| Budget Amount *help |
¥17,550,000 (Direct Cost: ¥13,500,000、Indirect Cost: ¥4,050,000)
Fiscal Year 2019: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2018: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2017: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2016: ¥8,840,000 (Direct Cost: ¥6,800,000、Indirect Cost: ¥2,040,000)
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| Outline of Final Research Achievements |
We can adapt to unfamiliar environments through active motor experience. Recent neurorehabilitation study using robots or brain-computer interface (BCI) technology suggest that passive motor experience would play a measurable role in motor recovery, however our knowledge on passive motor learning is limited.
To clarify the effects of passive motor experience on human motor learning, we performed a visuomotor learning experiments guided by a robotic manipulandum. In the study, we further investigate whether the active motor command generation with/without error presentation during passive motor experience can affect the formation of internal model for future active motor execution.
The experimental result suggests that recognizing prediction error is effective for constructing internal model even in passive motor experience. Analyzing the change of body representation between before and after the passive motor experience is future work.
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