Topological Schemas of Memory Spaces.

Topological Schemas of Memory Spaces.
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DOI:
10.3389/fncom.2018.00027
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发表时间:
2018
影响因子:
3.2
通讯作者:
Dabaghian YA
Dabaghian YA
中科院分区:
医学4区
文献类型:
--
作者:
Babichev A;Dabaghian YA

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海马认知图是空间环境的神经元表征,在计算神经科学文献中被广泛讨论了几十年。然而,最近的研究指出,海马体在产生另一个认知框架记忆空间中起着重要作用,它不仅包含空间记忆,还包含非空间记忆。与认知地图不同,记忆空间被广泛理解为“事件表征之间的互连网络”,尚未从理论角度进行研究。在这里,我们提出了一个数学方法,允许建模的记忆空间建设性的,作为神经元尖峰活动的副现象,从而将认知神经生理学的几个重要概念联系起来。首先,我们认为记忆空间具有拓扑性质,这一假设允许在平等的基础上处理海马功能的空间和非空间方面。然后,我们在不同的环境中的海马记忆空间建模,并证明所产生的结构自然地结合相应的认知地图,并提供了更广泛的背景下解释空间信息。最后,我们提出了一个正式的描述记忆巩固过程,连接记忆空间的莫里斯的认知图式启发式表示所获得的记忆,用于解释在给定的环境中的学习和记忆巩固的动态。所提出的方法允许评估这些结构作为最紧凑的表示的内存空间的结构。
Hippocampal cognitive map—a neuronal representation of the spatial environment—is widely discussed in the computational neuroscience literature for decades. However, more recent studies point out that hippocampus plays a major role in producing yet another cognitive framework—the memory space—that incorporates not only spatial, but also non-spatial memories. Unlike the cognitive maps, the memory spaces, broadly understood as “networks of interconnections among the representations of events,” have not yet been studied from a theoretical perspective. Here we propose a mathematical approach that allows modeling memory spaces constructively, as epiphenomena of neuronal spiking activity and thus to interlink several important notions of cognitive neurophysiology. First, we suggest that memory spaces have a topological nature—a hypothesis that allows treating both spatial and non-spatial aspects of hippocampal function on equal footing. We then model the hippocampal memory spaces in different environments and demonstrate that the resulting constructions naturally incorporate the corresponding cognitive maps and provide a wider context for interpreting spatial information. Lastly, we propose a formal description of the memory consolidation process that connects memory spaces to the Morris' cognitive schemas-heuristic representations of the acquired memories, used to explain the dynamics of learning and memory consolidation in a given environment. The proposed approach allows evaluating these constructs as the most compact representations of the memory space's structure.
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