Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth

Zaixu Cui, Adam R. Pines, Bart Larsen, Valerie J. Sydnor, Hongming Li, Azeez Adebimpe, Aaron F. Alexander-Bloch, Dani S. Bassett, Max Bertolero, Monica E. Calkins, Christos Davatzikos, Damien A. Fair, Ruben C. Gur, Raquel E. Gur, Tyler M. Moore, Sheila Shanmugan, Russell T. Shinohara, Jacob W. Vogel, Cedric H. Xia, Yong FanTheodore D. Satterthwaite

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Background: The spatial layout of large-scale functional brain networks differs between individuals and is particularly variable in the association cortex, implicated in a broad range of psychiatric disorders. However, it remains unknown whether this variation in functional topography is related to major dimensions of psychopathology in youth. Methods: The authors studied 790 youths ages 8 to 23 years who had 27 minutes of high-quality functional magnetic resonance imaging data as part of the Philadelphia Neurodevelopmental Cohort. Four correlated dimensions were estimated using a confirmatory correlated traits factor analysis on 112 item-level clinical symptoms, and one overall psychopathology factor with 4 orthogonal dimensions were extracted using a confirmatory factor analysis. Spatially regularized nonnegative matrix factorization was used to identify 17 individual-specific functional networks for each participant. Partial least square regression with split-half cross-validation was conducted to evaluate to what extent the topography of personalized functional networks encodes major dimensions of psychopathology. Results: Personalized functional network topography significantly predicted unseen individuals’ major dimensions of psychopathology, including fear, psychosis, externalizing, and anxious-misery. Reduced representation of association networks was among the most important features for the prediction of all 4 dimensions. Further analysis revealed that personalized functional network topography predicted overall psychopathology (r = 0.16, permutation testing p < .001), which drove prediction of the 4 correlated dimensions. Conclusions: These results suggest that individual differences in functional network topography in association networks is related to overall psychopathology in youth. Such results underscore the importance of considering functional neuroanatomy for personalized diagnostics and therapeutics in psychiatry.

Original languageEnglish (US)
Pages (from-to)973-983
Number of pages11
JournalBiological psychiatry
Volume92
Issue number12
DOIs
StatePublished - Dec 15 2022

Bibliographical note

Publisher Copyright:
© 2022 Society of Biological Psychiatry

Keywords

  • Adolescence
  • Functional MRI
  • Functional topography
  • Individualized parcellation
  • P-factor
  • Psychopathology

Fingerprint

Dive into the research topics of 'Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth'. Together they form a unique fingerprint.

Cite this