Place-grid cells dynamic coupling enables error minimization for path integration

FERNANDEZ LEON, JOSE A.; UYSAL, AHMET KERIM; JI, DAOYUN

Simposio; 4th Interdisciplinary Navigation Symposium (iNav 2022); 2022

Navigation is one of the most fundamental animal skills. Grid cells (GCs) in the medial entorhinal cortex (MEC) use speed and direction to map the environment during spatial navigation. In turn, hippocampal place cells (PCs) encode place and seem to minimize the accumulated error of GCs for path integration. Despite PCs and GCs being part of a generalized path integration system, the dynamic relationship between both cell types and the involved mechanism for error minimization is yet to be understood. Recent theoretical studies have suggested the possibility of a network of loops between the Hippocampus and MEC. We hypothesized that the dynamical coupling between these cell types could coordinate the integration of velocity input to the GCs network and update the network’s estimated position using PC network signals. A realistic toroidal topology model of GCs was implemented based on path integration to address this issue. The grid network received velocity information of a simulated animal and PCs’ information through their place fields (PFs). Place cell-like neurons were modeled by defining their PFs through visual flow detection and proximity information during the animal’s exploration of a squared arena. PCs were activated by the information from GCs with a similar spatial phase but a diverse spacing and orientation. PFs appeared mostly during early exploration, helping to decrease the path integration error of GCs. PFs closer to the animal’s current location contributed more to minimizing the error accumulation than distal PFs. Relatively slow-emergent PCs enabled anchoring signals for a precise GCs path integration. Consistent with our experimental observations that place cells can retrieve spatial information from grid-like cells to create a more accurate spatial representation, the dynamic coupling between PCs and GCs may be one of the key components of the brain’s navigational system.