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A computational model of working memory based on spike-timing- dependent plasticity
Frontiers in Computational Neuroscience ( IF 2.1 ) Pub Date : 2021-03-31 , DOI: 10.3389/fncom.2021.630999
Qiu-Sheng Huang , Hui Wei

Working memory is closely involved in various cognitive activities, but its neural mechanism is still under exploration. The mainstream view has long been that persistent activity is the neural basis of working memory, but recent experiments have observed that activity-silent memory can also be correctly recalled. The underlying mechanism of activity-silent memory is considered to be an alternative scheme that rejects the theory of persistent activity. We propose a working memory model based on spike-timing-dependent plasticity (STDP). Different from models based on spike-rate coding, our model adopts precise timed patterns of action potentials to represent information, so it can flexibly encode new memory representation. The model can work in both persistent and silent states, i.e., it is compatible with both of these seemingly conflicting neural mechanisms.

中文翻译:

基于尖峰时间相关可塑性的工作记忆计算模型

工作记忆与各种认知活动密切相关,但其神经机制仍在探索中。长期以来,主流观点一直认为持久性活动是工作记忆的神经基础,但是最近的实验已经观察到,沉默活动性记忆也可以被正确召回。沉默活动记忆的潜在机制被认为是拒绝持久活动理论的替代方案。我们提出了一种基于依赖于尖峰时序的可塑性(STDP)的工作记忆模型。与基于尖峰速率编码的模型不同,我们的模型采用精确的动作电位定时模式来表示信息,因此可以灵活地对新的内存表示进行编码。该模型可以在持久状态和静默状态下工作,即
更新日期:2021-03-31
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