Towards a faithful stochastic model for brain digital twins

RESUMO

Twinning the brain means reproducing its electrical activity with fidelity. This activity arises from many neuronal mechanisms across several scales, from a single neuron to whole brain regions. Current large initiatives rely on models that each capture only a few of these mechanisms. Some act at the scale of a single neuron, others at the scale of neuronal populations. No single model captures both scales with fidelity. We propose a new stochastic model, based on a combination of Random Neural Networks and Markov-Modulated Poisson Processes, that would improve the fidelity of a brain digital twin. We map the model to the Discrete Event System Specification. This yields an initial executable simulation model suitable for incorporation into a brain digital twin.