This research will use behavioral, brain imaging, and computational modelling techniques to investigate the neural bases and mechanisms of human cognitive control. A powerful method for elucidating cognitive mechanisms is to tax cognitive processing to the point at which some aspect of its underlying structure is revealed. Here, we use normal emotion as a methodological technique for challenging cognitive processing. This approach might be especially informative because normal emotion has specific influences on self-regulation and control.
In behavioral and brain imaging studies, we will test predictions of the computational model under two related but distinct types of emotional challenge: induced emotional states, and the delivery of unexpected rewards. Human participants will perform various cognitive tasks either while in emotional states or while receiving unexpected rewards. Using functional magnetic resonance imaging (fMRI), we will identify areas of the brain that are not only critical for cognitive control but also are sensitive to modulation by emotion and reward. We will then perform computer simulations to test whether the model can capture detailed aspects of the behavioral and brain imaging data.
These studies will further scientific knowledge by both testing and extending an existing theory of cognitive control. In particular, it will help refine how our under-standing of specific brain regions (i.e., the prefrontal cortex) might mediate cognitive control, and how normal emotion influences those control systems. This work could enhance our understanding of human performance, and lead to improved techniques for optimizing performance using emotion. In addition, these studies could provide another step toward a detailed understanding of the normal interactions between cognition and emotion. This could be of practical value in helping to understand mental disorders such as depression, anxiety, and drug addiction.
