Spiking cerebellar model with multiple plasticity sites reproduces eye blinking classical conditioning


Eye blinking classical conditioning is one of the most extensively studied paradigms related to the cerebellum. In this work we have defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in computational simulations reproducing the eye blinking classical conditioning in multiple sessions of acquisition and extinction. We used two models: one with only the cortical plasticity and another with three plasticity sites, one plasticity at cortical level and two at nuclear level. We have compared the behavioral outcome of the two different models and proved that the model with a distributed plasticity produces a faster and more stable acquisition of conditioned responses in the reacquisition phase with respect to the single plasticity model. This behavior is explained by the effect of the nuclear plasticities, which have a slow dynamics and can express memory consolidation and savings.

7th International IEEE/EMBS Conference on Neural Engineering (NER)
Jesús Garrido
Jesús Garrido
Associate Professor

Associate professor in Computation technology, senior researcher at the Computational Neuroscience and Neurorobotics Lab and principal investigator of the VALERIA lab of the University of Granada.