Fan, Denggui;
Qi, Lixue;
Hou, Songan;
Wang, Qingyun;
Baier, Gerold;
(2024)
The seizure classification of focal epilepsy based on the network motif analysis.
Brain Research Bulletin
, 207
, Article 110879. 10.1016/j.brainresbull.2024.110879.
Preview |
PDF
1-s2.0-S0361923024000121-main.pdf - Published Version Download (7MB) | Preview |
Abstract
Due to the complexity of focal epilepsy and its risk for transiting to the generalized epilepsy, the development of reliable classification methods to accurately predict and classify focal and generalized seizures is critical for the clinical management of patients with epilepsy. In order to holistically understand the seizure propagation behavior of focal epilepsy, we propose a three-node motif reduced network by respectively simplifying the focal region, surrounding healthy region and their critical regions as the single node. Because three-node motif can richly characterize information evolutions, the motif analysis method could comprehensively investigate the seizure behavior of focal epilepsy. Firstly, we define a new seizure propagation marker value to capture the seizure onsets and intensity. Based on the three-node motif analysis, it is shown that the focal seizure and spreading can be categorized as inhibitory seizure, focal seizure, focal-critical seizure and generalized seizures, respectively. The four types of seizures correspond to specific modal types respectively, reflecting the strong correlation between seizure behavior and information flow evolution. In addition, it is found that the intensity difference of outflow and inflow information from the critical node (connection heterogeneity) and the excitability of the critical node significantly affected the distribution and transition of the four seizure types. In particular, the method of local linear stability analysis also verifies the effectiveness of four types of seizures classification. In sum, this paper computationally confirms the complex dynamic behavior of focal seizures, and the study of criticality is helpful to propose novel seizure control strategies.
Type: | Article |
---|---|
Title: | The seizure classification of focal epilepsy based on the network motif analysis |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.brainresbull.2024.110879 |
Publisher version: | https://doi.org/10.1016/j.brainresbull.2024.110879 |
Language: | English |
Additional information: | © 2024 The Author(s). Published by Elsevier Inc. under a Creative Commons license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Cortical motifs, Epileptor model, Focal seizures, Generalized seizures |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology |
URI: | https://discovery.ucl.ac.uk/id/eprint/10186137 |
Archive Staff Only
View Item |