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Differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis
BACKGROUND: Juvenile myoclonus epilepsy (JME) is an idiopathic generalized epilepsy syndrome. Functional connectivity studies based on graph theory have demonstrated changes in functional connectivity among different brain regions in patients with JME and healthy controls. However, previous studies...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582565/ https://www.ncbi.nlm.nih.gov/pubmed/37859762 http://dx.doi.org/10.3389/fnins.2023.1214687 |
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author | Luo, Dadong Liu, Yaqing Zhang, Ningning Wang, Tiancheng |
author_facet | Luo, Dadong Liu, Yaqing Zhang, Ningning Wang, Tiancheng |
author_sort | Luo, Dadong |
collection | PubMed |
description | BACKGROUND: Juvenile myoclonus epilepsy (JME) is an idiopathic generalized epilepsy syndrome. Functional connectivity studies based on graph theory have demonstrated changes in functional connectivity among different brain regions in patients with JME and healthy controls. However, previous studies have not been able to clarify why visual stimulation or increased cognitive load induces epilepsy symptoms in only some patients with JME. METHODS: This study constructed a small-world network for the visualization of functional connectivity of brain regions in patients with JME, based on system mapping. We used the node reduction method repeatedly to identify the core nodes of the resting brain network of patients with JME. Thereafter, a functional connectivity network of the core brain regions in patients with JME was established, and it was analyzed manually with white matter tracks restriction to explain the differences in symptom distribution in patients with JME. RESULTS: Patients with JME had 21 different functional connections in their resting state, and no significant differences in their distribution were noted. The thalamus, cerebellum, basal ganglia, supplementary motor area, visual cortex, and prefrontal lobe were the core brain regions that comprised the functional connectivity network in patients with JME during their resting state. The betweenness centrality of the prefrontal lobe and the visual cortex in the core functional connectivity network of patients with JME was lower than that of the other brain regions. CONCLUSION: The functional connectivity and node importance of brain regions of patients with JME changed dynamically in the resting state. Abnormal discharges originating from the thalamus, cerebellum, basal ganglia, supplementary motor area, visual cortex, and prefrontal cortex are most likely to lead to seizures in patients with JME. Further, the low average value of betweenness centrality of the prefrontal and visual cortices explains why visual stimulation or increased cognitive load can induce epileptic symptoms in only some patients with JME. |
format | Online Article Text |
id | pubmed-10582565 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105825652023-10-19 Differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis Luo, Dadong Liu, Yaqing Zhang, Ningning Wang, Tiancheng Front Neurosci Neuroscience BACKGROUND: Juvenile myoclonus epilepsy (JME) is an idiopathic generalized epilepsy syndrome. Functional connectivity studies based on graph theory have demonstrated changes in functional connectivity among different brain regions in patients with JME and healthy controls. However, previous studies have not been able to clarify why visual stimulation or increased cognitive load induces epilepsy symptoms in only some patients with JME. METHODS: This study constructed a small-world network for the visualization of functional connectivity of brain regions in patients with JME, based on system mapping. We used the node reduction method repeatedly to identify the core nodes of the resting brain network of patients with JME. Thereafter, a functional connectivity network of the core brain regions in patients with JME was established, and it was analyzed manually with white matter tracks restriction to explain the differences in symptom distribution in patients with JME. RESULTS: Patients with JME had 21 different functional connections in their resting state, and no significant differences in their distribution were noted. The thalamus, cerebellum, basal ganglia, supplementary motor area, visual cortex, and prefrontal lobe were the core brain regions that comprised the functional connectivity network in patients with JME during their resting state. The betweenness centrality of the prefrontal lobe and the visual cortex in the core functional connectivity network of patients with JME was lower than that of the other brain regions. CONCLUSION: The functional connectivity and node importance of brain regions of patients with JME changed dynamically in the resting state. Abnormal discharges originating from the thalamus, cerebellum, basal ganglia, supplementary motor area, visual cortex, and prefrontal cortex are most likely to lead to seizures in patients with JME. Further, the low average value of betweenness centrality of the prefrontal and visual cortices explains why visual stimulation or increased cognitive load can induce epileptic symptoms in only some patients with JME. Frontiers Media S.A. 2023-10-04 /pmc/articles/PMC10582565/ /pubmed/37859762 http://dx.doi.org/10.3389/fnins.2023.1214687 Text en Copyright © 2023 Luo, Liu, Zhang and Wang. 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 Luo, Dadong Liu, Yaqing Zhang, Ningning Wang, Tiancheng Differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis |
title | Differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis |
title_full | Differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis |
title_fullStr | Differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis |
title_full_unstemmed | Differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis |
title_short | Differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis |
title_sort | differences in the distribution of triggers among resting state networks in patients with juvenile myoclonic epilepsy explained by network analysis |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582565/ https://www.ncbi.nlm.nih.gov/pubmed/37859762 http://dx.doi.org/10.3389/fnins.2023.1214687 |
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