Mostrar el registro sencillo del ítem

dc.contributor.authorCasellato, Claudia
dc.contributor.authorAntonietti, Alberto
dc.contributor.authorGarrido Alcázar, Jesús Alberto 
dc.contributor.authorFerrigno, Giancarlo
dc.contributor.authorD'Angelo, Egidio
dc.contributor.authorPedrocchi, Alessandra
dc.date.accessioned2015-05-04T10:44:49Z
dc.date.available2015-05-04T10:44:49Z
dc.date.issued2015
dc.identifier.citationCasellato, C.; et al. Distributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor tasks. Frontiers in Computational Neuroscience, 9:24 (2015). [http://hdl.handle.net/10481/35875]es_ES
dc.identifier.issn1662-5188
dc.identifier.urihttp://hdl.handle.net/10481/35875
dc.description.abstractThe cerebellum plays a crucial role in motor learning and it acts as a predictive controller. Modeling it and embedding it into sensorimotor tasks allows us to create functional links between plasticity mechanisms, neural circuits and behavioral learning. Moreover, if applied to real-time control of a neurorobot, the cerebellar model has to deal with a real noisy and changing environment, thus showing its robustness and effectiveness in learning. A biologically inspired cerebellar model with distributed plasticity, both at cortical and nuclear sites, has been used. Two cerebellum-mediated paradigms have been designed: an associative Pavlovian task and a vestibulo-ocular reflex, with multiple sessions of acquisition and extinction and with different stimuli and perturbation patterns. The cerebellar controller succeeded to generate conditioned responses and finely tuned eye movement compensation, thus reproducing human-like behaviors. Through a productive plasticity transfer from cortical to nuclear sites, the distributed cerebellar controller showed in both tasks the capability to optimize learning on multiple time-scales, to store motor memory and to effectively adapt to dynamic ranges of stimuli.es_ES
dc.description.sponsorshipThis work was supported by grants of European Union: REALNET (FP7-ICT270434) and Human Brain Project (HBP-604102).es_ES
dc.language.isoenges_ES
dc.publisherFrontiers Foundationes_ES
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/270434es_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es_ES
dc.subjectCerebellar modeles_ES
dc.subjectNeurorobotes_ES
dc.subjectMotor learninges_ES
dc.subjectDistributed plasticityes_ES
dc.subjectLong term plasticityes_ES
dc.titleDistributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor taskses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.3389/fncom.2015.00024


Ficheros en el ítem

[PDF]

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License
Excepto si se señala otra cosa, la licencia del ítem se describe como Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License