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Functional parcellation using time courses of instantaneous connectivity

期刊

NEUROIMAGE
卷 170, 期 -, 页码 31-40

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2017.07.027

关键词

Parcellation; Resting state; FMRI; Motor cortex; Thalamus; Subcortex; Entorhinal cortex

资金

  1. McDonnell Center for Systems Neuroscience at Washington University
  2. Wellcome Trust UK Strategic Award [098369/Z/12/Z]
  3. Netherlands Organisation for Scientific Research [NWO-Vidi 864-12-003]
  4. Marie Curie International Incoming Fellowship from the European Research Council under the European Union's Seventh Framework Programme/ERC [327340]
  5. [1U54MH091657]

向作者/读者索取更多资源

Functional neuroimaging studies have led to understanding the brain as a collection of spatially segregated functional networks. It is thought that each of these networks is in turn composed of a set of distinct sub-regions that together support each networks function. Considering the sub-regions to be an essential part of the brain's functional architecture, several strategies have been put forward that aim at identifying the functional sub-units of the brain by means of functional parcellations. Current parcellation strategies typically employ a bottom-up strategy, creating a parcellation by clustering smaller units. We propose a novel top down parcellation strategy, using time courses of instantaneous connectivity to subdivide an initial region of interest into sub-regions. We use split-half reproducibility to choose the optimal number of sub-regions. We apply our Instantaneous Connectivity Parcellation (ICP) strategy on high-quality resting-state FMRI data, and demonstrate the ability to generate parcellations for thalamus, entorhinal cortex, motor cortex, and subcortex including brainstem and striatum. We evaluate the subdivisions against available cytoarchitecture maps to show that our parcellation strategy recovers biologically valid subdivisions that adhere to known cytoarchitectural features. (C) 2017 Elsevier Inc. All rights reserved.

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