Our research investigates the computational and neural mechanisms underlying cognitive control, decision making and learning. In order to answer fundamental questions regarding the architecture of the brain, we develop computational models characterizing the interaction of brain regions implicated in the acquisition and execution of complex cognitive tasks. Our models integrate empirical findings from different methodologies (single-unit neurophysiology, EEG, fMRI, and behavioral) and different perspectives (cognitive, affective, and clinical neuroscience) to derive quantifiable predictions regarding the function of the brain. We test these predictions using a variety of methods, including behavioral studies, fMRI (univariate, model-based, and multi-voxel pattern analysis), and EEG. Our goal is to develop a neural blueprint detailing the structure and function of networks supporting sophisticated cognitive behavior.