Back to Search Start Over

A resting-state functional connectivity study in patients at high risk for sudden unexpected death in epilepsy.

Authors :
Tang, Yingying
Chen, Qin
Yu, Xiaofeng
Xia, Wei
Luo, Chunyan
Huang, XiaoQi
Tang, Hehan
Gong, QiYong
Zhou, Dong
Source :
Epilepsy & Behavior. Dec2014, Vol. 41, p33-38. 6p.
Publication Year :
2014

Abstract

Objective Seizure-related respiratory and cardiac dysfunctions were once thought to be the direct cause of sudden unexpected death in epilepsy (SUDEP), but both may be secondary to postictal cerebral inhibition. An important issue that has not been explored to date is the neural network basis of cerebral inhibition. Our aim was to investigate the features of neural networks in patients at high risk for SUDEP using a blood oxygen level-dependent (BOLD) resting-state functional connectivity (FC) approach. Subjects and methods Resting-state functional magnetic resonance imaging (Rs-fMRI) data were recorded from 13 patients at high risk for SUDEP and 12 patients at low risk for SUDEP. Thirteen cerebral regions that are closely related to cardiorespiratory activity were selected as regions of interest (ROIs). The ROI-wise resting-state FC analysis was compared between the two groups. Results Compared with patients at low risk for SUDEP, patients at high risk exhibited significant reductions in the resting-state FC between the pons and the right thalamus, the midbrain and the right thalamus, the bilateral anterior cingulate cortex (ACC) and the right thalamus, and the left thalamus and the right thalamus. Conclusions This investigation is the first to use neuroimaging methods in research on the mechanism of SUDEP and demonstrates the abnormally decreased resting-state FC in the ACC–thalamus–brainstem circuit in patients at high risk for SUDEP. These findings highlight the need to understand the fundamental neural network dysfunction in SUDEP, which may fill the missing link between seizure-related cardiorespiratory dysfunction and SUDEP, and provide a promising neuroimaging biomarker for risk prediction of SUDEP. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15255050
Volume :
41
Database :
Academic Search Index
Journal :
Epilepsy & Behavior
Publication Type :
Academic Journal
Accession number :
99920611
Full Text :
https://doi.org/10.1016/j.yebeh.2014.08.140