人类连接体项目
静息状态功能磁共振成像
连接体
神经影像学
功能磁共振成像
计算机科学
神经科学
扫描仪
人脑
神经功能成像
人工智能
功能连接
模式识别(心理学)
心理学
作者
Stephen M. Smith,Christian F. Beckmann,Jesper Andersson,Edward J. Auerbach,Janine Bijsterbosch,Gwenaëlle Douaud,Eugene Duff,David Feinberg,Ludovica Griffanti,Michael P. Harms,Michael Kelly,Timothy O. Laumann,Karla L. Miller,Steen Moeller,Steve Petersen,Jonathan D. Power,Gholamreza Salimi‐Khorshidi,Abraham Z. Snyder,An T. Vu,Mark W. Woolrich
出处
期刊:NeuroImage
[Elsevier BV]
日期:2013-05-20
卷期号:80: 144-168
被引量:1714
标识
DOI:10.1016/j.neuroimage.2013.05.039
摘要
Resting-state functional magnetic resonance imaging (rfMRI) allows one to study functional connectivity in the brain by acquiring fMRI data while subjects lie inactive in the MRI scanner, and taking advantage of the fact that functionally related brain regions spontaneously co-activate. rfMRI is one of the two primary data modalities being acquired for the Human Connectome Project (the other being diffusion MRI). A key objective is to generate a detailed in vivo mapping of functional connectivity in a large cohort of healthy adults (over 1000 subjects), and to make these datasets freely available for use by the neuroimaging community. In each subject we acquire a total of 1h of whole-brain rfMRI data at 3 T, with a spatial resolution of 2×2×2 mm and a temporal resolution of 0.7s, capitalizing on recent developments in slice-accelerated echo-planar imaging. We will also scan a subset of the cohort at higher field strength and resolution. In this paper we outline the work behind, and rationale for, decisions taken regarding the rfMRI data acquisition protocol and pre-processing pipelines, and present some initial results showing data quality and example functional connectivity analyses.
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