A cognitive layer architecture to support large-language model performance in psychotherapy interactions.

Max Rollwage¹, Jessica McFadyen², Keno Juchems², Annamaria Balogh², Sashank Pisupati², Margareta-Theodora Mircea², Tobias U Hauser^2,3,4,5, George Prichard², Ross Harper²

¹Limbic, London, UK. rollwagm@gmail.com.

²Limbic, London, UK.

³Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.

⁴Department of Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tubingen, Tubingen, Germany.

⁵German Center for Mental Health (DZPG), Tubingen, Germany.

PubMed DOI

Abstract

Clinician-patient conversations form the cornerstone of mental healthcare. Large language models (LLMs) could hold promise for this domain but their effectiveness in patient-facing interactions remains largely unproven. Here we introduce a cognitive layer architecture that enhances general-purpose LLMs with specialized clinical psychotherapeutic reasoning capabilities. In a randomized, double-blin…

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