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Transforming psychiatry with computational and brain-based methods

Nature Computational Science volume 5, pages 844–847 (2025)Cite this article

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Integrating computational methods with brain-based data presents a path to precision psychiatry by capturing individual neurobiological variation, improving diagnosis, prognosis, and personalized care. This Viewpoint highlights advances in normative and foundation models, the importance of clinically grounded principles, and the role of robust measurement and interpretability in progressing mental health care.

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Authors and Affiliations

  1. Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA

    Teddy J. Akiki & Leanne M. Williams

  2. National Center for PTSD, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA

    Teddy J. Akiki

  3. Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA

    Leanne M. Williams

  4. Department of Psychiatry and Psychotherapy, University Hospital Tübingen, Tübingen, Germany

    Thomas Wolfers & Yanwu Yang

  5. German Center for Mental Health (DZPG), Jena & Tübingen, Germany

    Thomas Wolfers & Yanwu Yang

  6. Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King’s College London, London, UK

    Daniel Stahl

  7. School of Psychology, Trinity College Dublin, Dublin, Ireland

    Claire M. Gillan

  8. Trinity College Institute for Neuroscience, Trinity College Dublin, Dublin, Ireland

    Claire M. Gillan

  9. FutureNeuro Research Ireland Centre, Trinity College Dublin, Dublin, Ireland

    Claire M. Gillan

Authors
  1. Teddy J. Akiki
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  2. Leanne M. Williams
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  3. Thomas Wolfers
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  4. Yanwu Yang
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  5. Daniel Stahl
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  6. Claire M. Gillan
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Corresponding authors

Correspondence to Teddy J. Akiki, Leanne M. Williams, Thomas Wolfers, Yanwu Yang, Daniel Stahl or Claire M. Gillan.

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Competing interests

L.M.W. declares US patent applications 10/034,645 and 15/820,338: Systems and methods for detecting complex networks in MRI image data. T.W. is a founding shareholder and advisor to Baba-Vision. T.J.A., Y.Y., D.S. and C.M.G. declare no competing interests.

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Akiki, T.J., Williams, L.M., Wolfers, T. et al. Transforming psychiatry with computational and brain-based methods. Nat Comput Sci 5, 844–847 (2025). https://doi.org/10.1038/s43588-025-00884-9

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