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

被引:43
|
作者
Caldara, Roberto
Seghier, Mohamed L.
Rossion, Bruno
Lazeyras, Francois
Michel, Christoph
Hauert, Claude-Alain
机构
[1] Univ Glasgow, Ctr Cognit Neuroimaging, Dept Psychol, Glasgow G12 8QB, Lanark, Scotland
[2] Univ Hosp Geneva, Dept Radiol, Geneva, Switzerland
[3] Univ Louvain, Unite Cognit & Dev, B-3001 Louvain, Belgium
[4] Univ Louvain, Neurophysiol Lab, B-3001 Louvain, Belgium
[5] Univ Geneva, Fac Med, Geneva, Switzerland
[6] Univ Geneva, Fac Psychol, Geneva, Switzerland
关键词
functional magnetic resonance imaging; face recognition; fusiform gyrus;
D O I
10.1016/j.neuroimage.2005.12.011
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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 gyros ('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. (c) 2005 Elsevier Inc. All rights reserved.
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页码:313 / 319
页数:7
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