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Manipulating the structure of natural scenes using wavelets to study the functional architecture of perceptual hierarchies in the brain

机译:使用小波进行操纵自然场景的结构,以研究大脑中感知层次结构的功能架构

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摘要

Functional neuroimaging experiments that employ naturalistic stimuli (natural scenes, films, spoken narratives) provide insights into cognitive function “in the wild”. Natural stimuli typically possess crowded, spectrally dense, dynamic, and multimodal properties within a rich multiscale structure. However, when using natural stimuli, various challenges exist for creating parametric manipulations with tight experimental control. Here, we revisit the typical spectral composition and statistical dependences of natural scenes, which distinguish them from abstract stimuli. We then demonstrate how to selectively degrade subtle statistical dependences within specific spatial scales using the wavelet transform. Such manipulations leave basic features of the stimuli, such as luminance and contrast, intact. Using functional neuroimaging of human participants viewing degraded natural images, we demonstrate that cortical responses at different levels of the visual hierarchy are differentially sensitive to subtle statistical dependences in natural images. This demonstration supports the notion that perceptual systems in the brain are optimally tuned to the complex statistical properties of the natural world. The code to undertake these stimulus manipulations, and their natural extension to dynamic natural scenes (films), is freely available.
机译:功能性神经影像学实验,采用自然刺激(自然场景,电影,口语叙述)在野外的认知功能中提供了洞察力。在丰富的多尺度结构中,天然刺激通常具有拥挤,光谱密集,动态和多模峰特性。然而,在使用自然刺激时,存在具有紧密实验控制的参数化操纵的各种挑战。在这里,我们重新审视自然场景的典型光谱组成和统计依赖性,这将它们与抽象刺激区分开来。然后,我们演示了如何在使用小波变换中选择性地降低特定的空间尺度内的细微统计依赖性。这种操纵留出刺激的基本特征,例如亮度和对比度,完好无损。使用人参与者的功能神经模仿观察降级的自然图像,我们证明了不同水平的视觉等级水平的皮质反应对自然图像中的微妙统计依赖性差异敏感。该示范支持概念,大脑中的感知系统最佳地调整到自然界的复杂统计特性。采取这些刺激操纵的代码及其对动态自然场景(电影)的自然延伸,可自由地提供。

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