Transdiagnostic connectome-based predictive modeling of negative emotion regulation using general functional connectivity
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[EMBARGOED UNTIL 12/01/2026] Negative emotion regulation (NegER) is a fundamental construct involved in the onset, maintenance and treatment of multiple psychiatric disorders and thus represents a target for transdiagnostic modeling. However, validated transdiagnostic predictive neuromarkers of NegER remain uncharacterized. Analyses used a transdiagnostic sample (N=501) composed of healthy controls (HC) and individuals with substance use disorders, mood disorders, and/or chronic pain that underwent functional magnetic resonance imaging (fMRI: resting-state and ER task-state) and had in-scanner NegER task performance. Connectome-based predictive modeling (CPM) using general functional connectivity (GFC: concatenated rest and task) was used to predict inscanner NegER task performance. Cross-validated CPMs were then assessed for robustness, test-retest reliability, external-validity, were neuroanatomically characterized, and assessed for clinical utility. Group differences in NegER task performance and NegER CPMs were also assessed. NegER task performance differed across groups with HC showing the greatest task performance. Cross-validated NegER CPMs were successfully identified, were highly robust to alternative model building settings, demonstrated good-to-excellent test-retest reliability, and were successfully externally-validated. CPM performance was highest when using features from the whole-brain. NegER CPM network strengths differed across groups with HC showing the most adaptive connectivity patterns. Lastly, NegER CPM network strengths were also associated with clinical measures. This study identified a robust, reliable, and generalizable transdiagnostic fMRI FC neuromarker of NegER with clinical utility.
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Ph. D.