Emotional reaction recognition from EEG

In this study we explore the application of pattern recognition models for recognizing emotional reactions elicited by videos from electroencephalography (EEG). We show that both the presence and magnitude of each emotion can be predicted above chance levels with up to 88% accuracy. Furthermore, we show that there are differences in classifiability for different emotions and participants, but whether a participant's data can be classified with respect to different emotions can itself be predicted from their EEG.