Representational structure of fMRI/EEG responses to dynamic facial expressions
Face perception provides an excellent example of how the brain processes nuanced visual differences and transforms 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 e...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-11-01
|
| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811922007467 |
| _version_ | 1811192601416564736 |
|---|---|
| author | I. Muukkonen V.R. Salmela |
| author_facet | I. Muukkonen V.R. Salmela |
| author_sort | I. Muukkonen |
| collection | DOAJ |
| description | Face perception provides an excellent example of how the brain processes nuanced visual differences and transforms 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 expression, 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. |
| first_indexed | 2024-04-11T23:55:07Z |
| format | Article |
| id | doaj.art-6fd4c86bf12d45dba1b0addc2321e528 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-04-11T23:55:07Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-6fd4c86bf12d45dba1b0addc2321e5282022-12-22T03:56:23ZengElsevierNeuroImage1095-95722022-11-01263119631Representational structure of fMRI/EEG responses to dynamic facial expressionsI. Muukkonen0V.R. Salmela1Department of Psychology and Logopedics, University of Helsinki, FinlandCorresponding author.; Department of Psychology and Logopedics, University of Helsinki, FinlandFace perception provides an excellent example of how the brain processes nuanced visual differences and transforms 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 expression, 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.http://www.sciencedirect.com/science/article/pii/S1053811922007467EEGfMRIRSAFacial expressionDecodingFace perception |
| spellingShingle | I. Muukkonen V.R. Salmela Representational structure of fMRI/EEG responses to dynamic facial expressions NeuroImage EEG fMRI RSA Facial expression Decoding Face perception |
| title | Representational structure of fMRI/EEG responses to dynamic facial expressions |
| title_full | Representational structure of fMRI/EEG responses to dynamic facial expressions |
| title_fullStr | Representational structure of fMRI/EEG responses to dynamic facial expressions |
| title_full_unstemmed | Representational structure of fMRI/EEG responses to dynamic facial expressions |
| title_short | Representational structure of fMRI/EEG responses to dynamic facial expressions |
| title_sort | representational structure of fmri eeg responses to dynamic facial expressions |
| topic | EEG fMRI RSA Facial expression Decoding Face perception |
| url | http://www.sciencedirect.com/science/article/pii/S1053811922007467 |
| work_keys_str_mv | AT imuukkonen representationalstructureoffmrieegresponsestodynamicfacialexpressions AT vrsalmela representationalstructureoffmrieegresponsestodynamicfacialexpressions |