TY - JOUR
T1 - An efficient coding theory for a dynamic trajectory predicts non-uniform allocation of entorhinal grid cells to modules
AU - Mosheiff, Noga
AU - Agmon, Haggai
AU - Moriel, Avraham
AU - Burak, Yoram
N1 - Publisher Copyright:
© 2017 Mosheiff et al.
PY - 2017/6
Y1 - 2017/6
N2 - Grid cells in the entorhinal cortex encode the position of an animal in its environment with spatially periodic tuning curves with different periodicities. Recent experiments established that these cells are functionally organized in discrete modules with uniform grid spacing. Here we develop a theory for efficient coding of position, which takes into account the temporal statistics of the animal’s motion. The theory predicts a sharp decrease of module population sizes with grid spacing, in agreement with the trend seen in the experimental data. We identify a simple scheme for readout of the grid cell code by neural circuitry, that can match in accuracy the optimal Bayesian decoder. This readout scheme requires persistence over different timescales, depending on the grid cell module. Thus, we propose that the brain may employ an efficient representation of position which takes advantage of the spatiotemporal statistics of the encoded variable, in similarity to the principles that govern early sensory processing.
AB - Grid cells in the entorhinal cortex encode the position of an animal in its environment with spatially periodic tuning curves with different periodicities. Recent experiments established that these cells are functionally organized in discrete modules with uniform grid spacing. Here we develop a theory for efficient coding of position, which takes into account the temporal statistics of the animal’s motion. The theory predicts a sharp decrease of module population sizes with grid spacing, in agreement with the trend seen in the experimental data. We identify a simple scheme for readout of the grid cell code by neural circuitry, that can match in accuracy the optimal Bayesian decoder. This readout scheme requires persistence over different timescales, depending on the grid cell module. Thus, we propose that the brain may employ an efficient representation of position which takes advantage of the spatiotemporal statistics of the encoded variable, in similarity to the principles that govern early sensory processing.
UR - http://www.scopus.com/inward/record.url?scp=85021716000&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1005597
DO - 10.1371/journal.pcbi.1005597
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C2 - 28628647
AN - SCOPUS:85021716000
SN - 1553-734X
VL - 13
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 6
M1 - e1005597
ER -