Estimating sensor-space EEG connectivity: Identifying best performing methods for functional connectivity in simulated data

Our paper provides an evidence-base for the influence of referencing, epoch length and number, controls for volume conduction, and different FC metrics on EEG-FC measurement. Using this evidence, we present an initial and promising account of the best performing (pre-)processing choices for robust EEG-FC assessment.

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Publication Details

Journal
Clinical Neurophysiology
Published
2025-04-08
DOI
https://doi.org/10.1016/j.clinph.2025.03.043
Citations
2
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
2.86
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article

Estimating sensor-space EEG connectivity: Identifying best performing methods for functional connectivity in simulated data

Neil W. Bailey, Aleksandra Miljevic, Paul B. Fitzgerald, Oscar W. Murphy
2 citations
Clinical Neurophysiology
Functional Brain Connectivity Studies
2.86
article

Estimating sensor-space EEG connectivity: Identifying best performing methods for functional connectivity in simulated data

Neil W. Bailey, Aleksandra Miljevic, Paul B. Fitzgerald, Oscar W. Murphy
article en
2 citations

Abstract

Our paper provides an evidence-base for the influence of referencing, epoch length and number, controls for volume conduction, and different FC metrics on EEG-FC measurement. Using this evidence, we present an initial and promising account of the best performing (pre-)processing choices for robust EEG-FC assessment.

Clinical NeurophysiologyVol. 174
Australian National University (AU), Bionics Institute (AU), Monash University (AU)
Openalex Percentile: Top 11%
Functional Brain Connectivity Studies
2.86
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