Grid Cell related papers

[mthiboust]

@adam

Regarding mathematical models: There are a lot of models, that are out there and I think they can be grouped into 3 categories:

• CAN (Continous Attractor Network): A special connectivity ensures that velocity information is integrated. The connectivity is rather unlikely to be found in biological systems and all the models that tried to produce the connectivity relied on the fact, that neurons are physically placed in a special way on the neural sheet. This however was not observed in the entorhinal cortex.
• OI (Oscillatory Inference): In those models you have VCO cells (Velocity controlled oscillator cells) that project to the grid cell layer. Because of emerging interference patterns, grid cells form in that layer. Those models can explain theta precession, but require very stable oscillators, which is not very likely in biological systems.
• Single Cell Models: In those models, a specific learning rule and some other parameters allow to obtain grid cells. However those model are not able to do path integration. “The Emergence of Grid Cells: Intelligent Design or Just Adaptation?”

Thanks @adam! Your explanations are very helpful to structure my mental cognitive maps about grid cells modelling

One of my favorite paper on grid cells is this one (about biology, not mathematical modelling):

A map-like micro-organization of grid cells in the medial entorhinal cortex