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Related Experiment Video

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Evaluating phase synchronization methods in fMRI: A comparison study and new approaches.

Hamed Honari1, Ann S Choe2, Martin A Lindquist3

  • 1Department of Electrical and Computer Engineering, Johns Hopkins University, USA.

Neuroimage
|January 1, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces the cosine of the relative phase (CRP) for analyzing brain connectivity using resting-state functional magnetic resonance imaging (rs-fMRI). CRP offers improved accuracy in detecting temporal changes in functional connectivity compared to existing methods.

Keywords:
Circular statisticsFunctional connectivityInstantaneous phase synchronizationPhase synchronization detectionResting-state fMRITime-varying phase synchronization

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Signal Processing

Background:

  • Growing interest in time-varying functional connectivity using resting-state functional magnetic resonance imaging (rs-fMRI).
  • Phase synchronization (PS) is a key metric for assessing relationships between brain region signals over time.
  • Existing methods like windowed phase synchronization (WPS) and instantaneous phase synchronization (IPS) have limitations.

Purpose of the Study:

  • To compare different phase synchronization (PS) methods for analyzing time-varying functional connectivity in rs-fMRI data.
  • To introduce and evaluate a novel approach, the cosine of the relative phase (CRP), within the instantaneous phase synchronization (IPS) framework.
  • To highlight the importance of band-pass filtering and discuss alternatives like Empirical Mode Decomposition (EMD).

Main Methods:

  • Comparison of windowed phase synchronization (WPS) and instantaneous phase synchronization (IPS) methods.
  • Introduction of the cosine of the relative phase (CRP) metric.
  • Evaluation through simulations and application to rs-fMRI data.
  • Emphasis on band-pass filtering for valid PS analysis.

Main Results:

  • The cosine of the relative phase (CRP) method outperforms other tested techniques.
  • CRP effectively overcomes issues of undetected temporal transitions in functional connectivity.
  • CRP provides a more detailed distribution of phase synchronization measures compared to phase coherence, aiding in brain state clustering.

Conclusions:

  • The cosine of the relative phase (CRP) is a robust and improved method for analyzing time-varying functional connectivity in rs-fMRI.
  • CRP enhances the detection of dynamic brain network changes and facilitates the identification of recurring brain states.
  • Proper data preprocessing, including band-pass filtering, is crucial for accurate phase synchronization analysis.