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 visu al information (spatial frequencies, or SF) contribute to this fundamental brain function. Huma n 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 one minute. By ins erting highly variable natural face images as every 8 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, sugges ting that the brain can – at a single glance – discriminate vastly different faces from multiple u nsegmented object categories using only very coarse visual information. Local features (e.g., ey es) are not yet discernable at this threshold, indicating that fast face detection critically reli es on global facial configuration. Interestingly, t he face-selective neural response continued to increas e with additional higher SF content until saturation around >50 cycles/image, potentially sup porting higher-level recognition functions (e.g., facial identity recognition).