Control of noise-induced coherent oscillations in three-neuron motifs

Florian Bönsel,Claus Metzner,Marius E Yamakou,Patrick Krauss

doi:10.1007/s11571-021-09770-2

Florian Bönsel, Claus Metzner + Show 2 more

Open Access

https://doi.org/10.1007/s11571-021-09770-2

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Abstract

The phenomenon of self-induced stochastic resonance (SISR) requires a nontrivial scaling limit between the deterministic and the stochastic timescales of an excitable system, leading to the emergence of coherent oscillations which are absent without noise. In this paper, we numerically investigate SISR and its control in single neurons and three-neuron motifs made up of the Morris–Lecar model. In single neurons, we compare the effects of electrical and chemical autapses on the degree of coherence of the oscillations due to SISR. In the motifs, we compare the effects of altering the synaptic time-delayed couplings and the topologies on the degree of SISR. Finally, we provide two enhancement strategies for a particularly poor degree of SISR in motifs with chemical synapses: (1) we show that a poor SISR can be significantly enhanced by attaching an electrical or an excitatory chemical autapse on one of the neurons, and (2) we show that by multiplexing the motif with a poor SISR to another motif (with a high SISR in isolation), the degree of SISR in the former motif can be significantly enhanced. We show that the efficiency of these enhancement strategies depends on the topology of the motifs and the nature of synaptic time-delayed couplings mediating the multiplexing connections.

Highlights

Noise is ubiquitous in biological systems and in particular in neural systems
In this work, we focus on self-induced stochastic resonance (SISR) in single ML neurons, 3NMs of time-delayed coupled neurons, and how it can be controlled through autapses (Van Der Loos and Glaser 1972; Lubke et al 1996) and multiplexing (Battiston 2017)
We investigate the degree of SISR in a single isolated ML neuron with an inhibitory chemical autapse and how it varies with the autaptic coupling strength jac;inh, time delay sac;inh, and the noise intensity r

Summary

Introduction

Noise is ubiquitous in biological systems and in particular in neural systems. Contrary to the intuitive perception of noise as deteriorating signal quality (McDonnell and Ward 2011), several studies have shown the constructive effects of noise on neural dynamics (Longtin 1993; Patel and Kosko 2008; Gang et al 1993; Gutkin et al 2007), perception and cognition (Krauss et al 2016, 2017, 2018; Schilling et al 2020, 2021). In Yamakou and Jost (2019) and Yamakou et al (2020), the enhancement of SISR is based on the configuration of the electrical and chemical synapses between the connected neurons within a layer network and between layers in a multiplex network. This communication can be achieved simultaneously at different ranges of oscillation frequency (Fries 2015), which would not be possible if they show incoherent behavior Motivated by these studies, in this work, we focus on SISR in single ML neurons, 3NMs of time-delayed coupled neurons, and how it can be controlled through autapses (Van Der Loos and Glaser 1972; Lubke et al 1996) and multiplexing (Battiston 2017).

Can a poor degree of SISR in a motif be enhanced by multiplexing?

Findings

Summary and conclusions