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Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency

Preoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of indi...

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Autores principales: Wen, Tanya, Hsieh, Shulan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740778/
https://www.ncbi.nlm.nih.gov/pubmed/26869896
http://dx.doi.org/10.3389/fnhum.2016.00006
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author Wen, Tanya
Hsieh, Shulan
author_facet Wen, Tanya
Hsieh, Shulan
author_sort Wen, Tanya
collection PubMed
description Preoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual’s level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated with internet addiction tendency, and one with connections negatively correlated with internet addiction tendency. The two networks are interconnected mostly at frontal regions, which might reflect alterations in the frontal region for different aspects of cognitive control (i.e., for control of internet usage and gaming skills). Next, we categorized the brain into several large regional subgroupings, and found that the majority of proportions of connections in the two networks correspond to the cerebellar model of addiction which encompasses the four-circuit model. Lastly, we observed that the brain regions with the most inter-regional connections associated with internet addiction tendency replicate those often seen in addiction literature, and is corroborated by our meta-analysis of internet addiction studies. This research provides a better understanding of large-scale networks involved in internet addiction tendency and shows that pre-clinical levels of internet addiction are associated with similar regions and connections as clinical cases of addiction.
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spelling pubmed-47407782016-02-11 Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency Wen, Tanya Hsieh, Shulan Front Hum Neurosci Neuroscience Preoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual’s level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated with internet addiction tendency, and one with connections negatively correlated with internet addiction tendency. The two networks are interconnected mostly at frontal regions, which might reflect alterations in the frontal region for different aspects of cognitive control (i.e., for control of internet usage and gaming skills). Next, we categorized the brain into several large regional subgroupings, and found that the majority of proportions of connections in the two networks correspond to the cerebellar model of addiction which encompasses the four-circuit model. Lastly, we observed that the brain regions with the most inter-regional connections associated with internet addiction tendency replicate those often seen in addiction literature, and is corroborated by our meta-analysis of internet addiction studies. This research provides a better understanding of large-scale networks involved in internet addiction tendency and shows that pre-clinical levels of internet addiction are associated with similar regions and connections as clinical cases of addiction. Frontiers Media S.A. 2016-02-01 /pmc/articles/PMC4740778/ /pubmed/26869896 http://dx.doi.org/10.3389/fnhum.2016.00006 Text en Copyright © 2016 Wen and Hsieh. http://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) or licensor 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
Wen, Tanya
Hsieh, Shulan
Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency
title Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency
title_full Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency
title_fullStr Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency
title_full_unstemmed Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency
title_short Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency
title_sort network-based analysis reveals functional connectivity related to internet addiction tendency
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740778/
https://www.ncbi.nlm.nih.gov/pubmed/26869896
http://dx.doi.org/10.3389/fnhum.2016.00006
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