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

Alberto Antonietti, Claudia Casellato, Jesus A. Garrido, Egidio D'Angelo, Alessandra Pedrocchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationInternational IEEE/EMBS Conference on Neural Engineering, NER
PublisherIEEE Computer Society
Pages296-299
Number of pages4
Volume2015-July
ISBN (Print)9781467363891
DOIs
Publication statusPublished - Jul 1 2015
Event7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, France
Duration: Apr 22 2015Apr 24 2015

Other

Other7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
CountryFrance
CityMontpellier
Period4/22/154/24/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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