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Altered brain network topology related to working memory in internet addiction

BACKGROUND AND AIMS: The working memory (WM) ability of internet addicts and the topology underlying the WM processing in internet addiction (IA) are poorly understood. In this study, we employed a graph theoretical framework to characterize the topological properties of the IA brain network in the...

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Autores principales: Wang, Hongxia, Sun, Yan, Lan, Fan, Liu, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Akadémiai Kiadó 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8939409/
https://www.ncbi.nlm.nih.gov/pubmed/32644933
http://dx.doi.org/10.1556/2006.2020.00020
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author Wang, Hongxia
Sun, Yan
Lan, Fan
Liu, Yan
author_facet Wang, Hongxia
Sun, Yan
Lan, Fan
Liu, Yan
author_sort Wang, Hongxia
collection PubMed
description BACKGROUND AND AIMS: The working memory (WM) ability of internet addicts and the topology underlying the WM processing in internet addiction (IA) are poorly understood. In this study, we employed a graph theoretical framework to characterize the topological properties of the IA brain network in the source cortical space during WM task. METHODS: A sample of 24 subjects with IA and 23 matched healthy controls (HCs) performed visual 2-back task. Exact Low Resolution Electromagnetic Tomography was adopted to project the pre-processed EEG signals into source space. Subsequently, Lagged phase synchronization was calculated between all pairs of Brodmann areas, the graph theoretical approaches were then employed to estimate the brain topological properties of all participants during the WM task. RESULTS: We found better WM behavioral performance in IA subjects compared with the HCs. Moreover, compared to the HC group, more integrated and hierarchical brain network was revealed in the IA subjects in alpha band. And altered regional centrality was mainly resided in frontal and limbic lobes. In addition, significant relationships between the IA severity and the significant altered graph indices were found. CONCLUSIONS: In conclusion, these findings provide evidence to support the notion that altered topological configuration may underline changed WM function observed in IA.
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spelling pubmed-89394092022-04-08 Altered brain network topology related to working memory in internet addiction Wang, Hongxia Sun, Yan Lan, Fan Liu, Yan J Behav Addict Full-length Report BACKGROUND AND AIMS: The working memory (WM) ability of internet addicts and the topology underlying the WM processing in internet addiction (IA) are poorly understood. In this study, we employed a graph theoretical framework to characterize the topological properties of the IA brain network in the source cortical space during WM task. METHODS: A sample of 24 subjects with IA and 23 matched healthy controls (HCs) performed visual 2-back task. Exact Low Resolution Electromagnetic Tomography was adopted to project the pre-processed EEG signals into source space. Subsequently, Lagged phase synchronization was calculated between all pairs of Brodmann areas, the graph theoretical approaches were then employed to estimate the brain topological properties of all participants during the WM task. RESULTS: We found better WM behavioral performance in IA subjects compared with the HCs. Moreover, compared to the HC group, more integrated and hierarchical brain network was revealed in the IA subjects in alpha band. And altered regional centrality was mainly resided in frontal and limbic lobes. In addition, significant relationships between the IA severity and the significant altered graph indices were found. CONCLUSIONS: In conclusion, these findings provide evidence to support the notion that altered topological configuration may underline changed WM function observed in IA. Akadémiai Kiadó 2020-06 2020-07-07 /pmc/articles/PMC8939409/ /pubmed/32644933 http://dx.doi.org/10.1556/2006.2020.00020 Text en © 2020 The Author(s) https://creativecommons.org/licenses/by-nc/4.0/Open Access statement. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated.
spellingShingle Full-length Report
Wang, Hongxia
Sun, Yan
Lan, Fan
Liu, Yan
Altered brain network topology related to working memory in internet addiction
title Altered brain network topology related to working memory in internet addiction
title_full Altered brain network topology related to working memory in internet addiction
title_fullStr Altered brain network topology related to working memory in internet addiction
title_full_unstemmed Altered brain network topology related to working memory in internet addiction
title_short Altered brain network topology related to working memory in internet addiction
title_sort altered brain network topology related to working memory in internet addiction
topic Full-length Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8939409/
https://www.ncbi.nlm.nih.gov/pubmed/32644933
http://dx.doi.org/10.1556/2006.2020.00020
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