Abstract

The ability to track space and time relies on neural networks in the hippocampus and entorhinal cortex. These networks contain specialized position-coding cell types, including place cells in the hippocampus and grid cells in the medial entorhinal cortex. I will show how recent technological developments allow the dynamics of thousands of place cells and grid cells to be monitored during behaviour. Based on experiments with these new technologies, I will show how the dynamics of grid cells arises in large neural populations. In agreement with continuous attractor network models of grid cells, the joint activity of grid cells from a single grid module operates on a low-dimensional manifold with the topology of a torus. The toroidal topology emerges early in postnatal development, before the onset of spatial experience, and before opening of ear canals and eyes. Network dynamics in grid cells is strongly related to the dynamics of place cells, and grid cells may be responsible for transitions between discrete spatial maps in the hippocampus. Finally, I will show how time is encoded across seconds to hours in the population state space of neural networks in the lateral entorhinal cortex and how specialized dynamics in this region provides the brain with a neural code that segments the passage of cumulative experience into discrete time chunks that may serve as building blocks for reconstructive temporal memory.