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Estimating sensor-space EEG connectivity: Identifying optimal artifact reduction techniques for functional

Aleksandra Miljevic1, Oscar W Murphy2, Paul B Fitzgerald3

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Summary

Optimizing electroencephalography (EEG) preprocessing enhances functional brain connectivity (FC) analysis. The best pipeline uses Independent Component Analysis (ICA) or wavelet-enhanced ICA (wICA) for artifact reduction and current source density (CSD) re-referencing for reliable alpha band FC measures.

Keywords:
Alpha frequencyEEGElectroencephalographyFCFunctional connectivityLifespan

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Electroencephalography (EEG) is crucial for assessing functional brain connectivity (FC).
  • Variability in EEG preprocessing methods leads to inconsistent research findings.
  • Standardizing preprocessing is essential for reliable EEG-FC measurements.

Purpose of the Study:

  • To evaluate the impact of different EEG preprocessing steps on functional brain connectivity (FC) measurements.
  • To identify preprocessing pipelines that improve the detection of age-related differences in alpha band FC.
  • To assess the test-retest reliability of FC measures across various preprocessing strategies.

Main Methods:

  • Utilized the open-source BrainClinics.com EEG data repository.
  • Compared artifact reduction techniques: Independent Component Analysis (ICA), wavelet-enhanced ICA (wICA), and Multi-channel Wiener Filters (MWF).
  • Evaluated epoch lengths (2s vs. 6s), re-referencing montages (CAR vs. CSD), and FC metrics (iCOH, rMSC, wPLI).

Main Results:

  • The optimal pipeline combined ICA or wICA for artifact reduction with current source density (CSD) re-referencing.
  • This pipeline demonstrated superior detection of age-related alpha band FC differences.
  • The chosen methods also yielded high test-retest reliability for FC measures.

Conclusions:

  • An optimized EEG preprocessing pipeline enhances the detection of meaningful effects in sensor space EEG.
  • The recommended pipeline (ICA/wICA artifact reduction, CSD re-referencing, rMSC metric) provides robust and reliable alpha frequency FC analysis.
  • This standardization is vital for reducing heterogeneity and improving the reproducibility of EEG research.