Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, United Kingdom; Neuromuscular Diagnostics, Department of Sport and Health Sciences, Technical University of Munich, 80992 Munich, Germany.
Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, United Kingdom; Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, United Kingdom.
eNeuro. 2016 Aug 23;3(4). doi: 10.1523/ENEURO.0070-16.2016. eCollection 2016 Jul-Aug.
The coordinate system in which humans learn novel motor skills is controversial. The representation of sensorimotor skills has been extensively studied by examining generalization after learning perturbations specifically designed to be ambiguous as to their coordinate system. Recent studies have found that learning is not represented in any simple coordinate system and can potentially be accounted for by a mixed representation. Here, instead of probing generalization, which has led to conflicting results, we examine whether novel dynamics can be learned when explicitly and unambiguously presented in particular coordinate systems. Subjects performed center-out reaches to targets in the presence of a force field, while varying the orientation of their hand (i.e., the wrist angle) across trials. Different groups of subjects experienced force fields that were explicitly presented either in Cartesian coordinates (field independent of hand orientation), in object coordinates (field rotated with hand orientation), or in anti-object coordinates (field rotated counter to hand orientation). Subjects learned to represent the dynamics when presented in either Cartesian or object coordinates, learning these as well as an ambiguous force field. However, learning was slower for the object-based dynamics and substantially impaired for the anti-object presentation. Our results show that the motor system is able to tune its representation to at least two natural coordinate systems but is impaired when the representation of the task does not correspond to a behaviorally relevant coordinate system. Our results show that the motor system can sculpt its representation through experience to match those of natural tasks.
人类学习新运动技能的坐标系存在争议。通过研究专门设计的、在坐标系上具有模糊性的学习后扰动的泛化,人们广泛研究了运动技能的表示。最近的研究发现,学习不是以任何简单的坐标系表示的,并且可以通过混合表示来解释。在这里,我们不是通过探究导致结果相互矛盾的泛化来检验,而是检查当特定坐标系中明确且明确地呈现新动力学时,是否可以进行学习。在存在力场的情况下,受试者执行中心外到达目标的动作,同时在手的方向(即手腕角度)上改变试验。不同组的受试者经历了明确以笛卡尔坐标系(与手方向无关的力场)、物体坐标系(随手方向旋转的力场)或反物体坐标系(与手方向相反的力场)呈现的力场。当以笛卡尔坐标系或物体坐标系呈现时,受试者学会了表示动力学,同时还学会了表示模糊的力场。然而,基于物体的动力学的学习速度较慢,对于反物体呈现的学习则受到严重影响。我们的结果表明,运动系统能够将其表示调整到至少两个自然坐标系,但当任务的表示与行为相关的坐标系不对应时,系统就会受到损害。我们的结果表明,运动系统可以通过经验来塑造其表示,以匹配自然任务的表示。