Response Dynamics in an Olivocerebellar Spiking Neural Network With Non-linear Neuron Properties.

ABSTRACT: Sensorimotor signals are integrated and processed by the cerebellar circuit to predict accurate control of actions. In order to investigate how single neuron dynamics and geometrical modular connectivity affect cerebellar processing, we have built an olivocerebellar Spiking Neural Network (SNN) based on a novel simplification algorithm for single point models (Extended Generalized Leaky Integrate and Fire, EGLIF) capturing essential non-linear neuronal dynamics (e.g., pacemaking, bursting, adaptation, oscillation and resonance). EGLIF models specifically tuned for each neuron type were embedded into an olivocerebellar scaffold reproducing realistic spatial organization and physiological convergence and divergence ratios of connections. In order to emulate the circuit involved in an eye bli

SUBMITTER: Geminiani A 

PROVIDER: S-EPMC6779816 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature