The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Supramodal Representations of Perceived Emotions in the Human Brain
Open accessAbstract
Basic emotional states (such as anger, fear, and joy) can be similarly conveyed by the face, the body, and the voice. Are there human brain regions that represent these emotional mental states regardless of the sensory cues from which they are perceived? To address this question, in the present study participants evaluated the intensity of emotions perceived from face movements, body movements, or vocal intonations, while their brain activity was measured with functional magnetic resonance imaging (fMRI). Using multivoxel pattern analysis, we compared the similarity of response patterns across modalities to test for brain regions in which emotion-specific patterns in one modality (e.g., faces) could predict emotion-specific patterns in another modality (e.g., bodies). A whole-brain searchlight analysis revealed modality-independent but emotion category-specific activity patterns in medial prefrontal cortex (MPFC) and left superior temporal sulcus (STS). Multivoxel patterns in these regions contained information about the category of the perceived emotions (anger, disgust, fear, happiness, sadness) across all modality comparisons (face–body, face–voice, body–voice), and independently of the perceived intensity of the emotions. No systematic emotion-related differences were observed in the overall amplitude of activation in MPFC or STS. These results reveal supramodal representations of emotions in high-level brain areas previously implicated in affective processing, mental state attribution, and theory-of-mind. We suggest that MPFC and STS represent perceived emotions at an abstract, modality-independent level, and thus play a key role in the understanding and categorization of others' emotional mental states.
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Cites
Russell, J. A. (1980) · Journal of Personality and Social Psychology · doi:10.1037/h0077714 · Cited by 16,334
Cognitive and emotional influences in anterior cingulate cortex
Bush, G., Luu, P., & Posner, M. I. (2000) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01483-2 · Cited by 6,259
People thinking about thinking peopleThe role of the temporo-parietal junction in “theory of mind”
Saxe, R., & Kanwisher, N. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00230-1 · Cited by 2,316 · cited 2×
“Several fMRI studies have also implicated the posterior STS/TPJ in the understanding of others’ minds (Gallagher et al., 2000; Saxe and Kanwisher, 2003; Decety and Grezès, 2006; Gobbini et al., 2007).”
BackgroundDevelopment and neurophysiology of mentalizing
Frith, U., & Frith, C. D. (2003) · Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rstb.2002.1218 · Cited by 2,306
Beyond mind-reading: multi-voxel pattern analysis of fMRI data
Norman, K. A., Polyn, S. M., Detre, G. J., & Haxby, J. V. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.07.005 · Cited by 2,271
Functional imaging of ‘theory of mind’
Gallagher, H. L., & Frith, C. D. (2003) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(02)00025-6 · Cited by 2,092
Invariant visual representation by single neurons in the human brain
Quiroga, R. Q., Reddy, L., Kreiman, G., Koch, C., & Fried, I. (2005) · Nature · doi:10.1038/nature03687 · Cited by 1,988
Decoding the visual and subjective contents of the human brain
Kamitani, Y., & Tong, F. (2005) · Nature Neuroscience · doi:10.1038/nn1444 · Cited by 1,829
The Social Brain: Neural Basis of Social Knowledge
Adolphs, R. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.60.110707.163514 · Cited by 1,827
Effects of Attention and Emotion on Face Processing in the Human Brain
Vuilleumier, P., Armony, J. L., Driver, J., & Dolan, R. J. (2001) · Neuron · doi:10.1016/s0896-6273(01)00328-2 · Cited by 1,664
Self-citation
Cited by
The theory of constructed emotion: an active inference account of interoception and categorization
Barrett, L. F. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw154 · Cited by 1,426
“…et al., 2012, 2015) Multimodal summaries of emotion concepts are represented in the default mode network Human neuroimaging: task-related data (Peelen et al., 2010; Skerry and Saxe, 2015) Default mode and salience network interconnectivity is associated with the intensity of emotional…”
The theory of constructed emotion: an active inference account of interoception and categorization
Barrett, L. F. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx060 · Cited by 1,009
“…et al., 2012, 2015) Multimodal summaries of emotion concepts are represented in the default mode network Human neuroimaging: task-related data (Peelen et al., 2010; Skerry and Saxe, 2015) Default mode and salience network interconnectivity is associated with the intensity of emotional…”
Toward a brain-based componential semantic representation
Binder, J. R., Conant, L. L., Humphries, C. J., Fernandino, L., Simons, S. B., Aguilar, M., & Desai, R. H. (2016) · Cognitive Neuropsychology · doi:10.1080/02643294.2016.1147426 · Cited by 367
Distributed Representations in Memory: Insights from Functional Brain Imaging
Rissman, J., & Wagner, A. D. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-120710-100344 · Cited by 299
Identifying emotions on the basis of neural activation
Kassam, K. S., Markey, A. R., Cherkassky, V. L., Loewenstein, G., & Just, M. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066032 · Cited by 306
Metadata
- Authors
- Peelen, M. V., Atkinson, A. P., & Vuilleumier, P.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2010-07-28
- Volume
- 30
- Issue
- 30
- Pages
- 10127-10134
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- OpenAlex
- W2100358226
- Cited by
- 422
- References
- 19
- FWCI
- 17.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
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