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Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake

AIMS: Currently, there are only a few studies concerning brain functional alterations after acute alcohol exposure, and the majority of existing studies attach more importance to the spatial properties of brain function without considering the temporal properties. The current study adopted sliding w...

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Autores principales: Zhang, Gengbiao, Li, Ni, Liu, Hongkun, Zheng, Hongyi, Zheng, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531019/
https://www.ncbi.nlm.nih.gov/pubmed/36203810
http://dx.doi.org/10.3389/fnins.2022.974778
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author Zhang, Gengbiao
Li, Ni
Liu, Hongkun
Zheng, Hongyi
Zheng, Wenbin
author_facet Zhang, Gengbiao
Li, Ni
Liu, Hongkun
Zheng, Hongyi
Zheng, Wenbin
author_sort Zhang, Gengbiao
collection PubMed
description AIMS: Currently, there are only a few studies concerning brain functional alterations after acute alcohol exposure, and the majority of existing studies attach more importance to the spatial properties of brain function without considering the temporal properties. The current study adopted sliding window to investigate the resting-state brain networks in healthy volunteers after acute alcohol intake and to explore the dynamic changes in network connectivity. MATERIALS AND METHODS: Twenty healthy volunteers were enrolled in this study. Blood-oxygen-level-dependent (BOLD) data prior to drinking were obtained as control, while that 0.5 and 1 h after drinking were obtained as the experimental group. Reoccurring functional connectivity patterns (states) were determined following group independent component analysis (ICA), sliding window analysis and k-means clustering. Between-group comparisons were performed with respect to the functional connectivity states fractional windows, mean dwell time, and the number of transitions. RESULTS: Three optimal functional connectivity states were identified. The fractional windows and mean dwell time of 0.5 h group and 1 h group increased in state 3, while the fraction window and mean dwell time of 1 h group decreased in state 1. State 1 is characterized by strong inter-network connections between basal ganglia network (BGN) and sensorimotor network (SMN), BGN and cognitive executive network (CEN), and default mode network (DMN) and visual network (VN). However, state 3 is distinguished by relatively weak intra-network connections in SMN, VN, CEN, and DMN. State 3 was thought to be a characteristic connectivity pattern of the drunk brain. State 1 was believed to represent the brain’s main connection pattern when awake. Such dynamic changes in brain network connectivity were consistent with participants’ subjective feelings after drinking. CONCLUSION: The current study reveals the dynamic change in resting-state brain functional network connectivity before and after acute alcohol intake. It was discovered that there might be relatively independent characteristic functional network connection patterns under intoxication, and the corresponding patterns characterize the clinical manifestations of volunteers. As a valuable imaging biomarker, dynamic functional network connectivity (dFNC) offers a new approach and basis for further explorations on brain network alterations after alcohol consumption and the alcohol-related mechanisms for neurological damage.
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spelling pubmed-95310192022-10-05 Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake Zhang, Gengbiao Li, Ni Liu, Hongkun Zheng, Hongyi Zheng, Wenbin Front Neurosci Neuroscience AIMS: Currently, there are only a few studies concerning brain functional alterations after acute alcohol exposure, and the majority of existing studies attach more importance to the spatial properties of brain function without considering the temporal properties. The current study adopted sliding window to investigate the resting-state brain networks in healthy volunteers after acute alcohol intake and to explore the dynamic changes in network connectivity. MATERIALS AND METHODS: Twenty healthy volunteers were enrolled in this study. Blood-oxygen-level-dependent (BOLD) data prior to drinking were obtained as control, while that 0.5 and 1 h after drinking were obtained as the experimental group. Reoccurring functional connectivity patterns (states) were determined following group independent component analysis (ICA), sliding window analysis and k-means clustering. Between-group comparisons were performed with respect to the functional connectivity states fractional windows, mean dwell time, and the number of transitions. RESULTS: Three optimal functional connectivity states were identified. The fractional windows and mean dwell time of 0.5 h group and 1 h group increased in state 3, while the fraction window and mean dwell time of 1 h group decreased in state 1. State 1 is characterized by strong inter-network connections between basal ganglia network (BGN) and sensorimotor network (SMN), BGN and cognitive executive network (CEN), and default mode network (DMN) and visual network (VN). However, state 3 is distinguished by relatively weak intra-network connections in SMN, VN, CEN, and DMN. State 3 was thought to be a characteristic connectivity pattern of the drunk brain. State 1 was believed to represent the brain’s main connection pattern when awake. Such dynamic changes in brain network connectivity were consistent with participants’ subjective feelings after drinking. CONCLUSION: The current study reveals the dynamic change in resting-state brain functional network connectivity before and after acute alcohol intake. It was discovered that there might be relatively independent characteristic functional network connection patterns under intoxication, and the corresponding patterns characterize the clinical manifestations of volunteers. As a valuable imaging biomarker, dynamic functional network connectivity (dFNC) offers a new approach and basis for further explorations on brain network alterations after alcohol consumption and the alcohol-related mechanisms for neurological damage. Frontiers Media S.A. 2022-09-20 /pmc/articles/PMC9531019/ /pubmed/36203810 http://dx.doi.org/10.3389/fnins.2022.974778 Text en Copyright © 2022 Zhang, Li, Liu, Zheng and Zheng. 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
Zhang, Gengbiao
Li, Ni
Liu, Hongkun
Zheng, Hongyi
Zheng, Wenbin
Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake
title Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake
title_full Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake
title_fullStr Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake
title_full_unstemmed Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake
title_short Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake
title_sort dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531019/
https://www.ncbi.nlm.nih.gov/pubmed/36203810
http://dx.doi.org/10.3389/fnins.2022.974778
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