Electroencephalographic Connectivity: A Fundamental Guide and Checklist for Optimal Study Design and Evaluation

Area of Science:

• Neuroscience
• Computational Neuroscience
• Biomedical Engineering

Background:

• Electroencephalography (EEG) is widely used to estimate brain connectivity.
• Significant heterogeneity exists in EEG connectivity analysis methods, impacting result reliability.
• Variability stems from differences in conceptualization, data collection, and preprocessing.

Purpose of the Study:

• To address the heterogeneity in EEG connectivity analysis.
• To provide recommendations and a quality assessment checklist for EEG connectivity studies.
• To enhance the synthesizability and comparability of EEG connectivity research.

Main Methods:

• Review of factors influencing EEG connectivity estimates.
• Discussion of methods to control for confounding factors.
• Development of a novel checklist for quality assessment.

Main Results:

• Identified key factors affecting EEG connectivity: referencing, epoch parameters, volume conduction, artifact removal, and statistical comparisons.
• Proposed strategies to mitigate confounds associated with these factors.
• Developed a checklist to guide quality assessment in EEG connectivity studies.

Conclusions:

• Standardization of EEG connectivity procedures and reporting is crucial.
• Recommendations and the checklist aim to improve robustness and comparability.
• Future research should focus on implementing standardized practices for more reliable brain connectivity insights.