静息状态功能磁共振成像
连接组学
神经科学
计算机科学
连接体
人类连接体项目
信号(编程语言)
功能磁共振成像
大脑活动与冥想
功能连接
人工智能
模式识别(心理学)
心理学
脑电图
程序设计语言
作者
Luisa Raimondo,ĺcaro A.F. Oliveira,Jurjen Heij,Nikos Priovoulos,Prantik Kundu,Renata Ferranti Leoni,Wietske van der Zwaag
出处
期刊:NeuroImage
[Elsevier]
日期:2021-11-01
卷期号:243: 118503-118503
被引量:48
标识
DOI:10.1016/j.neuroimage.2021.118503
摘要
Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.
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