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本文引用的文献

1
Reorganization of finger coordination patterns during adaptation to rotation and scaling of a newly learned sensorimotor transformation.在适应新学习的感觉运动转换的旋转和缩放过程中,手指协调模式的重组。
J Neurophysiol. 2011 Jan;105(1):454-73. doi: 10.1152/jn.00247.2010. Epub 2010 Oct 27.
2
An explicit strategy prevails when the cerebellum fails to compute movement errors.当小脑无法计算运动误差时,就会出现明确的策略。
Cerebellum. 2010 Dec;9(4):580-6. doi: 10.1007/s12311-010-0201-x.
3
Dissociating variability and effort as determinants of coordination.区分变异性和努力作为协调的决定因素。
PLoS Comput Biol. 2009 Apr;5(4):e1000345. doi: 10.1371/journal.pcbi.1000345. Epub 2009 Apr 10.
4
Learning algorithms for human-machine interfaces.人机界面的学习算法
IEEE Trans Biomed Eng. 2009 May;56(5):1502-11. doi: 10.1109/TBME.2009.2013822. Epub 2009 Feb 6.
5
Differences in context and feedback result in different trajectories and adaptation strategies in reaching.情境和反馈的差异会导致伸手动作中不同的轨迹和适应策略。
PLoS One. 2009;4(1):e4214. doi: 10.1371/journal.pone.0004214. Epub 2009 Jan 16.
6
Contributions of online visual feedback to the learning and generalization of novel finger coordination patterns.在线视觉反馈对新型手指协调模式学习与泛化的作用
J Neurophysiol. 2008 May;99(5):2546-57. doi: 10.1152/jn.01044.2007. Epub 2008 Mar 19.
7
A computational model for redundant human three-dimensional pointing movements: integration of independent spatial and temporal motor plans simplifies movement dynamics.一种用于冗余人体三维指向运动的计算模型:独立空间和时间运动计划的整合简化了运动动力学。
J Neurosci. 2007 Nov 28;27(48):13045-64. doi: 10.1523/JNEUROSCI.4334-06.2007.
8
Separate adaptive mechanisms for controlling trajectory and final position in reaching.用于控制伸手动作中轨迹和最终位置的独立自适应机制。
J Neurophysiol. 2007 Dec;98(6):3600-13. doi: 10.1152/jn.00121.2007. Epub 2007 Oct 3.
9
An implicit plan overrides an explicit strategy during visuomotor adaptation.在视觉运动适应过程中,隐性计划会优先于显性策略。
J Neurosci. 2006 Apr 5;26(14):3642-5. doi: 10.1523/JNEUROSCI.5317-05.2006.
10
Remapping hand movements in a novel geometrical environment.在新颖的几何环境中重新映射手部动作。
J Neurophysiol. 2005 Dec;94(6):4362-72. doi: 10.1152/jn.00380.2005. Epub 2005 Sep 7.

视觉运动对运动学习的影响。

The influence of visual motion on motor learning.

机构信息

Department of Biomedical Engineering, Northwestern University, Evanston, Illinois 60208, USA.

出版信息

J Neurosci. 2012 Jul 18;32(29):9859-69. doi: 10.1523/JNEUROSCI.5528-11.2012.

DOI:10.1523/JNEUROSCI.5528-11.2012
PMID:22815501
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3437549/
Abstract

How does visual perception shape the way we coordinate movements? Recent studies suggest that the brain organizes movements based on minimizing reaching errors in the presence of motor and sensory noise. We present an alternative hypothesis in which movement trajectories also result from acquired knowledge about the geometrical properties of the object that the brain is controlling. To test this hypothesis, we asked human subjects to control a simulated kinematic linkage by continuous finger motion, a completely novel experience. This paradigm removed all biases arising from influences of limb dynamics and past experience. Subjects were exposed to two different types of visual feedback; some saw the entire simulated linkage and others saw only the moving extremity. Consistent with our hypothesis, subjects learned to move the simulated linkage along geodesic lines corresponding to the geometrical structure of the observed motion. Thus, optimizing final accuracy is not the unique determinant of trajectory formation.

摘要

视觉感知如何塑造我们协调运动的方式?最近的研究表明,大脑根据在存在运动和感觉噪声的情况下最小化到达误差来组织运动。我们提出了一个替代假设,即运动轨迹也是基于大脑控制的物体的几何属性的习得知识而产生的。为了检验这一假设,我们要求人类受试者通过连续的手指运动来控制一个模拟的运动链,这是一种全新的体验。这种范式消除了由于肢体动力学和过去经验的影响而产生的所有偏差。受试者接触到两种不同类型的视觉反馈;一些人看到了整个模拟的连接,而另一些人只看到了移动的末端。与我们的假设一致,受试者学会了沿着与观察到的运动的几何结构相对应的测地线移动模拟的连接。因此,优化最终精度并不是轨迹形成的唯一决定因素。