Deep belief network learns context dependent behavior (Raudies, Zilli, Hasselmo 2014)

We tested a rule generalization capability with a Deep Belief Network (DBN), Multi-Layer Perceptron network, and the combination of a DBN with a linear perceptron (LP). Overall, the combination of the DBN and LP had the highest success rate for generalization.

Model Type: Connectionist Network

Simulation Environment: MATLAB

Implementer(s): Raudies, Florian [florian.raudies at]


Raudies F, Zilli EA, Hasselmo ME. (2014). Deep belief networks learn context dependent behavior. PloS one. 9 [PubMed]

This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.