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当在动态动作中检测到结构时,注意力会重新组织。

Attention reorganizes as structure is detected in dynamic action.

作者信息

Hard Bridgette Martin, Meyer Meredith, Baldwin Dare

机构信息

Department of Psychology and Neuroscience, Duke University, Durham, NC, 27708, USA.

Department of Psychology, Otterbein University, Westerville, OH, USA.

出版信息

Mem Cognit. 2019 Jan;47(1):17-32. doi: 10.3758/s13421-018-0847-z.

Abstract

Once one sees a pattern, it is challenging to "unsee" it; discovering structure alters processing. Precisely what changes as this happens is unclear, however. We probed this question by tracking changes in attention as viewers discovered statistical patterns within unfolding event sequences. We measured viewers' "dwell times" (e.g., Hard, Recchia, & Tversky, 2011) as they advanced at their own pace through a series of still-frame images depicting a sequence of event segments ("actions") that were discoverable only via sensitivity to statistical regularities among the component motion elements. "Knowledgeable" adults, who had had the opportunity to learn these statistical regularities prior to the slideshow viewing, displayed dwell-time patterns indicative of sensitivity to the statistically defined higher-level segmental structure; "naïve" adults, who lacked the opportunity for prior viewing, did not. These findings clarify that attention reorganizes in conjunction with statistically guided discovery of segmental structure within continuous human activity sequences. As patterns emerge in the mind, attention redistributes selectively to target boundary regions, perhaps because they represent highly informative junctures of "predictable unpredictability."

摘要

一旦一个人看到了一种模式,就很难“不再看到”它;发现结构会改变认知过程。然而,当这种情况发生时究竟发生了什么变化尚不清楚。我们通过追踪观众在展开的事件序列中发现统计模式时注意力的变化来探究这个问题。我们测量了观众以自己的节奏浏览一系列静止图像时的“停留时间”(例如,哈德、雷基亚和特沃斯基,2011年),这些图像描绘了一系列事件片段(“动作”),这些片段只能通过对组成运动元素之间的统计规律的敏感度来发现。“有经验的”成年人在观看幻灯片之前有机会学习这些统计规律,他们的停留时间模式表明对统计定义的更高层次的片段结构敏感;而“天真的”成年人没有提前观看的机会,则没有表现出这种敏感。这些发现表明,在连续的人类活动序列中,注意力会随着对片段结构的统计引导发现而重新组织。随着模式在脑海中浮现,注意力会有选择地重新分配到目标边界区域,这可能是因为这些区域代表了“可预测的不可预测性”的高度信息交汇点。

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