Using computational models of learning to advance cognitive behavioral therapy

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This paper proposes formalizing cognitive behavioral therapy, specifically exposure therapy and cognitive restructuring, as computational models of learning to better understand their mechanisms of change. The authors review literature on reinforcement and representation learning to map these algorithms onto therapeutic processes. The resource is intended for researchers interested in developing a theory-driven computational approach to psychotherapy.

ID
4d23d6da7c644e5e
Source org
PubMed Central
Author
Isabel M. Berwian (Princeton University), Peter Hitchock (Emory University), Sashank Pisupati (Princeton University), Gila Schoen (Geha Mental Health Center), Yael Niv (Princeton University)
Published
2025-04-27
OA status
gold
DOI
10.1038/s44271-025-00251-4
PMID
Not recorded
PMCID
Not recorded
Citations
7

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BibTeX

@article{allodium:4d23d6da7c644e5e,
  title = {Using computational models of learning to advance cognitive behavioral therapy},
  author = {Isabel M. Berwian and Peter Hitchock and Sashank Pisupati and Gila Schoen and Yael Niv},
  year = {2025},
  journal = {PubMed Central},
  doi = {10.1038/s44271-025-00251-4},
  url = {https://doi.org/10.1038/s44271-025-00251-4}
}

RIS

TY  - JOUR
TI  - Using computational models of learning to advance cognitive behavioral therapy
AU  - Berwian, Isabel M.
AU  - Hitchock, Peter
AU  - Pisupati, Sashank
AU  - Schoen, Gila
AU  - Niv, Yael
PY  - 2025
PB  - PubMed Central
DO  - 10.1038/s44271-025-00251-4
UR  - https://doi.org/10.1038/s44271-025-00251-4
ER  -

APA

Berwian, I. M., Hitchock, P., Pisupati, S., Schoen, G., & Niv, Y. (2025). Using computational models of learning to advance cognitive behavioral therapy. PubMed Central. https://doi.org/10.1038/s44271-025-00251-4

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