Computational Psychotherapy Lab
How do interventions for affective disorders lead to change, and how can we determine which intervention a specific individual will benefit from?
The Computational Psychotherapy Lab addresses these questions by modelling psychological interventions as processes of learning and memory. We formalise these processes using recent advancements in computational frameworks such as reinforcement learning and Bayesian inference, which allow us to derive precise hypotheses about how interventions operate and how they can be improved.
To test these hypotheses, we develop behavioural tasks and models that capture learning, memory, and decision-making processes, and apply them in longitudinal clinical intervention studies. This approach enables us to identify mechanisms of change and to develop predictors of treatment response that can inform the selection of interventions.
Our work spans the full pipeline from task and model development to clinical trials. In the long term, we aim to establish a mechanistic, learning-based framework for understanding how interventions produce lasting change and how they can be optimally combined and sequenced. With this approach, we aim to improve the effectiveness of psychological interventions and tailor them more closely to individuals.
Key references
Berwian, I. M., Ren, Y., Pisupati, S., Ding, J., Moon, S., Chiu, J. C., Chandrasekhar, D., & Niv, Y. (2025 under review). Selective maintenance of aversive memories as a mechanism of spontaneous recovery of fear [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/2kdtf_v1
Ding, J., Chiu, J. C., Moon, S., Ren, Y., Turner, D. M., Shoval, G., Niv, Y., & Berwian, I. M. (2026). Protocol for a randomized trial to predict the efficacy of cognitive and behavioral interventions for symptoms of depression. Frontiers in Psychiatry, 17, Article 1774560. https://doi.org/10.3389/fpsyt.2026.1774560
Berwian, I. M., Wenzel, J. G., Collins, A. G. E., Seifritz, E., Stephan, K. E., Walter, H., & Huys, Q. J. M. (2020). Computational mechanisms of effort and reward decisions in patients with depression and their association with relapse after antidepressant discontinuation. JAMA Psychiatry, 77(5), 513–522. https://doi.org/10.1001/jamapsychiatry.2019.4971