title: Identifying Emotions on the Basis of Neural Activation.
abstract: We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame) while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1) neural activation of the same individual in other trials, 2) neural activation of other individuals who experienced similar trials, and 3) neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing.
authors.affiliation: Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Karim S
authors.initials: KS
authors.lastname: Kassam
authors.forename: Amanda R
authors.initials: AR
authors.lastname: Markey
authors.forename: Vladimir L
authors.initials: VL
authors.lastname: Cherkassky
authors.forename: George
authors.initials: G
authors.lastname: Loewenstein
authors.forename: Marcel Adam
authors.initials: MA
authors.lastname: Just
mesh_terms: D001499:Bayes Theorem; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology; D004644:Emotions / Q000502:physiology*; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009474:Neurons / Q000502:physiology*; D055815:Young Adult