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中层次特征差异支持早期的生命性和物体大小区分:来自脑电图解码的证据。

Mid-level Feature Differences Support Early Animacy and Object Size Distinctions: Evidence from Electroencephalography Decoding.

机构信息

Harvard University.

出版信息

J Cogn Neurosci. 2022 Aug 1;34(9):1670-1680. doi: 10.1162/jocn_a_01883.

DOI:10.1162/jocn_a_01883
PMID:35704550
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9438936/
Abstract

Responses to visually presented objects along the cortical surface of the human brain have a large-scale organization reflecting the broad categorical divisions of animacy and object size. Emerging evidence indicates that this topographical organization is supported by differences between objects in mid-level perceptual features. With regard to the timing of neural responses, images of objects quickly evoke neural responses with decodable information about animacy and object size, but are mid-level features sufficient to evoke these rapid neural responses? Or is slower iterative neural processing required to untangle information about animacy and object size from mid-level features, requiring hundreds of milliseconds more processing time? To answer this question, we used EEG to measure human neural responses to images of objects and their texform counterparts-unrecognizable images that preserve some mid-level feature information about texture and coarse form. We found that texform images evoked neural responses with early decodable information about both animacy and real-world size, as early as responses evoked by original images. Furthermore, successful cross-decoding indicates that both texform and original images evoke information about animacy and size through a common underlying neural basis. Broadly, these results indicate that the visual system contains a mid-level feature bank carrying linearly decodable information on animacy and size, which can be rapidly activated without requiring explicit recognition or protracted temporal processing.

摘要

大脑皮质表面对视觉呈现的物体的反应具有大规模的组织,反映了生物性和物体大小的广泛分类划分。新出现的证据表明,这种地形组织是由物体在中等水平感知特征上的差异所支持的。关于神经反应的时间,物体的图像会迅速引发可解码的关于生物性和物体大小的神经反应,但中等水平的特征是否足以引发这些快速的神经反应?或者需要更慢的迭代神经处理来从中等水平的特征中梳理出关于生物性和物体大小的信息,需要再多几百毫秒的处理时间?为了回答这个问题,我们使用 EEG 测量了人类对物体图像及其 texform 对应物(不可识别的图像,保留了一些关于纹理和粗略形状的中等水平特征信息)的神经反应。我们发现,texform 图像引发了关于生物性和真实世界大小的早期可解码神经反应,早在原始图像引发的反应之前。此外,成功的交叉解码表明,texform 和原始图像都通过一个共同的潜在神经基础来引发关于生物性和大小的信息。总的来说,这些结果表明,视觉系统包含一个中等水平的特征库,其中包含关于生物性和大小的线性可解码信息,可以在不需要明确识别或长时间处理的情况下快速激活。

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