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自动人脸识别是否依赖于头部朝向?

Does automatic human face categorization depend on head orientation?

机构信息

Division of Psychology, School of Social Sciences, Nanyang Technological University, Singapore; Psychological Sciences Research Institute & Institute of Neuroscience, University of Louvain, Belgium.

Psychological Sciences Research Institute & Institute of Neuroscience, University of Louvain, Belgium; Department of Behavioural and Cognitive Sciences, Institute of Cognitive Science & Assessment, University of Luxembourg, Luxembourg.

出版信息

Cortex. 2021 Aug;141:94-111. doi: 10.1016/j.cortex.2021.03.030. Epub 2021 Apr 27.

DOI:10.1016/j.cortex.2021.03.030
PMID:34049256
Abstract

Whether human categorization of visual stimuli as faces is optimal for full-front views, best revealing diagnostic features but lacking depth cues, remains largely unknown. To address this question, we presented 16 human observers with unsegmented natural images of different living and non-living objects at a fast rate (f = 12 Hz), with natural face images appearing at f/9 = 1.33 Hz. Faces posing all full-front or at ¾ side view angles appeared in separate sequences. Robust frequency-tagged 1.33 Hz (and harmonic) occipito-temporal electroencephalographic (EEG) responses reflecting face-selective neural activity did not differ in overall amplitude between full-front and ¾ side views. Despite this, alternating between full-front and ¾ side views within a sequence led to significant responses at specific harmonics of .67 Hz (f/18), objectively isolating view-dependent face-selective responses over occipito-temporal regions. Critically, a time-domain analysis showed that these view-dependent face-selective responses reflected only an earlier response to full-front than ¾ side views by 8-13 ms. Overall, these findings indicate that the face-selective neural representation is as robust for ¾ side faces as for full-front faces in the human brain, but full-front views provide a slightly earlier processing-time advantage as compared to rotated face views.

摘要

人类对视觉刺激进行分类,将其归类为面部,这种分类方式是否最适合完全正面视角,从而最大限度地揭示诊断特征,但缺乏深度线索,目前还知之甚少。为了解决这个问题,我们以 12 赫兹(Hz)的快速速率向 16 名人类观察者呈现不同的生活和非生活物体的未分割自然图像,其中自然面部图像以 1.33 Hz(f/9=1.33 Hz)的频率出现。完全正面或 3/4 侧面视角的面部以单独的序列出现。反映面部选择性神经活动的稳健的、以频率标记的 1.33 Hz(和 1.33 Hz 的谐波)枕颞部脑电图(EEG)响应,在整体幅度上,在完全正面视角和 3/4 侧面视角之间没有差异。尽管如此,在序列中交替出现完全正面视角和 3/4 侧面视角会导致在特定的.67 Hz(f/18)谐波处产生显著的响应,客观上在枕颞区域分离出依赖于视角的面部选择性响应。至关重要的是,时域分析表明,这些依赖于视角的面部选择性响应仅反映了与 3/4 侧面视角相比,人类大脑中对完全正面视角的响应更早,早 8-13 毫秒。总的来说,这些发现表明,在人类大脑中,3/4 侧面的面部与完全正面的面部一样,具有强大的面部选择性神经表示,但与旋转的面部视图相比,完全正面的视图提供了稍微提前的处理时间优势。

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引用本文的文献

1
Natural Contrast Statistics Facilitate Human Face Categorization.自然对比度统计有助于人类面孔分类。
eNeuro. 2022 Oct 6;9(5). doi: 10.1523/ENEURO.0420-21.2022. Print 2022 Sep-Oct.