Test-retest reliability of spectral parameterization by 1/f characterization using SpecParam

Daniel J McKeown*, Anna J Finley, Nicholas J Kelley, James F Cavanagh, Hannah A D Keage, Oliver Baumann, Victor R Schinazi, Ahmed A Moustafa, Douglas J Angus

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

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Abstract

SpecParam (formally known as FOOOF) allows for the refined measurements of electroencephalography periodic and aperiodic activity, and potentially provides a non-invasive measurement of excitation: inhibition balance. However, little is known about the psychometric properties of this technique. This is integral for understanding the usefulness of SpecParam as a tool to determine differences in measurements of cognitive function, and electroencephalography activity. We used intraclass correlation coefficients to examine the test-retest reliability of parameterized activity across three sessions (90 minutes apart and 30 days later) in 49 healthy young adults at rest with eyes open, eyes closed, and during three eyes closed cognitive tasks including subtraction (Math), music recall (Music), and episodic memory (Memory). Intraclass correlation coefficients were good for the aperiodic exponent and offset (intraclass correlation coefficients > 0.70) and parameterized periodic activity (intraclass correlation coefficients > 0.66 for alpha and beta power, central frequency, and bandwidth) across conditions. Across all three sessions, SpecParam performed poorly in eyes open (40% of participants had poor fits over non-central sites) and had poor test-retest reliability for parameterized periodic activity. SpecParam mostly provides reliable metrics of individual differences in parameterized neural activity. More work is needed to understand the suitability of eyes open resting data for parameterization using SpecParam.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalCerebral Cortex
Early online date14 Dec 2023
DOIs
Publication statusPublished - Jan 2024

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