American Statistical Association New York City Metropolitan Area Chapter New York State Psychiatric Institute at Columbia University Medical Center Biostatistics Seminar

Most statistical analyses of fMRI data assume that the exact nature, timing and duration of the psychological processes being studied are known. However, in many areas of psychological inquiry (e.g. studies on memory, motivation, emotion and drug uptake), it is hard to specify this information a priori. In this talk, we discuss a spatio-temporal model that can be used to analyze this type of data. The approach allows for the estimation of voxel-specific distributions of onset times and durations from the fMRI response assuming no functional form (e.g., no assumed neural or hemodynamic response), and allowing for the possibility that some subjects may show no response. The distributions can be used to estimate the probability that a voxel is activated as a function of time, and to cluster voxels based on characteristics of their onset, duration, and anatomical location.

Martin Lindquist has a Ph.D. in statistics from Rutgers University and was a post-doctoral student at the Center for Magnetic Resonance Research (CMRR) at the University of Minnesota. He is currently an Associate Professor in the Department of Statistics at Columbia University. His research focuses on designing k-space sampling trajectories, image reconstruction and developing new statistical methods for the analysis of functional magnetic resonance imaging (fMRI) data.