Welinder Peter E, Burak Yoram, Fiete Ila R
Computation and Neural Systems, California Institute of Technology, Pasadena, California, USA.
Hippocampus. 2008;18(12):1283-300. doi: 10.1002/hipo.20519.
We review progress on the modeling and theoretical fronts in the quest to unravel the computational properties of the grid cell code and to explain the mechanisms underlying grid cell dynamics. The goals of the review are to outline a coherent framework for understanding the dynamics of grid cells and their representation of space; to critically present and draw contrasts between recurrent network models of grid cells based on continuous attractor dynamics and independent-neuron models based on temporal interference; and to suggest open questions for experiment and theory.
我们回顾了在揭示网格细胞编码的计算特性以及解释网格细胞动力学潜在机制的研究中，建模和理论方面所取得的进展。本次综述的目的是勾勒出一个连贯的框架，以理解网格细胞的动力学及其对空间的表征；批判性地呈现基于连续吸引子动力学的网格细胞循环网络模型与基于时间干扰的独立神经元模型之间的差异并进行对比；并提出实验和理论方面的开放性问题。
