Understanding individual face discrimination by means of fast periodic visual stimulation
- PMID: 24728131
- DOI: 10.1007/s00221-014-3934-9
Understanding individual face discrimination by means of fast periodic visual stimulation
Abstract
This paper reviews a fast periodic visual stimulation (FPVS) approach developed recently to make significant progress in understanding visual discrimination of individual faces. Displaying pictures of faces at a periodic frequency rate leads to a high signal-to-noise ratio (SNR) response in the human electroencephalogram, at the exact frequency of stimulation, a so-called steady-state visual evoked potential (SSVEP, Regan in Electroencephalogr Clin Neurophysiol 20:238-248, 1966). For fast periodic frequency rates, i.e., between 3 and 9 Hz, this response is reduced if the exact same face identity is repeated compared to the presentation of different face identities, the largest difference being observed over the right occipito-temporal cortex. A 6-Hz stimulation rate (cycle duration of ~170 ms) provides the largest difference between different and repeated faces, as also evidenced in face-selective areas of the ventral occipito-temporal cortex in functional magnetic resonance imaging. This high-level discrimination response is reduced following inversion and contrast-reversal of the faces and can be isolated without subtraction thanks to a fast periodic oddball paradigm. Overall, FPVS provides a response that is objective (i.e., at an experimentally defined frequency), implicit, has a high SNR and is directly quantifiable in a short amount of time. Although the approach is particularly appealing for understanding face perception, it can be generalized to study visual discrimination of complex visual patterns such as objects and visual scenes. The advantages of the approach make it also particularly well-suited to investigate these functions in populations who cannot provide overt behavioral responses and can only be tested for short durations, such as infants, young children and clinical populations.
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