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成瘾医学的静息态功能连接性分析:从个体位点到复杂网络

Resting state functional connectivity analysis for addiction medicine: From individual loci to complex networks.

作者信息

Pariyadath Vani, Gowin Joshua L, Stein Elliot A

机构信息

Neuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, USA.

Section on Human Psychopharmacology, Intramural Research Program, National Institute on Alcohol Abuse and Addiction, National Institutes of Health, Bethesda, MD, USA.

出版信息

Prog Brain Res. 2016;224:155-73. doi: 10.1016/bs.pbr.2015.07.015. Epub 2015 Nov 3.

DOI:10.1016/bs.pbr.2015.07.015
PMID:26822358
Abstract

Resting state functional connectivity (rsFC) has provided a new and valuable tool for investigating network-level dysfunction in addiction. Following the recent development of a framework of large scale network disruptions, we have been able to arrive at unique insights into craving-related aspects of addiction using rsFC. However, such network-level advancement has thus far eluded our understanding of mesocorticolimbic involvement in addiction. Given the importance of this system in vulnerability and resilience to addiction, understanding mesocorticolimbic dynamics to the same extent could provide critical insights into the disease. To this end, we review here recent studies on addiction that employ rsfC and suggest a new approach, one that combines a novel model for addiction with new experimental techniques as well as participant groups, to accelerate progress in this arena.

摘要

静息态功能连接(rsFC)为研究成瘾中的网络层面功能障碍提供了一种新的且有价值的工具。随着大规模网络破坏框架的最新发展,我们已经能够利用rsFC对成瘾中与渴望相关的方面获得独特见解。然而,到目前为止,这种网络层面的进展还未能让我们理解中脑皮质边缘系统在成瘾中的作用。鉴于该系统在成瘾易感性和恢复力方面的重要性,同样程度地理解中脑皮质边缘系统动态变化可为该疾病提供关键见解。为此,我们在此回顾最近使用rsfC进行的成瘾研究,并提出一种新方法,即将一种新的成瘾模型与新的实验技术以及参与者群体相结合,以加速这一领域的进展。

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