Candidate Examples for a Computational Approach to Address Practical Problems in Psychiatry

Scientists and clinicians can utilize a model-based framework to develop computational approaches to psychiatric practice and bring scientifi c discoveries to a clinical interface. This chapter describes a general modeling perspective, which complements those derived in previous chapters, and provides distinct examples to highlight the scientifi c and preclinical research that can evolve out of a computational framework to offer new tools for clinical practice. It begins by reviewing areas of theoretical and modeling studies that have reached a critical mass and outlines the pathophysiological insights that have been revealed. Three particular models are used to demonstrate how clinical questions, relating to understanding disease mechanisms and predicting treatment response, could be potentially addressed using an integrated computational framework. First, the phasic dopamine temporal difference model shows how neurophysiological and neuroanatomical research, incorporated into a learning circuit model, provides a constrained hypothesis testing framework, related to the likely multiple mechanisms contributing to addiction. Second, a potential application of generative models of neuroimaging measurements (dynamic causal models of EEG data) Group photos (top left to bottom right) Rosalyn Moran, Klaas Stephan, Cameron Carter, Michael Breakspear, Read Montague, Frederike Petzschner, Matthew Botvinick, Martin Paulus, Peter Kalivas, Read Montague, Rosalyn Moran, Matthew Botvinick, Martin Paulus, Peter Kalivas, group discussion, Michael Breakspear, Frederike Petzschner, Klaas Stephan, Matthew Botvinick and Read Montague, Rosalyn Moran, Cameron Carter From “Computational Psychiatry: New Perspectives on Mental Illness,” A. David Redish and Joshua A. Gordon, eds. 2016. Strüngmann Forum Reports, vol. 20, series ed. J. Lupp. Cambridge, MA: MIT Press. ISBN 978-0-262-03542-2.