Department of Psychology, Princeton University Princeton, NJ, USA.
Front Hum Neurosci. 2013 May 6;7:171. doi: 10.3389/fnhum.2013.00171. eCollection 2013.
The pattern of generalization following motor learning can provide a probe on the neural mechanisms underlying learning. For example, the breadth of generalization to untrained regions of space after visuomotor adaptation to targets in a restricted region of space has been attributed to the directional tuning properties of neurons in the motor system. Building on this idea, the effect of different types of perturbations on generalization (e.g., rotation vs. visual translation) have been attributed to the selection of differentially tuned populations. Overlooked in this discussion is consideration of how the context of the training environment may constrain generalization. Here, we explore the role of context by having participants learn a visuomotor rotation or a translational shift in two different contexts, one in which the array of targets were presented in a circular arrangement and the other in which they were presented in a rectilinear arrangement. The perturbation and environments were either consistent (e.g., rotation with circular arrangement) or inconsistent (e.g., rotation with rectilinear arrangement). The pattern of generalization across the workspace was much more dependent on the context of the environment than on the perturbation, with broad generalization for the rectilinear arrangement for both types of perturbations. Moreover, the generalization pattern for this context was evident, even when the perturbation was introduced in a gradual manner, precluding the use of an explicit strategy. We describe how current models of generalization might be modified to incorporate these results, building on the idea that context provides a strong bias for how the motor system infers the nature of the visuomotor perturbation and, in turn, how this information influences the pattern of generalization.
运动学习后的泛化模式可以为学习的神经机制提供一个探测。例如,在视觉运动适应限制空间区域的目标后,对未训练空间区域的广泛泛化可归因于运动系统中神经元的方向调谐特性。在此基础上,不同类型的扰动对泛化的影响(例如,旋转与视觉平移)归因于不同调谐群体的选择。在这个讨论中,忽略了考虑训练环境的上下文如何限制泛化。在这里,我们通过让参与者在两种不同的环境中学习视觉运动旋转或平移转换来探索上下文的作用,一种环境中目标数组以圆形排列呈现,另一种环境中目标数组以直线排列呈现。扰动和环境要么一致(例如,圆形排列的旋转),要么不一致(例如,直线排列的旋转)。工作空间的泛化模式更多地取决于环境的上下文,而不是扰动,对于两种类型的扰动,直线排列的泛化范围都很广。此外,即使在逐渐引入扰动的情况下,这种上下文的泛化模式也是显而易见的,排除了使用显式策略的可能性。我们描述了如何修改当前的泛化模型以纳入这些结果,其基础是上下文为运动系统如何推断视觉运动扰动的性质提供了一个强有力的偏见,进而影响了泛化模式。