## EMFit

EMFit is a matlab toolbox for hierarchical fitting of computational / RL models to trial-by-trial decision data. It provides an extensive set of example likelihood functions for several different tasks, and extensive tools for model validation and comparison. The code is open-source and hosted on github.

EMFit page on github## TCPW

The Transcontinental Computational Psychiatry Workgroup hosts a regular online series of talks on computational psychiatry. We encourage speakers to combine a tutorial part on their methods with example applications in the domain of mental health.

TCPW Website## Interested in computational psychiatry?

If you are interested in computational psychiatry, you would greatly benefit from both mathematical / theoretical and clinical expertise. A good starting point would be:

### General introduction

### Clinical

- Basic understanding of major diagnoses
- Some understanding of the lived experience, e.g. through clinical shadowing / experience, or from reading autobiographies such as
- Kay Jamison – An Unquiet Mind
- Elyn Saks – The Centre Cannot Hold

- Basic understanding of psychotherapy
- Basic understanding of pharmacotherapy

### Theoretical / Mathematical

You need some experience with and understanding of differential equations, linear algebra, Bayesian inference and mathematical statistics and reinforcement learning:

- General textbook: Riley, Hobson and Bence – Mathematical Methods for Engineering and Physics
- Linear algebra: Fraleigh and Beauregard – Linear Algebra
- Stats and machine learning: David MacKay – Information Theory, Inference, and Learning Algorithms
- Reinforcement learning: Sutton and Barto – Reinforcement Learning