Astrocytic resource diffusion stabilizes persistent activity in neural fields

TL;DR

This paper presents a coupled astrocyte-neural field model showing how astrocytic resource diffusion stabilizes persistent neural activity, enhancing working memory models.

Contribution

It introduces a novel coupled model incorporating astrocytic resource dynamics and analyzes how diffusion and replenishment stabilize neural activity.

Findings

Astrocytic diffusion smooths resource asymmetries caused by bump displacements.

Synaptic replenishment transfers smoothing from astrocytes back to synapses.

Strong diffusion and replenishment suppress drift and expand bump stability regimes.

Abstract

Persistent neural activity underlying working memory requires sustained synaptic transmission, yet the metabolic and neurotransmitter support provided by astrocyte networks is largely absent from spatially extended neural circuit models. We introduce a coupled astrocyte-neural field model in which synaptic efficacy is regulated by depletion and recovery of a conserved resource pool recycled and spatially redistributed through diffusively coupled astrocytes. We obtain explicit stationary bump profiles and self-consistency conditions for bump width and amplitude on a canonical ring architecture. Linearizing about these solutions while carefully accounting for perturbations at bump boundaries, we analyze the resulting spectral problem governing stability. Our analysis, supported by numerical simulations and low-dimensional Fourier truncations, reveals a two-stage stabilization mechanism: astrocytic diffusion smooths resource asymmetries created by small bump displacements, and synaptic replenishment transfers this smoothing back to the synaptic pool. Together, sufficiently strong diffusion and replenishment suppress drift instabilities and enlarge the parameter regime in which stationary bumps persist.