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海马体和新皮层中的模式分离、完成及分类

Pattern separation, completion, and categorisation in the hippocampus and neocortex.

作者信息

Rolls Edmund T

机构信息

Oxford Centre for Computational Neuroscience, Oxford, England, United Kingdom; University of Warwick, Department of Computer Science, Coventry CV4 7AL, England, United Kingdom.

出版信息

Neurobiol Learn Mem. 2016 Mar;129:4-28. doi: 10.1016/j.nlm.2015.07.008. Epub 2015 Jul 17.

Abstract

The mechanisms for pattern completion and pattern separation are described in the context of a theory of hippocampal function in which the hippocampal CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The factors important in the pattern completion in CA3 and also a large number of independent memories stored in CA3 include: a sparse distributed representation, representations that are independent due to the randomizing effect of the mossy fibres, heterosynaptic long-term depression as well as long-term potentiation in the recurrent collateral synapses, and diluted connectivity to minimize the number of multiple synapses between any pair of CA3 neurons which otherwise distort the basins of attraction. Recall of information from CA3 is implemented by the entorhinal cortex perforant path synapses to CA3 cells, which in acting as a pattern associator allow some pattern generalization. Pattern separation is performed in the dentate granule cells using competitive learning to convert grid-like entorhinal cortex firing to place-like fields, and in the dentate to CA3 connections that have diluted connectivity. Recall to the neocortex is achieved by a reverse hierarchical series of pattern association networks implemented by the hippocampo-cortical backprojections, each one of which performs some pattern generalization, to retrieve a complete pattern of cortical firing in higher-order cortical areas. New results on competitive networks show which factors contribute to their ability to perform pattern separation, pattern clustering, and pattern categorisation, and how these apply in different hippocampal and neocortical systems.

摘要

模式完成和模式分离的机制是在一种海马体功能理论的背景下进行描述的。在该理论中,海马体CA3系统作为一个单一的吸引子或自联想网络运行,以实现任何空间位置(啮齿动物中的地点,或灵长类动物中的空间视图)与物体或奖励之间的快速、一次性联想,并在从任何部分进行回忆时完成整个记忆。对CA3中的模式完成以及存储在CA3中的大量独立记忆很重要的因素包括:稀疏分布式表征、由于苔藓纤维的随机化效应而独立的表征、异突触长期抑制以及递归侧支突触中的长期增强,以及稀释连接性以最小化任何一对CA3神经元之间多重突触的数量,否则会扭曲吸引盆。从CA3中回忆信息是通过内嗅皮质穿通路径与CA3细胞的突触来实现的,这些突触作为模式关联器允许一些模式泛化。模式分离在齿状颗粒细胞中通过竞争学习来执行,将网格状的内嗅皮质放电转换为位置样场,并在齿状与CA3的连接中进行,这些连接具有稀释的连接性。通过海马体-皮质反向投射实现的一系列反向分层模式关联网络来回想起新皮质,其中每一个都执行一些模式泛化,以在高阶皮质区域中检索完整的皮质放电模式。关于竞争网络的新结果表明了哪些因素有助于它们执行模式分离、模式聚类和模式分类的能力,以及这些因素如何应用于不同的海马体和新皮质系统。

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