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Exploration of interictal to ictal transition in epileptic seizures using a neural mass model.
Yang, Chunfeng; Luo, Qingbo; Shu, Huazhong; Le Bouquin Jeannès, Régine; Li, Jianqing; Xiang, Wentao.
Affiliation
  • Yang C; Key Laboratory of Computer Network and Information Integration of Ministry of Education, Southeast University, Nanjing, 210096 China.
  • Luo Q; Jiangsu Provincal Joint International Research Laboratory of Medical Information Processing, Southeast University, Nanjing, 210096 China.
  • Shu H; Centre de Recherche en Information Biomédicale Sino-français, Southeast University & Université de Rennes 1, Nanjing, 210096 China.
  • Le Bouquin Jeannès R; Key Laboratory of Computer Network and Information Integration of Ministry of Education, Southeast University, Nanjing, 210096 China.
  • Li J; Jiangsu Provincal Joint International Research Laboratory of Medical Information Processing, Southeast University, Nanjing, 210096 China.
  • Xiang W; Centre de Recherche en Information Biomédicale Sino-français, Southeast University & Université de Rennes 1, Nanjing, 210096 China.
Cogn Neurodyn ; 18(3): 1215-1225, 2024 Jun.
Article de En | MEDLINE | ID: mdl-38826671
ABSTRACT
An epileptic seizure can usually be divided into three stages interictal, preictal, and ictal. However, the seizure underlying the transition from interictal to ictal activities in the brain involves complex interactions between inhibition and excitation in groups of neurons. To explore this mechanism at the level of a single population, this paper employed a neural mass model, named the complete physiology-based model (cPBM), to reconstruct electroencephalographic (EEG) signals and to infer the changes in excitatory/inhibitory connections related to excitation-inhibition (E-I) balance based on an open dataset recorded for ten epileptic patients. Since epileptic signals display spectral characteristics, spectral dynamic causal modelling (DCM) was applied to quantify these frequency characteristics by maximizing the free energy in the framework of power spectral density (PSD) and estimating the cPBM parameters. In addition, to address the local maximum problem that DCM may suffer from, a hybrid deterministic DCM (H-DCM) approach was proposed, with a deterministic annealing-based scheme applied in two directions. The H-DCM approach adjusts the temperature introduced in the objective function by gradually decreasing the temperature to obtain relatively good initialization and then gradually increasing the temperature to search for a better estimation after each maximization. The results showed that (i) reconstructed EEG signals belonging to the three stages together with their PSDs can be reproduced from the estimated parameters of the cPBM; (ii) compared to DCM, traditional D-DCM and anti D-DCM, the proposed H-DCM shows higher free energies and lower root mean square error (RMSE), and it provides the best performance for all stages (e.g., the RMSEs between the reconstructed PSD computed from the reconstructed EEG signal and the sample PSD obtained from the real EEG signal are 0.33 ± 0.08, 0.67 ± 0.37 and 0.78 ± 0.57 in the interictal, preictal and ictal stages, respectively); and (iii) the transition from interictal to ictal activity can be explained by an increase in the connections between pyramidal cells and excitatory interneurons and between pyramidal cells and fast inhibitory interneurons, as well as a decrease in the self-loop connection of the fast inhibitory interneurons in the cPBM. Moreover, the E-I balance, defined as the ratio between the excitatory connection from pyramidal cells to fast inhibitory interneurons and the inhibitory connection with the self-loop of fast inhibitory interneurons, is also significantly increased during the epileptic seizure transition. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-023-09976-6.
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Cogn Neurodyn Année: 2024 Type de document: Article

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Cogn Neurodyn Année: 2024 Type de document: Article
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