Oscillation-driven memory encoding, maintenance and recall in an entorhinal-hippocampal circuit model

Abstract

During the execution of working memory tasks, task-relevant information is processed by local circuits across multiple brain regions. How this multi-area computation is conducted by the brain remains largely unknown. To explore such mechanisms in spatial working memory, we constructed a neural network model involving parvalbumin-positive, somatostatin-positive and vasoactive intestinal polypeptide-positive interneurons in the hippocampal CA1 and the superficial and deep layers of medial entorhinal cortex (MEC). Our model is based on a hypothesis that cholinergic modulations differently regulate information flows across CA1 and MEC at memory encoding, maintenance and recall during delayed nonmatching-to-place tasks. In the model, theta oscillation coordinates the proper timing of interactions between these regions. Furthermore, the model predicts that MEC is engaged in decoding as well as encoding spatial memory, which we confirmed by experimental data analysis. Thus, our model accounts for the neurobiological characteristics of the cross-area information routing underlying working memory tasks.