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Corentin Jacques, Bruno Rossion; The contribution of Fourier amplitude spectrum differences to the early electrophysiological (i.e. P1) amplitude difference between face and nonface object categories. Journal of Vision 2010;10(7):662. doi: https://doi.org/10.1167/10.7.662.
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© ARVO (1962-2015); The Authors (2016-present)
Event-related potential (ERP) studies in humans indicate that the early activation of visual face representations in the human brain takes place during the time-window of the occipito-temporal N170 component. Similarly to the N170, the P1 visual component preceding the N170 has also been reported as being larger in response to face compared to nonface stimuli. This observation has been taken by some authors as evidence for an early sensitivity to faces in the visual cortex at around 100 ms. However, because the P1 component is highly sensitive to manipulations of the spatial frequency content of an image, part of the P1 amplitude difference between faces and nonfaces may be related to differences between the Fourier amplitude spectrums (FAS, a parameter that conveys the global low-level statistics of an image) of these categories. To identify the contribution of the FAS to the P1 amplitude difference between face and nonface stimuli we recorded ERPs while subjects viewed faces and cars either in their original unaltered version or in a version in which the Fourier phase information of one category was combined with the FAS of the other category. When presented in their original version, faces elicited a larger P1 compared to cars, in line with previous observations. This effect was most consistent over the right hemisphere occipito-temporal electrodes. In contrast, switching the FAS between faces and cars resulted in a larger P1 for cars, again mainly over the right occipito-temporal electrodes. These findings suggest that the P1 amplitude difference between face and nonface stimuli are, at least partly, related to differences in the FAS between these categories. Moreover, even though these P1 differences do not reflect face categorization per se, they may nevertheless reflect the use of lower-level visual statistic frequently associated with a human face to allow fast basic-level face categorization.
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