Lectures, Fundamentals of Computational Psychiatry course, ISMMS, 10/2022

These are the slides I have used for my lectures as part of the Fundamentals of Computational Psychiatry Course, organized at ISMMS over the months of October and November 2022

Lecture 5, parameter optimization, where I introduce the concepts of optimizing model parameters to best fit a target behavior. On this matter see also Daw’s “Trial-by-trial data analysis using computational models

Lecture 7, Bayesian observer, where I introduce the concepts of Bayesian inference and the basic principles of Bayesian models of behavior.

Lecture 8, Bayesian networks, where I introduce the concepts of Bayesian networks and the associated principles of causality.

For both Lecture 7 and 8, I also suggest to read Ma’s “Bayesian models of perception and action” (available to purchase as well as to download for free).

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