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Dynamic Functional Connectivity Analysis Using Network-Based Brain State Identification, Application on Temporal Lobe Epilepsy Publisher Pubmed



Fallahi A1 ; Hashemifesharaki SS2 ; Hoseinitabatabaei N3 ; Pooyan M4 ; Nazemzadeh MR5
Authors
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Authors Affiliations
  1. 1. Hamedan University of Technology, Biomedical Engineering Department, Hamedan, Iran
  2. 2. Pars Hospital, Pars Advanced Medical Research Center, Tehran, Iran
  3. 3. Tehran University of Medical Sciences, Medical School, Tehran, Iran
  4. 4. Shahed University, Biomedical Engineering Department, Tehran, Iran
  5. 5. Tehran University of Medical Sciences, Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Instruments Institute (AMTII), Tehran, Iran

Source: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society# EMBS Published:2023


Abstract

Epilepsy is a brain network disorder caused by discharges of interconnected groups of neurons and resulting brain dysfunction. The brain network can be characterized by intra- and inter-regional functional connectivity (FC). However, since the BOLD signal is inherently non-stationary, the FC is evidenced to be varying over time. Considering the dynamic characteristics of the functional network, we aimed to obtain dynamic brain states and their properties using network-based analyses for the comparison of healthy control and temporal lobe epilepsy (TLE) groups and also lateralization of TLE patients. We used dwelling time, transition time, and brain network connection in each state as the dynamic features for this purpose. Results showed a significant difference in dwelling time and transition time between the healthy control group and both left TLE and right TLE groups and also a significant difference in brain network connections between the left and right TLE groups. © 2023 IEEE.
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