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Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals

Author

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  • Banerjee, Archi
  • Sanyal, Shankha
  • Patranabis, Anirban
  • Banerjee, Kaushik
  • Guhathakurta, Tarit
  • Sengupta, Ranjan
  • Ghosh, Dipak
  • Ghose, Partha

Abstract

Music has been proven to be a valuable tool for the understanding of human cognition, human emotion, and their underlying brain mechanisms. The objective of this study is to analyze the effect of Hindustani music on brain activity during normal relaxing conditions using electroencephalography (EEG). Ten male healthy subjects without special musical education participated in the study. EEG signals were acquired at the frontal (F3/F4) lobes of the brain while listening to music at three experimental conditions (rest, with music and without music). Frequency analysis was done for the alpha, theta and gamma brain rhythms. The finding shows that arousal based activities were enhanced while listening to Hindustani music of contrasting emotions (romantic/sorrow) for all the subjects in case of alpha frequency bands while no significant changes were observed in gamma and theta frequency ranges. It has been observed that when the music stimulus is removed, arousal activities as evident from alpha brain rhythms remain for some time, showing residual arousal. This is analogous to the conventional ‘Hysteresis’ loop where the system retains some ‘memory’ of the former state. This is corroborated in the non linear analysis (Detrended Fluctuation Analysis) of the alpha rhythms as manifested in values of fractal dimension. After an input of music conveying contrast emotions, withdrawal of music shows more retention as evidenced by the values of fractal dimension.

Suggested Citation

  • Banerjee, Archi & Sanyal, Shankha & Patranabis, Anirban & Banerjee, Kaushik & Guhathakurta, Tarit & Sengupta, Ranjan & Ghosh, Dipak & Ghose, Partha, 2016. "Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 110-120.
    • Handle: RePEc:eee:phsmap:v:444:y:2016:i:c:p:110-120
    DOI: 10.1016/j.physa.2015.10.030
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    References listed on IDEAS

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    1. Karkare, Siddharth & Saha, Goutam & Bhattacharya, Joydeep, 2009. "Investigating long-range correlation properties in EEG during complex cognitive tasks," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2067-2073.
    2. Joydeep Bhattacharya, 2009. "Increase of Universality in Human Brain during Mental Imagery from Visual Perception," PLOS ONE, Public Library of Science, vol. 4(1), pages 1-11, January.
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    Cited by:

    1. Sanyal, Shankha & Banerjee, Archi & Patranabis, Anirban & Banerjee, Kaushik & Sengupta, Ranjan & Ghosh, Dipak, 2016. "A study on Improvisation in a Musical performance using Multifractal Detrended Cross Correlation Analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 67-83.
    2. Lahmiri, Salim, 2017. "Multifractal analysis of Moroccan family business stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 183-191.
    3. Pal, Mayukha & P., Manimaran & Panigrahi, Prasanta K., 2022. "A multi scale time–frequency analysis on Electroencephalogram signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    4. Yen-Chieh Chen & Meng-Chien Li & Shou-Der Weng & Yi-Chieh Wang, 2023. "A Descriptive Survey of Atmospheric Music Broadcasting in Hot Spring Hotels and Its Further Marketing Strategy," SAGE Open, , vol. 13(1), pages 21582440221, January.

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