Associate Professor, Cognitive Neuroscience; Affiliated Faculty: Neuroscience Institute and Mind-Brain Institute
A key goal of cognitive neuroscience is to understand the relationship between neuroanatomy (i.e. connectivity and local circuitry), experience, and neural representations. I study this relationship in using many techniques with an emphasis on human fMRI and behavior. I utilize a data-driven approach paired with many conditions allowing for the data-driven quantification of the structure of neural representations. I apply this approach in a number of domains including visual object recognition, the representation of words, concepts, and scenes, mental imagery, and working memory. I also study patient populations with deficits in these processes resulting from either brain damage or disorder (e.g. autism). Ultimately, achieving convergence between data gained from studying animals, humans, and patient populations with a variety of methods is the only way to overcome the inherent limitations of any method of studying the brain of living, behaving organisms.
Ph.D. 2006, Carnegie Mellon University