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A Comparison of Actual and Artifactual Features Based on Fractal Analyses: Resting-State MEG Data

  • Montri Phothisonothai
  • Hiroyuki Tsubomi
  • Aki Kondo
  • Yuko Yoshimura
  • Mitsuru Kikuchi
  • Yoshio Minabe
  • Katsumi Watanabe
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 212)

Abstract

Future standardized system for distinguishing actual and artifactual magnetoencephalogram (MEG) data is an essential tool. In this paper, we proposed the quantitative parameters based on fractal dimension (FD) analyses in which the FD may convey different features before and after artifact removal. The six FD algorithms based on time-series computation, namely, box-counting method (BCM), variance fractal dimension (VFD), Higuchi’s method (HM), Kazt’s method (KM), detrended fluctuation analysis (DFA), and modified zero-crossing rate (MZCR) were compared. These approaches measure nonlinear-behavioral responses in the resting-state MEG data. Experimental results showed that the FD value of actual MEG was increased statistically in comparison with the artifactual MEG. The DFA and the HM present a best performance for analyzing simulated data and resting-state MEG data, respectively.

Keywords

Fractal dimension Complexity measure MEG Nonlinear analysis Artifact removal 

Notes

Acknowledgments

This research was supported by the Japan Society for the Promotion of Science (JSPS) and the Hokuriku Innovation Cluster for Health Science (MEXT Program for Fostering Regional Innovation).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Montri Phothisonothai
    • 1
  • Hiroyuki Tsubomi
    • 2
  • Aki Kondo
    • 1
  • Yuko Yoshimura
    • 3
  • Mitsuru Kikuchi
    • 3
  • Yoshio Minabe
    • 3
  • Katsumi Watanabe
    • 1
  1. 1.Research Center for Advanced Science and TechnologyThe University of TokyoTokyoJapan
  2. 2.Faculty of HumanitiesThe University of ToyamaToyamaJapan
  3. 3.Research Center for Child Mental DevelopmentGraduate School of Medical Science Kanazawa UniversityKanazawaJapan

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