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 |

REPOSITORIES: biostudies-literature

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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.