Emergence of task-dependent representations in working memory circuits

• Main Authors: Cristina eSavin, Jochen eTriesch
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2014-05-01
• Series: Frontiers in Computational Neuroscience
• Subjects: Prefrontal Cortex; STDP; synaptic scaling; working memory; Intrinsic Plasticity; reward-dependent learning
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00057/full

A wealth of experimental evidence suggests that working memory circuits preferentially represent information that is behaviorally relevant. Still, we are missing a mechanistic account of how these representations come about. Here we provide a simple explanation for a range of experimental findings, in light of prefrontal circuits adapting to task constraints by reward-dependent learning. In particular, we model a neural network shaped by reward-modulated spike-timing dependent plasticity (r-STDP) and homeostatic plasticity (intrinsic excitability and synaptic scaling). We show that the experimentally-observed neural representations naturally emerge in an initially unstructured circuit as it learns to solve several working memory tasks. These results point to a critical, and previously unappreciated, role for reward-dependent learning in shaping prefrontal cortex activity.