For the first time, scientists at Carnegie Mellon University have identified which emotion a person is experiencing based on brain activity.
The study combines functional magnetic resonance imaging and machine learning to measure brain signals to accurately read emotions in individuals. The findings illustrate how the brain categorizes feelings, giving researchers the first reliable process to analyze emotions. Until now, research on emotions has been long stymied by the lack of reliable methods to evaluate them, mostly because people are often reluctant to honestly report their feelings. Further complicating matters is that many emotional responses may not be consciously experienced.
Identifying emotions based on neural activity builds on previous discoveries by CMU's Marcel Just and Tom M. Mitchell, which used similar techniques to create a computational model that identifies individuals' thoughts of concrete objects, often dubbed "mind reading."