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意外事件会扰乱视觉运动工作记忆并增加猜测行为。

Unexpected events disrupt visuomotor working memory and increase guessing.

作者信息

Finzi R Dawn, Postle Bradley R, Brady Timothy F, Aron Adam R

机构信息

Psychology Department, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92103, USA.

Psychology Department, University of Wisconsin-Madison, Madison, WI, USA.

出版信息

Psychon Bull Rev. 2018 Apr;25(2):651-657. doi: 10.3758/s13423-017-1319-3.

Abstract

When an unexpected event, such as a car horn honking, occurs in daily life, it often disrupts our train of thought. In the lab, this effect was recently modeled with a task in which verbal working memory (WM) was disrupted by unexpected auditory events (Wessel et al. in Nature Communications, 7, 11195, 2016). Here we tested whether this effect extends to a different type of WM-namely, visuomotor. We found that unexpected auditory events similarly decremented visuomotor WM. Moreover, this effect persisted for many more trials than had previously been shown for verbal WM, and the effect occurred for two different types of unexpected auditory events. Furthermore, we found that unexpected events decremented WM by decreasing the quantity, but not necessarily the quality, of items stored. These results showed an impact of unexpected events on visuomotor WM that was statistically robust and endured across time. They also showed that the effect was based on an increase in guessing, consistent with a neuroscience-inspired theory that unexpected events "wipe out" WM by stopping the ongoing maintenance of the trace. This new task paradigm is an excellent vehicle for further explorations of distractibility.

摘要

在日常生活中,当出现诸如汽车喇叭鸣响之类的意外事件时,往往会扰乱我们的思路。最近在实验室中,通过一项任务模拟了这种效应,在该任务中,意外听觉事件会干扰言语工作记忆(WM)(韦塞尔等人,《自然通讯》,7卷,11195页,2016年)。在此,我们测试了这种效应是否也适用于另一种类型的工作记忆,即视觉运动工作记忆。我们发现,意外听觉事件同样会使视觉运动工作记忆下降。此外,与之前在言语工作记忆中所显示的相比,这种效应在更多的试验中持续存在,并且两种不同类型的意外听觉事件都会产生这种效应。此外,我们发现意外事件通过减少存储项目的数量而非质量来降低工作记忆。这些结果表明,意外事件对视觉运动工作记忆有统计学上显著且持久的影响。它们还表明,这种效应是基于猜测的增加,这与一种受神经科学启发的理论一致,即意外事件通过停止对痕迹的持续维持来“清除”工作记忆。这种新的任务范式是进一步探索注意力分散性的绝佳工具。

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