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Age-related variation in EEG to music stimulation: A nonlinear analysis

The study was intended to analyze the effect of three types of music, namely Indian classical music, Bhajan (spiritual anthem) music and rock music, on the electroencephalogram (EEG) activity for two different age groups, viz. young subjects (23–27 years) and elder subjects (40–55 years). We recorded EEG in 10 healthy elder subjects and 10 healthy young subjects at eyes closed condition during without music and with music stimuli. A nonlinear methods named Detrended Fluctuation (DFA) utilized for scaling property analysis, Multiscale Entropy (MSE) utilized for complexity (irregularity) analysis and Correlation Dimension (CD) utilized for correlation of EEG signals. It was found that, except DFA both the methods showed significant difference in the value of estimated parameters with different type of music stimuli. Scaling exponent of DFA and Correlation Dimension were higher in elder subjects than younger subjects, but in MSE the value of Sample Entropy found higher for young subjects. The conclusion was derived from the experiment that the complexity of EEG signal increases with music and self-similarity of EEG signal decreases with music stimuli in both age groups. However, complexity of EEG signal was higher in younger subject than elder subject except to bhajan music stimuli. The self-similarity of EEG signal was improved for younger than elder subjects with music stimuli. This study signifies that aging affects the variations in EEG when music stimulation applied.