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  • 标题:Tandem internal models execute motor learning in the cerebellum
  • 本地全文:下载
  • 作者:Takeru Honda ; Soichi Nagao ; Yuji Hashimoto
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2018
  • 卷号:115
  • 期号:28
  • 页码:7428-7433
  • DOI:10.1073/pnas.1716489115
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:In performing skillful movement, humans use predictions from internal models formed by repetition learning. However, the computational organization of internal models in the brain remains unknown. Here, we demonstrate that a computational architecture employing a tandem configuration of forward and inverse internal models enables efficient motor learning in the cerebellum. The model predicted learning adaptations observed in hand-reaching experiments in humans wearing a prism lens and explained the kinetic components of these behavioral adaptations. The tandem system also predicted a form of subliminal motor learning that was experimentally validated after training intentional misses of hand targets. Patients with cerebellar degeneration disease showed behavioral impairments consistent with tandemly arranged internal models. These findings validate computational tandemization of internal models in motor control and its potential uses in more complex forms of learning and cognition.
  • 关键词:motor control ; forward model ; inverse model ; cerebellar degeneration ; prism adaptation
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