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Why use a connectivity-based approach to study stroke and recovery of function?

Abstract：

:The brain is organized into a set of widely distributed networks. Therefore, although structural damage from stroke is focal, remote dysfunction can occur in regions connected to the area of lesion. Historically, neuroscience has focused on local processing due in part to the absence of tools to study the function of distributed networks. In this article we discuss how a more comprehensive understanding of the effects of stroke can be attained using resting state functional connectivity BOLD magnetic resonance imaging (resting state fcMRI). Resting state fcMRI has a number of advantages over task-evoked fMRI for studying brain network reorganization in response to stroke, including the ability to image subjects with a broad range of impairments and the ability to study multiple networks simultaneously. We describe our rationale for using resting state connectivity as a tool for investigating the neural substrates of stroke recovery in a heterogeneous population of stroke patients and discuss the main questions we hope to answer, in particular whether resting state fcMRI measures in the acute phase of stroke can predict subsequent recovery. Early results suggest that disruption of inter-hemispheric connectivity in the somatomotor network and the dorsal attention network is more strongly associated with behavioral impairment in those domains than is intra-hemispheric connectivity within either the lesioned or unaffected hemisphere. We also observe in the somatomotor network an interesting interaction between corticospinal tract damage and decreased inter-hemispheric connectivity that suggests that both processes combine to contribute to neuromotor impairment after stroke. A connectivity-based approach will provide greater insight into network reorganization in the acute and chronic phases after stroke and will contribute to improving prognostic ability and the development of therapeutic interventions.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Carter AR,Shulman GL,Corbetta M

doi

10.1016/j.neuroimage.2012.02.070

subject

Has Abstract

pub_date

2012-10-01 00:00:00

pages

2271-80

issue

4

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(12)00255-8

journal_volume

62

pub_type

杂志文章,评审

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