4.3 Article

Analysis of Network Models with Neuron-Astrocyte Interactions

Journal

NEUROINFORMATICS
Volume 21, Issue 2, Pages 375-406

Publisher

HUMANA PRESS INC
DOI: 10.1007/s12021-023-09622-w

Keywords

astrocyte; computational model; intracellular calcium; neuron-astrocyte network; simulation; synapse

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Neural networks are widely used in modeling brain systems to explore global dynamics and emergent properties, and recent research has focused on neuron-astrocyte interactions and astrocytic modulation of neural dynamics. Various computational models incorporating these interactions have been developed to study synchronization, information transfer, synaptic plasticity, and other aspects. This study analyzes the evolution of network models with at least two neurons and astrocytes, and proposes a systematic framework for describing and categorizing cell-cell interaction schemes in neuron-astrocyte networks. The study also highlights the need for more comprehensive data and computational tools to further understand the contribution of astrocytes to brain functions.
Neural networks, composed of many neurons and governed by complex interactions between them, are a widely accepted formalism for modeling and exploring global dynamics and emergent properties in brain systems. In the past decades, experimental evidence of computationally relevant neuron-astrocyte interactions, as well as the astrocytic modulation of global neural dynamics, have accumulated. These findings motivated advances in computational glioscience and inspired several models integrating mechanisms of neuron-astrocyte interactions into the standard neural network formalism. These models were developed to study, for example, synchronization, information transfer, synaptic plasticity, and hyperexcitability, as well as classification tasks and hardware implementations. We here focus on network models of at least two neurons interacting bidirectionally with at least two astrocytes that include explicitly modeled astrocytic calcium dynamics. In this study, we analyze the evolution of these models and the biophysical, biochemical, cellular, and network mechanisms used to construct them. Based on our analysis, we propose how to systematically describe and categorize interaction schemes between cells in neuron-astrocyte networks. We additionally study the models in view of the existing experimental data and present future perspectives. Our analysis is an important first step towards understanding astrocytic contribution to brain functions. However, more advances are needed to collect comprehensive data about astrocyte morphology and physiology in vivo and to better integrate them in data-driven computational models. Broadening the discussion about theoretical approaches and expanding the computational tools is necessary to better understand astrocytes' roles in brain functions.

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