Computational models of neurotransmission at cerebellar synapses unveil the impact on network computation - Masoli, Stefano; Rizza, Martina Francesca; Tognolina, Marialuisa; Prestori, Francesca; D’Angelo, Egidio (Frontiers in Computational Neuroscience, 2022)
The neuroscientific field is benefitting from the conjoint evolution of experimental and computational techniques allowing to reconstruct and simulate complex models of neurons and synapses. Chemical synapses are characterized by mechanisms of presynaptic vesicle cycling, neurotransmitter diffusion and postsynaptic receptor activation, which eventually lead to postsynaptic currents and subsequent membrane potential changes. These mechanisms have been accurately modelled for different synapses and receptor types (AMPA, NMDA and GABA) of the cerebellar cortical network allowing to simulate their impact on computation. Of special relevance is short-term synaptic plasticity generating spatio-temporal filtering in local microcircuits and controlling burst transmission and information flow through the network. Here we show how data-driven computational models recapitulate the properties of neurotransmission at cerebellar synapses. Simulation of microcircuit models are starting to unveil how the diverse synaptic mechanisms shape the spatiotemporal profiles of circuit activity and computation.