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Updated: Sep 2, 2025

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
Published on: December 18, 2016
Abnormal percent amplitude of fluctuation and functional connectivity within and between networks in benign epilepsy
Ke Xu1, Fuqin Wang2, Bowen Geng1
1Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China; Xi'an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, China.
Background:
Benign epilepsy with centrotemporal spikes (BECTS) is one of the most common childhood epilepsy syndromes. The neural basis of BECTS is still poorly understood. This study aimed to further investigate the possible neural mechanisms of BECTS by comparing percent amplitude of fluctuation (PerAF) of resting-state functional magnetic resonance imaging (RS-fMRI) signal of each brain voxel and connectivity within and between related networks in children with BECTS and healthy controls (HCs).
Methods:
Firstly, we used PerAF method to investigate brain functional alteration and defined the regions of interest (ROIs) where children with BECTS exhibited significant PerAF alterations compared to HCs. We then divided these ROIs into different networks based on previous findings and investigated alterations of functional connectivity within and between networks in children with BECTS. Receiver operating characteristic (ROC) curve was employed to assess the reliable biomarker for distinguishing children with BECTS from HCs based on the intergroup PerAF differences.
Results:
Children with BECTS showed decreased PerAF in the left middle frontal cortex (MFC), right precentral gyrus, left precuneus (PCUN), bilateral posterior cingulate cortex (PCC), left angular gyrus, left inferior parietal lobule (IPL), right supplementary motor area (SMA) and left primary somatosensory cortex (S1) compared to HCs. The IPL and PCC exhibited higher classification power by ROC analysis. Moreover, our findings exhibited increased Intra-network connectivity in the default mode network (DMN), and increased inter-network connectivity of the sensorimotor network (SMN) with Broca's area and DMN.
Conclusions:
Our study investigated the abnormal PerAF and functional brain networks in children with BECTS, which might provide new insights into the pathological mechanisms of BECTS.
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