Topic: Computational Psychiatry

Psychotic disorders are devastating conditions without any mechanistic treatment available. One major hurdle in the biological study of psychosis is the challenge of rigorously probing this condition in pre-clinical animal models. The goal of our research is to develop and exploit innovative frameworks for the study of psychosis in mice. In our present work, where we developed a cross-species computational psychiatry approach to probe hallucination-like perception. This enabled us to directly relate human and mouse behavior, and to demonstrate and dissect the causal role of striatal dopamine i

Risk occupies a central role in both the theory and practice of decision-making. Although it is deeply implicated in many conditions involving dysfunctional behavior and thought, modern theoretical approaches to understanding and mitigating risk in either one-shot or sequential settings, which are derived largely from finance and economics, have yet to permeate fully the fields of neural reinforcement learning and computational psychiatry. I will discuss the use of dynamic and static versions of one prominent approach, namely conditional value-at-risk, to examine both the nature of risk avoida