pydbm

Python package implementing the Dynamic Belief Model (DBM) by Yu and Cohen (2008).

This package is a lightweight Python package to implement the Dynamic Belief Model (DBM) by Yu and Cohen (2008). The DBM is a normative computational model from psychology. It can be used to et trial-to-trial estimates of the probability of an event occuring on a given trial, given the trial history before.

Installation

To install, simply clone the respository

git clone https://github.com/Gilles86/pydbm/

Then install the Python package using

python setup.py install

Or, when you need super powers, because you work at a university with underpaid sysadmins

sudo python setup.py install

I would recommend to use the Jupyter notebook environment.

Examples

See here for an example of how to fit the DBM to synthetic data.

References

Yu, A. J., & Cohen, J. D. (2008). Sequential effects: Superstition or rational behavior? Advances in Neural Information Processing Systems, 21, 1873–1880.
Ide, J. S., Shenoy, P., Yu, A. J., & Li, C. S. R. (2013). Bayesian Prediction and Evaluation in the Anterior Cingulate Cortex. Journal of Neuroscience, 33(5), 2039–2047. http://doi.org/10.1523/JNEUROSCI.2201-12.2013