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Time-Varying Scalp EEG Network Patterns for Music Tempo Perception

  • Wei Xu
  • Yin Tian
  • Haiyong Zhang
  • Huiling Zhang
  • Zhongyan Wang
  • Li Yang
  • Shuxing Zheng
  • Yupan Shi
  • Xing Zhao
  • Dechun Zhao
  • Xiuxing Wang
  • Yu Pang
  • Zhangyong Li
Conference paper
Part of the Advances in Cognitive Neurodynamics book series (ICCN)

Abstract

In the present study, we used the time-varying scalp network analysis method of electroencephalography (EEG) to investigate information flows among different tempos perception in the alpha band. The results showed the network hubs of different tempos existed variously. Only during listening to normal tempo (52 bpm), the strongest out-degree of hubs is distributed in the right hemisphere and the information flow transferred from the left to the right hemisphere. Based on these findings, we proposed that the left hemisphere did not prime the processing until the necessary information had been transferred from the right hemisphere. This study was the first to use time-varying network method based on adaptive directed transfer function (ADTF) to investigate music-related EEG activities and proposed a novel method to reveal the neural mechanisms on music tempo.

Keywords

EEG Time-varying network Network pattern Alpha Music tempo 

Notes

Acknowledgments

This research was supported by the National Natural Science Foundation of China (#61671097); the Chongqing advanced and applied basic research project cstc2015jcyjA10024.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Wei Xu
    • 1
  • Yin Tian
    • 1
  • Haiyong Zhang
    • 1
  • Huiling Zhang
    • 1
  • Zhongyan Wang
    • 1
  • Li Yang
    • 1
  • Shuxing Zheng
    • 1
  • Yupan Shi
    • 1
  • Xing Zhao
    • 1
  • Dechun Zhao
    • 1
  • Xiuxing Wang
    • 1
  • Yu Pang
    • 1
  • Zhangyong Li
    • 1
  1. 1.Bio-information College, Chongqing Key Laboratory of Photoelectronic Information Sensing and Transmitting TechnologyChongqing High School Innovation Team of Architecture and Core Technologies of Smart Medical System, Chongqing University of Posts and TelecommunicationsChongqingChina

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