Literature DB >> 9753117

Role of the cerebellum in reaching movements in humans. II. A neural model of the intermediate cerebellum.

N Schweighofer1, J Spoelstra, M A Arbib, M Kawato.   

Abstract

The cerebellum is essential for the control of multijoint movements; when the cerebellum is lesioned, the performance error is more than the summed errors produced by single joints. In the companion paper (Schweighofer et al., 1998), a functional anatomical model for visually guided arm movement was proposed. The model comprised a basic feedforward/feedback controller with realistic transmission delays and was connected to a two-link, six-muscle, planar arm. In the present study, we examined the role of the cerebellum in reaching movements by embedding a novel, detailed cerebellar neural network in this functional control model. We could derive realistic cerebellar inputs and the role of the cerebellum in learning to control the arm was assessed. This cerebellar network learned the part of the inverse dynamics of the arm not provided by the basic feedforward/feedback controller. Despite realistically low inferior olive firing rates and noisy mossy fibre inputs, the model could reduce the error between intended and planned movements. The responses of the different cell groups were comparable to those of biological cell groups. In particular, the modelled Purkinje cells exhibited directional tuning after learning and the parallel fibres, due to their length, provide Purkinje cells with the input required for this coordination task. The inferior olive responses contained two different components; the earlier response, locked to movement onset, was always present and the later response disappeared after learning. These results support the theory that the cerebellum is involved in motor learning.

Entities:  

Keywords:  Non-programmatic

Mesh:

Year:  1998        PMID: 9753117     DOI: 10.1046/j.1460-9568.1998.00007.x

Source DB:  PubMed          Journal:  Eur J Neurosci        ISSN: 0953-816X            Impact factor:   3.386


  29 in total

1.  Long-term potentiation of intrinsic excitability at the mossy fiber-granule cell synapse of rat cerebellum.

Authors:  S Armano; P Rossi; V Taglietti; E D'Angelo
Journal:  J Neurosci       Date:  2000-07-15       Impact factor: 6.167

2.  The composite neuron: a realistic one-compartment Purkinje cell model suitable for large-scale neuronal network simulations.

Authors:  A D Coop; G N Reeke
Journal:  J Comput Neurosci       Date:  2001 Mar-Apr       Impact factor: 1.621

3.  Diffusion of nitric oxide can facilitate cerebellar learning: A simulation study.

Authors:  N Schweighofer; G Ferriol
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-12       Impact factor: 11.205

4.  QUANTITATIVE MODELING OF SPATIO-TEMPORAL DYNAMICS OF INFERIOR OLIVE NEURONS WITH A SIMPLE CONDUCTANCE-BASED MODEL.

Authors:  Yuichi Katori; Eric J Lang; Miho Onizuka; Mitsuo Kawato; Kazuyuki Aihara
Journal:  Int J Bifurcat Chaos       Date:  2010-03       Impact factor: 2.836

5.  Modelling the control of interceptive actions.

Authors:  P J Beek; J C Dessing; C E Peper; D Bullock
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2003-09-29       Impact factor: 6.237

6.  On-line compensation for perturbations of a reaching movement is cerebellar dependent: support for the task dependency hypothesis.

Authors:  Yury Shimansky; Jian-Jun Wang; Richard A Bauer; Vlastislav Bracha; James R Bloedel
Journal:  Exp Brain Res       Date:  2003-12-03       Impact factor: 1.972

7.  Kinematics of wrist joint flexion in overarm throws made by skilled subjects.

Authors:  D B Debicki; P L Gribble; S Watts; J Hore
Journal:  Exp Brain Res       Date:  2003-11-04       Impact factor: 1.972

8.  Chaos may enhance information transmission in the inferior olive.

Authors:  Nicolas Schweighofer; Kenji Doya; Hidekazu Fukai; Jean Vianney Chiron; Tetsuya Furukawa; Mitsuo Kawato
Journal:  Proc Natl Acad Sci U S A       Date:  2004-03-22       Impact factor: 11.205

9.  Two modes of error processing in reaching.

Authors:  Frederic Magescas; Christian Urquizar; Claude Prablanc
Journal:  Exp Brain Res       Date:  2008-11-15       Impact factor: 1.972

10.  Adaptive-filter models of the cerebellum: computational analysis.

Authors:  Paul Dean; John Porrill
Journal:  Cerebellum       Date:  2008       Impact factor: 3.847

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