Selective Development of Anticorrelated Networks in the Intrinsic Functional Organization of the Human Brain
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Chai-2013-Selective Developmen.pdf
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Author(s)
Ofen, Noa
Gabrieli, John D. E.
Chai, Xiaoqian
Gabrieli, Susan
Date Issued
March 2014
Journal
Journal of Cognitive Neuroscience
Publisher
MIT Press
Citation
Chai, Xiaoqian J., Noa Ofen, John D. E. Gabrieli, and Susan Whitfield-Gabrieli. “Selective Development of Anticorrelated Networks in the Intrinsic Functional Organization of the Human Brain.” Journal of Cognitive Neuroscience 26, no. 3 (March 2014): 501-513. © 2014 Massachusetts Institute of Technology
Version
Final published version
Abstract
We examined the normal development of intrinsic functional connectivity of the default network (brain regions typically deactivated for attention-demanding tasks) as measured by resting-state fMRI in children, adolescents, and young adults ages 8–24 years. We investigated both positive and negative correlations and employed analysis methods that allowed for valid interpretation of negative correlations and that also minimized the influence of motion artifacts that are often confounds in developmental neuroimaging. As age increased, there were robust developmental increases in negative correlations, including those between medial pFC (MPFC) and dorsolateral pFC (DLPFC) and between lateral parietal cortices and brain regions associated with the dorsal attention network. Between multiple regions, these correlations reversed from being positive in children to negative in adults. Age-related changes in positive correlations within the default network were below statistical threshold after controlling for motion. Given evidence in adults that greater negative correlation between MPFC and DLPFC is associated with superior cognitive performance, the development of an intrinsic anticorrelation between MPFC and DLPFC may be a marker of the large growth of working memory and executive functions that occurs from childhood to young adulthood.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1162/jocn_a_00517
