Individualized functional brain mapping machine learning prediction of symptom-change resulting from selective kappa-opioid antagonism in an anhedonic sample from a Fast-Fail trial
Using an ensemble of machine learning approaches, we identified individual differences in subcortical individualized systems data that predicted clinical change that was specific to KOR antagonism.
Authors
- Jeff A. Valenti (ORCID: https://orcid.org/0000-0003-3305-6281)
- Moria J. Smoski (ORCID: https://orcid.org/0000-0003-3175-8327)
- Poorvi Keshava
- Andrew D. Krystal (ORCID: https://orcid.org/0000-0002-6702-781X)
- Diego A. Pizzagalli (ORCID: https://orcid.org/0000-0002-7772-1143)
- Matthew D. Sacchet (ORCID: https://orcid.org/0000-0002-8619-5237)
- Shane W. Walsh
Institutions
- Harvard University (US)
- Duke University (US)
- University of California, San Francisco (US)
- McLean Hospital (US)
- Massachusetts General Hospital (US)
Publication Details
- Journal
- Journal of Mood and Anxiety Disorders
- Published
- 2025-05-09
- DOI
- https://doi.org/10.1016/j.xjmad.2025.100126
- Citations
- 1
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- Brain and Behavior Research Foundation
- Fundação Bial
- Ad Astra Chandaria Foundation
- National Institute of Mental Health