A Pragmatic Approach to Understand Hebbian Cell Assembly

Pub Date : 2021-04-01 DOI:10.4018/ijcini.20210401.oa6
C. Kumar, Radhika Shivhare, A. Abraham, Jinhai Li, Annapurna Jonnalagadda
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引用次数: 1

Abstract

Formed at the cerebral cortex, neuron cell assemblies are regarded as basic units in cortical representation. Proposed by Hebb, these cell assemblies are regarded as the distributed neural representation of relevant objects, concepts or constellations. Each cell assembly contains a group of neurons having strong mutual excitatory connections. During a stimulus, these cells get activated. This activation either performs a given action or represent a given percept or concept in brain. This theory is in the strongest connection of the problem of concept forming in the brain. The challenge is to model coordinated activity among neurons in brain mathematically. The need of modelling it mathematically enables this paper to give clear view of functionality of Hebbian cell assembly. Therefore this paper proposes a pragmatic approach to Hebbian cell assemblies using mathematical model grounded in lattice based formalism that utilizes Galois connections. During this proposal, the authors also show the connections of the proposal to cognitive model of memory in particularly long-term memory (LTM).
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用实用的方法来理解希伯比细胞组装
神经元细胞群形成于大脑皮层,是大脑皮层表征的基本单位。由Hebb提出,这些细胞集合被视为相关对象、概念或星座的分布式神经表示。每个细胞集合都包含一组具有强烈相互兴奋联系的神经元。在刺激过程中,这些细胞被激活。这种激活要么执行给定的动作,要么代表大脑中给定的感知或概念。这个理论与大脑中概念形成的问题有着最密切的联系。挑战在于用数学方法模拟大脑中神经元之间的协调活动。对其进行数学建模的需要使本文能够清楚地了解Hebbian细胞组装的功能。因此,本文提出了一种实用的方法,以网格为基础的形式主义利用伽罗瓦连接的数学模型为基础的Hebbian细胞组件。在这一提议中,作者还展示了提议与认知记忆模型的联系,特别是长期记忆(LTM)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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