Literature DB >> 30176988

A neural-level model of spatial memory and imagery.

Andrej Bicanski1, Neil Burgess1.   

Abstract

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.
© 2018, Bicanski et al.

Entities:  

Keywords:  computational model; episodic memory; neuroscience; none; scene construction; spatial cognition; spatially selective cells; trace cells

Mesh:

Year:  2018        PMID: 30176988      PMCID: PMC6122954          DOI: 10.7554/eLife.33752

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.140


  155 in total

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  28 in total

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