weilongzheng/pfc_md_modeling

Recurrent Neural Networks of Mediodorsal Thalamus and Prefrontal Cortex in Temporal Contexts

Recurrent Neural Networks of Mediodorsal Thalamus and Prefrontal Cortex in Temporal Contexts

Model Framework

We develop recurrent neural networks with a thalamus-like component and synaptic plasticity rules to model the thalamocortical interactions in cognitive flexibility. We find that the MD component is able to extract context information by integrating context-relevant traces over trials and to suppress context-irrelevant neurons in the PFC. Incorporating the MD disjoints the contextual representations and enables efficient population coding in the PFC.

Get started with training and testing

• Train a default network with train.py for the cognitive task in Rikhye et al. 2018

• Perform decoding analysis for context and rule with decoding_analysis.py

Dependencies

The code is tested in Python 3.6.