Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland; and
Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland; and Department of Otolaryngology-Head and Neck Surgery, The Johns Hopkins University School of Medicine, Baltimore, Maryland.
J Neurophysiol. 2014 May;111(10):2084-93. doi: 10.1152/jn.00779.2013. Epub 2014 Mar 5.
Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation.
自适应过程对于维持身体运动的准确性至关重要,依赖于错误存储和处理机制。尽管经典的适应性研究范式,但这些持续的纠错机制的证据也应该在其他运动中检测到。尽管存在这种联系,但当前的适应模型在使用基线行为的测量值预测适应能力时受到挑战。另一方面,我们之前已经确定了在一种特殊形式的基线行为中存在的纠错过程,即预测性扫视的生成。这个过程表现出长期的trial-to-trial 相关性,逐渐衰减(作为幂律),最好用分形时间序列分析的工具来描述。由于这个基线任务和适应都涉及到错误存储和处理,我们试图在预测性扫视的纠错过程的 trial-to-trial 相关性和受试者在适应任务中改变扫视幅度的能力之间找到联系。在这里,我们发现了这样一种关系:预测过程中的 trial-to-trial 相关性越强,适应的获取速度就越快。这加强了先前在运动控制中发现的预测和适应之间的联系,并表明当前的适应模型不足以捕捉这些纠错过程的完整动态。更好地理解预测和适应之间的错误处理相似性可能为使用基线任务预测适应能力提供一种手段。这将在物理治疗和运动适应范式的一般设计中具有许多潜在的用途。