The fusiform face area is tuned for curvilinear patterns with more high-contrasted elements in the upper part

Caldara, R., Seghier, M. L., Rossion, B., Lazeyras, F., Michel, C. and Hauert, C.-A. (2006) The fusiform face area is tuned for curvilinear patterns with more high-contrasted elements in the upper part. NeuroImage, 31(1), pp. 313-319. (doi: 10.1016/j.neuroimage.2005.12.011) (PMID:6460963)

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Abstract

The ability to identify conspecifics from the face is of primary interest for human social behavior. Newborns' visual preference for schematic face-like stimuli has been recently related to a sensitivity for visual patterns with a greater number of elements in the upper compared to the lower part. At the adult level, neuroimaging studies have identified a network of cortical areas devoted to the detection and identification of faces. However, whether and how low-level structural properties of face stimuli contribute to the preferential response to faces in these areas remain to be clarified. Using functional magnetic resonance imaging (fMRI), here we investigated whether the adults' face-sensitive cortical areas show a preference for top-heavy patterns, similarly to newborns' preference. Twelve participants were presented with head-shaped and square patterns with either more elements in the upper or the lower vertical part. In the right fusiform gyrus (‘fusiform face area’, FFA), an area showing a preference for faces over other visual object categories, there was a larger activation for curvilinear patterns with more high-contrast elements in the upper part, even though these patterns were not perceived as face stimuli. These findings provide direct evidence that the FFA is tuned for geometrical properties fitting best with the structure of faces, a computational mechanism that might drive the automatic detection of faces in the visual world.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Caldara, Professor Roberto
Authors: Caldara, R., Seghier, M. L., Rossion, B., Lazeyras, F., Michel, C., and Hauert, C.-A.
College/School:College of Science and Engineering > School of Psychology
Journal Name:NeuroImage
Publisher:Elsevier
ISSN:1053-8119
ISSN (Online):1095-9572
Published Online:07 February 2006

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