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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Sayal, A. , Guedes, A. G. , Almeida, I. , Pereira, D. J. , Lima, C. F., Panda, R. ...Direito, B. (2025). Decoding musical valence and arousal: Exploring the neural correlates of music-evoked emotions and the role of expressivity features. IEEE Transactions on Affective Computing. 16 (2), 1247-1259
Exportar Referência (IEEE)
A. Sayal et al.,  "Decoding musical valence and arousal: Exploring the neural correlates of music-evoked emotions and the role of expressivity features", in IEEE Transactions on Affective Computing, vol. 16, no. 2, pp. 1247-1259, 2025
Exportar BibTeX
@article{sayal2025_1765067419491,
	author = "Sayal, A.  and Guedes, A. G.  and Almeida, I.  and Pereira, D. J.  and Lima, C. F. and Panda, R.  and Paiva, R. P.  and Sousa, T.  and Castelo-Branco, M.  and Bernardino, I.  and Direito, B.",
	title = "Decoding musical valence and arousal: Exploring the neural correlates of music-evoked emotions and the role of expressivity features",
	journal = "IEEE Transactions on Affective Computing",
	year = "2025",
	volume = "16",
	number = "2",
	doi = "10.1109/TAFFC.2024.3507192",
	pages = "1247-1259",
	url = "https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369"
}
Exportar RIS
TY  - JOUR
TI  - Decoding musical valence and arousal: Exploring the neural correlates of music-evoked emotions and the role of expressivity features
T2  - IEEE Transactions on Affective Computing
VL  - 16
IS  - 2
AU  - Sayal, A. 
AU  - Guedes, A. G. 
AU  - Almeida, I. 
AU  - Pereira, D. J. 
AU  - Lima, C. F.
AU  - Panda, R. 
AU  - Paiva, R. P. 
AU  - Sousa, T. 
AU  - Castelo-Branco, M. 
AU  - Bernardino, I. 
AU  - Direito, B.
PY  - 2025
SP  - 1247-1259
SN  - 1949-3045
DO  - 10.1109/TAFFC.2024.3507192
UR  - https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369
AB  - Music conveys both basic emotions, like joy and sadness, and complex ones, such as tenderness and nostalgia. Its effects on emotion regulation and reward have attracted much research attention, as the neural correlates of music-evoked emotions may inform neurorehabilitation interventions. Here, we used fMRI to decode and examine the neural correlates of perceived valence and arousal in music excerpts. Twenty participants were scanned while listening to 96 music excerpts, classified beforehand into four categories varying in valence and arousal. Music modulated activity in cortical regions, most noticeably in music-specific subregions of the auditory cortex, thalamus, and regions of the reward network such as the amygdala. Using multivoxel pattern analysis, we created a computational model to decode the perceived valence and arousal of the music excerpts with above-chance accuracy. We further explored associations between musical features and brain activity in valence-, arousal-, reward-, and auditory-related networks. The results emphasize the involvement of distinct musical features, notably expressive features such as vibrato and tonal and spectral dissonance in valence, arousal, and reward brain networks. Using ecologically valid music stimuli, we contribute to delineating the neural correlates of music-evoked emotions with potential implications in the development of novel music-based neurorehabilitation strategies.
ER  -