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n 回溯任务训练有助于提高错误后表现。

N-Back Task Training Helps to Improve Post-error Performance.

作者信息

Li Qing, Long Quanshan, Hu Na, Tang Yancheng, Chen Antao

机构信息

Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China.

出版信息

Front Psychol. 2020 Mar 11;11:370. doi: 10.3389/fpsyg.2020.00370. eCollection 2020.

DOI:10.3389/fpsyg.2020.00370
PMID:32218757
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7078347/
Abstract

Improved performance on working memory (WM) through training has been widely expected to transfer to other domains. Recent studies have proposed that WM training could enhance the autonomous coordination of WM processes. Based on the shared processes between WM and error processing, our present study explored the transfer effect of 15 days of training on post-error performance, during the n-back task, compared to a simple visual search task. Participants were randomly assigned to either the training ( = 22) or control ( = 18) group. We found that WM training successfully improved WM performance. After training, compared with the control group, the training group showed a significant reduction in post-error slowing (PES); however, post-error accuracy and the flanker effect were not modulated by WM training. Moreover, we observed a significant, negative correlation between the changes in PES and WM from pretest to posttest and classified two groups based on these changes in PES with 70% accuracy. Thus, in our present sample, WM training improved post-error performance. We propose that the skill of controlling information flow, developed during WM training, is transferable to other tasks and discuss the implications of current findings for understanding the generation of PES.

摘要

人们普遍期望通过训练提高工作记忆(WM)的表现,从而能迁移到其他领域。最近的研究表明,WM训练可以增强WM过程的自主协调能力。基于WM与错误处理之间的共享过程,我们目前的研究探讨了与简单视觉搜索任务相比,15天的训练对n-back任务中错误后表现的迁移效应。参与者被随机分配到训练组(n = 22)或对照组(n = 18)。我们发现WM训练成功提高了WM表现。训练后,与对照组相比,训练组的错误后反应减慢(PES)显著降低;然而,错误后准确性和侧翼效应并未受到WM训练的调节。此外,我们观察到从预测试到后测试,PES变化与WM之间存在显著的负相关,并根据PES的这些变化以70%的准确率将两组进行了分类。因此,在我们目前的样本中,WM训练改善了错误后表现。我们提出,在WM训练过程中发展起来的控制信息流的技能可迁移到其他任务中,并讨论了当前研究结果对理解PES产生的意义。

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