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Individual Variation in Functional Topography of Association Networks in Youth.

Authors :
Cui, Zaixu
Li, Hongming
Xia, Cedric H.
Larsen, Bart
Adebimpe, Azeez
Baum, Graham L.
Cieslak, Matt
Gur, Raquel E.
Gur, Ruben C.
Moore, Tyler M.
Oathes, Desmond J.
Alexander-Bloch, Aaron F.
Raznahan, Armin
Roalf, David R.
Shinohara, Russell T.
Wolf, Daniel H.
Davatzikos, Christos
Bassett, Danielle S.
Fair, Damien A.
Fan, Yong
Source :
Neuron. Apr2020, Vol. 106 Issue 2, p340-340. 1p.
Publication Year :
2020

Abstract

The spatial distribution of large-scale functional networks on the cerebral cortex differs between individuals and is particularly variable in association networks that are responsible for higher-order cognition. However, it remains unknown how this functional topography evolves in development and supports cognition. Capitalizing on advances in machine learning and a large sample imaged with 27 min of high-quality functional MRI (fMRI) data (n = 693, ages 8–23 years), we delineate how functional topography evolves during youth. We found that the functional topography of association networks is refined with age, allowing accurate prediction of unseen individuals' brain maturity. The cortical representation of association networks predicts individual differences in executive function. Finally, variability of functional topography is associated with fundamental properties of brain organization, including evolutionary expansion, cortical myelination, and cerebral blood flow. Our results emphasize the importance of considering the plasticity and diversity of functional neuroanatomy during development and suggest advances in personalized therapeutics. • Functional topography is most variable in association cortex in youth • Functional topography is refined during youth and encodes brain maturity • Association network functional topography predicts executive function Cui et al. demonstrate that individual-specific functional networks are refined during youth in humans. Furthermore, the functional topography of association networks predicts individual differences in executive function. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08966273
Volume :
106
Issue :
2
Database :
Academic Search Index
Journal :
Neuron
Publication Type :
Academic Journal
Accession number :
142792341
Full Text :
https://doi.org/10.1016/j.neuron.2020.01.029