Literature DB >> 17533757

Reorganization of brain activity for multiple internal models after short but intensive training.

Hiroshi Imamizu1, Satomi Higuchi, Akihiro Toda, Mitsuo Kawato.   

Abstract

Internal models are neural mechanisms that can mimic the input-output properties of controlled objects. Our studies have shown that: 1) an internal model for a novel tool is acquired in the cerebellum (Imamizu et al., 2000); 2) internal models are modularly organized in the cerebellum (Imamizu et al., 2003); 3) their outputs are sent to the premotor regions after learning (Tamada et al., 1999); and 4) the prefrontal and parietal regions contribute to the blending of the outputs (Imamizu et al., 2004). Here, we investigated changes in global neural networks resulting from the acquisition of a new internal model. Human subjects manipulated three types of rotating joystick whose cursor appeared at a position rotated 60 degrees, 110 degrees, or 160 degrees around the screen's center. In a pre-test after long-term training (5 days) for the 60 degrees and 160 degrees joysticks, brain activation was scanned during manipulation of the three joysticks. The subjects were then trained for the 110 degrees for only 25 min. In a post-test, activation was scanned using the same method as the pre-test. Comparisons of the post-test to the pre-test revealed that the volume of activation decreased in most of the regions where activation for the three rotations was observed. However, there was an increase in volume at a marginally significant level (p < .08) only in the inferior-lateral cerebellum and only for the 110 degrees joystick. In the cerebral cortex, activation related to 110 degrees decreased in the prefrontal and parietal regions but increased in the premotor and supplementary motor area (SMA) regions. These results can be explained by a model in which outputs of the 60 degrees and 160 degrees internal models are blended by prefrontal and parietal regions to cope with the novel 110 degrees joystick before the 25-minute training; after the acquisition within the cerebellum of an internal model for the 110 degrees, output is directly sent to the premotor and SMA regions, and activation in these regions increases.

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Mesh:

Year:  2007        PMID: 17533757     DOI: 10.1016/s0010-9452(08)70459-3

Source DB:  PubMed          Journal:  Cortex        ISSN: 0010-9452            Impact factor:   4.027


  31 in total

1.  Motor imagery in typing: effects of typing style and action familiarity.

Authors:  Martina Rieger
Journal:  Psychon Bull Rev       Date:  2012-02

2.  Manual skill generalization enhanced by negative viscosity.

Authors:  Felix C Huang; James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2010-07-21       Impact factor: 2.714

Review 3.  Cerebellar internal models: implications for the dexterous use of tools.

Authors:  Hiroshi Imamizu; Mitsuo Kawato
Journal:  Cerebellum       Date:  2012-06       Impact factor: 3.847

4.  Brain mechanisms for predictive control by switching internal models: implications for higher-order cognitive functions.

Authors:  Hiroshi Imamizu; Mitsuo Kawato
Journal:  Psychol Res       Date:  2009-04-04

5.  Neural correlates of predictive and postdictive switching mechanisms for internal models.

Authors:  Hiroshi Imamizu; Mitsuo Kawato
Journal:  J Neurosci       Date:  2008-10-15       Impact factor: 6.167

6.  Consensus paper: the cerebellum's role in movement and cognition.

Authors:  Leonard F Koziol; Deborah Budding; Nancy Andreasen; Stefano D'Arrigo; Sara Bulgheroni; Hiroshi Imamizu; Masao Ito; Mario Manto; Cherie Marvel; Krystal Parker; Giovanni Pezzulo; Narender Ramnani; Daria Riva; Jeremy Schmahmann; Larry Vandervert; Tadashi Yamazaki
Journal:  Cerebellum       Date:  2014-02       Impact factor: 3.847

7.  Reach adaptation: what determines whether we learn an internal model of the tool or adapt the model of our arm?

Authors:  JoAnn Kluzik; Jörn Diedrichsen; Reza Shadmehr; Amy J Bastian
Journal:  J Neurophysiol       Date:  2008-07-02       Impact factor: 2.714

8.  Motor and non-motor error and the influence of error magnitude on brain activity.

Authors:  Karin Graziella Nadig; Lutz Jäncke; Roger Lüchinger; Kai Lutz
Journal:  Exp Brain Res       Date:  2009-12-06       Impact factor: 1.972

9.  The impact of cerebellar transcranial direct current stimulation (tDCS) on learning fine-motor sequences.

Authors:  Renee E Shimizu; Allan D Wu; Jasmine K Samra; Barbara J Knowlton
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-01-05       Impact factor: 6.237

10.  Control of aperture closure initiation during reach-to-grasp movements under manipulations of visual feedback and trunk involvement in Parkinson's disease.

Authors:  Miya Kato Rand; Martin Lemay; Linda M Squire; Yury P Shimansky; George E Stelmach
Journal:  Exp Brain Res       Date:  2009-11-10       Impact factor: 1.972

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