Ultra-coarse, single-glance human face detection in a dynamic visual stream

Effective human interaction depends on our ability to rapidly detect faces in dynamic visual environments. Here we asked how basic units of visual information (spatial frequencies, or SF) contribute to this fundamental brain function. Human observers viewed initially blurry, unrecognizable natural object images presented at a fast 12 Hz rate and parametrically increasing in SF content over the course of 1 minute. By inserting highly variable natural face images as every 8th stimulus, we captured an objective neural index of face detection in participants' electroencephalogram (EEG) at exactly 1.5 Hz. This face-selective signal emerged over the right occipito-temporal cortex at <5 cycles/image, suggesting that the brain can - at a single glance - discriminate vastly different faces from multiple unsegmented object categories using only very coarse visual information. Local features (e.g., eyes) are not yet discernable at this threshold, indicating that fast face detection critically relies on global facial configuration. Interestingly, the face-selective neural response continued to increase with additional higher SF content until saturation around > 50 cycles/image, potentially supporting higher-level recognition functions (e.g., facial identity recognition).