University of Cambridge > Talks.cam > Department of Psychiatry & CPFT Thursday Lunchtime Seminar Series > Interoceptive Self-Inference: An Embodied Approach to Computational Psychiatry

Interoceptive Self-Inference: An Embodied Approach to Computational Psychiatry

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Our ability to learn from an ever-changing, volatile world is essential. Convergent evidence suggests that deficits in the ability to update beliefs in the face of such uncertainty may underpin a variety of psychiatric illnesses. In parallel, we know that many such disorders are accompanied by profound somatic and visceral disruptions, and these are in turn underpinned by the very same neural machinery which encodes decision uncertainty. Here, I will present evidence that metacognitive awareness of uncertainty is biased by visceral arousal. On the basis of these findings, we recently proposed a new computational model of “interoceptive self-inference”, in which the brain samples the volatility of visceral rhythms to predict future decision uncertainty. On this basis, we argue that disordered interoceptive beliefs and/or visceral sensation can both act to produce pervasive decision biases such as those which characterize the major mood and neurodevelopmental disorders.

This talk is part of the Department of Psychiatry & CPFT Thursday Lunchtime Seminar Series series.

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