This presentation is an introduction to Computational Psychiatry, showing how concepts such as the Markov Blanket and Bayesian Inference can help us to understand how the brain enhances survival by constantly updating its models of external and internal states. These updates occur via a process called active inference wherein the brain makes predictions about internal and external states, acts upon them, and updates its models based on sensory data. Like other prey species, humans have evolved sensitive threat-detection systems that trigger defensive responses when danger is perceived and deactivate them when safety is sensed. These high-energy responses divert energy resources from cognitive mechanisms involved in model updates, and functions such as digestion and immunological processes. While a policy of prioritizing caution (better safe than sorry) enables quick responses to threats, it can also hinder accurate model updates and lead to ongoing mismatches between expectation and reality-a process implicated in many clinical disorders. Impaired safety-sensing parallels a faulty thermostat unable to detect warmth, keeping defensive circuits on high alert and stalling error correction. Trauma and genetics are likely causes of such impairments and there will be a discussion of how active inference principles can be applied to everyday practice.
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