Metastability in a System of Spiking Neurons with Synaptic Plasticity - Archive ouverte HAL Access content directly
Preprints, Working Papers, ... Year : 2021

Metastability in a System of Spiking Neurons with Synaptic Plasticity

Abstract

After reviewing the behavioral studies of working memory and of its cellular substrate, we argue that metastable states constitute candidates for the type of transient information storage required by working memory. We then present a simple neural network model made of stochastic units whose synapses exhibit short-term facilitation. This model was specifically designed to be analytically tractable, simple to simulate numerically and to exhibit a strong form of metastability. We present both numerical results: the existence of metastable states able to represent scalar quantities; and analytical ones: the properties of the metastable states that can be fully deduced from an implicit equation once the 4 model parameters have been specified.
Fichier principal
Vignette du fichier
Andre_Pouzat_MSSNSP.pdf (562.08 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03281732 , version 1 (08-07-2021)
hal-03281732 , version 2 (19-07-2021)
hal-03281732 , version 3 (06-02-2024)

Identifiers

  • HAL Id : hal-03281732 , version 1

Cite

Morgan André, Christophe Pouzat. Metastability in a System of Spiking Neurons with Synaptic Plasticity. 2021. ⟨hal-03281732v1⟩
367 View
166 Download

Share

Gmail Facebook X LinkedIn More