A neural-level model of spatial memory and imagery

• Main Authors: Andrej Bicanski, Neil Burgess
• Format: Article
• Language: English
• Published: eLife Sciences Publications Ltd 2018-09-01
• Series: eLife
• Subjects: computational model; episodic memory; spatially selective cells; spatial cognition; scene construction; trace cells
• Online Access: https://elifesciences.org/articles/33752

We present a model of how neural representations of egocentric spatial experiences in parietal cortex interface with viewpoint-independent representations in medial temporal areas, via retrosplenial cortex, to enable many key aspects of spatial cognition. This account shows how previously reported neural responses (place, head-direction and grid cells, allocentric boundary- and object-vector cells, gain-field neurons) can map onto higher cognitive function in a modular way, and predicts new cell types (egocentric and head-direction-modulated boundary- and object-vector cells). The model predicts how these neural populations should interact across multiple brain regions to support spatial memory, scene construction, novelty-detection, ‘trace cells’, and mental navigation. Simulated behavior and firing rate maps are compared to experimental data, for example showing how object-vector cells allow items to be remembered within a contextual representation based on environmental boundaries, and how grid cells could update the viewpoint in imagery during planning and short-cutting by driving sequential place cell activity.