At what level of spatial resolution can the human brain recognize a familiar face in a crowd of strangers? Does it depend on whether one approaches or rather moves back from the crowd? To answer these questions, 16 observers viewed different unsegmented images of unfamiliar faces alternating at 6 Hz, with spatial frequency (SF) content progressively increasing (i.e., coarse-to-fine) or decreasing (fine-to-coarse) in different sequences. Variable natural images of celebrity faces every sixth stimulus generated an objective neural index of single-glanced automatic familiar face recognition (FFR) at 1 Hz in participants’ electroencephalogram (EEG). For blurry images increasing in spatial resolution, the neural FFR response over occipitotemporal regions emerged abruptly with additional cues at about 6.3–8.7 cycles/head width, immediately reaching amplitude saturation. When the same images progressively decreased in resolution, the FFR response disappeared already below 12 cycles/head width, thus providing no support for a predictive coding hypothesis. Overall, these observations indicate that rapid automatic recognition of heterogenous natural views of familiar faces is achieved from coarser visual inputs than generally thought, and support a coarse-to-fine FFR dynamics in the human brain.

中文翻译：

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人脑中从粗到精（r）的自动熟悉人脸识别

人脑可以在多大的空间分辨率下识别出一群陌生人中熟悉的面孔？这是否取决于一个人是接近还是远离人群？为了回答这些问题，16 名观察者以 6 Hz 的频率交替观察了不熟悉面孔的不同未分割图像，空间频率 (SF) 内容在不同序列中逐渐增加（即从粗到细）或减少（从细到粗）。在参与者的脑电图 (EEG) 中，每六次刺激产生的名人面孔的可变自然图像以 1 Hz 的频率生成单眼自动熟悉面孔识别 (FFR) 的客观神经指数。对于空间分辨率增加的模糊图像，枕颞区域的神经 FFR 反应突然出现，额外的线索约为 6.3-8.7 个周期/头部宽度，立即达到幅度饱和。当相同图像的分辨率逐渐降低时，FFR 响应在 12 个周期/头宽以下已经消失，因此不支持预测编码假设。总体而言，这些观察表明，熟悉面孔的异质自然视图的快速自动识别是通过比通常认为的更粗略的视觉输入实现的，并支持人脑中从粗到细的 FFR 动态。