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空间记忆的重现抑制认知地图中的拓扑波动。

Replays of spatial memories suppress topological fluctuations in cognitive map.

作者信息

Babichev Andrey, Morozov Dmitriy, Dabaghian Yuri

机构信息

Department of Computational and Applied Mathematics, Rice University, Houston, TX, USA.

Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

出版信息

Netw Neurosci. 2019 Jul 1;3(3):707-724. doi: 10.1162/netn_a_00076. eCollection 2019.

Abstract

The spiking activity of the hippocampal place cells plays a key role in producing and sustaining an internalized representation of the ambient space-a cognitive map. These cells do not only exhibit location-specific spiking during navigation, but also may rapidly replay the navigated routs through endogenous dynamics of the hippocampal network. Physiologically, such reactivations are viewed as manifestations of "memory replays" that help to learn new information and to consolidate previously acquired memories by reinforcing synapses in the parahippocampal networks. Below we propose a computational model of these processes that allows assessing the effect of replays on acquiring a robust topological map of the environment and demonstrate that replays may play a key role in stabilizing the hippocampal representation of space.

摘要

海马体位置细胞的尖峰活动在生成和维持周围空间的内化表征——认知地图中起着关键作用。这些细胞不仅在导航过程中表现出位置特异性的尖峰活动,还可能通过海马体网络的内源性动力学快速重放已导航的路线。从生理学角度来看,这种重新激活被视为“记忆重放”的表现,有助于学习新信息,并通过增强海马旁网络中的突触来巩固先前获得的记忆。下面我们提出了一个关于这些过程的计算模型,该模型可以评估重放在获取环境的稳健拓扑地图方面的作用,并证明重放在稳定海马体对空间的表征中可能起着关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bd3/6663216/7a66b05c50c8/netn-03-707-g001.jpg

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