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Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis
Epilepsy is one of the most common neurological disorders worldwide. Recent findings suggest that the brain is a complex system composed of a network of neurons, and seizure is considered an emergent property resulting from its interactions. Based on this perspective, network physiology has emerged...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399918/ https://www.ncbi.nlm.nih.gov/pubmed/36034337 http://dx.doi.org/10.3389/fncir.2022.747910 |
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author | Batista Tsukahara, Victor Hugo de Oliveira Júnior, Jordão Natal de Oliveira Barth, Vitor Bruno de Oliveira, Jasiara Carla Rosa Cota, Vinicius Maciel, Carlos Dias |
author_facet | Batista Tsukahara, Victor Hugo de Oliveira Júnior, Jordão Natal de Oliveira Barth, Vitor Bruno de Oliveira, Jasiara Carla Rosa Cota, Vinicius Maciel, Carlos Dias |
author_sort | Batista Tsukahara, Victor Hugo |
collection | PubMed |
description | Epilepsy is one of the most common neurological disorders worldwide. Recent findings suggest that the brain is a complex system composed of a network of neurons, and seizure is considered an emergent property resulting from its interactions. Based on this perspective, network physiology has emerged as a promising approach to explore how brain areas coordinate, synchronize and integrate their dynamics, both under perfect health and critical illness conditions. Therefore, the objective of this paper is to present an application of (Dynamic) Bayesian Networks (DBN) to model Local Field Potentials (LFP) data on rats induced to epileptic seizures based on the number of arcs found using threshold analytics. Results showed that DBN analysis captured the dynamic nature of brain connectivity across ictogenesis and a significant correlation with neurobiology derived from pioneering studies employing techniques of pharmacological manipulation, lesion, and modern optogenetics. The arcs evaluated under the proposed approach achieved consistent results based on previous literature, in addition to demonstrating robustness regarding functional connectivity analysis. Moreover, it provided fascinating and novel insights, such as discontinuity between forelimb clonus and generalized tonic-clonic seizure (GTCS) dynamics. Thus, DBN coupled with threshold analytics may be an excellent tool for investigating brain circuitry and their dynamical interplay, both in homeostasis and dysfunction conditions. |
format | Online Article Text |
id | pubmed-9399918 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93999182022-08-25 Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis Batista Tsukahara, Victor Hugo de Oliveira Júnior, Jordão Natal de Oliveira Barth, Vitor Bruno de Oliveira, Jasiara Carla Rosa Cota, Vinicius Maciel, Carlos Dias Front Neural Circuits Neuroscience Epilepsy is one of the most common neurological disorders worldwide. Recent findings suggest that the brain is a complex system composed of a network of neurons, and seizure is considered an emergent property resulting from its interactions. Based on this perspective, network physiology has emerged as a promising approach to explore how brain areas coordinate, synchronize and integrate their dynamics, both under perfect health and critical illness conditions. Therefore, the objective of this paper is to present an application of (Dynamic) Bayesian Networks (DBN) to model Local Field Potentials (LFP) data on rats induced to epileptic seizures based on the number of arcs found using threshold analytics. Results showed that DBN analysis captured the dynamic nature of brain connectivity across ictogenesis and a significant correlation with neurobiology derived from pioneering studies employing techniques of pharmacological manipulation, lesion, and modern optogenetics. The arcs evaluated under the proposed approach achieved consistent results based on previous literature, in addition to demonstrating robustness regarding functional connectivity analysis. Moreover, it provided fascinating and novel insights, such as discontinuity between forelimb clonus and generalized tonic-clonic seizure (GTCS) dynamics. Thus, DBN coupled with threshold analytics may be an excellent tool for investigating brain circuitry and their dynamical interplay, both in homeostasis and dysfunction conditions. Frontiers Media S.A. 2022-08-10 /pmc/articles/PMC9399918/ /pubmed/36034337 http://dx.doi.org/10.3389/fncir.2022.747910 Text en Copyright © 2022 Batista Tsukahara, de Oliveira Júnior, de Oliveira Barth, de Oliveira, Rosa Cota and Maciel. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Batista Tsukahara, Victor Hugo de Oliveira Júnior, Jordão Natal de Oliveira Barth, Vitor Bruno de Oliveira, Jasiara Carla Rosa Cota, Vinicius Maciel, Carlos Dias Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis |
title | Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis |
title_full | Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis |
title_fullStr | Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis |
title_full_unstemmed | Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis |
title_short | Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis |
title_sort | data-driven network dynamical model of rat brains during acute ictogenesis |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399918/ https://www.ncbi.nlm.nih.gov/pubmed/36034337 http://dx.doi.org/10.3389/fncir.2022.747910 |
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