Examining Remapping Phenomena in a Computational Model of the Hippocampus

Abstract

The hippocampus is a brain structure known to be involved in high-level cognitive features such as memory and navigation. Spatially responsive cells in the hippocampal region, known as place cells and grid cells, have given neuroscientists an opportunity to try to decipher the neural implementation of computations performed by the hippocampus. Important insights toward this goal might be offered by studying the phenomena of global remapping and rate remapping, known from hippocampal experiments, that relate changes in the environment to changes in neural activity. This project implements a biologically plausible neural network that models grid cells, place cells and other parts of the hippocampus in order to computationally reproduce the remapping phenomena. The implemented model successfully exhibits both global and rate remapping, and thus offers a potential framework for a better understanding of why these phenomena occur.