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The representational dynamics of visual objects in rapid serial visual processing streams

机译:快速串行视觉处理流中的视觉对象的代表性动态

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In our daily lives, we are bombarded with a stream of rapidly changing visual input. Humans have the remarkable capacity to detect and identify objects in fast-changing scenes. Yet, when studying brain representations, stimuli are generally presented in isolation. Here, we studied the dynamics of human vision using a combination of fast stimulus presentation rates, electroencephalography and multivariate decoding analyses. Using a presentation rate of 5 images per second, we obtained the representational structure of a large number of stimuli, and showed the emerging abstract categorical organisation of this structure. Furthermore, we could separate the temporal dynamics of perceptual processing from higher-level target selection effects. In a second experiment, we used the same paradigm at 20Hz to show that shorter image presentation limits the categorical abstraction of object representations. Our results show that applying multivariate pattern analysis to every image in rapid serial visual processing streams has unprecedented potential for studying the temporal dynamics of the structure of representations in the human visual system.
机译:在我们的日常生活中,我们被轰炸为快速改变的视觉输入。人类具有显着的能力来检测和识别快速变化的场景中的物体。然而,当研究脑表示时,通常以分离呈现刺激。在这里,我们使用快速刺激呈现率,脑电图和多变量解码分析的组合研究了人类视觉的动态。每秒使用5张图像的演示速率,我们获得了大量刺激的代表性结构,并显示了这种结构的新兴抽象分类组织。此外,我们可以将感知处理的时间动态与更高级别的目标选择效果分开。在第二个实验中,我们在20Hz中使用相同的范式以显示更短的图像表示限制了对象表示的分类抽象。我们的结果表明,对快速串行视觉处理流中的每张图像对多变量模式分析对研究人类视觉系统中的表示结构的时间动态具有前所未有的潜力。

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