4.7 Article

Representational structure of fMRI/EEG responses to dynamic facial expressions

期刊

NEUROIMAGE
卷 263, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2022.119631

关键词

EEG; fMRI; RSA; Facial expression; Decoding; Face perception; Dynamic faces

资金

  1. Academy of Finland [298329]
  2. Academy of Finland (AKA) [298329, 298329] Funding Source: Academy of Finland (AKA)

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Face perception is an example of how the brain processes visual differences and represents identities and emotional expressions. This study investigates the neural processing of facial expressions using videos with varying intensity and category (happy, angry, surprised). The results show that different brain regions encode expression category and intensity differently, with IFG-FA playing a specific role in encoding expression intensity.
Face perception provides an excellent example of how the brain processes nuanced visual differences and trans-forms them into behaviourally useful representations of identities and emotional expressions. While a body of literature has looked into the spatial and temporal neural processing of facial expressions, few studies have used a dimensionally varying set of stimuli containing subtle perceptual changes. In the current study, we used 48 short videos varying dimensionally in their intensity and category (happy, angry, surprised) of expression. We measured both fMRI and EEG responses to these video clips and compared the neural response patterns to the predictions of models based on image features and models derived from behavioural ratings of the stimuli. In fMRI, the inferior frontal gyrus face area (IFG-FA) carried information related only to the intensity of the expres-sion, independent of image-based models. The superior temporal sulcus (STS), inferior temporal (IT) and lateral occipital (LO) areas contained information about both expression category and intensity. In the EEG, the coding of expression category and low-level image features were most pronounced at around 400 ms. The expression intensity model did not, however, correlate significantly at any EEG timepoint. Our results show a specific role for IFG-FA in the coding of expressions and suggest that it contains image and category invariant representations of expression intensity.

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