title: Spiking Neural Network With Distributed Plasticity Reproduces Cerebellar Learning in Eye Blink Conditioning Paradigms.
abstract: OBJECTIVE
  In this study, we defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in computational simulations that reproduce associative motor tasks in multiple sessions of acquisition and extinction.
  
  
  METHODS
  By evolutionary algorithms, we tuned the cerebellar microcircuit to find out the near-optimal plasticity mechanism parameters that better reproduced human-like behavior in eye blink classical conditioning, one of the most extensively studied paradigms related to the cerebellum. We used two models: one with only the cortical plasticity and another including two additional plasticity sites at nuclear level.
  
  
  RESULTS
  First, both spiking cerebellar models were able to well reproduce the real human behaviors, in terms of both "timing" and "amplitude", expressing rapid acquisition, stable late acquisition, rapid extinction, and faster reacquisition of an associative motor task. Even though the model with only the cortical plasticity site showed good learning capabilities, the model with distributed plasticity produced faster and more stable acquisition of conditioned responses in the reacquisition phase. This behavior is explained by the effect of the nuclear plasticities, which have slow dynamics and can express memory consolidation and saving.
  
  
  CONCLUSIONS
  We showed how the spiking dynamics of multiple interactive neural mechanisms implicitly drive multiple essential components of complex learning processes.
  
  
  CONCLUSIONS
  This study presents a very advanced computational model, developed together by biomedical engineers, computer scientists, and neuroscientists. Since its realistic features, the proposed model can provide confirmations and suggestions about neurophysiological and pathological hypotheses and can be used in challenging clinical applications.
authors.forename: Alberto
authors.initials: A
authors.lastname: Antonietti
authors.forename: Claudia
authors.initials: C
authors.lastname: Casellato
authors.forename: Jesús A
authors.initials: JA
authors.lastname: Garrido
authors.forename: Niceto R
authors.initials: NR
authors.lastname: Luque
authors.forename: Francisco
authors.initials: F
authors.lastname: Naveros
authors.forename: Eduardo
authors.initials: E
authors.lastname: Ros
authors.forename: Egidio
authors.initials: E
authors.lastname: D' Angelo
authors.forename: Alessandra
authors.initials: A
authors.lastname: Pedrocchi
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D001767:Blinking / Q000502:physiology*; D002531:Cerebellum / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009473:Neuronal Plasticity / Q000502:physiology*