Under the Hood: Using Computational Psychiatry to Make Psychological Therapies More Mechanism-Focused - Nair, Akshay; Rutledge, Robb B.; Mason, Liam (Frontiers in Psychiatry, 2020)
Psychological therapies are an important part of the treatment of a range of psychiatric disorders such as depression and anxiety. There is a growing desire to understand the shared mechanisms by which therapies effect change so as to improve treatment outcomes. Here we argue that adopting a computational framework may be one such approach. Computational psychiatry aims to provide a theoretical framework for moving between higher-level psychological constructs to neural circuits by modelling these constructs, like emotions, decisions and beliefs, mathematically. These models are explicit hypotheses that contain quantifiable variables and parameters derived from each individual’s behaviour. This approach has two advantages. Firstly, some of the variables described by these models appears to reflect the neural activity of specific brain regions. Secondly, the parameters estimated by these models may offer a unique description of a patient’s symptoms which can be used to both tailor therapy and track its effect. In doing so this approach may offer some additional granularity in understanding how psychological therapies are working. Although this field shows significant promise, we also highlight several of the key hurdles that must first be overcome before clinical translation of computational insights can be realised.