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视觉探索动力学是低维的,并受内在因素驱动。

Visual exploration dynamics are low-dimensional and driven by intrinsic factors.

机构信息

Department of Neuroscience, University of Padova, Padova, Italy.

Padova Neuroscience Center (PNC), University of Padova, Padova, Italy.

出版信息

Commun Biol. 2021 Sep 17;4(1):1100. doi: 10.1038/s42003-021-02608-x.

Abstract

When looking at visual images, the eyes move to the most salient and behaviourally relevant objects. Saliency and semantic information significantly explain where people look. Less is known about the spatiotemporal properties of eye movements (i.e., how people look). We show that three latent variables explain 60% of eye movement dynamics of more than a hundred observers looking at hundreds of different natural images. The first component explaining 30% of variability loads on fixation duration, and it does not relate to image saliency or semantics; it approximates a power-law distribution of gaze steps, an intrinsic dynamic measure, and identifies observers with two viewing styles: static and dynamic. Notably, these viewing styles were also identified when observers look at a blank screen. These results support the importance of endogenous processes such as intrinsic dynamics to explain eye movement spatiotemporal properties.

摘要

当观察视觉图像时,眼睛会移动到最显著和行为上最相关的物体上。显著度和语义信息可以很好地解释人们的注视点位置。然而,人们对于眼动(即人们如何看)的时空特征了解较少。我们发现,三个潜在变量可以解释超过一百名观察者观看数百张不同自然图像时 60%的眼动动态。第一个解释 30%可变性的成分与注视持续时间有关,它与图像显著度或语义无关;它近似于注视点步骤的幂律分布,这是一种内在的动态测量,可以识别出具有两种观察方式的观察者:静态和动态。值得注意的是,当观察者观看空白屏幕时,也可以识别出这些观察方式。这些结果支持了内在动态等内源性过程对于解释眼动时空特征的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd8/8448835/f9a7e2cafda9/42003_2021_2608_Fig1_HTML.jpg

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