Grid cells in the medial entorhinal cortex (MEC) encode position using a distributed representation across multiple neural populations (modules), each possessing a distinct spatial scale. The modular structure of the representation confers the grid cell neural code with large capacity. Yet, the modularity poses significant challenges for the neural circuitry that maintains the representation, and updates it based on self motion. Small incompatible drifts in different modules, driven by noise, can rapidly lead to large, abrupt shifts in the represented position, resulting in catastrophic readout errors. Here we propose a theoretical model of coupled modules. The coupling suppresses incompatible drifts, allowing for a stable embedding of a two dimensional variable (position) in a higher dimensional neural attractor, while preserving the large capacity. We propose that coupling of this type may be implemented by recurrent synaptic connectivity within the mEC with a relatively simple and biologically plausible structure.
This is a theoretical work. There are no data sets associated with it.
- Yoram Burak
- Yoram Burak
- Yoram Burak
- Noga Mosheiff
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Stephanie Palmer, University of Chicago, United States
© 2019, Mosheiff & Burak
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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