Aix Marseille Univ, CNRS, ISM, Marseille, France.
Department of Neuroscience, University of Pennsylvania, Philadelphia, USA.
Psychol Res. 2020 Jun;84(4):866-880. doi: 10.1007/s00426-018-1110-8. Epub 2018 Nov 8.
The human nervous system displays such plasticity that we can adapt our motor behavior to various changes in environmental or body properties. However, how sensorimotor adaptation generalizes to new situations and new effectors, and which factors influence the underlying mechanisms, remains unclear. Here we tested the general hypothesis that differences across participants can be exploited to uncover what drives interlimb transfer. Twenty healthy adults adapted to prismatic glasses while reaching to visual targets with their dominant arm. Classic adaptation and generalization across movement directions were observed but transfer to the non-dominant arm was not significant and inter-individual differences were substantial. Interlimb transfer resulted for some participants in a directional shift of non-dominant arm movements that was consistent with an encoding of visuomotor adaptation in extrinsic coordinates. For some other participants, transfer was consistent with an intrinsic coordinate system. Simple and multiple regression analyses showed that a few kinematic parameters such as peak acceleration (or peak velocity) and variability of movement direction were correlated with interlimb transfer. Low peak acceleration and low variability were related to extrinsic transfer, while high peak acceleration and high variability were related to intrinsic transfer. Motor variability was also positively correlated with the magnitude of the after-effect systematically observed on the dominant arm. Overall, these findings on unconstrained movements support the idea that individual movement features could be linked to the sensorimotor adaptation and its generalization. The study also suggests that distinct movement characteristics may be related to different coordinate frames of action representations in the nervous system.
人类神经系统具有很强的可塑性，能够根据环境或身体属性的各种变化来调整运动行为。然而，传感器运动适应如何推广到新的情况和新的效应器，以及哪些因素影响潜在机制，目前尚不清楚。在这里，我们测试了一个普遍假设，即参与者之间的差异可以被利用来揭示是什么驱动了肢体间的转移。20 名健康成年人在使用主导手臂达到视觉目标时，适应了棱镜眼镜。观察到了经典的适应和跨运动方向的泛化，但对非主导手臂的转移并不显著，个体间差异很大。对于一些参与者来说，肢体间的转移导致非主导手臂的运动方向发生了方向性的变化，这与外在坐标系中视觉运动适应的编码一致。对于其他一些参与者来说，转移与内在坐标系一致。简单和多元回归分析表明，一些运动学参数，如峰值加速度（或峰值速度）和运动方向的可变性，与肢体间的转移有关。低峰值加速度和低可变性与外在转移有关，而高峰值加速度和高可变性与内在转移有关。运动可变性也与在主导手臂上系统观察到的后效的大小呈正相关。总的来说，这些关于非约束运动的发现支持了这样一种观点，即个体运动特征可能与传感器运动适应及其泛化有关。该研究还表明，不同的运动特征可能与神经系统中不同的动作表示坐标系有关。
