Alteration of cerebello-thalamocortical spontaneous low-frequency oscillations in juvenile myoclonic epilepsy

Increased cerebellar vermis volume following repetitive transcranial magnetic stimulation in drug-resistant epilepsy: a voxel-based morphometry study

Introduction

Voxel-based morphometry (VBM) was applied to explore structural changes induced by repetitive transcranial magnetic stimulation (rTMS) and the relationship with clinical outcomes. Moreover, the relationship between each segmented regional gray matter (GM) volume was investigated to identify circuits involved in the rTMS treatment process in patients with drug-resistant epilepsy (DRE).

Methods

Nineteen patients with DRE were finally included in the analysis. A session of rTMS was applied for 5 consecutive days. Participants received either 1,000 or 3,000 pulses, at a frequency of 0.5 Hz and the intensity was set at 90% of the individual's resting motor threshold. VBM analysis was performed to explore regional GM volume changes 2 months after rTMS application. The regional volume change was correlated with seizure reduction rate. Relationships between changes in GM volume in each anatomically parcellated region were analyzed using a fully-automated segmentation pipeline.

Results

Compared to the baseline, seizure frequency was reduced, and quality of life was improved after rTMS treatment. Regional volume was increased in the cerebellar vermis 2 months after rTMS application. The increased cerebellar vermis volume correlated with the reduced seizure frequency. Regional volume changes in the cerebellar vermis were correlated with changes in the subcortical and cortical GM regions including the thalamus, caudate, and frontal cortex.

Discussion

These results indicate that rTMS treatment effectively reduced seizure frequency in patients with DRE. Increased volume in the cerebellar vermis and activations of the cerebello-thalamo-cortical circuit may be a crucial mechanism underlying the effectiveness of rTMS application in patients with DRE.

Development and Validation of Artificial Intelligence Models for Prognosis Prediction of Juvenile Myoclonic Epilepsy with Clinical and Radiological Features

Background: Juvenile myoclonic epilepsy (JME) is a common adolescent epilepsy characterized by myoclonic, generalized tonic-clonic, and sometimes absence seizures. Prognosis varies, with many patients experiencing relapse despite pharmacological treatment. Recent advances in imaging and artificial intelligence suggest that combining microstructural brain changes with traditional clinical variables can enhance potential prognostic biomarkers identification. Methods: A retrospective study was conducted on patients with JME at the Severance Hospital, analyzing clinical variables and magnetic resonance imaging (MRI) data. Machine learning models were developed to predict prognosis using clinical and radiological features. Results: The study utilized six machine learning models, with the XGBoost model demonstrating the highest predictive accuracy (AUROC 0.700). Combining clinical and MRI data outperformed models using either type of data alone. The key features identified through a Shapley additive explanation analysis included the volumes of the left cerebellum white matter, right thalamus, and left globus pallidus. Conclusions: This study demonstrated that integrating clinical and radiological data enhances the predictive accuracy of JME prognosis. Combining these neuroanatomical features with clinical variables provided a robust prediction of JME prognosis, highlighting the importance of integrating multimodal data for accurate prognosis.

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.

Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI

BACKGROUND

Hyperkinetic movement disorders (HMD) manifest as abnormal and uncontrollable movements. Despite reported involvement of several neural circuits, exact connectivity profiles remain elusive.

OBJECTIVES

Providing a comprehensive literature review of resting-state brain connectivity alterations using resting-state fMRI (rs-fMRI). We additionally discuss alterations from the perspective of brain networks, as well as correlations between connectivity and clinical measures.

METHODS

A systematic review was performed according to PRISMA guidelines and searching PubMed until October 2022. Rs-fMRI studies addressing ataxia, chorea, dystonia, myoclonus, tics, tremor, and functional movement disorders (FMD) were included. The standardized mean difference was used to summarize findings per region in the Automated Anatomical Labeling atlas for each phenotype. Furthermore, the activation likelihood estimation meta-analytic method was used to analyze convergence of significant between-group differences per phenotype. Finally, we conducted hierarchical cluster analysis to provide additional insights into commonalities and differences across HMD phenotypes.

RESULTS

Most articles concerned tremor (51), followed by dystonia (46), tics (19), chorea (12), myoclonus (11), FMD (11), and ataxia (8). Altered resting-state connectivity was found in several brain regions: in ataxia mainly cerebellar areas; for chorea, the caudate nucleus; for dystonia, sensorimotor and basal ganglia regions; for myoclonus, the thalamus and cingulate cortex; in tics, the basal ganglia, cerebellum, insula, and frontal cortex; for tremor, the cerebello-thalamo-cortical circuit; finally, in FMD, frontal, parietal, and cerebellar regions. Both decreased and increased connectivity were found for all HMD. Significant spatial convergence was found for dystonia, FMD, myoclonus, and tremor. Correlations between clinical measures and resting-state connectivity were frequently described.

