Mosheiff Noga, Agmon Haggai, Moriel Avraham, Burak Yoram
Racah Institute of Physics, Hebrew University of Jerusalem, Jerusalem, Israel.
Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem, Israel.
PLoS Comput Biol. 2017 Jun 19;13(6):e1005597. doi: 10.1371/journal.pcbi.1005597. eCollection 2017 Jun.
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.
内嗅皮层中的网格细胞通过具有不同周期性的空间周期性调谐曲线对动物在其环境中的位置进行编码。最近的实验表明，这些细胞在功能上以具有均匀网格间距的离散模块进行组织。在这里，我们提出了一种位置高效编码理论，该理论考虑了动物运动的时间统计信息。该理论预测模块种群大小会随着网格间距急剧减小，这与实验数据中观察到的趋势一致。我们确定了一种由神经回路读出网格细胞编码的简单方案，其准确性可与最优贝叶斯解码器相匹配。这种读出方案需要在不同时间尺度上保持，这取决于网格细胞模块。因此，我们提出大脑可能采用一种位置的高效表示方式，该方式利用了编码变量的时空统计信息，这类似于早期感觉处理所遵循的原则。
