Discrete neural signatures of basic emotions

Heini Saarimäki*, Athanasios Gotsopoulos, Iiro P. Jääskeläinen, Jouko Lampinen, Patrik Vuilleumier, Riitta Hari, Mikko Sams, Lauri Nummenmaa

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

164 Citations (Scopus)

Abstract

Categorical models of emotions posit neurally and physiologically distinct human basic emotions. We tested this assumption by using multivariate pattern analysis (MVPA) to classify brain activity patterns of 6 basic emotions (disgust, fear, happiness, sadness, anger, and surprise) in 3 experiments. Emotions were induced with short movies or mental imagery during functional magnetic resonance imaging. MVPA accurately classified emotions induced by both methods, and the classification generalized from one induction condition to another and across individuals. Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex. Thus, specific neural signatures across these regions hold representations of different emotional states in multimodal fashion, independently of how the emotions are induced. Similarity of subjective experiences between emotions was associated with similarity of neural patterns for the same emotions, suggesting a direct link between activity in these brain regions and the subjective emotional experience.

Original languageEnglish
Pages (from-to)2563-2573
Number of pages11
JournalCerebral Cortex
Volume26
Issue number6
Early online date2015
DOIs
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Emotion
  • FMRI
  • MVPA
  • Pattern classification

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