Face recognition is one of the most complex functions of the human mind/brain, so that no artificial device can surpass human abilities in this function. The goal of this project is to understand a fundamental aspect of face recognition, individual face perception: how, from sensory information, does the human mind/brain build a visual representation of a particular face? To clarify this question, I will introduce the method of steady-state visual evoked potentials (SSVEPs) in the field of face perception. This approach has never been applied to face perception, but we recently started using it and collected strong data demonstrating the feasibility of the approach. It is based on the repetitive stimulation of the visual system at a fixed frequency rate, and the recording on the human scalp of an electrical response (electroencephalogram, EEG) that oscillates at that specific frequency rate. Because of its extremely high signal-to-noise ratio and its non-ambiguity with respect to the measurement of the signal of interest, this method is ideal to assess the human brain’s sensitivity to facial identity, non-invasively, and with the exact same approach in normal adults, infants and children, as well as clinical populations. SSVEP will also allow “tagging” different features of a stimulus with different stimulation frequencies (“frequency-tagging” method), and thus measure the representation and processing of these features independently, as well as their potential integration. Overall, this proposal should shed light on understanding one of the most complex function of the human mind/brain, while its realization will undoubtedly generate relevant data and paradigms useful for understanding other aspects of face processing (e.g., perception of facial expression) and high-level visual perception processes in general.