Jeremy Purcell (MNC)

Title: Using fMRI to Quantify Increased Differentiation of Neural Representations Due to Learning

Abstract: Indexing and tracking learning induced neural changes via neuroimaging methods such as fMRI can provide a valuable tool for understanding how the brain learns new information. In this talk, I will discuss a novel approach to quantifying differentiation of local neural representations via functional Magnetic Resonance Imaging (fMRI). This approach termed Local-Heterogeneity Regression (Local-Hreg) essentially applies long-distance functional connectivity approaches to probe local neural dynamics.  I will introduce this approach within the context of a study of neurotypical adults in reading, and then present its application in a longitudinal study of language recovery in acquired dysgraphia due to stroke. Although this work is of specific interest to the study of the neural basis of written language recovery, I argue that the application of this approach (Local-Hreg) is of more general interest in that it can potentially be used to index and track learning in a variety of cognitive domains and populations. 

Jeremy Purcell is a Faculty Research Scientist at the Maryland Neuroimaging Center whose research focuses on how the mind represents written language, the nature of spares neural representations, and on neuroimaging research tool building.