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Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis
OBJECTIVE: Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnor...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299970/ https://www.ncbi.nlm.nih.gov/pubmed/25610771 http://dx.doi.org/10.1016/j.nicl.2014.11.018 |
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author | Caeyenberghs, K. Powell, H.W.R. Thomas, R.H. Brindley, L. Church, C. Evans, J. Muthukumaraswamy, S.D. Jones, D.K. Hamandi, K. |
author_facet | Caeyenberghs, K. Powell, H.W.R. Thomas, R.H. Brindley, L. Church, C. Evans, J. Muthukumaraswamy, S.D. Jones, D.K. Hamandi, K. |
author_sort | Caeyenberghs, K. |
collection | PubMed |
description | OBJECTIVE: Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. METHODS: Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. RESULTS: Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. CONCLUSIONS: Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients. |
format | Online Article Text |
id | pubmed-4299970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-42999702015-01-21 Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis Caeyenberghs, K. Powell, H.W.R. Thomas, R.H. Brindley, L. Church, C. Evans, J. Muthukumaraswamy, S.D. Jones, D.K. Hamandi, K. Neuroimage Clin Regular Article OBJECTIVE: Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. METHODS: Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. RESULTS: Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. CONCLUSIONS: Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients. Elsevier 2014-11-27 /pmc/articles/PMC4299970/ /pubmed/25610771 http://dx.doi.org/10.1016/j.nicl.2014.11.018 Text en © 2014 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). |
spellingShingle | Regular Article Caeyenberghs, K. Powell, H.W.R. Thomas, R.H. Brindley, L. Church, C. Evans, J. Muthukumaraswamy, S.D. Jones, D.K. Hamandi, K. Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis |
title | Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis |
title_full | Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis |
title_fullStr | Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis |
title_full_unstemmed | Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis |
title_short | Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis |
title_sort | hyperconnectivity in juvenile myoclonic epilepsy: a network analysis |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299970/ https://www.ncbi.nlm.nih.gov/pubmed/25610771 http://dx.doi.org/10.1016/j.nicl.2014.11.018 |
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