Activity Stabilization in a Population Model of Working Memory by Sinusoidal and Noisy Inputs.

Nikita Novikov,Boris Gutkin,Denis Zakharov,Victoria Moiseeva

doi:10.3389/fncir.2021.647944

Abstract

According to mechanistic theories of working memory (WM), information is retained as stimulus-dependent persistent spiking activity of cortical neural networks. Yet, how this activity is related to changes in the oscillatory profile observed during WM tasks remains a largely open issue. We explore joint effects of input gamma-band oscillations and noise on the dynamics of several firing rate models of WM. The considered models have a metastable active regime, i.e., they demonstrate long-lasting transient post-stimulus firing rate elevation. We start from a single excitatory-inhibitory circuit and demonstrate that either gamma-band or noise input could stabilize the active regime, thus supporting WM retention. We then consider a system of two circuits with excitatory intercoupling. We find that fast coupling allows for better stabilization by common noise compared to independent noise and stronger amplification of this effect by in-phase gamma inputs compared to anti-phase inputs. Finally, we consider a multi-circuit system comprised of two clusters, each containing a group of circuits receiving a common noise input and a group of circuits receiving independent noise. Each cluster is associated with its own local gamma generator, so all its circuits receive gamma-band input in the same phase. We find that gamma-band input differentially stabilizes the activity of the “common-noise” groups compared to the “independent-noise” groups. If the inter-cluster connections are fast, this effect is more pronounced when the gamma-band input is delivered to the clusters in the same phase rather than in the anti-phase. Assuming that the common noise comes from a large-scale distributed WM representation, our results demonstrate that local gamma oscillations can stabilize the activity of the corresponding parts of this representation, with stronger effect for fast long-range connections and synchronized gamma oscillations.

Highlights

The concept of working memory (WM) characterizes the ability of the brain to retain in an active form certain information that is relevant to a current task, but is not perceived at the particular moment by sensory systems (Baddeley, 2003)
We explore stabilization of the metastable active regime by external gammaband and white-noise inputs, both of which are assumed to come from neural populations not explicitly included into the model
We vary the NMDA:AMPA ratio of the inter-circuit connections and parameters of the inputs; for each parameter combination we evaluate the effectiveness of stabilization

Summary

Introduction

The concept of working memory (WM) characterizes the ability of the brain to retain in an active form certain information that is relevant to a current task, but is not perceived at the particular moment by sensory systems (Baddeley, 2003). The delay-period gamma activity presumably reflects activation of the neural populations that represent the WM content (Roux and Uhlhaas, 2014) This is supported by the findings that the delay-period gamma activity is higher than in the passive observation task (Wimmer et al, 2016), increases with WM load (Howard et al, 2003; van Vugt et al, 2010; Kornblith et al, 2016; Lundqvist et al, 2016) and only in the task-relevant regions (Kaiser et al, 2003; Jokisch and Jensen, 2007) or at those cortical sites that contain neurons selective to the WM content (Kornblith et al, 2016; Lundqvist et al, 2016)

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