Candidate Examples for a Computational Approach to Address Practical Problems in Psychiatry
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 scientific 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 scientific 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. 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. A potential application of generative models of neuroimaging measurements (dynamic causal models of EEG data) is described to predict individual treatment responses in patients with schizophrenia. The third example offers a novel approach to quantifying patient outcomes under a “recovery model” of psychiatric illness. In conclusion, consideration is given to the community efforts needed to support the validation of these and future applications.
Keywords: Strüngmann Forum Report, biophysical models, modeling allostasis, HPA axis, addiction, dopamine, glutamate, schizophrenia
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