Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pcbi.1000808
Title: The organization of local and distant functional connectivity in the human brain
Authors: Sepulcre J.
Liu H.
Talukdar T.
Martincorena I.
Thomas Yeo B.T. 
Buckner R.L.
Keywords: adult
article
brain function
brain mapping
brain region
controlled study
female
human
human experiment
male
mental performance
nerve cell network
normal human
sensorimotor cortex
biological model
biology
brain cortex
cluster analysis
methodology
neocortex
nuclear magnetic resonance imaging
physiology
Adult
Cerebral Cortex
Cluster Analysis
Computational Biology
Female
Humans
Magnetic Resonance Imaging
Male
Models, Neurological
Neocortex
Issue Date: 2010
Publisher: Public Library of Science
Citation: Sepulcre J., Liu H., Talukdar T., Martincorena I., Thomas Yeo B.T., Buckner R.L. (2010). The organization of local and distant functional connectivity in the human brain. PLoS Computational Biology 6 (6) : 1-15. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pcbi.1000808
Abstract: Information processing in the human brain arises from both interactions between adjacent areas and from distant projections that form distributed brain systems. Here we map interactions across different spatial scales by estimating the degree of intrinsic functional connectivity for the local (≤14 mm) neighborhood directly surrounding brain regions as contrasted with distant (>14 mm) interactions. The balance between local and distant functional interactions measured at rest forms a map that separates sensorimotor cortices from heteromodal association areas and further identifies regions that possess both high local and distant cortical-cortical interactions. Map estimates of network measures demonstrate that high local connectivity is most often associated with a high clustering coefficient, long path length, and low physical cost. Task performance changed the balance between local and distant functional coupling in a subset of regions, particularly, increasing local functional coupling in regions engaged by the task. The observed properties suggest that the brain has evolved a balance that optimizes information-processing efficiency across different classes of specialized areas as well as mechanisms to modulate coupling in support of dynamically changing processing demands. We discuss the implications of these observations and applications of the present method for exploring normal and atypical brain function. © 2010 Sepulcre et al.
Source Title: PLoS Computational Biology
URI: https://scholarbank.nus.edu.sg/handle/10635/165419
ISSN: 1553734X
DOI: 10.1371/journal.pcbi.1000808
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