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Related Experiment Video

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Cortical Source Analysis of High-Density EEG Recordings in Children
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Feasibility of Reconstructing Source Functional Connectivity with Low-Density EEG.

Dung A Nguyen-Danse1, Shobana Singaravelu1, Léa A S Chauvigné1

  • 1Imaging-Assisted Neurorehabilitation Lab, Department of Clinical Neurophysiology, University of Geneva, Av. de Beau-Séjour 26, 1211, Geneva, Switzerland.

Brain Topography
|August 20, 2021
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Summary

Reconstructing functional connectivity (FC) using low-density electroencephalography (EEG) is challenging but feasible. Beamformer-based source reconstruction methods show promise for real-world applications, outperforming other techniques with fewer electrodes.

Keywords:
Alpha oscillationsElectroencephalographyFunctional connectivityLow–densityNeurofeedback

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Last Updated: Oct 23, 2025

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Functional connectivity (FC) is a key target for neuromodulation and performance enhancement.
  • Current reliable FC assessment using electroencephalography (EEG) requires high-density setups and extensive preparation, limiting real-world applications.

Purpose of the Study:

  • To investigate the feasibility of reconstructing source FC using low-density EEG montages.
  • To evaluate the impact of electrode density and head models on FC reconstruction accuracy.
  • To assess the ability of low-density EEG to capture inter-individual variations in coherence strength.

Main Methods:

  • Source FC was reconstructed using inverse solutions and quantified via absolute imaginary coherence in alpha frequencies.
  • Simulated and real EEG datasets were used, comparing 19 vs. 128 electrodes and template vs. individual MRI-based head models.
  • Various reconstruction approaches, including beamformers, sensor FC, and sLORETA, were compared for 19-electrode data.

Main Results:

  • Reduced electrode density led to less reliable reconstructions of coherent sources and coupling strength.
  • Source FC derived from beamformers outperformed sensor FC, ICA-based FC, and sLORETA-based source FC with 19 electrodes.
  • Beamformer-based source FC uniquely captured neural correlates of motor behavior.

Conclusions:

  • Reconstructing FC from low-density EEG presents challenges.
  • The use of beamformer-based source reconstruction techniques offers a feasible approach for low-density EEG applications.