Jennifer Marie Davie Yoon, Ph.D. - US grants

DESCRIPTION (provided by applicant): Faces are a rich source of information, offering a window to identity, ethnicity, age, gender, and changing mental and emotional states. Recognizing this facial information is critical for social interaction and is atypical in developmental disorders of social communication such as autism and Williams Syndrome. The processing involved in decoding facial information is thought to depend on a network of core perceptual face processing regions in the brain (e.g., Haxby, 2000;Johnson 2005) that undergo prolonged maturation well into adolescence (Golarai et al, 2007, 2008;Grill-Spector et al, 2008). However, little is known about the anatomical pattern of connectivity of the core perceptual face processing network or about the typical developmental timecourse of these connections. I propose to combine advanced neuroimaging methods to characterize the pattern of anatomical connections that define the network for face processing in the typically-developing brain from 7 years of age through adulthood. This study will be the first to provide estimates of the likelihood and strength of connectivity between core face-selective regions in human children and adults. In the same subjects, I will also collect behavioral measurements of face recognition (identity, expression). This will allow me to relate quantitative measures of structural properties of likely white matter connections between face processing regions with the degree of gray matter face-selectivity at the neurophysiological level, and face recognition performance at the behavioral level. By charting the typical developmental timecourse of white matter connections, this research is a critical prerequisite for understanding how the structural organization of the face processing network is disturbed in developmental disorders of social information processing such as autism and Williams Syndrome. Understanding the timecourse of typical development in the specific white matter connections important for face processing may help to identify time windows and targets for treatment interventions.