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Conference Papers Year : 2018

A Simple Reservoir Model of Working Memory with Real Values

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Anthony Strock
  • Function : Author
Nicolas P. Rougier
Xavier Hinaut

Abstract

The prefrontal cortex is known to be involved in many high-level cognitive functions, in particular, working memory. Here, we study to what extent a group of randomly connected units (namely an Echo State Network, ESN) can store and main-tain (as output) an arbitrary real value from a streamed input, i.e., can act as a sustained working memory unit. Furthermore, we explore to what extent such an architecture can take advantage of the stored value in order to produce non-linear computations. Comparison between different architectures (with and without feedback, with and without a working memory unit) shows that an explicit memory improves the performances.
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Dates and versions

hal-01803594 , version 1 (15-06-2018)

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Anthony Strock, Nicolas P. Rougier, Xavier Hinaut. A Simple Reservoir Model of Working Memory with Real Values. 2018 International Joint Conference on Neural Networks (IJCNN), Jul 2018, Rio de Janeiro, Brazil. ⟨10.1109/IJCNN.2018.8489262⟩. ⟨hal-01803594⟩
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