Abstract
The neural basis of face recognition has been extensively investigated. Using functional magnetic resonance imaging, several regions have been identified in the human ventral visual stream that seem to be involved in processing and identifying faces, but the nature of face representations in these regions is not well known. In particular, multi-voxel pattern analyses (MVPA) have revealed distributed maps within these regions, but did not reveal the organizing principles of these maps. We isolated different types of perceptual and conceptual face properties to determine which properties are mapped in which regions. A set of faces was created with systematic manipulations of featural and configural visual characteristics. The face set consisted of 9 faces (one base face and 8 faces equally different from the base face), differing from each other in terms of featural information (with differences in eye colour, eyebrow thickness and lip thickness), and configural information (eyes apart or close together, mouth up or down). In a second part of the study, context information was added to most of the faces (a name, location and occupation). Data were analyzed by training linear support vector machines (SVMs) to classify multi-voxel pattern analyses. Maps in face-selective regions represented both configural and featural differences between faces. Fusiform and more anterior temporal face-selective patches also represented whether or not a face had been trained (associated with a background story), but could not distinguish between the two locations with which the faces were associated. In contrast, the non-face-selective parahippocampal place area represented which context information was associated with a face (differentiating between faces associated with the same or a different location). Together, these findings demonstrate how regions that are often treated as unitary modules contain distributed maps that have specific properties and that show a progression from purely visual maps to context-driven maps.
Meeting abstract presented at VSS 2013