Dataset Information

Juvenile myoclonic epilepsy has hyper dynamic functional connectivity in the dorsolateral frontal cortex.

ABSTRACT:

Purpose

Characterize the static and dynamic functional connectivity for subjects with juvenile myoclonic epilepsy (JME) using a quantitative data-driven analysis approach.

Methods

Whole-brain resting-state functional MRI data were acquired on a 3 T whole-body clinical MRI scanner from 18 subjects clinically diagnosed with JME and 25 healthy control subjects. 2-min sliding-window approach was incorporated in the quantitative data-driven data analysis framework to assess both the dynamic and static functional connectivity in the resting brains. Two-sample t-tests were performed voxel-wise to detect the differences in functional connectivity metrics based on connectivity strength and density.

Results

The static functional connectivity metrics based on quantitative data-driven analysis of the entire 10-min acquisition window of resting-state functional MRI data revealed significantly enhanced functional connectivity in JME patients in bilateral dorsolateral prefrontal cortex, dorsal striatum, precentral and middle temporal gyri. The dynamic functional connectivity metrics derived by incorporating a 2-min sliding window into quantitative data-driven analysis demonstrated significant hyper dynamic functional connectivity in the dorsolateral prefrontal cortex, middle temporal gyrus and dorsal striatum. Connectivity strength metrics (both static and dynamic) can detect more extensive functional connectivity abnormalities in the resting-state functional networks (RFNs) and depict also larger overlap between static and dynamic functional connectivity results.

Conclusion

Incorporating a 2-min sliding window into quantitative data-driven analysis of resting-state functional MRI data can reveal additional information on the temporally fluctuating RFNs of the human brain, which indicate that RFNs involving dorsolateral prefrontal cortex have temporal varying hyper dynamic characteristics in JME patients. Assessing dynamic along with static functional connectivity may provide further insights into the abnormal function connectivity underlying the pathological brain functioning in JME.

SUBMITTER: Wang Y

PROVIDER: S-EPMC6412974 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Juvenile myoclonic epilepsy has hyper dynamic functional connectivity in the dorsolateral frontal cortex.

Wang Yanlu Y Berglund Ivanka Savic IS Uppman Martin M Li Tie-Qiang TQ

NeuroImage. Clinical 20181119

<h4>Purpose</h4>Characterize the static and dynamic functional connectivity for subjects with juvenile myoclonic epilepsy (JME) using a quantitative data-driven analysis approach.<h4>Methods</h4>Whole-brain resting-state functional MRI data were acquired on a 3 T whole-body clinical MRI scanner from 18 subjects clinically diagnosed with JME and 25 healthy control subjects. 2-min sliding-window approach was incorporated in the quantitative data-driven data analysis framework to assess both the dy ...[more]

PMID: 30527355

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Project description:Objective: It is indisputable that the functional connectivity of the brain network in juvenile myoclonic epilepsy (JME) patients is abnormal. As a mathematical extension of the traditional network model, the multilayer network can fully capture the fluctuations of brain imaging data with time, and capture subtle abnormal dynamic changes. This study assumed that the dynamic structure of JME patients is abnormal and used the multilayer network framework to analyze the change brain community structure in JME patients from the perspective of dynamic analysis. Methods: First, functional magnetic resonance imaging (fMRI) data were obtained from 35 JME patients and 34 healthy control subjects. In addition, the communities of the two groups were explored with the help of a multilayer network model and a multilayer community detection algorithm. Finally, differences were described by metrics that are specific to the multilayer network. Results: Compared with healthy controls, JME patients had a significantly lower modularity degree of the brain network. Furthermore, from the level of the functional network, the integration of the default mode network (DMN) and visual network (VN) in JME patients showed a significantly higher trend, and the flexibility of the attention network (AN) also increased significantly. At the node level, the integration of seven nodes of the DMN was significantly increased, the integration of five nodes of the VN was significantly increased, and the flexibility of three nodes of the AN was significantly increased. Moreover, through division of the core-peripheral system, we found that the left insula and left cuneus were core regions specific to the JME group, while most of the peripheral systems specific to the JME group were distributed in the prefrontal cortex and hippocampus. Finally, we found that the flexibility of the opercular part of the inferior frontal gyrus was significantly correlated with the severity of JME symptoms. Conclusion: Our findings indicate that the dynamic community structure of JME patients is indeed abnormal. These results provide a new perspective for the study of dynamic changes in communities in JME patients.

Project description:ObjectiveGeneralized epilepsy syndromes often confer multiple types of seizures, but it is not known if these seizures activate separate or overlapping brain networks. Recently, we reported that mice with a juvenile myoclonic epilepsy mutation (Gabra1[A322D]) exhibited both absence and myoclonic generalized seizures. Here, we determined the time course of sensorimotor cortex activation and the spatial distribution of spike voltage during these two seizures.MethodsWe implanted Gabra1+/A322D mice with multiple electroencephalography (EEG) electrodes over bilateral somatosensory cortex barrel fields (S1) and anterior (aM1) and posterior (pM1) motor cortices and recorded absence seizures/spike-wave discharges (SWDs) and myoclonic seizures. We used nonlinear-association analyses and cross-correlation calculations to determine the strength, leading regions, and time delays of cortical coupling from the preictal to ictal states and within the spike and interspike periods. The distribution of spike voltage was also measured in SWDs and myoclonic seizures.ResultsEEG connectivity among all electrode pairs increased at the onset of both SWDs and myoclonic seizures. Surprisingly, during spikes of both seizure types, S1 led M1 with similar delay times. Myoclonic seizure spikes started more focally than SWD spikes, with a significant majority appearing first only in S1 electrodes, whereas a substantial fraction of SWD spikes were detected first in S1 and at least one M1 electrode. The absolute voltage of myoclonic seizure spikes was significantly higher than that of SWD spikes, and there was a greater relative voltage over M1 during myoclonic seizure spikes than in the first one to two SWD spikes.SignificanceThe leading sites in S1 and similar delay times suggest both SWDs and myoclonic seizures activate overlapping networks in sensorimotor cortex and thus, therapeutically targeting of this network could potentially treat both seizures. Spike focality, absolute voltage, and voltage distribution provide insight into neuronal activation during these two seizure types.

Dataset Information

Juvenile myoclonic epilepsy has hyper dynamic functional connectivity in the dorsolateral frontal cortex.

Purpose

Methods

Results

Conclusion

Publications

Juvenile myoclonic epilepsy has hyper dynamic functional connectivity in the dorsolateral frontal cortex.

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