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海马体中的并行处理流。

Parallel processing streams in the hippocampus.

机构信息

Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD, USA.

Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

Curr Opin Neurobiol. 2020 Oct;64:127-134. doi: 10.1016/j.conb.2020.03.004. Epub 2020 Jun 5.

Abstract

The hippocampus performs two complementary processes, pattern separation and pattern completion, to minimize interference and maximize the storage capacity of memories. Classic computational models have suggested that the dentate gyrus (DG) supports pattern separation and the putative attractor circuitry in CA3 supports pattern completion. However, recent evidence of functional heterogeneity along the CA3 transverse axis of the hippocampus suggests that the DG and proximal CA3 work as a functional unit for pattern separation, while distal CA3 forms an autoassociative network for pattern completion. We propose that the outputs of these functional circuits, combined with direct projections from entorhinal cortex to CA1, form interconnected, parallel processing circuits to support accurate memory storage and retrieval.

摘要

海马体执行两种互补的过程,模式分离和模式完成,以最小化干扰并最大限度地提高记忆的存储容量。经典的计算模型表明,齿状回(DG)支持模式分离,而 CA3 中的假定吸引子电路支持模式完成。然而,最近在海马体 CA3 横轴上的功能异质性的证据表明,DG 和近端 CA3 作为模式分离的功能单元工作,而远端 CA3 形成用于模式完成的自联想网络。我们提出,这些功能电路的输出,结合来自内侧嗅皮层到 CA1 的直接投射,形成相互连接的并行处理电路,以支持准确的记忆存储和检索。

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