A Flexible Model of Working Memory
A Flexible Model of Working Memory
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DOI：
10.1016/j.neuron.2019.04.020
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发表时间：
2019-07-03
期刊：
影响因子：
16.2
通讯作者：
Buschman, Timothy J.
中科院分区：
文献类型：
--
作者：
Bouchacourt, Flora;Buschman, Timothy J.
工作记忆是认知的基础，使人能够“记住”信息。工作记忆的一个决定性特征是它的灵活性：我们可以记住任何东西。然而，典型的工作记忆模型依赖于微调的、内容特定的吸引子来持续维持神经活动，因此不允许行为中观察到的灵活性。在这里，我们提出了一种灵活的工作记忆模型，它通过两层神经元之间的随机循环连接来维持表征：结构化的“感觉”层和随机连接的非结构化层。由于交互相对于所存储的内容是未调整的，因此网络保留任何任意输入。然而，在我们的模型中，这种灵活性是有代价的：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，我们的模型还捕获了工作记忆的其他几个关键行为和神经生理学特征。
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.