Novel large scale brain network models for EEG epileptic pattern generations
Article
Article Title | Novel large scale brain network models for EEG epileptic pattern generations |
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ERA Journal ID | 17852 |
Article Category | Article |
Authors | Al-Hossenat, Auhood (Author), Song, Bo (Author), Wen, Peng (Author) and Li, Yan (Author) |
Journal Title | Expert Systems with Applications |
Journal Citation | 194 |
Article Number | 116477 |
Number of Pages | 17 |
Year | 2022 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 0957-4174 |
1873-6793 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.eswa.2021.116477 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0957417421017577 |
Abstract | Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different morphologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNMS) by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural connectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different lobes from both hemispheres (left and right). The network nodes of Results: The proposed network models were developed and evaluated by simulations. Different abnormal patterns of EEG brain activities such as HFOS ripples on spikes, spikes, continuous spikes, sporadic spikes and ploy2 spikes ranging from 94-144 Hz were regenerated. Different morphology patterns of abnormality were generated from novel BNMs and the epileptiform abnormal pattern obtained in actual EEG and other computational models were also compared. Significant: This study is able to assist researchers and clinical doctors in the field of epilepsy to better understand the complex neural mechanisms behind the abnormal oscillatory activities, which may lead to the discovery of new clinical interventions in epilepsy. |
Keywords | low and high gamma EEG, EEG seizure-like signal, connectome-based brain network modelling, temporal dynamics of Stefanescu-Jirsa 2D, TVB |
ANZSRC Field of Research 2020 | 460207. Modelling and simulation |
400399. Biomedical engineering not elsewhere classified | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | School of Sciences |
School of Mechanical and Electrical Engineering | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q6zv8/novel-large-scale-brain-network-models-for-eeg-epileptic-pattern-generations
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