Advances in brain imaging technology have given us the ability to observe the entire human brain in action. At the same time, great steps have been made in the development of computational algorithms that look for structure in massive amounts of data. My research interest at-large is combining these tools to understand how the brain is organized — from modules, to networks, to systems — so that it enables humans to perform a myriad of functions. In particular, I am interested in understanding the brain mechanisms at the basis of the cognitive-affective states that we routinely experience in our daily lives, and how these states are represented in the human brain.

Towards that goal, I perform functional MRI experiments allied with psychophysiological experiments, and employ various data analysis and machine learning techniques to attempt to unravel the brain mechanisms involved in the production and experience of emotions. Part of the challenge is to devise effective experiments to address these questions, given the limitations of the measurements we can perform, and the inherent difficulties involved in eliciting changes in cognitive-affective states in conditions that resemble real-life situations.

Emotions modulate decision making, and early affective experiences may to a large extent determine who we become in the future. Understanding the brain mechanisms that give rise to emotions in healthy people is relevant not only as a scientific endeavor but because it may shed light on the causes of affective disorders that afflict many adolescents and adults in the world.