Revealing spatio-spectral electroencephalographic dynamics of musical mode and tempo perception by independent component analysis

Abstract

Background: Music conveys emotion by manipulating musical structures, particularly musical mode- and tempo-impact. The neural correlates of musical mode and tempo perception revealed by electroencephalography (EEG) have not been adequately addressed in the literature.

Method: This study used independent component analysis (ICA) to systematically assess spatio-spectral EEG dynamics associated with the changes of musical mode and tempo.

Results: Empirical results showed that music with major mode augmented delta-band activity over the right sensorimotor cortex, suppressed theta activity over the superior parietal cortex, and moderately suppressed beta activity over the medial frontal cortex, compared to minor-mode music, whereas fast-tempo music engaged significant alpha suppression over the right sensorimotor cortex.

Conclusion: The resultant EEG brain sources were comparable with previous studies obtained by other neuroimaging modalities, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). In conjunction with advanced dry and mobile EEG technology, the EEG results might facilitate the translation from laboratory-oriented research to real-life applications for music therapy, training and entertainment in naturalistic environments.

Figure 1

Scalp maps and dipole source locations of six independent component clusters across twenty-four subjects. Left panel: Individual scalp maps indicate components found by ICA for a single subject. Middle panel: Mean scalp maps averaged across components within a cluster. Right panel: Plot of 3D dipole source locations and their projections onto the MNI brain template. (A) lateral occipital (n = 16, s = 11), (B) right sensorimotor (n = 16, s = 16), (C) left sensorimotor (n = 16, s = 15), (D) medial parietal (n = 12, s = 12), (E) medial frontal (n = 11, s = 11), and (F) superior parietal (n = 10, s = 9) (representing the number of components n contributed by the number of subjects s within a cluster).

Figure 2

Consistency of six independent component clusters. The averaged and individual IC log-power spectra (dB) are plotted in red and gray lines, respectively, and the corresponding mean scalp maps of clusters are superimposed on the panels. (A) Lateral occipital cluster, (B) Right sensorimotor cluster, (C) Left sensorimotor cluster, (D) Medial parietal cluster, (E) Medial frontal cluster, and (F) Superior parietal cluster. (G) A 3D overview of equivalent dipole locations of the six clusters of interest and their projections onto the MNI brain template. Dots in the same color represent the components grouped into the same cluster.

Figure 3

Averaged spectral dynamics for IC clusters in response to musical mode and tempo. (A-D, left) The centroids of equivalent dipole locations of selected IC clusters are projected onto the MNI brain template. (A-D, right) The averaged time courses (across music excerpts, left plot) and the averaged mean values of the time courses (across excerpts and time points, right plot) of cluster spectra. The red lines indicate the spectral changes in music with major mode/fast tempo, whereas the blue lines represent the spectral changes in music with minor mode/slow tempo. Note that the first five seconds of 30s music presentation was removed for spectral baseline correlation. Music in major mode significantly induced (A) higher right sensorimotor (x = 35, y = -26, z = 45) delta power (F_(1,12) = 7.15, p < 0.021) and (B) lower superior parietal (x = 6, y = -56, z = 64) theta power (F_(1,12)=9.87, p < 0.009) versus music in minor mode. Music in fast tempo significantly induced (C) lower right sensorimotor alpha power versus music in slow tempo (F_(1,12) = 5.68, p < 0.035). (D) The superior parietal delta exhibited insignificance in response to musical mode changed (F_(1,12)=0.01, p = 0.909), which was used for comparing the superior parietal theta (B).