fMRI and machine learning identify emotions


Carnegie Mellon researchers have developed “a new method with the potential to identify emotions without relying on people’s ability to self-report” using a combination of fMRI and machine learning.

They recruited 10 actors from the university’s drama school to act out emotions including anger, happiness, pride and shame, while inside an fMRI scanner,  multiple times in random order.  To ensure that researchers were able to measure actual emotions and not just the acting out of emotions, participants viewed emotion-eliciting images while undergoing fMRI scans.

The findings illustrate how the brain categorizes feelings, giving researchers the first reliable process to analyze emotions.  Emotion research has been difficult because of a lack of reliable evaluation methods, caused by a subject’s reluctance to honestly report feelings and the potential of emotional responses not being consciously experienced. Researchers plan to apply this new identification method to a number of problems, including identifying emotions that individuals are attempting to suppress and multiple emotions experienced simultaneously.

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