Individual Variation in Functional Topography of Association Networks in Youth

Zaixu Cui, Hongming Li, Cedric H. Xia, Bart Larsen, Azeez Adebimpe, Graham L. Baum, Matt Cieslak, Raquel E. Gur, Ruben C. Gur, Tyler M. Moore, Desmond J. Oathes, Aaron F. Alexander-Bloch, Armin Raznahan, David R. Roalf, Russell T. Shinohara, Daniel H. Wolf, Christos Davatzikos, Danielle S. Bassett, Damien A. Fair, Yong FanTheodore D. Satterthwaite

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)340-353.e8
Issue number2
StatePublished - Apr 22 2020
Externally publishedYes

Bibliographical note

Funding Information:
This study was supported by R01MH113550, R01EB022573, R01MH107703, RF1MH116920, R01MH112847, P50MH096891, R01MH11186, K01MH102609, R01MH107235, R01NS085211, RC2MH08998, RC2MH089924, and the Penn/CHOP Lifespan Brain Institute. We thank Ru Kong and Jingwei Li for help with the MS-HBM. T.D.S. and Z.C. designed the study. Z.C. and T.D.S. performed the analyses with support from H.L. B.L. A.A. G.L.B. and M.C. H.L. and Y.F. provided parcellation tools. H.L. replicated all analyses. Z.C. C.H.X. and T.D.S. created the figures. A.A. M.C. T.M.M. D.R.R. and T.D.S. completed data preprocessing. R.E.G. R.C.G. C.D. and T.D.S. provided resources. D.S.B. A.F.A.-B. A.R. D.J.O. R.T.S. D.H.W. C.D. D.A.F. and Y.F. commented on analyses. Z.C. and T.D.S. wrote the manuscript with review and editing from all other authors. R.T.S. has received income from Genentech/Roche. All other authors declare no competing interests.

Publisher Copyright:
© 2020 Elsevier Inc.


  • MRI
  • adolescence
  • cognition
  • cognitive control
  • development
  • executive function
  • functional MRI
  • network
  • parcellation
  • topography

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