Computational Modelling of Cerebellum Granule Neuron Temporal Responses for Auditory and Visual Stimuli

Abstract

Sensorimotor signals from the cerebral cortex modulate the pattern generating metaheuristic capabilities of cerebellum. To better understand the functional integration of multisensory information by the single granule neurons and the role of multimodal information in motor guidance of cerebellum, we have modelled granular layer microcircuit in the cerebellum and analysed the encoding of information during the auditory and visual stimuli. A multi-compartmental granule neuron model comprising of excitatory and inhibitory synapses was used and in vivo like behaviour was modelled with the short and long bursts. The change in intrinsic parameters in the model helped to quantify the effect of spike-time dependent plasticity in the firing of granule neurons. Computer simulations implicate coding correlation of output patterns to temporal excitatory stimuli. We observed the role of induced plasticity and granular layer role in sparse recoding of auditory and visual inputs and the model predict how plasticity mechanisms affect the average amount of information transmitted through the single granule neurons during multimodal stimuli.