Paper Info
Title
Cross-Modal Consistency Of Epileptogenic Network In Seeg And Resting-State Fmri
Abstract
Electrophysiological recording and metabolic imaging are two complimentary techniques in preoperative evaluation of epilepsy surgery. High frequency electrical brain activity has been increasingly used in localizing seizure onset zone (SOZ) owing to the development of stereo-EEG (SEEG) technique. However, SEEG recording has no capacity of whole brain coverage as functional MRI. In this study, we performed cross-modal validation of epileptogenic network defined by SEEG and that by resting-state fMRI on individual brain of epilepsy patients. Epileptogenicity index (EI) based on abnormal high frequency SEEG signals was employed to define the epileptogenic network in electrophysiology. Meanwhile, taking the SEEG sites with highest EI as the seed, resting-state functional MRI and connectivity analysis were used to define the epileptogenic network in hemodynamics. The spatial consistency of these two networks was measured by ROC, and the average AUC reached 0.87, which proved a good consistency between electrophysiological and hemodynamic networks in epileptic brain. The difference part in resting-state fMRI network may supplement the SEEG electrode coverage, to reveal more information about epileptic network.
Year
DOI
Venue
2019
10.1109/ner.2019.8716989
2019 9TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER)
Field
DocType
ISSN
Computer vision,Pattern recognition,Computer science,Resting state fMRI,Stereoelectroencephalography,Artificial intelligence,Modal
Conference
1948-3546
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Tong Zhao1147.30
Haixiang Wang200.34
Kang Wang32510.98
Xiaojiao Yang400.34
Wenjing Zhou5102.75
Bo Hong625333.74