fMRI Brown Bag: November 12

Please join us for a talk given by Phil Kragel, post-doc and research associate, Institute of Cognitive Science, UC-Boulder.

Understanding emotions as distributed brain representations

Abstract:

Emotion is central to human experience; it influences cognition, behavior, health, and well-being. Despite their importance and self-evidence, emotions are notoriously difficult to define scientifically. The recent integration of non-invasive imaging and machine learning approaches allows for subjective emotional experiences to be objectively mapped onto brain activity in humans, paving the way for a better understanding of how brain activity produces emotional behavior. In this talk, I will present research combining ideas from psychology, neuroscience, and machine learning to build models of human brain activity that track the engagement of distinct affective processes. I will discuss fMRI research exploring how emotional states can be identified by distributed patterns of human brain activity, how these patterns can predict spontaneous variation in emotional states and traits across individuals, and how neural network models can be used to understand how the brain detects emotional situations. Finally, I will describe how these computational approaches can be used to advance emotion theory, and to provide novels targets for cognitive and therapeutic interventions.