Study Of Functional Connectivity Induced By Resting And Motor Task In Generalized Tonic-Clonic Seizures Epilepsy

Generalized tonic-clonic seizures(GTCS)is a type of generalized epilepsy,characterized by abnormal synchronous discharges across the bilateral cerebral hemispheres without any evidence of structural brain lesions.In recent years,a large number of studies based on static and dynamic functional connectivity analysis have found abnormal functional networks related to motor executive dysfunction in patients with epilepsy.Moreover,most researches have investigated brain abnormalities in patients with epilepsy during the resting state,while fewer researches investigated network connectivity during motor tasks.A growing body of research has suggested that white-matter functional signals have potential value for characterizing physiological and pathological brain functional states.Therefore,the thesis first explored the abnormal changes in the dynamic functional connectivity characteristics of gray-and white-matter regions in patients with GTCS in a resting state and then added a motor-task state to uncover multi-dimensional profiles of epileptic brain networks in different states.Dynamic functional connectivity analysis in the resting state was first conducted in the thesis.Based on resting-state functional magnetic resonance imaging data of 50 patients with GTCS and 52 gender-and age-matched healthy controls,functional connectivity analysis was performed using a sliding-window approach.The iterative Louvain temporal modular algorithm was employed for community detection to capture dynamic functional features at the network as well as brain region levels.In terms of the network level,In comparison with the healthy controls,patients with GTCS demonstrated abnormally enhanced functional connectivity strength between the community of sensorimotor-ventral attention network and the community of default-visual network in the resting state.In terms of brain region level,patients with GTCS exhibited high dynamic variability in multiple brain regions within the sensorimotor,default mode,and salience network.These findings indicated the instability of the epileptic brain network in the resting state,which might be related to the disturbed intrinsic brain state and disordered primary sensory and perceptual information processing.Furthermore,the thesis investigated the abnormal functional connectivity across the resting state and the motor task state in patients with GTCS.The k-means clustering algorithm was used to identify white-matter functional networks in resting and motor task states,respectively.Compared with healthy controls,patients with GTCS showed many abnormal connections in the motor task state,whereas no significant differences of connections were observed in the resting state.In addition,significantly attenuated across-state functional connectivity was found in GTCS.Converged results of this thesis indicated that motor task is helpful to further explore the abnormalities of epileptic brain networks and reveal the instability in the brain state transformation in patients with GTCS.Overall,this thesis explored the mutability of epileptic networks in GTCS from multiple perspectives,combining resting state data and task state data at the brain region and network level,and integrating gray-matter and white-matter networks,suggesting the susceptibility of motor systems in patients,and providing further evidence for analysis the brain network theory of GTCS.