Different Functional Network Connectivity Patterns in Epilepsy: A Rest-State fMRI Study on Mesial Temporal Lobe Epilepsy and Benign Epilepsy With Centrotemporal Spike.

Jianzhong Yin,Qing Yu,Zhijuan Chen,Aikedan Aisikaer,Weidong Yang,Cong Fu

doi:10.3389/fneur.2021.668856

Abstract

The stark discrepancy in the prognosis of epilepsy is closely related to brain damage features and underlying mechanisms, which have not yet been unraveled. In this study, differences in the epileptic brain functional connectivity states were explored through a network-based connectivity analysis between intractable mesial temporal lobe epilepsy (MTLE) patients and benign epilepsy with centrotemporal spikes (BECT). Resting state fMRI imaging data were collected for 14 MTLE patients, 12 BECT patients and 16 healthy controls (HCs). Independent component analysis (ICA) was performed to identify the cortical functional networks. Subcortical nuclei of interest were extracted from the Harvard-Oxford probability atlas. Network-based statistics were used to detect functional connectivity (FC) alterations across intranetworks and internetworks, including the connectivity between cortical networks and subcortical nuclei. Compared with HCs, MTLE patients showed significant lower activity between the connectivity of cortical networks and subcortical nuclei (especially hippocampus) and lower internetwork FC involving the lateral temporal lobe; BECT patients showed normal cortical-subcortical FC with hyperconnectivity between cortical networks. Together, cortical-subcortical hypoconnectivity in MTLE suggested a low efficiency and collaborative network pattern, and this might be relevant to the final decompensatory state and the intractable prognosis. Conversely, cortical-subcortical region with normal connectivity remained well in global cooperativity, and compensatory internetwork hyperconnectivity caused by widespread cortical abnormal discharge, which might account for the self-limited clinical outcome in BECT. Based on the fMRI functional network study, different brain network patterns might provide a better explanation of mechanisms in different types of epilepsy.

Highlights

Epilepsy derives from the long-term spontaneous abnormal discharge of neurons in the brain, resulting in hypersynchronization of the cortical-cortical and subcorticalcortical regions, leading to brain dysfunction and behavioral abnormalities
The inclusion criteria for patients with mesial temporal lobe epilepsy (MTLE) and benign epilepsy with centrotemporal spikes (BECT) were as follows: [1] typical clinical manifestations and specific EEG characteristics according to International League Against Epilepsy (ILAE) [21]; [2] the presence of routine clinical scans, including highresolution 3D T1-weighted and FLAIR magnetic resonance imaging (MRI) and high in-plane resolution 2D coronal T2-weighted MRI according to the Harmonized Neuroimaging Of Epilepsy Structural Sequences (HARNESS) [22]; [3] no evidence of other structural brain abnormalities due to hypoplasia of brain parenchyma, brain trauma, tumor, etc; and [4] MTLE patients should be diagnosed as the drugs resistance epilepsy [23] and the patients with BECT should respond well to anti-epileptic drugs (AEDs)
A post hoc test was performed to find that the BECT-healthy controls (HCs) contrast (p < 0.001) and BECT-MTLE contrast (p < 0.001) were significant

Summary

Introduction

Epilepsy derives from the long-term spontaneous abnormal discharge of neurons in the brain, resulting in hypersynchronization of the cortical-cortical and subcorticalcortical regions, leading to brain dysfunction and behavioral abnormalities. About 25% epilepsy patients with a dissatisfied clinical control of seizure even with the optimal anti-epileptic drugs (AEDs) [1]. The most common drug-resistant epilepsy in adults is mesial temporal lobe epilepsy (MTLE) [2], accounting for 80% of temporal lobe onset seizures [3]. Some of the epilepsy patients have a good response to AEDs and even achieve a seizure-free result, such as benign epilepsy with centrotemporal spikes (BECT). BECT is the most common form of childhood focal epilepsy and is usually idiopathic without structural brain abnormalities [4]. Patients with MTLE and BECT might mark different prognosis by different brain compensatory patterns. The two patterns manifest brain networks abnormalities usually caused by epileptic discharges in widespread brain areas in MTLE and BECT. Resting state functional connectivity (RSFC) could be used to detect the network -level epileptic effect

Methods

Results

Conclusion