Tanpura Drone and Brain Response

Abstract

Electroencephalography (EEG) was performed on 10 participants using a simple acoustical stimuli i.e., a Tanpura drone. The Tanpura drone is free from any semantic content and is used with a hypothesis that it provides a specific resting environment for the listeners. The EEG data was extracted for all the frontal electrodes viz. F3, F4, F7, F8, Fp1, Fp2 and Fz. Empirical Mode Decomposition (EMD) is applied on the acquired raw EEG signal to make it noise free as far as possible. Wavelet Transform (WT) technique was used to segregate alpha and theta brain rhythms from the denoised EEG signal. Non linear analysis in the form of Multifractal Detrended Fluctuation Analysis (MFDFA) was carried out on the extracted alpha and theta time series data to study the variation of their complexity. It was found that in all the frontal electrodes alpha as well as theta complexity increases as is evident from the increase of multifractal spectral width. This study is entirely new and gives interesting data regarding neural activation of the alpha and theta brain rhythms while listening to simple acoustical stimuli. The importance of this study lies in the context of finding a baseline for human emotion quantification using multifractal spectral width as a parameter as well as in the field of cognitive music therapy.