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A Flexible Model of Working Memory

机译:灵活的工作记忆模型

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摘要

Working memory is fundamental to cognition, allowing one to hold information "in mind.'' A defining characteristic of working memory is its flexibility: we can hold anything in mind. However, typical models of working memory rely on finely tuned, content-specific attractors to persistently maintain neural activity and therefore do not allow for the flexibility observed in behavior. Here, we present a flexible model of workingmemory that maintains representations through random recurrent connections between two layers of neurons: a structured "sensory'' layer and a randomly connected, unstructured layer. As the interactions are untuned with respect to the content being stored, the network maintains any arbitrary input. However, in our model, this flexibility comes at a cost: the random connections overlap, leading to interference between representations and limiting the memory capacity of the network. Additionally, our model captures several other key behavioral and neurophysiological characteristics of working memory.
机译:工作记忆是认知的基础,允许一个人举办信息“记住”。“工作记忆的定义特征是它的灵活性:我们可以牢记任何内容。但是,工作记忆的典型模型依赖于精细调整的内容持续维持神经活动的吸引子,因此不允许在行为中观察到的灵活性。在这里,我们介绍了一种灵活的工作模型,通过两层神经元之间的随机复发连接来保持表示:一个结构化的“感官”层和随机的连接,非结构化层。随着对存储的内容的相互作用未经核开,网络维护任何任意输入。但是,在我们的模型中,这种灵活性以成本为准:随机连接重叠,导致表示之间的干扰并限制网络的内存容量。此外,我们的模型捕获了工作记忆的其他几个关键行为和神经生理学特征。

著录项

  • 来源
    《Neuron》 |2019年第1期|共22页
  • 作者单位

    Princeton Univ Princeton Neurosci Inst Princeton NJ 08540 USA;

    Princeton Univ Princeton Neurosci Inst Princeton NJ 08540 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 神经病学;
  • 关键词

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