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Computational Models of Timing Mechanisms in the Cerebellar Granular Layer

A long-standing question in neuroscience is how the brain controls movement that requires precisely timed muscle activations. Studies using Pavlovian delay eyeblink conditioning provide good insight into this question. In delay eyeblink conditioning, which is believed to involve the cerebellum, a su...

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Detalles Bibliográficos
Autores principales: Yamazaki, Tadashi, Tanaka, Shigeru
Formato: Texto
Lenguaje:English
Publicado: Springer-Verlag 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788136/
https://www.ncbi.nlm.nih.gov/pubmed/19495900
http://dx.doi.org/10.1007/s12311-009-0115-7
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author Yamazaki, Tadashi
Tanaka, Shigeru
author_facet Yamazaki, Tadashi
Tanaka, Shigeru
author_sort Yamazaki, Tadashi
collection PubMed
description A long-standing question in neuroscience is how the brain controls movement that requires precisely timed muscle activations. Studies using Pavlovian delay eyeblink conditioning provide good insight into this question. In delay eyeblink conditioning, which is believed to involve the cerebellum, a subject learns an interstimulus interval (ISI) between the onsets of a conditioned stimulus (CS) such as a tone and an unconditioned stimulus such as an airpuff to the eye. After a conditioning phase, the subject’s eyes automatically close or blink when the ISI time has passed after CS onset. This timing information is thought to be represented in some way in the cerebellum. Several computational models of the cerebellum have been proposed to explain the mechanisms of time representation, and they commonly point to the granular layer network. This article will review these computational models and discuss the possible computational power of the cerebellum.
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spelling pubmed-27881362009-12-04 Computational Models of Timing Mechanisms in the Cerebellar Granular Layer Yamazaki, Tadashi Tanaka, Shigeru Cerebellum Article A long-standing question in neuroscience is how the brain controls movement that requires precisely timed muscle activations. Studies using Pavlovian delay eyeblink conditioning provide good insight into this question. In delay eyeblink conditioning, which is believed to involve the cerebellum, a subject learns an interstimulus interval (ISI) between the onsets of a conditioned stimulus (CS) such as a tone and an unconditioned stimulus such as an airpuff to the eye. After a conditioning phase, the subject’s eyes automatically close or blink when the ISI time has passed after CS onset. This timing information is thought to be represented in some way in the cerebellum. Several computational models of the cerebellum have been proposed to explain the mechanisms of time representation, and they commonly point to the granular layer network. This article will review these computational models and discuss the possible computational power of the cerebellum. Springer-Verlag 2009-06-05 2009 /pmc/articles/PMC2788136/ /pubmed/19495900 http://dx.doi.org/10.1007/s12311-009-0115-7 Text en © The Author(s) 2009 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Article
Yamazaki, Tadashi
Tanaka, Shigeru
Computational Models of Timing Mechanisms in the Cerebellar Granular Layer
title Computational Models of Timing Mechanisms in the Cerebellar Granular Layer
title_full Computational Models of Timing Mechanisms in the Cerebellar Granular Layer
title_fullStr Computational Models of Timing Mechanisms in the Cerebellar Granular Layer
title_full_unstemmed Computational Models of Timing Mechanisms in the Cerebellar Granular Layer
title_short Computational Models of Timing Mechanisms in the Cerebellar Granular Layer
title_sort computational models of timing mechanisms in the cerebellar granular layer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788136/
https://www.ncbi.nlm.nih.gov/pubmed/19495900
http://dx.doi.org/10.1007/s12311-009-0115-7
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