CONCLUSION

Key brain regions contributing to functional connectivity changes across HMD often overlap. Possible increases and decreases of functional connections of a specific region emphasize that HMD should be viewed as a network disorder. Despite the complex interplay of physiological and methodological factors, this review serves to gain insight in brain connectivity profiles across HMD phenotypes.

Altered Cerebro-Cerebellar Effective Connectivity in New-Onset Juvenile Myoclonic Epilepsy

(1) Objective: Resting-state fMRI studies have indicated that juvenile myoclonic epilepsy (JME) could cause widespread functional connectivity disruptions between the cerebrum and cerebellum. However, the directed influences or effective connectivities (ECs) between these brain regions are poorly understood. In the current study, we aimed to evaluate the ECs between the cerebrum and cerebellum in patients with new-onset JME. (2) Methods: Thirty-four new-onset JME patients and thirty-four age-, sex-, and education-matched healthy controls (HCs) were included in this study. We compared the degree centrality (DC) between the two groups to identify intergroup differences in whole-brain functional connectivity. Then, we used a Granger causality analysis (GCA) to explore JME-caused changes in EC between cerebrum regions and cerebellum regions. Furthermore, we applied a correlation analysis to identify associations between aberrant EC and disease severity in patients with JME. (3) Results: Compared to HCs, patients with JME showed significantly increased DC in the left cerebellum posterior lobe (CePL.L), the right inferior temporal gyrus (ITG.R) and the right superior frontal gyrus (SFG.R), and decreased DC in the left inferior frontal gyrus (IFG.L) and the left superior temporal gyrus (STG.L). The patients also showed unidirectionally increased ECs from cerebellum regions to the cerebrum regions, including from the CePL.L to the right precuneus (PreCU.R), from the left cerebellum anterior lobe (CeAL.L) to the ITG.R, from the right cerebellum posterior lobe (CePL.R) to the IFG.L, and from the left inferior semi-lunar lobule of the cerebellum (CeISL.L) to the SFG.R. Additionally, the EC from the CeISL.L to the SFG.R was negatively correlated with the disease severity. (4) Conclusions: JME patients showed unidirectional EC disruptions from the cerebellum to the cerebrum, and the negative correlation between EC and disease severity provides a new perspective for understanding the cerebro-cerebellar neural circuit mechanisms in JME.

Altered brain activity in juvenile myoclonic epilepsy with a monotherapy: a resting-state fMRI study

Background

Juvenile myoclonic epilepsy (JME) is the most common syndrome of idiopathic generalized epilepsy. Although resting-state functional magnetic resonance imaging (rs-fMRI) studies have found thalamocortical circuit dysfunction in patients with JME, the pathophysiological mechanism of JME remains unclear. In this study, we used three complementary parameters of rs-fMRI to investigate aberrant brain activity in JME patients in comparison to that of healthy controls.

Methods

Rs-fMRI and clinical data were acquired from 49 patients with JME undergoing monotherapy and 44 age- and sex-matched healthy controls. After fMRI data preprocessing, the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated and compared between the two groups. Correlation analysis was conducted to explore the relationship between local brain abnormalities and clinical features in JME patients.

Results

Compared with the controls, the JME patients exhibited significantly decreased fALFF, ReHo and DC in the cerebellum, inferior parietal lobe, and visual cortex (including the fusiform and the lingual and middle occipital gyri), and increased DC in the right orbitofrontal cortex. In the JME patients, there were no regions with reduced ReHo compared to the controls. No significant correlation was observed between regional abnormalities of fALFF, ReHo or DC, and clinical features.

Conclusions

We demonstrated a wide range of abnormal functional activity in the brains of patients with JME, including the prefrontal cortex, visual cortex, default mode network, and cerebellum. The results suggest dysfunctions of the cerebello-cerebral circuits, which provide a clue on the potential pathogenesis of JME.

