Collective Dynamics in Spiking Neural Networks Beyond Dale's Principle

TL;DR

This paper introduces a minimal model of neurons that violate Dale's principle, demonstrating how mixed excitatory and inhibitory effects influence neural dynamics and information processing in spiking neural networks.

Contribution

The study presents a novel 'Bilingual' neuron model that violates Dale's principle, revealing new dynamical regimes and information-processing signatures in neural networks.

Findings

Transitions between synchronous and asynchronous dynamics

Distinct information-processing signatures near phase transitions

Potential role in regulating large-scale neural oscillations

Abstract

Dale's Principle has historically guided neuroscience research as a valuable rule of thumb, namely that all synapses on each neuron release the same set of neurotransmitters. Most existing Spiking Neuron Network models share this dichotomous assumption that neurons are either excitatory or inhibitory; however, recent experimental evidence points towards co-release mechanisms that violate this assumption. Here, we introduce a minimal model of "Bilingual" neurons violating Dale's principle that can exert both excitatory and inhibitory effects. We identify parameter regimes in which this architecture exhibits transitions between synchronous and asynchronous dynamics that differ quantitatively from those observed in a matched monolingual control architecture. We report distinct information-processing signatures both at the level of neurons and higher-order interactions between them near the phase transitions. These results suggest that the population of neurons violating Dales principle may provide an alternative mechanism for regulating large-scale oscillatory activity in neural circuits.