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DOI 10.1109/embc40787.2023.10339957

Медицинская библиотека · Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2023

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

Fallahi Alireza, Hashemi-Fesharaki Seyed Sohrab, Hoseini-Tabatabaei Narges, Pooyan Mohammad, Nazem-Zadeh Mohammad-Reza

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Аннотация

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.

Для цитирования: Fallahi Alireza, Hashemi-Fesharaki Seyed Sohrab, Hoseini-Tabatabaei Narges, Pooyan Mohammad, Nazem-Zadeh Mohammad-Reza. Dynamic Functional Connectivity Analysis Using Network-Based Brain State Identification, Application on Temporal Lobe Epilepsy.. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2023. DOI: 10.1109/embc40787.2023.10339957.

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