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连续跟踪任务范式中隐式波形特定学习的可靠检测

Reliable Detection of Implicit Waveform-Specific Learning in Continuous Tracking Task Paradigm.

作者信息

Yang Limin, Wan Feng, Nan Wenya, Zhu Frank, Hu Yong

机构信息

Department of Electrical and Computer Engineering, University of Macau, Macau S.A.R., China.

Department of Psychology, College of Education, Shanghai Normal University, Shanghai, China.

出版信息

Sci Rep. 2017 Sep 26;7(1):12333. doi: 10.1038/s41598-017-11977-5.

Abstract

Implicit waveform-specific (IWS) learning during a typical continuous tracking task paradigm has been reported for decades, as evidenced by better tracking improvement on the repeated segment of a specific target waveform than random segments. However, the occurrence of the IWS learning in such a task paradigm has been challenged by several unsuccessful results in recent literature. This research concerns reliable detection of the induced IWS learning and to this end, proposes to use the similarity between the cursor and the target along the direction corresponding to the waveform pattern as the performance measure. A 3-day experiment designed with full examination on IWS learning including a practice phase, an immediate test phase and a consolidation test phase after 24 hours was conducted to validate the feasibility and sensitivity of the Pearson's correlation coefficient on the vertical movement r in this study. Experiment results indicate that r is more sensitive in detecting the IWS learning in all phases compared to the conventional root mean square error (RMSE) performance measure. The findings confirm the importance of the performance measure in implicit learning research and the similarity measure in accordance with the waveform could be promising for waveform-specific learning detection in this paradigm.

摘要

在典型的连续跟踪任务范式中,隐式波形特定(IWS)学习已经被报道了数十年,具体表现为在特定目标波形的重复段上比随机段有更好的跟踪改善。然而,近期文献中的一些不成功结果对这种任务范式中IWS学习的出现提出了挑战。本研究关注诱导IWS学习的可靠检测,为此,建议将光标与目标在对应波形模式方向上的相似度用作性能度量。设计了一个为期3天的实验,全面考察IWS学习,包括一个练习阶段、一个即时测试阶段以及24小时后的巩固测试阶段,以验证本研究中垂直运动r的皮尔逊相关系数的可行性和敏感性。实验结果表明,与传统的均方根误差(RMSE)性能度量相比,r在所有阶段检测IWS学习时更敏感。这些发现证实了性能度量在隐式学习研究中的重要性,并且根据波形的相似度度量在这种范式中进行波形特定学习检测可能很有前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6deb/5615060/841ad68f4cdb/41598_2017_11977_Fig1_HTML.jpg

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