Title: A Simple Reservoir Model of Working Memory with Real Values,
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
maintain (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.