Altered Structural Brain Networks in Refractory and Nonrefractory Idiopathic Generalized Epilepsy

Introduction: Idiopathic generalized epilepsy (IGE) is a collection of generalized nonlesional epileptic network disorders. Around 20-40% of patients with IGE are refractory to antiseizure medication, and mechanisms underlying refractoriness are poorly understood. Here, we characterize structural brain network alterations and determine whether network alterations differ between patients with refractory and nonrefractory IGE. Methods: Thirty-three patients with IGE (10 nonrefractory and 23 refractory) and 39 age- and sex-matched healthy controls were studied. Network nodes were segmented from T1-weighted images, while connections between these nodes (edges) were reconstructed from diffusion magnetic resonance imaging (MRI). Diffusion networks of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and streamline count (Count) were studied. Differences between all patients, refractory, nonrefractory, and control groups were computed using network-based statistics. Nodal volume differences between groups were computed using Cohen's d effect size calculation. Results: Patients had significantly decreased bihemispheric FA and Count networks and increased MD and RD networks compared with controls. Alterations in network architecture, with respect to controls, differed depending on treatment outcome, including predominant FA network alterations in refractory IGE and increased nodal volume in nonrefractory IGE. Diffusion MRI networks were not influenced by nodal volume. Discussion: Although a nonlesional disorder, patients with IGE have bihemispheric structural network alterations that may differ between patients with refractory and nonrefractory IGE. Given that distinct nodal volume and FA network alterations were observed between treatment outcome groups, a multifaceted network analysis may be useful for identifying imaging biomarkers of refractory IGE.

Cerebello-thalamofrontal dysconnectivity in paroxysmal kinesigenic dyskinesia: A resting-state fMRI study

INTRODUCTION

The pathophysiology of paroxysmal kinesigenic dyskinesia (PKD) remains elusive to date; however, several lines of evidence from neuroimaging studies suggest involvement of the basal ganglia-thalamocortical network in PKD. We combined fractional amplitude of low-frequency fluctuation (fALFF) and seed-based functional connectivity (FC) analyses in order to comprehensively investigate intrinsic brain activity alterations and their relationships with disease severity in patients with idiopathic PKD.

METHODS

Resting-state functional MRI data were obtained and processed in 34 PKD patients and 34 matched controls. fALFF and seed-based FC maps were computed and compared between patients and controls. Linear regression analysis was further performed between regional fALFF values or FC strengths and clinical parameters in patients.

RESULTS

PKD patients had a significant increase in fALFF in bilateral thalamus and cerebellum compared with controls. FC analysis seeding at the thalamic clusters revealed significant FC increases in motor cortex and supplementary motor area in PKD patients relative to controls. Longer disease duration was associated with increasing FC strength between the thalamus and motor cortex.

CONCLUSION

We have provided evidence for abnormal intrinsic activity in the cerebello-thalamic circuit and increased thalamofrontal FC in PKD patients, implicating interictal cerebello-thalamofrontal dysconnectivity in the pathophysiology of PKD. Given the increasing FC strength in proportion to disease duration, the thalamofrontal hyperconnectivity might reflect either a consequence of recurrent dyskinesias on the brain or an innate pathology causing dyskinesias in PKD.

Brivaracetam Modulates Short-Term Synaptic Activity and Low-Frequency Spontaneous Brain Activity by Delaying Synaptic Vesicle Recycling in Two Distinct Rodent Models of Epileptic Seizures

Brivaracetam (BRV) is an anti-seizure drug for the treatment of focal and generalized epileptic seizures shown to augment short-term synaptic fatigue by slowing down synaptic vesicle recycling rates in control animals. In this study, we sought to investigate whether altered short-term synaptic activities could be a pathological hallmark during the interictal periods of epileptic seizures in two well-established rodent models, as well as to reveal BRV's therapeutic roles in altered short-term synaptic activities and low-frequency band spontaneous brain hyperactivity in these models. In our study, the electrophysiological field excitatory post-synaptic potential (fEPSP) recordings were performed in rat hippocampal brain slices from the CA1 region by stimulation of the Schaffer collateral/commissural pathway with or without BRV (30 μM for 3 h) in control or epileptic seizure (induced by pilocarpine (PILO) or high potassium (h-K⁺)) models. Short-term synaptic activities were induced by 5, 10, 20, and 40-Hz stimulation sequences. The effects of BRV on pre-synaptic vesicle mobilization were visually assessed by staining the synaptic vesicles with FM1-43 dye followed by imaging with a two-photon microscope. In the fEPSP measurements, short-term synaptic fatigue was found in the control group, while short-term synaptic potentiation (STP) was detected in both PILO and h-K⁺ models. STP was decreased after the slices were treated with BRV (30 μM) for 3 h. BRV also exhibited its therapeutic benefits by decreasing abnormal peak power (frequency range of 8-13 Hz, 31% of variation for PILO model, 25% of variation for h-K⁺ model) and trough power (frequency range of 1-4 Hz, 66% of variation for PILO model, 49% of variation for h-K⁺ model), and FM1-43 stained synaptic vesicle mobility (64% of the variation for PILO model, 45% of the variation for h-K⁺ model) in these epileptic seizure models. To the best of our knowledge, this was the first report that BRV decreased the STP and abnormal low-frequency brain activities during the interictal phase of epileptic seizures by slowing down the mobilization of synaptic vesicles in two rodent models. These mechanistic findings would greatly advance our understanding of BRV's pharmacological role in pathomechanisms of epileptic seizures and its treatment strategy optimization to avoid or minimize BRV-induced possible adverse side reactions.

