Zhang Zhihui, Tang Fengzhen, Li Yiping, Feng Xisheng
University of Science and Technology of China, Hefei, 230026 China.
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016 China.
Cogn Neurodyn. 2024 Jun;18(3):1227-1243. doi: 10.1007/s11571-023-09972-w. Epub 2023 Apr 20.
The grid cells in the medial entorhinal cortex are widely recognized as a critical component of spatial cognition within the entorhinal-hippocampal neuronal circuits. To account for the hexagonal patterns, several computational models have been proposed. However, there is still considerable debate regarding the interaction between grid cells and place cells. In response, we have developed a novel grid-cell computational model based on cognitive space transformation, which established a theoretical framework of the interaction between place cells and grid cells for encoding and transforming positions between the local frame and global frame. Our model not only can generate the firing patterns of the grid cells but also reproduces the biological experiment results about the grid-cell global representation of connected environments and supports the conjecture about the underlying reason. Moreover, our model provides new insights into how grid cells and place cells integrate external and self-motion cues.
内嗅皮层中的网格细胞被广泛认为是内嗅-海马神经元回路中空间认知的关键组成部分。为了解释六边形模式,已经提出了几种计算模型。然而,关于网格细胞和位置细胞之间的相互作用仍存在相当大的争议。作为回应,我们基于认知空间变换开发了一种新型网格细胞计算模型,该模型建立了位置细胞和网格细胞之间相互作用的理论框架,用于编码和转换局部框架和全局框架之间的位置。我们的模型不仅可以生成网格细胞的放电模式,还能重现关于网格细胞对相连环境的全局表征的生物学实验结果,并支持关于其潜在原因的推测。此外,我们的模型为网格细胞和位置细胞如何整合外部和自身运动线索提供了新的见解。