| Literature DB >> 25924952 |
Heini Saarimäki1,2, Athanasios Gotsopoulos1, Iiro P Jääskeläinen1, Jouko Lampinen1, Patrik Vuilleumier3,4, Riitta Hari1, Mikko Sams1, Lauri Nummenmaa1,5.
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.Entities:
Keywords: MVPA; emotion; fMRI; pattern classification
Mesh:
Year: 2015 PMID: 25924952 DOI: 10.1093/cercor/bhv086
Source DB: PubMed Journal: Cereb Cortex ISSN: 1047-3211 Impact factor: 5.357