamus could play a crucial role in generalized epileptic activity in JME.

Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures

The purpose of this study was to evaluate the spatiotemporal Consistency of spontaneous activities in local brain regions in patients with generalized tonic-clonic seizures (GTCS). The resting-state fMRI data were acquired from nineteen patients with GTCS and twenty-two matched healthy subjects. FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) metric was used to analyze the spontaneous activity in whole brain. The FOCA difference between two groups were detected using a two sample t-test analysis. Correlations between the FOCA values and features of seizures were analyzed. The findings of this study showed that patients had significantly increased FOCA in motor-related cortex regions, including bilateral supplementary motor area, paracentral lobule, precentral gyrus and left basal ganglia, as well as a substantial reduction of FOCA in regions of default mode network (DMN) and parietal lobe. In addition, several brain regions in DMN demonstrated more reduction with longer duration of epilepsy and later onset age, and the motor-related regions showed higher FOCA value in accompany with later onset age. These findings implicated the abnormality of motor-related cortical network in GTCS which were associated with the genesis and propagation of epileptiform activity. And the decreased FOCA in DMN might reflect the intrinsic disturbance of brain activity. Moreover, our study supported that the FOCA might be potential tool to investigate local brain spontaneous activity related with the epileptic activity, and to provide important insights into understanding the underlying pathophysiological mechanisms of GTCS.