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 50 cycles/image, potentially supporting higher-level recognition functions (e.g., facial identity recognition). •We aim to define the minimal spatial frequency (SF) content for face detection.•Naturalistic faces appear at strict periodic intervals in a rapid stream of objects.•SF content of images increases gradually over 1 min (blurry → clear).•Neural face detection response arises on the basis of very coarse SF information.•Global face configuration, not local features, drives face/object categorization.