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适应虚拟和真实滑动杆视动转换的轨迹。

The trajectory of adaptation to the visuo-motor transformation of virtual and real sliding levers.

机构信息

IfADo, Leibniz Research Centre for Working Environment and Human Factors, Ardeystrasse 67, 44139, Dortmund, Germany.

出版信息

Exp Brain Res. 2010 Mar;201(3):549-60. doi: 10.1007/s00221-009-2071-3. Epub 2009 Nov 10.

DOI:10.1007/s00221-009-2071-3
PMID:19902192
Abstract

We studied adaptation to the visuo-motor transformation of a virtual and a real two-sided sliding lever. In a previous study (Sülzenbrück and Heuer in Exp Brain Res 195:153-165, 2009) we had found essentially no differences. However, adaptation had been restricted to a simplified symmetry approximation of the transformation. In the present study practice conditions were designed to facilitate adaptation (e.g., terminal rather than continuous visual feedback). In visual open-loop tests, differences between the effects of practice with a virtual and a real lever were found for curvature of hand movements, whereas movement end positions were not different. Curved hand movements induced by the use of the real lever persisted in subsequent open-loop tests with the virtual lever. Early in practice end-position errors were strongly biased toward the simplified symmetry approximation, but this bias was reduced later on. Thus, the symmetry approximation is a transient state in the trajectory of adaptation that is reached quickly and from which there is a slow and gradual transition to an accurate internal representation of the visuo-motor transformation of the sliding lever.

摘要

我们研究了对虚拟和真实双边滑动杆的视动转换的适应。在之前的研究中(Sülzenbrück 和 Heuer 在 Exp Brain Res 195:153-165, 2009),我们发现没有本质的差异。然而,适应仅限于转换的简化对称近似。在本研究中,练习条件的设计旨在促进适应(例如,终端而不是连续的视觉反馈)。在视觉开环测试中,在使用虚拟和真实杠杆进行练习的效果之间发现了手运动曲率的差异,而运动末端位置没有差异。使用真实杠杆引起的弯曲手运动在随后的虚拟杠杆开环测试中持续存在。在练习的早期,末端位置误差强烈偏向于简化对称近似,但后来这种偏差减小了。因此,对称近似是适应轨迹中的一个瞬态状态,它可以快速达到,并且从这个状态到滑动杆的视动转换的准确内部表示,存在缓慢而逐渐的过渡。

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Learning the visuomotor transformation of virtual and real sliding levers: simple approximations of complex transformations.学习虚拟和真实滑动杠杆的视觉运动转换:复杂转换的简单近似
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