Publication
A Pattern Recognition Framework to Investigate the Neural Correlates of Music
| dc.contributor.author | Guedes, Ana Gabriela | |
| dc.contributor.author | Sayal, Alexandre | |
| dc.contributor.author | Panda, Renato | |
| dc.contributor.author | Paiva, Rui Pedro | |
| dc.contributor.author | Direito, Bruno | |
| dc.date.accessioned | 2023-11-06T13:36:22Z | |
| dc.date.available | 2023-11-06T13:36:22Z | |
| dc.date.issued | 2023-10-27 | |
| dc.description.abstract | Music can convey fundamental emotions like happiness and sadness and more intricate feelings such as tenderness or grief. Understanding the neural mechanisms underlying music-induced emotions holds promise for innovative, personalised neurorehabilitation therapies using music. Our study investigates the link between perceived emotions in music and their corresponding neural responses, measured using fMRI. Fifteen participants underwent fMRI scans while listening to 96 musical excerpts categorised into quadrants based on Russell’s valence-arousal model. Neural correlates of valence and arousal were identified in neocortical regions, especially within music-specific sub-regions of the auditory cortex. Through multivariate pattern analysis, distinct emotional quadrants were decoded with an average accuracy of 62% ±15%, surpassing the chance level of 25%. This capacity to discern music’s emotional qualities has implications for psychological interventions and mood modulation, enhancing music-based treatments and neurofeedback learning. | pt_PT |
| dc.description.sponsorship | This work has been supported by Fundação para a Ciência e Tecnologia, grant EXPL/PSI-GER/0948/2021. Renato Panda was supported by Ci2 - FCT UIDP/05567/2020. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.26/47857 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.relation | Smart Cities Research Center | |
| dc.title | A Pattern Recognition Framework to Investigate the Neural Correlates of Music | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Smart Cities Research Center | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/3599-PPCDT/EXPL%2FPSI-GER%2F0948%2F2021/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05567%2F2020/PT | |
| oaire.citation.conferencePlace | Coimbra, Portugal | pt_PT |
| oaire.citation.endPage | 27 | pt_PT |
| oaire.citation.startPage | 26 | pt_PT |
| oaire.citation.title | 29th Portuguese Conference on Pattern Recognition (RECPAD 2023) | pt_PT |
| oaire.fundingStream | 3599-PPCDT | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Panda | |
| person.givenName | Renato | |
| person.identifier | WT5afVUAAAAJ | |
| person.identifier.ciencia-id | 661A-31CC-8D19 | |
| person.identifier.orcid | 0000-0003-2539-5590 | |
| person.identifier.scopus-author-id | 55354413900 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
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