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Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity

Resting-state functional connectivity (rsFC) provides novel insights into variabilities in neural networks associated with the use of addictive drugs or with addictive behavioral repertoire. However, given the broad mix of inconsistent findings across studies, identifying specific consistent pattern...

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Autores principales: Tolomeo, Serenella, Yu, Rongjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8799706/
https://www.ncbi.nlm.nih.gov/pubmed/35091540
http://dx.doi.org/10.1038/s41398-022-01792-6
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author Tolomeo, Serenella
Yu, Rongjun
author_facet Tolomeo, Serenella
Yu, Rongjun
author_sort Tolomeo, Serenella
collection PubMed
description Resting-state functional connectivity (rsFC) provides novel insights into variabilities in neural networks associated with the use of addictive drugs or with addictive behavioral repertoire. However, given the broad mix of inconsistent findings across studies, identifying specific consistent patterns of network abnormalities is warranted. Here we aimed at integrating rsFC abnormalities and systematically searching for large-scale functional brain networks in substance use disorder (SUD) and behavioral addictions (BA), through a coordinate-based meta-analysis of seed-based rsFC studies. A total of fifty-two studies are eligible in the meta-analysis, including 1911 SUD and BA patients and 1580 healthy controls. In addition, we performed multilevel kernel density analysis (MKDA) for the brain regions reliably involved in hyperconnectivity and hypoconnectivity in SUD and BA. Data from fifty-two studies showed that SUD was associated with putamen, caudate and middle frontal gyrus hyperconnectivity relative to healthy controls. Eight BA studies showed hyperconnectivity clusters within the putamen and medio-temporal lobe relative to healthy controls. Altered connectivity in salience or emotion-processing areas may be related to dysregulated affective and cognitive control-related networks, such as deficits in regulating elevated sensitivity to drug-related stimuli. These findings confirm that SUD and BA might be characterized by dysfunctions in specific brain networks, particularly those implicated in the core cognitive and affective functions. These findings might provide insight into the development of neural mechanistic biomarkers for SUD and BA.
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spelling pubmed-87997062022-02-07 Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity Tolomeo, Serenella Yu, Rongjun Transl Psychiatry Article Resting-state functional connectivity (rsFC) provides novel insights into variabilities in neural networks associated with the use of addictive drugs or with addictive behavioral repertoire. However, given the broad mix of inconsistent findings across studies, identifying specific consistent patterns of network abnormalities is warranted. Here we aimed at integrating rsFC abnormalities and systematically searching for large-scale functional brain networks in substance use disorder (SUD) and behavioral addictions (BA), through a coordinate-based meta-analysis of seed-based rsFC studies. A total of fifty-two studies are eligible in the meta-analysis, including 1911 SUD and BA patients and 1580 healthy controls. In addition, we performed multilevel kernel density analysis (MKDA) for the brain regions reliably involved in hyperconnectivity and hypoconnectivity in SUD and BA. Data from fifty-two studies showed that SUD was associated with putamen, caudate and middle frontal gyrus hyperconnectivity relative to healthy controls. Eight BA studies showed hyperconnectivity clusters within the putamen and medio-temporal lobe relative to healthy controls. Altered connectivity in salience or emotion-processing areas may be related to dysregulated affective and cognitive control-related networks, such as deficits in regulating elevated sensitivity to drug-related stimuli. These findings confirm that SUD and BA might be characterized by dysfunctions in specific brain networks, particularly those implicated in the core cognitive and affective functions. These findings might provide insight into the development of neural mechanistic biomarkers for SUD and BA. Nature Publishing Group UK 2022-01-28 /pmc/articles/PMC8799706/ /pubmed/35091540 http://dx.doi.org/10.1038/s41398-022-01792-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Tolomeo, Serenella
Yu, Rongjun
Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity
title Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity
title_full Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity
title_fullStr Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity
title_full_unstemmed Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity
title_short Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity
title_sort brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8799706/
https://www.ncbi.nlm.nih.gov/pubmed/35091540
http://dx.doi.org/10.1038/s41398-022-01792-6
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