Code to fit Bayesian versions of simple reinforcement learning models. Produces posteriors of learning rates and softmax choice parameters at both the individual and group levels.
Produces results in Lighthall et al. Feedback-based learning in aging: Contributions and trajectories of change in striatal and hippocampal systems.
Run from the command line with runmodel.py. Example analysis in Run_Models.ipynb.