A computational model of altered neuronal activity in altered gravity

Electrophysiological experiments have shown that neuronal activity changes upon exposure to altered gravity. More specifically, neurons firing rates increase during microgravity and decrease during centrifugal-induced hypergravity. Different biophysical explanations have been proposed for this phenomenon: however, they have not been backed by quantitative analyses nor simulations. More generally, classical computational models of neurons and networks do not account for the effect of altered gravity, which limits the possibility to perform in-silico experiments and simulations. Here, we propose computational implementations for different effects of altered gravity on cellular functions, and modify existing models to account for the effect of micro- and hyper-gravity. Firstly, in line with previous experiments, we suggest that microgravity could be modeled as an increase of the voltage-dependent channel transition rates, which is assumed to be the result of a higher membrane fluidity and can be readily implemented into the Hodgkin-Huxley model. Using in-silico simulations of single neurons, we show that this model of the influence of gravity on neuronal activity allows to reproduce the observed increased firing and burst rates. Secondly, we explore the role of mechano-gated (MG) ion channels on population activity. We show that recordings can be fitted by a network of connected excitatory neurons, whose activity is balanced by firing rate adaptation. Adding a small depolarizing current to account for the activation of MG channels also reproduces the observed increased firing and burst rates. Overall, our results fill an important gap in the literature, by providing a computational link between altered gravity and neuronal activity. Starting from historical observations of the effects of gravity on cellular functions, we derived gravity-sensitive models of neurons and networks, whose predictions could be refined using future experiments.