1. A schematic overview of the analysis stream underlying the treatment of computational psychiatry in this article.
A schematic overview of the analysis stream underlying the treatment of computational psychiatry in this article. The basic procedure involves specifying a model of behavior cast in terms of a Markov decision process (MDP). Under the assumption that choices are made in an approximately Bayes optimal fashion using active (Bayesian) inference, this model is sufficient to predict behavior. If we supplement the model specification (MDP) with empirical choice behavior (Data), we can estimate the prior beliefs responsible for those choices. If this is repeated for a series of subjects, the ensuing priors can then be analyzed in a random-effects (PEB) model to make inferences about group effects or to perform cross-validation. Furthermore, physiological and behavioral predictions can be used as expansion variables for fMRI or other neuroimaging time series (bottom left). The routines in the boxes refer to MATLAB routines that are available in the academic software SPM. These routines are sufficient to both simulate behavioral responses and analyze empirical or observed choice behaviour, at both the within-subject and between-subject levels. The final routine also enables cross-validation and predictions about a new subject’s prior beliefs using a leave-one-out scheme that may be useful for establishing the predictive validity of any models that are considered.
Philipp Schwartenbeck, and Karl Friston eneuro 2016;3:ENEURO
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