2016
DOI: 10.1093/scan/nsw048
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Independent component processes underlying emotions during natural music listening

Abstract: The aim of this study was to investigate the brain processes underlying emotions during natural music listening. To address this, we recorded high-density electroencephalography (EEG) from 22 subjects while presenting a set of individually matched whole musical excerpts varying in valence and arousal. Independent component analysis was applied to decompose the EEG data into functionally distinct brain processes. A k-means cluster analysis calculated on the basis of a combination of spatial (scalp topography an… Show more

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Cited by 49 publications
(54 citation statements)
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References 148 publications
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“…To understand common regional brain activation patterns in the 30 subjects, the K-means method75 was employed to cluster the scalp maps, power spectral densities, and dipole locations of the independent components5876. The independent components of the 30 subjects were clustered into 13 common regions: frontal midline, left frontal, right frontal, central midline, left temporal, right temporal, left motor, right motor, parietal, left occipital, occipital midline, right occipital, and limbic system.…”
Section: Methodsmentioning
confidence: 99%
“…To understand common regional brain activation patterns in the 30 subjects, the K-means method75 was employed to cluster the scalp maps, power spectral densities, and dipole locations of the independent components5876. The independent components of the 30 subjects were clustered into 13 common regions: frontal midline, left frontal, right frontal, central midline, left temporal, right temporal, left motor, right motor, parietal, left occipital, occipital midline, right occipital, and limbic system.…”
Section: Methodsmentioning
confidence: 99%
“…Some sensor-level EEG studies examined the physiological correlates of continuous changes in subjective emotional states while listening to a complete music piece (Mikutta et al 2012(Mikutta et al , 2014. Compared with sensor-level EEG analysis, recent studies adopted a mathematical approach (called sLORETA-ICA) combing source localization techniques with ICA to detect the independent functional networks during music listening (Jäncke and Alahmadi 2016;Rogenmoser et al 2016). Although the aforementioned studies investigated the oscillatory activation or functional networks during music listening, the specific networks emerging from dynamic processing of musical features are not yet fully understood (Meyer et al 2006).…”
Section: Introductionmentioning
confidence: 99%
“…AMYG showed an increased rs-FC with SI and SLOC in both hemispheres after listening to music, parietal areas of somatosensory functions and occipital areas involved in visual mental imagery (Platel et al, 1997). We found increased rs-FC of the AnG with the LG, possibly secondary to visual memory and visuo-limbic processes engaged after listening to music (Rogenmoser et al, 2016). The rs-FC increase of somatosensory cortices (SI and SII) and occipital association cortices with motor cortex and hippocampus support this hypothesis (Groussard et al, 2014; Frühholz et al, 2016).…”
Section: Discussionmentioning
confidence: 87%