Amplitude of Low-Frequency Fluctuation With Different Clinical Outcomes in Patients With Generalized Tonic-Clonic Seizures

BACKGROUND

Generalized tonic-clonic seizures (GTCS) are associated with significant disability and sudden unexpected death when they cannot be controlled. We aimed to explore the underlying neural substrate of the different responses to antiseizure drugs between the seizure-free (SF) and non-seizure-free (NSF) patients with GTCS through the amplitude of low-frequency fluctuation (ALFF) method.

METHODS

We calculated ALFF among the SF group, NSF group, and healthy controls (HCs) by collecting resting-state functional magnetic resonance imaging (rs-fMRI) data. One-way ANOVA was used to compare the ALFF of the three groups, and post-hoc analysis was done at the same time. Pearson's correlation analysis between ALFF in the discrepant brain areas and the clinical characteristics (disease course and age of onset of GTCS) was calculated after then.

RESULTS

A significant group effect was found in the right fusiform gyrus (R.FG), left fusiform gyrus (L.FG), left middle occipital gyrus (L.MOG), right inferior frontal gyrus (R.IFG), right precentral gyrus (R.PreG), right postcentral gyrus (R.PostG), and left calcarine sulcus (L.CS). The SF and NSF groups both showed increased ALFF in all discrepant brain areas compared to HCs except the R.IFG in the NSF group. Significantly higher ALFF in the bilateral FG and lower ALFF in the R.IFG were found in the NSF group compared to the SF group.

CONCLUSIONS

Higher ALFF in the bilateral FG were found in the NSF group compared to the SF and HC groups. Our findings indicate that abnormal brain activity in the FG may be one potential neural substrate to interpret the failure of seizure control in patients with GTCS.

A systematic review of resting-state and task-based fmri in juvenile myoclonic epilepsy

Functional neuroimaging modalities have enhanced our understanding of juvenile myoclonic epilepsy (JME) underlying neural mechanisms. Due to its non-invasive, sensitive and analytical nature, functional magnetic resonance imaging (fMRI) provides valuable insights into relevant functional brain networks and their segregation and integration properties. We systematically reviewed the contribution of resting-state and task-based fMRI to the current understanding of the pathophysiology and the patterns of seizure propagation in JME Altogether, despite some discrepancies, functional findings suggest that corticothalamo-striato-cerebellar network along with default-mode network and salience network are the most affected networks in patients with JME. However, further studies are required to investigate the association between JME's main deficiencies, e.g., motor and cognitive deficiencies and fMRI findings. Moreover, simultaneous electroencephalography-fMRI (EEG-fMRI) studies indicate that alterations of these networks play a role in seizure modulation but fall short of identifying a causal relationship between altered functional properties and seizure propagation. This review highlights the complex pathophysiology of JME, which necessitates the design of more personalized diagnostic and therapeutic strategies in this group.

Gray Matter Changes in Juvenile Myoclonic Epilepsy. A Voxel-Wise Meta-Analysis

Background and Objectives. Juvenile myoclonic epilepsy (JME) is an idiopathic generalized epileptic syndrome, with a genetic basis clinically identified by myoclonic jerks of the upper limbs upon awaking, generalized tonic-clonic seizures and less frequent absences. Although the brain magnetic resonance imaging (MRI) is by definition normal, computer-based Voxel-Based morphometry studies have shown a number of volumetric changes in patients with juvenile myoclonic epilepsy. Thus, the aim of the present Voxel-Wise Meta-Analysis was to determine the most consistent regional differences of gray matter volume between JME patients and healthy controls. Materials and Methods. The initial search returned 31 studies. After excluding reviews and studies without control groups or without detailed peak coordinates, 12 studies were finally included in the present meta-analysis. The total number of JME patients was 325, and that of healthy controls was 357. Results. Our study showed a statistically significant increase of the gray matter in the left median cingulate/paracingulate gyri, the right superior frontal gyrus, the left precentral gyrus, the right supplementary motor area and left supplementary motor area. It also showed a decrease in the gray matter volume in the left thalamus, and in the left insula. Conclusions. Our findings could be related to the functional deficits and changes described by previous studies in juvenile myoclonic epilepsy. In this way, the volumetric changes found in the present study could be related to the impaired frontal lobe functions, the emotional dysfunction and impaired pain empathy, and to the disrupted functional connectivity of supplementary motor areas described in JME. It additionally shows changes in the volume of the left thalamus, supporting the theory of thalamocortical pathways being involved in the pathogenesis of juvenile myoclonic epilepsy.

