A biologically plausible model of astrocyte-neuron networks in random and hub-driven connectivity

Abstract

Recent research studies in brain neural networks are highlighting the involvement of glial cells, in particular astrocytes, in synaptic modulation, memory formation, and neural synchronization, a role that has often been overlooked. Thus, theoretical models have begun incorporating astrocytes to better understand their functional impact. Additionally, the structural organization of neuron-neuron, astrocyte-neuron and astrocyte-astrocyte connections plays a crucial role in network dynamics.

Starting from a recently published astrocyte-neuron network model with neuron-neuron random connectivity, we provide an extensive evaluation of this same model, focusing on astrocytic dynamics, neuron-astrocyte connectivity, and spatial distribution of inhibitory neurons. We propose refinements to the model with the aim of improving the biological plausibility of the above described characteristics of the model. To assess the interplay between astrocytes and network topology, we compare four configurations: neural networks with and without astrocytes, each under random and hub-driven connectivity. Simulations are conducted using the Brian2 simulator, providing insights into how astrocytes and structural heterogeneity jointly influence neural dynamics. Our findings contribute to a deeper understanding of neuron-glia interactions and the impact of network topology on astrocyte-neuron network dynamics. In particular, while finding an expected decrease of neural firing activity due to astrocyte calcium dynamics, we also found that hub-driven topology trigger a much higher firing rate with respect to the random topology, even having this last one a much higher number of neuron-neuron connections.