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动态眼动实验的统计建模:多组情况下视觉刺激元素对视向行为的相对重要性。

Statistical modeling of dynamic eye-tracking experiments: Relative importance of visual stimulus elements for gaze behavior in the multi-group case.

机构信息

Department of Statistics, TU Dortmund University, Vogelpothsweg 78, 44227, Dortmund, Germany.

Department of Statistics, Ludwig Maximilian University of Munich, Ludwigstr. 33, 80539, Munich, Germany.

出版信息

Behav Res Methods. 2021 Dec;53(6):2650-2667. doi: 10.3758/s13428-021-01576-8. Epub 2021 May 23.

Abstract

This paper presents a model that allows group comparisons of gaze behavior while watching dynamic video stimuli. The model is based on the approach of Coutrot and Guyader (2017) and allows linear combinations of feature maps to form a master saliency map. The feature maps in the model are, for example, the dynamically salient contents of a video stimulus or predetermined areas of interest. The model takes into account temporal aspects of the stimuli, which is a crucial difference to other common models. The multi-group extension of the model introduced here allows to obtain relative importance plots, which visualize the effect of a specific feature of a stimulus on the attention and visual behavior for two or more experimental groups. These plots are interpretable summaries of data with high spatial and temporal resolution. This approach differs from many common methods for comparing gaze behavior between natural groups, which usually only include single-dimensional features such as the duration of fixation on a particular part of the stimulus. The method is illustrated by contrasting a sample of a group of persons with particularly high cognitive abilities (high achievement on IQ tests) with a control group on a psycholinguistic task on the conceptualization of motion events. In the example, we find no substantive differences in relative importance, but more exploratory gaze behavior in the highly gifted group. The code, videos, and eye-tracking data we used for this study are available online.

摘要

本文提出了一种模型,允许在观看动态视频刺激时对注视行为进行组间比较。该模型基于 Coutrot 和 Guyader(2017)的方法,允许特征图的线性组合形成主显著图。模型中的特征图例如是视频刺激的动态显著内容或预定的兴趣区域。该模型考虑了刺激的时间方面,这与其他常见模型有很大的不同。这里介绍的模型的多组扩展允许获得相对重要性图,这些图直观地显示了刺激的特定特征对两个或更多实验组的注意力和视觉行为的影响。这些图是具有高空间和时间分辨率的数据的可解释性摘要。这种方法与许多用于比较自然组之间注视行为的常用方法不同,后者通常只包括一维特征,例如在刺激的特定部分上的注视持续时间。该方法通过在心理语言学任务上对比具有高认知能力(智商测试中表现出色)的人群样本和对照组对运动事件的概念化来举例说明。在该示例中,我们没有发现相对重要性方面的实质性差异,但在高天赋组中发现了更多的探索性注视行为。我们用于这项研究的代码、视频和眼动追踪数据可在线获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0808/8613156/3ffbc6427dff/13428_2021_1576_Fig1_HTML.jpg

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