Alterations of the intrinsic amygdala-hippocampal network in juvenile myoclonic epilepsy

INTRODUCTION

Several lines of evidence suggest that the amygdala-hippocampus is involved in the epileptogenic network of juvenile myoclonic epilepsy (JME). The aim of this study was to investigate the alterations in the individual nuclei of the amygdala and hippocampal subfields, and the intrinsic amygdala-hippocampal network of patients with JME compared to healthy controls.

METHODS

This retrospective study conducted at a single tertiary hospital involved 35 patients with newly diagnosed JME, and 34 healthy subjects. We calculated the individual structural volumes of 18 nuclei in the amygdala, and 38 hippocampal subfields using three-dimensional volumetric T1-weighted imaging and FreeSurfer program. We also performed an analysis of the intrinsic amygdala-hippocampal global and local network based on these volumes using a graph theory and Brain Analysis using Graph Theory (BRAPH) program. We investigated the differences in these volumes and network measures between patients with JME and healthy controls.

RESULTS

There were no significant volume differences in the nuclei of the amygdala and hippocampal subfields between patients with JME and healthy controls. However, we found significant differences in the global network between patients with JME and healthy controls. The mean clustering coefficient was significantly decreased in patients with JME compared to healthy controls (0.473 vs. 0.653, p = .047). In addition, specific regions in the hippocampal subfields showed significant differences in the local network between the two groups. The betweenness centrality of the right CA1-head, right hippocampus-amygdala-transition area, left hippocampal fissure, left fimbria, and left CA3-head, was increased in patients with JME compared to healthy controls.

CONCLUSION

The intrinsic amygdala-hippocampal global and local networks differed in patients with JME compared to healthy controls, which may be related to the pathogenesis of JME, and memory dysfunction in patients with JME.

Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest. In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group. The sensitivity, specificity, and AUC (mean ± SD) of the regression model including metrics from both modalities were 74 ± 19%, 82 ± 18%, and 0.75 ± 0.12, respectively. Positive and negative predictive values (mean ± SD) of the regression model with both EEG and fMRI features are 84 ± 14% and 78 ± 12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05). Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample.

Resting-state functional MRI of the default mode network in epilepsy

The default mode network (DMN) is a major neuronal network that deactivates during goal-directed tasks. Recent advances in neuroimaging have shed light on its structure and function. Alterations in the DMN are increasingly recognized in a range of neurological and psychiatric conditions including epilepsy. This review first describes the current understanding of the DMN in health, normal aging, and disease as it is acquired via resting-state functional magnetic resonance imaging (MRI), before focusing on how it is affected in various types of focal and generalized epilepsy. These findings support the potential use of DMN parameters as future biomarkers in epilepsy research, diagnosis, and management.

Thalamic nuclei volumes and network in juvenile myoclonic epilepsy

OBJECTIVE

The aim of this study was to investigate the alterations of thalamic nuclei volumes and intrinsic thalamic networks in patients with juvenile myoclonic epilepsy (JME) compared to healthy controls.

METHODS

We enrolled 50 patients with JME and 42 healthy controls. We obtained structural volumes of the individual thalamic nuclei based on T1-weighted imaging and performed intrinsic thalamic network analysis using graph theoretical analysis. We analyzed the differences of thalamic nuclei volumes and intrinsic thalamic networks between the patients with JME and healthy controls.

RESULTS

In the patients with JME, there were significant alterations of thalamic nuclei volumes compared to healthy controls. Right laterodorsal and left suprageniculate nuclei volumes were significantly increased (0.0019% vs 0.0014%, P < .0001; 0.0011% vs 0.0008%, P = .0006, respectively), whereas left ventral posterolateral, left ventromedial, and left pulvinar inferior nuclei volumes (0.0572% vs 0.0664%, P = .0001; 0.0013% vs 0.0015%, P = .0002; 0.0120% vs 0.0140%, P < .0001, respectively) were decreased in the patients with JME. Furthermore, the intrinsic thalamic network of the patients with JME was significantly different from that of the healthy controls. The modularity in the patients with JME was significantly increased over that in healthy controls (0.0785 vs 0.0212, P = .039).

CONCLUSION

We found that there were significant alterations of thalamic nuclei volumes and intrinsic thalamic networks in patients with JME compared to healthy controls. These findings might contribute to the underlying pathogenesis of in JME.