Entorhinal-hippocampal interactions lead to globally coherent representations of space

Taiping Zeng , Bailu Si , Xiaoli Li
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Abstract

The firing maps of grid cells in the entorhinal cortex are thought to provide an efficient metric system capable of supporting spatial inference in all environments. However, whether spatial representations of grid cells are determined by local environment cues or are organized into globally coherent patterns remains undetermined. We propose a navigation model containing a path integration system in the entorhinal cortex and a cognitive map system in the hippocampus. In the path integration system, grid cell network and head direction (HD) cell network integrate movement and visual information, and form attractor states to represent the positions and head directions of the animal. In the cognitive map system, a topological map is constructed capturing the attractor states of the path integration system as nodes and the transitions between attractor states as links. On loop closure, when the animal revisits a familiar place, the topological map is calibrated to minimize odometry errors. The change of the topological map is mapped back to the path integration system, to correct the states of the grid cells and the HD cells. The proposed model was tested on iRat, a rat-like miniature robot, in a realistic maze. Experimental results showed that, after familiarization of the environment, both grid cells and HD cells develop globally coherent firing maps by map calibration and activity correction. These results demonstrate that the hippocampus and the entorhinal cortex work together to form globally coherent metric representations of the environment. The underlying mechanisms of the hippocampal-entorhinal circuit in capturing the structure of the environment from sequences of experience are critical for understanding episodic memory.

Abstract Image

内嗅-海马体的相互作用导致空间的全局连贯表征
内嗅皮层网格细胞的放电图被认为提供了一个有效的度量系统,能够在所有环境中支持空间推理。然而,网格细胞的空间表征是由局部环境线索决定的,还是被组织成全局一致的模式仍未确定。我们提出了一个导航模型,该模型包含了内嗅皮层的路径整合系统和海马体的认知地图系统。在路径整合系统中,网格细胞网络和头部方向(HD)细胞网络整合了运动和视觉信息,形成吸引子状态来表示动物的位置和头部方向。在认知地图系统中,以路径集成系统的吸引子状态为节点,以吸引子状态之间的转换为链接,构建拓扑地图。在环路关闭时,当动物重新回到熟悉的地方时,拓扑地图被校准以最小化里程计误差。拓扑图的变化被映射回路径集成系统,以校正网格单元和HD单元的状态。提出的模型在iRat上进行了测试,iRat是一个类似老鼠的微型机器人,在一个现实的迷宫中。实验结果表明,在熟悉环境后,网格细胞和高清细胞都能通过地图校准和活动校正生成全局相干的放电图。这些结果表明,海马体和内嗅皮层一起工作,形成了对环境的全局一致的度量表示。海马体-内嗅回路从经验序列中捕捉环境结构的潜在机制对于理解情景记忆至关重要。
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CiteScore
2.20
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