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Related Experiment Video

Updated: May 11, 2026

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG
09:35

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG

Published on: March 10, 2017

Statistical method for detecting phase shifts in alpha rhythm from human electroencephalogram data.

Yasushi Naruse1, Ken Takiyama, Masato Okada

  • 1Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology and Osaka University, Kobe, Hyogo 651-2492, Japan. y_naruse@nict.go.jp

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|May 18, 2013
PubMed
Summary

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This study introduces a new statistical method to detect phase shifts in human brain alpha rhythms from single electroencephalogram (EEG) trials. This approach offers practical insights into brain dynamics beyond conventional methods.

Area of Science:

  • Neuroscience
  • Signal Processing
  • Statistical Modeling

Background:

  • Alpha rhythms are crucial brain oscillations.
  • Detecting dynamic changes in brain activity is challenging.
  • Existing methods struggle with single-trial analysis.

Purpose of the Study:

  • To develop a novel statistical method for detecting discontinuous phase shifts in human alpha rhythms.
  • To analyze electroencephalogram (EEG) data from single trials.
  • To overcome limitations of conventional averaging methods.

Main Methods:

  • Utilized state space models and the line process technique.
  • Applied a Bayesian approach for discontinuity detection.
  • Validated the method with simulated and experimental EEG data.

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BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals
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BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Published on: April 26, 2024

EEG Mu Rhythm in Typical and Atypical Development
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EEG Mu Rhythm in Typical and Atypical Development

Published on: April 9, 2014

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Last Updated: May 11, 2026

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG
09:35

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG

Published on: March 10, 2017

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals
08:22

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Published on: April 26, 2024

EEG Mu Rhythm in Typical and Atypical Development
11:50

EEG Mu Rhythm in Typical and Atypical Development

Published on: April 9, 2014

Main Results:

  • Successfully detected phase and amplitude shifts in simulated single trials.
  • Identified stimulus-evoked phase shifts in experimental alpha rhythms from single EEG trials.
  • Observed consistent early-latency phase shifts and variable late-latency shifts in experimental data.

Conclusions:

  • The developed method is practical for analyzing single-trial EEG data.
  • It can detect phase shifts missed by conventional averaging techniques.
  • This method will advance the study of nonlinear alpha rhythm dynamics.