Functional connectivity using high density EEG shows competitive reliability and agreement across test/retest sessions.

J Neurosci Methods

Departments of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA 94305, USA; Wu Tsai Neuroscience Institute, 290 Jane Stanford Way, Rm E152, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), 3801 Miranda Ave, Palo Alto, CA 94304, USA. Electronic address:

Published: February 2022

Background: Electrophysiological resting state functional connectivity using high density electroencephalography (hdEEG) is gaining momentum. The increased resolution offered by hdEEG, usually either 128 or 256 channels, permits source localization of EEG signals on the cortical surface. However, the number of methodological options for the acquisition and analysis of resting state hdEEG is extremely large. These include acquisition duration, eyes open/closed, channel density, source localization methods, and functional connectivity metric.

New Methods: We undertake an extensive examination of the test-retest reliability and methodological agreement of all these options for regional measures of functional connectivity.

Results: Power envelope connectivity shows larger test-retest reliability than imaginary coherence across all bands. While channel density doesn't strongly impact reliability or agreement, source localization methods produce systematically different functional connectivity, highlighting an important obstacle for replicating results in the literature. Most importantly, reliability and agreement often plateaus at or after 6 minutes of acquisition, well beyond the typical duration of 3 minutes. Finally, our study demonstrates that resting EEG can be as or more reliable than resting fMRI acquired in the same individuals.

Conclusions: The competitive reliability and agreement of power envelope connectivity greatly increases our confidence in measuring resting state connectivity using EEG and its capacity to find individual differences.

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http://dx.doi.org/10.1016/j.jneumeth.2021.109424DOI Listing

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