Emergent functions of noise-driven spontaneous activity: Homeostatic maintenance of criticality and memory consolidation

TL;DR

This paper explores how noise-driven spontaneous activity in neural networks helps maintain criticality and excitatory-inhibitory balance, supporting memory and energy efficiency in the brain through simulations and experiments.

Contribution

It demonstrates that spontaneous neural activity, influenced by noise and plasticity, stabilizes criticality and EI balance, aiding memory and homeostasis, a novel insight into brain function.

Findings

Spontaneous activity maintains criticality and EI balance.

Disruption by stimuli is transient, with spontaneous activity restoring properties.

Supports memory consolidation and energy-efficient brain operation.

Abstract

Unlike digital computers, the brain exhibits spontaneous activity even during complete rest, despite the evolutionary pressure for energy efficiency. Inspired by the critical brain hypothesis, which proposes that the brain operates optimally near a critical point of phase transition in the dynamics of neural networks to improve computational efficiency, we postulate that spontaneous activity plays a homeostatic role in the development and maintenance of criticality. Criticality in the brain is associated with the balance between excitatory and inhibitory synaptic inputs (EI balance), which is essential for maintaining neural computation performance. Here, we hypothesize that both criticality and EI balance are stabilized by appropriate noise levels and spike-timing-dependent plasticity (STDP) windows. Using spiking neural network (SNN) simulations and in vitro experiments with dissociated neuronal cultures, we demonstrated that while repetitive stimuli transiently disrupt both criticality and EI balance, spontaneous activity can develop and maintain these properties and prolong the fading memory of past stimuli. Our findings suggest that the brain may achieve self-optimization and memory consolidation as emergent functions of noise-driven spontaneous activity. This noise-harnessing mechanism provides insights for designing energy-efficient neural networks, and may explain the critical function of sleep in maintaining homeostasis and consolidating memory.