Abstract

This study aimed to identify the neurophysiological correlates of two primary aroused affective states related to positive and negative emotions, and to create a classification model for each second of data. General and individualized models were built on the EEG data recorded from 98 participants while watching two contrasting ~20 min videos – one to elicit a negative affective state, and the other to induce positive affect. The final models were cross-validated on an additional 63 participants and the classifiers achieved similar results. The classifiers’ generalization capability was further estimated in a related study where 63 participants returned to watch videos that incorporated narratives with varying levels of fairness, justice, and character identification.