Quantitative Personality Predictions From a Brief EEG Recording

The assessment of personality is crucial not only for scientific inquiries but also for real-world applications such as personnel selection. In this article, we propose and validate a novel implicit measure to predict an individual's levels in the Big Five personality traits from 5 minutes of electroencephalography (EEG) recordings. Participants viewed Chinese words with positive, negative, and neutral emotions. The multi-channel event-related potentials elicited by these emotional words were used to train a sparse regression model for personality prediction. Results from a large test sample of 196 participants indicated that the personality scores derived from the proposed measure reached significant correlations with a commonly used questionnaire (r = .50, .60, .49, .55, and .49 for agreeableness, conscientiousness, neuroticism, openness, and extraversion, respectively). The EEG-based personality scores showed good external validity as well, capable of predicting behavioral indices and psychological adjustment similar to self-reported scores. Besides, the EEG-based scores were relatively stable across time, as reflected by the test-retest reliability of .5 ∼ .7 for the five personality traits within a cohort of 33 participants 19-78 days later. These evaluations suggest that the proposed measure can serve as a viable alternative to conventional personality questionnaires in practice.