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基于快速赫布学习的工作记忆模型。

A working memory model based on fast Hebbian learning.

作者信息

Sandberg A, Tegnér J, Lansner A

机构信息

Department of Numerical Analysis and Computer Science, Royal Institute of Technology, 100 44 Stockholm, Sweden.

出版信息

Network. 2003 Nov;14(4):789-802.

Abstract

Recent models of the oculomotor delayed response task have been based on the assumption that working memory is stored as a persistent activity state (a 'bump' state). The delay activity is maintained by a finely tuned synaptic weight matrix producing a line attractor. Here we present an alternative hypothesis, that fast Hebbian synaptic plasticity is the mechanism underlying working memory. A computational model demonstrates a working memory function that is more resistant to distractors and network inhomogeneity compared to previous models, and that is also capable of storing multiple memories.

摘要

最近的眼动延迟反应任务模型基于这样一种假设,即工作记忆以持续活动状态(“隆起”状态)存储。延迟活动由精细调整的突触权重矩阵维持,产生线性吸引子。在这里,我们提出另一种假设,即快速赫布突触可塑性是工作记忆的潜在机制。一个计算模型表明,与以前的模型相比,该工作记忆功能对干扰和网络不均匀性更具抗性,并且还能够存储多个记忆。

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