Code, Models, Tutorials

All of the models and code developed in my lab are available on our laboratory’s GitHub repository (www.github.com/UWCCDL); some of them are also available on other open-source repositories.

Models

Declarative vs. procedural decision-making

This is the code to fit the declarative and procedural models of decision-making to the Incentive Processing Task of the Human Connectome Project. The code was used in this paper.

https://github.com/UWCCDL/ProcVsDecl

Tutorials

Maximum Likelihood for ACT-R

Have you have worked in ACT-R and wanted to use Maximum Likelihood to fit and analyze your models? Here is a step-by-step tutorial with running examples! https://github.com/UWCCDL/MLExACTR

Textbook Code

This is the code from the free textbook I co-authored with Catherine Sibert. It covers examples of how to build reinforcement learning models, drift-diffusion models, memory models, and various types of neural networks in Python: https://github.com/TheRealDrDre/CompCogNeuro