Atypical Functional Connectivity in Tourette Syndrome Differs Between Children and Adults

Ashley N. Nielsen*, Caterina Gratton, Jessica A. Church, Nico U.F. Dosenbach, Kevin J. Black, Steven E. Petersen, Bradley L. Schlaggar, Deanna J. Greene

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Background: Tourette syndrome (TS) is a neuropsychiatric disorder with symptomatology that typically changes over development. Whether and how brain function in TS also differs across development has been largely understudied. Here, we used functional connectivity magnetic resonance imaging to examine whole-brain functional networks in children and adults with TS. Methods: Multivariate classification methods were used to find patterns among functional connections that distinguish individuals with TS from control subjects separately for children and adults (N = 202). We tested whether the patterns of connections that classify diagnosis in one age group (e.g., children) could classify diagnosis in another age group (e.g., adults). We also tested whether the developmental trajectory of these connections was altered in TS. Results: Diagnostic classification was successful in children and adults separately but expressly did not generalize across age groups, suggesting that the patterns of functional connections that best distinguished individuals with TS from control subjects were age specific. Developmental patterns among these functional connections used for diagnostic classification deviated from typical development. Brain networks in childhood TS appeared “older” and brain networks in adulthood TS appeared “younger” in comparison with typically developing individuals. Conclusions: Our results demonstrate that brain networks are differentially altered in children and adults with TS. The observed developmental trajectory of affected connections is consistent with theories of accelerated and/or delayed maturation, but may also involve anomalous developmental pathways. These findings further our understanding of neurodevelopmental trajectories in TS and carry implications for future applications aimed at predicting the clinical course of TS in individuals over development.

Original languageEnglish (US)
Pages (from-to)164-173
Number of pages10
JournalBiological psychiatry
Volume87
Issue number2
DOIs
StatePublished - Jan 15 2020

Keywords

  • Classification
  • Development
  • Functional connectivity
  • Machine learning
  • Tourette syndrome
  • fMRI

ASJC Scopus subject areas

  • Biological Psychiatry

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