MAR 14, 2019 8:00 AM PDT

Using Computational Psychiatry to Develop a Rigorous and Integrative Understanding of Psychiatric Disorders

Presented at: Neuroscience 2019
C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Associate Professor, Faculty of Medicine, University of Lisbon
    Biography
      Tiago V. Maia is an Associate Professor at the Faculty of Medicine of the University of Lisbon, a researcher at the Institute for Molecular Medicine in Lisbon, and a member of the Coordinating Council of the Mind-Brain College of the University of Lisbon (Portugal). He did his Ph.D. in Psychology at Carnegie Mellon University. Before returning to Portugal (his home country), he was an Assistant Professor of Clinical Neurobiology in the Department of Psychiatry at Columbia University. Research in his lab focuses on the integrated use of computational modeling, brain imaging, and behavioral experiments to understand the neural bases of several psychiatric disorders. His work has been published in several leading journals (e.g., Nature Neuroscience and PNAS). He has also played a very active role in the development and promotion of the emerging field of computational psychiatry (e.g., serving as guest editor or guest co-editor for special issues on the topic for Biological Psychiatry, Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, and Clinical Psychological Science). He was considered a "Rising Star" by the Association for Psychological Science.

    Abstract

    The contemporary understanding of psychiatric disorders typically consists of a vast but often poorly interrelated set of facts and hypotheses that fail to coalesce into an integrated whole. This situation is due, in part, to the social dynamics in the scientific fields that study psychiatric disorders; it is, however, also due to the absence of rigorous theoretical tools that support the development of a more integrative understanding. This talk will show how theoretical tools from computational psychiatry can foster such integrative understanding, using Tourette syndrome (TS) as an illustrative example. Specifically, the talk will show how a computational understanding of the functions of dopamine, together with the likely nature of dopaminergic dysfunction in TS revealed in molecular-imaging studies, can provide an integrated understanding of the mechanisms of action of the various medications used to treat TS, the time course of the response to those medications, the findings of increased reward and habit learning in TS, and a vast array of functional and structural imaging findings in TS, while simultaneously explaining how and why tics arise and are expressed. This approach, combining formal rigor with substantial explanatory and predictive power, holds the promise to bring to psychiatry what has undoubtedly been one of the key drivers of success in fields such as physics (and, indeed, in the remarkable development of our technological society).

    Learning Objectives: 

    1. Understand how computational models can be used as theoretical tools to provide rigorous, integrative accounts of psychiatric disorders.
    2. Understand how a computational understanding of the functions of dopamine, considered in conjunction with the likely nature of dopaminergic disturbances in Tourette syndrome, provides a cohesive explanation for a very broad range of findings in Tourette syndrome.


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