Objective: 

We aimed to investigate the EEG manifestations of concentrated music listening experience on four musical pieces belonging to four different musical genres: Turkish classical (Sufi), western classical (Vivaldi), rock (AC/DC) and pop (club beats) music.

Methods: 

21 right-handed male university students were selected for study. An audio file was prepared by attaching 3 minute-long segments of different musical pieces beginning with a three minutes of silence. Each subject was comfortably placed on a laboratory litter on supine position and EEG electrodes were attached over both temporal hemispheres at T4-T6 and T3-T5 points with a common earth electrode attached to the left earlobe. Each subject put on a pair of high-quality earphones for music presentation and a pulse transducer attached to their left hand middle finger. Before the actual audio file is presented, all subjects received a brief verbal suggestion to relax and concentrate on audio. Recording procedure started simultaneously with the audio presentation and continuous EEG and pulse recordings obtained using a digital data acquisition system, with a sampling rate of 1kHz. Recorded brain waves decomposed into delta, theta, alpha, beta and gamma frequencies and total power of each frequency were calculated together with the RMS values. In addition, false nearest neighbor fractions (FNFs) for different embedding dimensions were calculated and compared. FNFs are commonly used for finding the appropriate embedding dimension which can uncover useful information about the original unknown chaotic dynamics of the signal in phase space.

Results: 

According to our findings, nonlinear analysis techniques revealed that there is a significant similarity between the silent period and the period in which the Turkish classical music is presented, in terms of nonlinear parameters of the brain signals. All other types of musical pieces were significantly different than silent and Turkish classical music period.

Conclusions: 

Our findings suggest that the nonlinear analysis methods may be a useful tool to better understand the complex procedure of music perception and interpretation.