computational psychiatry
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Professor Geoffrey J Goodhill
The Department of Neuroscience at Washington University School of Medicine is seeking a tenure-track investigator at the level of Assistant Professor to develop an innovative research program in Theoretical/Computational Neuroscience. The successful candidate will join a thriving theoretical/computational neuroscience community at Washington University, including the new Center for Theoretical and Computational Neuroscience. In addition, the Department also has world-class research strengths in systems, circuits and behavior, cellular and molecular neuroscience using a variety of animal models including worms, flies, zebrafish, rodents and non-human primates. The Department’s focus on fundamental neuroscience, outstanding research support facilities, and the depth, breadth and collegiality of our culture provide an exceptional environment to launch your independent research program.
Why are we consistently inconsistent? On the neural mechanisms of behavioural inconsistency
The ubiquity of opportunity cost: Foraging and beyond
A key insight from the foraging literature is the importance of assessing the overall environmental quality — via global reward rate or similar measures, which capture the opportunity cost of time and can guide behavioral allocation toward relatively richer options. Meanwhile, the majority of research in decision neuroscience and computational psychiatry has focused instead on how choices are guided by much more local, event-locked evaluations: of individual situations, actions, or outcomes. I review a combination of research and theoretical speculation from my lab and others that emphasizes the role of foraging's average rewards and opportunity costs in a much larger range of decision problems, including risk, time discounting, vigor, cognitive control, and deliberation. The broad range of behaviors affected by this type of evaluation gives a new theoretical perspective on the effects of stress and autonomic mobilization, and on mood and the broad range of symptoms associated with mood disorders.
Advances in Computational Psychiatry: Understanding (cognitive) control as a network process
The human brain is a complex organ characterized by heterogeneous patterns of interconnections. Non-invasive imaging techniques now allow for these patterns to be carefully and comprehensively mapped in individual humans, paving the way for a better understanding of how wiring supports cognitive processes. While a large body of work now focuses on descriptive statistics to characterize these wiring patterns, a critical open question lies in how the organization of these networks constrains the potential repertoire of brain dynamics. In this talk, I will describe an approach for understanding how perturbations to brain dynamics propagate through complex wiring patterns, driving the brain into new states of activity. Drawing on a range of disciplinary tools – from graph theory to network control theory and optimization – I will identify control points in brain networks and characterize trajectories of brain activity states following perturbation to those points. Finally, I will describe how these computational tools and approaches can be used to better understand the brain's intrinsic control mechanisms and their alterations in psychiatric conditions.
Neurocomputational mechanisms underlying developmental psychiatric disorders
Hallucinating mice and dopamine – towards mechanistic treatment targets for psychosis
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 in hallucination-like perception. Our results suggest a neural circuit mechanism for the long-standing dopamine hypothesis of psychosis, and provide a new translational framework for the biological study of psychosis. This opens up exciting possibilities for advancing the biological understanding of psychosis and to identify mechanistic treatment targets.
Peril, Prudence and Planning as Risk, Avoidance and Worry
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 avoidant choices, encompassing such things as justified gambler's fallacies, and the optimal planning that can lead to consideration of such choices, with implications for offline, ruminative, thinking.
Towards better interoceptive biomarkers in computational psychiatry
Empirical evidence and theoretical models both increasingly emphasize the importance of interoceptive processing in mental health. Indeed, many mood and psychiatric disorders involve disturbed feelings and/or beliefs about the visceral body. However, current methods to measure interoceptive ability are limited in a number of ways, restricting the utility and interpretation of interoceptive biomarkers in psychiatry. I will present some newly developed measures and models which aim to improve our understanding of disordered brain-body interaction in psychiatric illnesses.
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