Evaluation of brain functional connectivity from electroencephalographic signals under different emotional states
| dc.contributor.author | Garcia-Martinez, Beatriz | por |
| dc.contributor.author | Fernandez-Caballero, Antonio | por |
| dc.contributor.author | Martinez-Rodrigo, Arturo | por |
| dc.contributor.author | Alcaraz, Raul | por |
| dc.contributor.author | Novais, Paulo | por |
| dc.date.accessioned | 2023-09-01T13:00:09Z | |
| dc.date.available | 2023-09-01T13:00:09Z | |
| dc.date.issued | 2022-04-23 | |
| dc.date.updated | 2023-08-31T13:59:54Z | |
| dc.description.abstract | The identification of the emotional states corresponding to the four quadrants of the valence/arousal space has been widely analyzed in the scientific literature by means of multiple techniques. Nevertheless, most of these methods were based on the assessment of each brain region separately, without considering the possible interactions among different areas. In order to study these interconnections, this study computes for the first time the functional connectivity metric called cross-sample entropy for the analysis of the brain synchronization in four groups of emotions from electroencephalographic signals. Outcomes reported a strong synchronization in the interconnections among central, parietal and occipital areas, while the interactions between left frontal and temporal structures with the rest of brain regions presented the lowest coordination. These differences were statistically significant for the four groups of emotions. All emotions were simultaneously classified with a 95.43% of accuracy, overcoming the results reported in previous studies. Moreover, the differences between high and low levels of valence and arousal, taking into account the state of the counterpart dimension, also provided notable findings about the degree of synchronization in the brain within different emotional conditions and the possible implications of these outcomes from a psychophysiological point of view. | por |
| dc.description.sponsorship | - This publication is part of the R&D Projects Nos. PID2020-115220RB-C21, EQC2019-006063P, funded by MCIN/AEI/10.13039/501100011033/, and 2018/11744, funded by "ERDF A way to make Europe". This work was partially supported by Biomedical Research Networking Centre in Mental Health (CIBERSAM) of the Instituto de Salud Carlos III. Beatriz Garcia-Martinez holds FPU16/03740 scholarship from Spanish Ministerio de Educacion y Formacion Profesional. | por |
| dc.distribution | international | por |
| dc.identifier.doi | 10.1142/S0129065722500265 | por |
| dc.identifier.eissn | 1793-6462 | |
| dc.identifier.issn | 0129-0657 | |
| dc.identifier.pmid | 35469551 | |
| dc.identifier.uri | https://hdl.handle.net/1822/86247 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.publisher | World Scientific Publishing | por |
| dc.relation.publisherversion | https://www.worldscientific.com/doi/10.1142/S0129065722500265 | por |
| dc.rights | openAccess | por |
| dc.subject | Electroencephalography | por |
| dc.subject | Functional connectivity | por |
| dc.subject | Cross-sample entropy | por |
| dc.subject | Emotions recognition | por |
| dc.subject.wos | Science & Technology | |
| dc.title | Evaluation of brain functional connectivity from electroencephalographic signals under different emotional states | por |
| dc.type | article | por |
| dspace.entity.type | Publication | en |
| oaire.citationIssue | 10 | por |
| oaire.citationVolume | 32 | por |
| sdum.export.identifier | 12718 | |
| sdum.journal | International Journal of Neural Systems | por |
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