TOWARDS MORPHOLOGICALLY AND BIOPHYSICALLY DETAILED COMPUTATIONAL MODELS OF ASTROCYTES

Astrocytes play a crucial role in regulating synaptic plasticity and higher-order brain functions, but the mechanistic principles underlying these processes remain poorly understood. Our studies concentrate on developing brain area-specific computational models to investigate astrocytic properties relevant for synaptic plasticity, memory and learning. Several tools for modeling cellular mechanisms exist, such as NEURON (Carnivale and Hines, 2006), NeuroRD (Oliveira et al., 2010), STEPS (Hepburn et al., 2012) and MCell (Stiles and Bartol, 2001). When developing detailed and biologically accurate models of astroglia, careful evaluation of available tools not conventionally used for glial modeling is essential to understand their capabilities and to decide whether to use these frameworks or develop custom models. To assess the usability of the above-mentioned tools, we implemented calcium diffusion and calcium-calmodulin reaction-diffusion models with astrocyte morphologies reconstructed from electron microscopy images (Nguyen et al., 2023; Shapson-Coe et al., 2024; Bae et al., 2025) utilizing CellRemorph toolkit (Keto and Manninen, 2023). Our results reveal variability in computational efficiency and implementation constraints, reflecting trade-offs between flexibility and accuracy in modeling fine astrocytic branchlets. This suggests that, while suited for neuronal models, not all these platforms are optimal for capturing the complexity required for astrocyte modeling. To address these limitations, we extend the biophysical framework of Manninen et al. (2020) and continue to incorporate astrocyte morphologies to explore the influence of astrocytic calcium signaling and morphology on synaptic plasticity. This approach provides a foundation for further investigations into the role of astrocytes in healthy brain function and in disease.