REMI: Reconstructing Episodic Memory During Internally Driven Path Planning

TL;DR

This paper introduces a system-level theory explaining how MEC and HC interactions support cue-triggered goal retrieval, path planning, and sensory reconstruction during internally driven navigation, validated through simulations.

Contribution

It proposes a novel wiring scheme connecting grid and place cells to enable goal recall, shortcut planning, and sensory reconstruction, supported by analytical and simulation results.

Findings

Grid-based planning allows shortcuts through unvisited locations.

Place cells trigger sensory reconstruction along planned routes.

The model demonstrates effective navigation in simulated environments.

Abstract

Grid cells in the medial entorhinal cortex (MEC) and place cells in the hippocampus (HC) both form spatial representations. Grid cells fire in triangular grid patterns, while place cells fire at specific locations and respond to contextual cues. How do these interacting systems support not only spatial encoding but also internally driven path planning, such as navigating to locations recalled from cues? Here, we propose a system-level theory of MEC-HC wiring that explains how grid and place cell patterns could be connected to enable cue-triggered goal retrieval, path planning, and reconstruction of sensory experience along planned routes. We suggest that place cells autoassociate sensory inputs with grid cell patterns, allowing sensory cues to trigger recall of goal-location grid patterns. We show analytically that grid-based planning permits shortcuts through unvisited locations and generalizes local transitions to long-range paths. During planning, intermediate grid states trigger place cell pattern completion, reconstructing sensory experiences along the route. Using a single-layer RNN modeling the HC-MEC loop with a planning subnetwork, we demonstrate these effects in both biologically grounded navigation simulations using RatatouGym and visually realistic navigation tasks using Habitat Sim.