Abstract
Recognizing a familiar face across widely variable natural images is a fundamental ability for us humans (Burton & Jenkins, 2011). Yet, it is difficult to capture this process reliably, without an explicit behavioural task. Here we designed a fast and automatic approach that required both discriminating highly familiar from unfamiliar faces and generalizing across different images of the same individual face. We recorded high-density electroencephalogram (EEG) at 6 Hz during brief 70 sec sequences of fast periodic visual stimulation (FPVS). During stimulation, unfamiliar faces were presented at 6Hz (base) with familiar (here famous) faces appearing as every 7th image at a stimulation rate of 0.86 Hz. Images showed faces across naturally occurring changes in view, expression or visual appearance. Throughout each sequence, base face identity varied at every stimulation cycle while the 0.86 Hz periodic famous identity stayed the same. Stimulation sequences were also shown at inverted orientation. Clear visual discrimination responses emerged to periodic presentations of the same familiar face over occipito-temporal electrodes. Importantly, familiarity responses were markedly reduced on inverted sequences, ruling out a low-level account. These findings indicate that the human brain can implicitly discriminate familiar from unfamiliar faces at a glance, and generalize across wide image variability. Our data demonstrate that FPVS-EEG is a highly sensitive tool to characterize rapid invariant familiar face recognition in the human brain.
Meeting abstract presented at VSS 2017