Neuroimaging research in our laboratory uses functional magnetic resonance imaging (fMRI) to study the mechanisms underlying decision making. To better understand this neuroimaging technique and its limitations, we have published studies on the basic properties of the hemodynamic response measured by fMRI. Properties investigated by our laboratory have included refractory effects associated with repeated stimulus presentation, stimulus-specific adaptation effects, differences in the hemodynamic response across individuals and subject groups, effects of signal-to-noise upon the reproducibility of activation, and the relation between fMRI activation and intracranially recorded activity. Some studies use pattern classification algorithms derived from machine learning (e.g., support vector machines, SVM) to identify local information carried across voxels within a brain region. We also apply functional connectivity techniques to understand large-scale networks in the brain — and how those networks contribute to behavior.
Finally, we explore major issues in neuroimaging research through review articles, meta-analyses, and our textbook Functional Magnetic Resonance Imaging (3nd edition published in 2014).