In silico modelling of neuron signal impact of cytokine storm-induced demyelination

TL;DR

This study uses a computer model to show how cytokine storms from viral infections can damage neuron signals by causing demyelination.

Contribution

The paper introduces a novel in silico model to analyze how cytokine storm-induced demyelination affects neuron signal propagation.

Findings

Demyelination from cytokine storms reduces signal power and spiking rate in neurons.

The proposed transfer function effectively models the weakening of action potential signals.

Neuron communication is impaired as demyelination progresses, affecting information processing.

Abstract

In this study, we develop an in silico model of a neuron’s behaviour under demyelination caused by a cytokine storm to investigate the effects of viral infections in the brain. We use a comprehensive model to measure how cytokine-induced demyelination affects the propagation of action potential (AP) signals within a neuron. We analysed the effects of neuron-neuron communications by applying information and communication theory at different levels of demyelination. Our simulations demonstrate that virus-induced degeneration can play a role in the signal power and spiking rate, which compromise the propagation and processing of information between neurons. We propose a transfer function to model the weakening effects on the AP. Our results show that demyelination induced by a cytokine storm not only degrades the signal but also impairs its propagation within the axon. Our proposed in silico model can analyse virus-induced neurodegeneration and enhance our understanding of virus-induced demyelination.

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