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Estimating the Relevance of World Disturbances to Explain Savings Interference and Long-Term Motor Adaptation Effects

机译:估计世界干扰与解释节余干扰和长期电机适应效果的相关性

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摘要

Recent studies suggest that motor adaptation is the result of multiple, perhaps linear processes each with distinct time scales. While these models are consistent with some motor phenomena, they can neither explain the relatively fast re-adaptation after a long washout period, nor savings on a subsequent day. Here we examined if these effects can be explained if we assume that the CNS stores and retrieves movement parameters based on their possible relevance. We formalize this idea with a model that infers not only the sources of potential motor errors, but also their relevance to the current motor circumstances. In our model adaptation is the process of re-estimating parameters that represent the body and the world. The likelihood of a world parameter being relevant is then based on the mismatch between an observed movement and that predicted when not compensating for the estimated world disturbance. As such, adapting to large motor errors in a laboratory setting should alert subjects that disturbances are being imposed on them, even after motor performance has returned to baseline. Estimates of this external disturbance should be relevant both now and in future laboratory settings. Estimated properties of our bodies on the other hand should always be relevant. Our model demonstrates savings, interference, spontaneous rebound and differences between adaptation to sudden and gradual disturbances. We suggest that many issues concerning savings and interference can be understood when adaptation is conditioned on the relevance of parameters.
机译:最近的研究表明,运动适应是多个(可能是线性)过程的结果,每个过程都有不同的时标。尽管这些模型与某些运动现象是一致的,但它们既不能解释较长的冲刷时间后相对较快的重新适应,也不能解释第二天的节省。在这里,如果我们假设CNS根据其可能的相关性来存储和检索运动参数,则我们检查了这些影响是否可以解释。我们用一个模型来将此思想形式化,该模型不仅可以推断出潜在的电机错误源,而且可以推断出它们与当前电机状况的相关性。在我们的模型中,适应是重新估计代表身体和世界的参数的过程。然后,世界参数相关的可能性是基于观察到的运动与未补偿估计的世界干扰时预测的运动之间的失配。因此,在实验室环境中适应较大的电动机错误应提醒受试者,即使电动机性能已恢复到基准水平,也将对其施加干扰。现在和将来的实验室设置中,对这种外部干扰的估计都应具有相关性。另一方面,我们身体的估计属性应始终具有相关性。我们的模型证明了节省,干扰,自发反弹以及对突然和渐进干扰的适应之间的差异。我们建议,当适应性取决于参数的相关性时,可以理解许多与节省和干扰有关的问题。

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