Computational Models for Calcium-Mediated Astrocyte Functions

Abstract

The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro, but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop the models. Thus, we would like to emphasize that only via reproducible research are we able to build better computational models for astrocytes, which truly advance science. Our study is the first to characterize in detail the biophysical and biochemical mechanisms that have been modeled for astrocytes.

Simulation of Ca2+oscillations in astrocytes mediated by amyloid beta in Alzheimer’s disease

“…The integration of the four different pathways mediated by Aβ has improved the biological plausibility of AD simulation. This shared computational model and the reproducible research would truly advance the understanding of AD [10].…”

A roadmap to integrate astrocytes into Systems Neuroscience

“…Although efforts are being made in the US Brain Initiative and the European Human Brain Project to develop studies incorporating non‐neuronal cells, it seems as though progress in astrocyte biology has advanced in parallel to Systems Neuroscience, and astrocytes have been excluded from unified theories of brain function, as previously noted (Poskanzer & Molofsky, ). Although extensive modeling of astrocytic Ca 2+ fluxes exists (Manninen, Havela, & Linne, ), and sporadic studies have explored the application of astrocyte‐based computations to artificial intelligence (Alvarellos‐Gonzalez, Pazos, & Porto‐Pazos, ; Porto‐Pazos et al, ), astrocytes are characteristically missing from advanced in silico modeling of neural circuits (Capone et al, ; Deneve, Alemi, & Bourdoukan, ; Gjorgjieva, Drion, & Marder, ; Markram et al, ).…”

Neuroinformatics and Computational Modelling as Complementary Tools for Neurotoxicology Studies

“…Such models can be used to shed light on the cellular and molecular mechanisms that contribute to the initiation and maintenance of, for example, short‐ and long‐term plasticity, learning and even the consolidation of memories . There exist also models that address gap junctions in glial networks and other phenomena common to non‐neuronal cells, such as astrocytes .…”

“…To ensure the testability and comparability of in silico models, it is thus essential that all in silico models and their source codes are stored in databases. Currently, the source codes written in different programming languages are only limitedly available in model repositories . Therefore, the description of in silico models, their source codes and experimental data used to construct and validate the in silico models should be openly available to the scientific community .…”