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 a participant was listening continuously to the long piece of naturalistic music.

Many areas in audio engineering, e.g., perceptual coding, strongly rely on knowledge and models of the human auditory system. Nonuniform frequency resolution and masking phenomenon are well studied aspects. Less attention has been paid to the temporal auditory resolution. In this pilot study the temporal resolution is tested by using short (0.55-4.15 ms) clicks called Bark-FAMlets. They form an orthogonal set of signals all having identical power spectra with uniform masking properties. Individual FAMlets differ only in phase by steps called an auditory unit delay (AUD). We found that 75% discrimination is achieved when the difference between two FAMlets is 22, 11 or 10 AUDs depending on the three test conditions used.