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使用固定预测性眼球追踪任务探索基于错误的运动学习的基本动力学。

Exploring the fundamental dynamics of error-based motor learning using a stationary predictive-saccade task.

机构信息

Department of Biomedical Engineering, The Johns Hopkins University, School of Medicine, Baltimore, Maryland, United States of America.

出版信息

PLoS One. 2011;6(9):e25225. doi: 10.1371/journal.pone.0025225. Epub 2011 Sep 23.

DOI:10.1371/journal.pone.0025225
PMID:21966462
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3179473/
Abstract

The maintenance of movement accuracy uses prior performance errors to correct future motor plans; this motor-learning process ensures that movements remain quick and accurate. The control of predictive saccades, in which anticipatory movements are made to future targets before visual stimulus information becomes available, serves as an ideal paradigm to analyze how the motor system utilizes prior errors to drive movements to a desired goal. Predictive saccades constitute a stationary process (the mean and to a rough approximation the variability of the data do not vary over time, unlike a typical motor adaptation paradigm). This enables us to study inter-trial correlations, both on a trial-by-trial basis and across long blocks of trials. Saccade errors are found to be corrected on a trial-by-trial basis in a direction-specific manner (the next saccade made in the same direction will reflect a correction for errors made on the current saccade). Additionally, there is evidence for a second, modulating process that exhibits long memory. That is, performance information, as measured via inter-trial correlations, is strongly retained across a large number of saccades (about 100 trials). Together, this evidence indicates that the dynamics of motor learning exhibit complexities that must be carefully considered, as they cannot be fully described with current state-space (ARMA) modeling efforts.

摘要

运动准确性的维持利用先前的运动误差来修正未来的运动计划;这个运动学习过程确保运动既快速又准确。预测性眼球运动的控制,即在前瞻性运动在视觉刺激信息可用之前就针对未来的目标进行,是分析运动系统如何利用先前的错误将运动引导到期望的目标的理想范例。预测性眼球运动构成一个静止过程(与典型的运动适应范例不同,数据的平均值和大致的可变性不会随时间变化)。这使我们能够研究试验间相关性,无论是在逐个试验的基础上还是在长试验块上。发现眼球运动误差在逐个试验的基础上以特定的方向进行校正(在同一方向上进行的下一次眼球运动将反映对当前眼球运动误差的校正)。此外,还有证据表明存在第二种调节过程,表现出长时记忆。也就是说,如通过试验间相关性测量的那样,性能信息在大量眼球运动中(约 100 次试验)得到强烈保留。这些证据表明,运动学习的动态表现出必须仔细考虑的复杂性,因为它们不能用当前的状态空间(ARMA)建模努力来充分描述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/726251e84a4e/pone.0025225.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/38f03889739a/pone.0025225.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/f6b115aec8d0/pone.0025225.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/b380f7090fe3/pone.0025225.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/9f88d6b35485/pone.0025225.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/7b07d8ea432a/pone.0025225.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/726251e84a4e/pone.0025225.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/38f03889739a/pone.0025225.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/f6b115aec8d0/pone.0025225.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/b380f7090fe3/pone.0025225.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/9f88d6b35485/pone.0025225.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/7b07d8ea432a/pone.0025225.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c10/3179473/726251e84a4e/pone.0025225.g006.jpg

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