网格状结构是路径集成的最佳选择
Grid-like structure is optimal for path integration
摘要：
内侧内嗅皮层的网格细胞被认为在路径整合中起关键作用。然而，路径集成和它们的射击场的网格状排列之间的关系仍然不清楚。我们提供的理论证据表明，网格状结构和路径整合密切相关。在一维中，网格状结构提供了路径积分的最佳解决方案，假设噪声相关结构是高斯的。在二维情况下，假设噪声为高斯噪声，当1-噪声相关性和神经元感受野结构都可以乘法分解为正交分量，2-分解后的相关矩阵的特征值比相应特征向量频率的平方衰减得快时，矩形网格结构是最优解。我们还将解决的解码机制，并表明解码的问题减少到任务相关信息的提取任务相关信息的存在下的问题。基于变化的总体编码为这个问题提供了最佳解决方案。
英文摘要：
Grid cells in medial entorhinal cortex are believed to play a key role in path integration. However, the relation between path integration and the grid-like arrangement of their firing field remains unclear. We provide theoretical evidence that grid-like structure and path integration are closely related. In one dimension, the grid-like structure provides the optimal solution for path integration assuming that the noise correlation structure is Gaussian. In two dimensions, assuming that the noise is Gaussian, rectangular grid-like structure is the optimal solution provided that 1- both noise correlation and receptive field structures of the neurons can be multiplicatively decomposed into orthogonal components and 2- the eigenvalues of the decomposed correlation matrices decrease faster than the square of the frequency of the corresponding eigenvectors. We will also address the decoding mechanism and show that the problem of decoding reduces to the problem of extracting task relevant information in the presence of task irrelevant information. Change-based Population Coding provides the optimal solution for this problem.
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