Reverse Correlation Mapping in V2 and V4

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DESCRIPTION (provided by applicant): The project goal is to explore the functional anatomy and mechanisms of face detection and recognition. Faces are a complex yet highly constrained subset of all possible visual shapes. Face-selective regions in the temporal lobe have been identified using functional magnetic resonance imaging (fMRI) as showing increased blood flow in response to visual stimulation with faces as opposed to images of other objects. MRI can therefore be used to target single-unit recording to these face-selective regions. The ability to specifically target fMRI-identified face patches for single-unit recording provides an unprecedented opportunity to record repeatedly from areas of temporal cortex entirely selective for faces. One bilateral set of face patches is in the lower bank of the superior temporal sulcus and likely corresponds to the human fusiform face area (FFA). This laboratory has successfully targeted single-unit recording to this face patch in two subjects, and in this region almost all (98%) of the single units recorded so far have shown strong response selectivity for faces. Single-unit electrophysiology and fMRI will be used in parallel and in conjunction to explore the functional specialization in the face-selective regions of the temporal lobe and the hierarchical organization of face processing, in particular whether distinct regions are dedicated to processing specific aspects of faces, such as emotional expression, view angle, or gaze direction. Single-unit reverse correlation mapping and fMRI will be used to map selectivity to large sets of faces varying in view angle, position, scale, illumination, and expression to explore the development of invariant coding along the face-processing hierarchy. Reverse-correlation mapping will be used to map selectivity for multiple facial features in a parameterized artificial-face space to determine how features are combined in these areas to generate face-selective response properties from simpler features or feature constellations. Face recognition is one of the most important aspects both socially and developmentally of higher-level visual processing. Understanding how the brain carries out such a complex yet specific process as face recognition will yield insights into human cognition as well as into neurological and psychiatric conditions in which face recognition is impaired, such as prosopagnosia, schizophrenia, and autism.