Visual Feedback Is Not Necessary for the Learning of Novel Dynamics
被引:73
作者:
Franklin, David W.
论文数: 0引用数: 0
h-index: 0
机构:
Natl Inst Informat & Commun Technol, Keihanna Sci City, Kyoto, Japan
ATR Computat Neurosci Labs, Keihanna Sci City, Kyoto, Japan
Univ Cambridge, Dept Engn, Cambridge CB2 1PZ, EnglandNatl Inst Informat & Commun Technol, Keihanna Sci City, Kyoto, Japan
Franklin, David W.
[1
,2
,3
]
So, Udell
论文数: 0引用数: 0
h-index: 0
机构:
ATR Computat Neurosci Labs, Keihanna Sci City, Kyoto, JapanNatl Inst Informat & Commun Technol, Keihanna Sci City, Kyoto, Japan
So, Udell
[2
]
Burdet, Etienne
论文数: 0引用数: 0
h-index: 0
机构:
Univ London Imperial Coll Sci Technol & Med, Dept Bioengn, London, EnglandNatl Inst Informat & Commun Technol, Keihanna Sci City, Kyoto, Japan
Burdet, Etienne
[4
]
Kawato, Mitsuo
论文数: 0引用数: 0
h-index: 0
机构:
ATR Computat Neurosci Labs, Keihanna Sci City, Kyoto, JapanNatl Inst Informat & Commun Technol, Keihanna Sci City, Kyoto, Japan
Kawato, Mitsuo
[2
]
机构:
[1] Natl Inst Informat & Commun Technol, Keihanna Sci City, Kyoto, Japan
[2] ATR Computat Neurosci Labs, Keihanna Sci City, Kyoto, Japan
[3] Univ Cambridge, Dept Engn, Cambridge CB2 1PZ, England
[4] Univ London Imperial Coll Sci Technol & Med, Dept Bioengn, London, England
来源:
PLOS ONE
|
2007年
/
2卷
/
12期
基金:
加拿大自然科学与工程研究理事会;
关键词:
D O I:
10.1371/journal.pone.0001336
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
Background. When learning to perform a novel sensorimotor task, humans integrate multi-modal sensory feedback such as vision and proprioception in order to make the appropriate adjustments to successfully complete the task. Sensory feedback is used both during movement to control and correct the current movement, and to update the feed-forward motor command for subsequent movements. Previous work has shown that adaptation to stable dynamics is possible without visual feedback. However, it is not clear to what degree visual information during movement contributes to this learning or whether it is essential to the development of an internal model or impedance controller. Methodology/Principle Findings. We examined the effects of the removal of visual feedback during movement on the learning of both stable and unstable dynamics in comparison with the case when both vision and proprioception are available. Subjects were able to learn to make smooth movements in both types of novel dynamics after learning with or without visual feedback. By examining the endpoint stiffness and force after learning it could be shown that subjects adapted to both types of dynamics in the same way whether they were provided with visual feedback of their trajectory or not. The main effects of visual feedback were to increase the success rate of movements, slightly straighten the path, and significantly reduce variability near the end of the movement. Conclusions/Significance. These findings suggest that visual feedback of the hand during movement is not necessary for the adaptation to either stable or unstable novel dynamics. Instead vision appears to be used to fine-tune corrections of hand trajectory at the end of reaching movements.