UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

The seizure classification of focal epilepsy based on the network motif analysis

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. Green open access

[thumbnail of 1-s2.0-S0361923024000121-main.pdf]
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
Downloads since deposit
28Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item