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Functional connectivity analysis in EEG source space: The choice of method.

Elham Barzegaran1, Maria G Knyazeva1

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Summary

Functional connectivity (FC) analysis using electroencephalography (EEG) is improved by source-space methods. Inverse-based source FC (ISFC) is best for high-density EEG, while cortical partial coherence (CPC) is preferred for low-density EEG.

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Area of Science:

  • Neuroscience
  • Signal Processing
  • Biomedical Engineering

Background:

  • Functional connectivity (FC) derived from electroencephalography (EEG) is crucial for understanding brain function.
  • Sensor-space FC analysis is limited by volume conductance effects, necessitating source-space approaches.
  • The applicability of source-space FC methods to low-density EEG (ldEEG) remains uncertain due to sampling limitations.

Purpose of the Study:

  • To investigate and compare the performance of two source-space FC methods: inverse-based source FC (ISFC) and cortical partial coherence (CPC).
  • To evaluate these methods across different EEG densities (high, mid, and low) and under varying simulation conditions (source location, SNR, source separation).

Main Methods:

  • Simulated EEG data with controlled oscillatory sources at varying locations and signal-to-noise ratios (SNRs).
  • Simulated two synchronized sources with adjustable distances and SNRs to assess method discrimination.
  • Implemented and compared ISFC and CPC methods for high-density EEG (hdEEG), mid-density EEG (mdEEG), and ldEEG.

Main Results:

  • Both ISFC and CPC performance degrade for deep sources due to localization inaccuracies and signal smoothing.
  • Method accuracy generally improves with increasing distance between simulated sources.
  • ISFC performed optimally with hdEEG and mdEEG, whereas CPC showed superior performance with ldEEG.

Conclusions:

  • For hdEEG, ISFC is the recommended method for superior FC estimation over CPC.
  • For ldEEG, CPC is the preferred method due to its robustness in conditions with limited spatial sampling.