Nicolas Davidenko, Ph.D. - US grants

[unreadable] DESCRIPTION (provided by applicant): The ability to recognize individual faces, despite their structural similarity, has been a focus of investigation for both neuroscientists and psychologists. Yet, there is no current unified account of face representation that combines the knowledge from these two disciplines. Functional magnetic resonance imaging (fMRI) has identified a region in the fusiform gyrus (the FFA) that responds preferentially to faces, but the neural mechanism by which individual faces are encoded is still unknown. Several behavioral phenomena have inspired "norm-based" models efface representation, where faces are coded as deviations from a norm, or prototype face. Until recently, the lack of a method for properly defining this norm and similarity relationships among faces has made it difficult to determine the neural basis of face representation. We propose a multidisciplinary approach combining the use of a new behaviorally validated face parameterization that affords these capabilities, high-resolution fMRI (HR-fMRI), and fMRI-adaptation, to parametrically probe the neural basis efface representation, addressing the following aims: - Aim 1: What is the response sensitivity of face-selective regions to the range of human faces? Using our parameterized model and HR-fMRI, we will characterize face-selectivity to a wide range of human face stimuli, expecting that typical faces will elicit the most activity, and distinctive faces the least. - Aim 2: How does the response sensitivity of face-selective regions change as a result of experience? Using a perceptual adaptation paradigm, we will induce face aftereffects that change the apparent distinctiveness of subsequently viewed faces. We predict that face-selective regions will respond more strongly to the same face when it is perceived as more typical than when it is perceived as more distinctive. - Aim 3: How sensitive are face-selective responses to changes in face similarity and gender? By parametrically manipulating similarity and measuring fMRI-adaptation, we will test the prediction that FFA is sensitive to face similarity and category, but other object-selective areas are only sensitive to similarity. [unreadable] [unreadable] [unreadable]

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Characterizing face representations in the ventral stream: effects of physical variability and distance from the average face fMRI research has identified regions in the human fusiform gyrus (FFA) and inferior occipital gyrus (IOG) that respond selectively to faces, but the mechanisms by which neurons in these regions represent different faces is highly debated. A prominent view posits that face-selective neurons employ a norm-based representation, responding more strongly to distinctive faces that deviate from the average face in particular directions in face space. However, in humans, evidence for this view is based on block-design fMRI experiments in which the within-block physical variability of face stimuli is not controlled across different blocks. If blocks of distinctive faces also contain more physically variable faces than blocks of typical faces, a larger BOLD response to distinctive blocks may indicate less adaptation during these high-variability blocks rather than preferential tuning to distinctive faces. To read about other projects ongoing at the Lucas Center, please visit http://rsl.stanford.edu/ (Lucas Annual Report and ISMRM 2011 Abstracts)