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Peer-reviewedCC BY-NC-NDNature Communications

Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease

  • Carrisa V. Cocuzza1,2,3,4
  • Sidhant Chopra5,6,7,8
  • Ashlea Segal9
  • Loïc Labache3,4
  • Rowena Chin4,10
  • Kaley Joss3
  • Avram J. Holmes3
10 affiliations
  1. 1Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA. [email protected]
  2. 2Department of Psychology, Yale University, New Haven, CT, USA. [email protected]
  3. 3Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
  4. 4Department of Psychology, Yale University, New Haven, CT, USA
  5. 5Center for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
  6. 6Orygen, Melbourne, VIC, Australia
  7. 7Center for Youth Mental Health, University of Melbourne, Melbourne, Australia
  8. 8Orygen, Melbourne, Australia
  9. 9Department of Neuroscience, Wu Tsai Institute, Yale University, New Haven, CT, USA
  10. 10Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
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Abstract

The network organization of the human brain dynamically reconfigures in response to changing environmental demands, an adaptive process that may be disrupted in a symptom-relevant manner across psychiatric illnesses. Here, in a transdiagnostic sample of participants with (n=134) and without (n=85) psychiatric diagnoses, functional connectomes from intrinsic (resting-state) and task-evoked fMRI were decomposed to identify constraints on brain network dynamics across six cognitive states. Hierarchical clustering of 110 clinical, behavioral, and cognitive measures identified participant-specific symptom profiles, revealing four core dimensions of functioning: internalizing, externalizing, cognitive, and social/reward. Brain network dynamics were flattened across cognitive states in individuals with psychiatric illness and could be used to accurately separate dimensional symptom profiles more robustly than both case-control status and primary diagnostic grouping. A key role of inhibitory cognitive control and frontoparietal network interactions was uncovered through systematic model comparison. We provide novel evidence that brain network dynamics can accurately differentiate the extent that psychiatrically-relevant dimensions of functioning are exhibited across health and disease.

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Cite

BibTeXRIS
BibTeX
@article{cocuzza2026brain,
  title = {{Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease}},
  author = {Carrisa V. Cocuzza and Sidhant Chopra and Ashlea Segal and Loïc Labache and Rowena Chin and Kaley Joss and Avram J. Holmes},
  journal = {Nature Communications},
  year = {2026},
  month = jul,
  doi = {10.1038/s41467-026-75585-6},
  url = {https://doi.org/10.1038/s41467-026-75585-6},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease
AU  - Carrisa V. Cocuzza
AU  - Sidhant Chopra
AU  - Ashlea Segal
AU  - Loïc Labache
AU  - Rowena Chin
AU  - Kaley Joss
AU  - Avram J. Holmes
PY  - 2026
DA  - 2026/07/21
JO  - Nature Communications
DO  - 10.1038/s41467-026-75585-6
UR  - https://doi.org/10.1038/s41467-026-75585-6
AB  - The network organization of the human brain dynamically reconfigures in response to changing environmental demands, an adaptive process that may be disrupted in a symptom-relevant manner across psychiatric illnesses. Here, in a transdiagnostic sample of participants with (n=134) and without (n=85) psychiatric diagnoses, functional connectomes from intrinsic (resting-state) and task-evoked fMRI were decomposed to identify constraints on brain network dynamics across six cognitive states. Hierarchical clustering of 110 clinical, behavioral, and cognitive measures identified participant-specific symptom profiles, revealing four core dimensions of functioning: internalizing, externalizing, cognitive, and social/reward. Brain network dynamics were flattened across cognitive states in individuals with psychiatric illness and could be used to accurately separate dimensional symptom profiles more robustly than both case-control status and primary diagnostic grouping. A key role of inhibitory cognitive control and frontoparietal network interactions was uncovered through systematic model comparison. We provide novel evidence that brain network dynamics can accurately differentiate the extent that psychiatrically-relevant dimensions of functioning are exhibited across health and disease.
SN  - 2041-1723
ER  -