Linking Brain Responses to Naturalistic Music Through Analysis of Ongoing EEG and Stimulus Features

Abstract

This study proposes a novel approach for the analysis of brain responses in the modality of ongoing EEG elicited by the naturalistic and continuous music stimulus. The 512-second long EEG data (recorded with 64 electrodes) are first decomposed into 64 components by independent component analysis (ICA) for each participant. Then, the spatial maps showing dipolar brain activity are selected in terms of the residual dipole variance through a single dipole model in brain imaging, and clustered into a pre-defined number (estimated by the minimum description length) of clusters. Subsequently, the temporal courses of the EEG theta and alpha oscillations of each component for each cluster are produced and correlated with the temporal courses of tonal and rhythmic features of the music. Using this approach, we found that the extracted temporal courses of the theta and alpha oscillations along central and occipital area of scalp in two of the selected clusters significantly correlated with the musical features representing progressions in the rhythmic content of the stimulus. We suggest that this demonstrates that with the proposed approach, we have managed to discover what kinds of brain responses were elicited when Manuscript a participant was listening continuously to the long piece of naturalistic music.

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

“…Accordingly, the fast-tempo-induced sensorimotor alpha suppression of the present study might imply that the musical tempo (beats per minute) drive motor imagery to some extent. Such musical tempo-driven sensorimotor alpha suppression has not been reported in the recent ICA-based music study [20]. In addition, an early EEG study [13] reported that changes in either tempo or mode would result in a frontal alpha-power asymmetry (F3 versus F4).…”

“…Compared to the recent ICA-based music study [20], the present study not only fully explored the spatio-spectral dynamics across EEG frequency bands (delta, theta, alpha, beta, and gamma), but also took a step further to investigate how the spatio-spectral dynamics of different brain networks were modulated by the musical mode and tempo. The discussions below will compare the resultant EEG dynamics in terms of brain locations and the spectral dynamics in the literature.…”

The Berlin Brain-Computer Interface: Progress Beyond Communication and Control

“…Unsupervised ICA-based approaches identified common features in the EEG of music listeners (Cong et al, 2012, 2013; Thompson, 2013). The results support the idea that the waveform envelope (which contains information about the timing of note onsets) is reflected in EEG and therefore provides a good starting point for linking music signals and brain signals.…”

Merging Neuroimaging and Multimedia: Methods, Opportunities, and Challenges

“…They concluded that high gamma band activations in or close to the superior temporal gyrus and precentral gyrus are significantly correlated with sound intensity. Cong et al [69] extracted five musical (tonal and rhythmic) features from a 512-s-long musical piece of modern tango, and correlated these features with EEG features. They showed empirically that the temporal courses of the theta and alpha oscillations along central and occipital areas significantly correlated with the musical features representing progressions in the rhythmic content of the stimulus.…”