Intrinsic and circuit mechanisms of predictive coding in a grid cell network model

Abstract

Grid cells in the medial entorhinal cortex (MEC) fire at the vertices of a hexagonal lattice, forming an allocentric code for the animal's current position. Recent studies have identified a class of grid cells that represent locations ahead of the animal. How do these predictive representations emerge from the wetware of the MEC? We developed a detailed conductance-based model of the MEC network, constrained by empirical data on the biophysical properties of stellate cells and the topology of the MEC network. The model revealed two mechanisms by which grid cells can signal future locations. First, hyperpolarizing inhibition from interneurons activates HCN channels in stellate cells, whose slow kinetics maintain a depolarizing influence after inhibition ends, advancing spike timing and shifting the inferred position forward by ~5% of a grid field diameter. Second, introducing asymmetry into the inhibitory connectivity, by skewing the Gaussian profile of interneuron-to-stellate connections, causes inhibition to rise more steeply and enables earlier spiking, advancing the inferred position by up to ~25%. A corollary of our model is that the extent of the predictive code changes monotonically along the dorsoventral axis of the MEC, following the experimentally measured dorsoventral gradient in HCN time constants.