MedicalResearch.com Interview with:
Kevin S. LaBar, Ph.D.
Professor and Head, Cognition & Cognitive Neuroscience Program
Co-Director of Undergraduate Studies in Neuroscience
Center for Cognitive Neuroscience
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Emotion research is limited by a lack of objective markers of emotional states. Most human research relies on self-report, but individuals may not have good insight into their own emotions. We have developed a new way to identify emotional states using brain imaging and machine learning tools. First, we induced emotional states using film and music clips while individuals were in an MRI scanner. We trained a computer algorithm to identify the brain areas that distinguished 7 emotions from each other (fear, anger, surprise, sadness, amusement, contentment, and a neutral state). This procedure created a brain map for each of the 7 emotions. Then, a new group of participants self-reported their emotional state every 30 seconds in an MRI scanner while no stimuli were presented. We could predict which emotion was spontaneously reported by the subjects by comparing their brain scans to each of the 7 emotion maps. Finally, in a large group of 499 subjects, we found that the presence of the fear map during rest predicted state and trait anxiety while the presence of the sadness map predicted state and trait depression.