Test–retest reliability of resting‐state EEG in young and older adults

Abstract

The quantification of resting‐state electroencephalography (EEG) is associated with a variety of measures. These include power estimates at different frequencies, microstate analysis, and frequency‐resolved source power and connectivity analyses. Resting‐state EEG metrics have been widely used to delineate the manifestation of cognition and to identify psychophysiological indicators of age‐related cognitive decline. The reliability of the utilized metrics is a prerequisite for establishing robust brain–behavior relationships and clinically relevant indicators of cognitive decline. To date, however, test–retest reliability examination of measures derived from resting human EEG, comparing different resting‐state measures between young and older participants, within the same adequately powered dataset, is lacking. The present registered report examined test–retest reliability in a sample of 95 young (age range: 20–35 years) and 93 older (age range: 60–80 years) participants. A good‐to‐excellent test–retest reliability was confirmed in both age groups for power estimates on both scalp and source levels as well as for the individual alpha peak power and frequency. Partial confirmation was observed for hypotheses stating good‐to‐excellent reliability of microstates measures and connectivity. Equal levels of reliability between the age groups were confirmed for scalp‐level power estimates and partially so for source‐level power and connectivity. In total, five out of the nine postulated hypotheses were empirically supported and confirmed good‐to‐excellent reliability of the most commonly reported resting‐state EEG metrics.

Test-retest reliability of spectral parameterization by 1/fcharacterization usingSpecParam

“…Furthermore, ICC for young adult resting-state recordings of the aperiodic exponent approximately 30 minutes apart are good to excellent (ICC's .78 -.93) over frontal, central, parietal, and occipital regions of interest (ROI), and when using parameterization settings that limit non-neural artifact by excluding high beta and gamma activity (Pathania et al 2021). This appears to be consistent after 1 week even in the presence of major drivers of between-subject variance, such as age (Popov et al 2023). Nevertheless, other aspects of parameterized periodic activity (e.g., central frequencies of periodic activity) need to be considered as PSYCHOMETRIC ANALYSIS OF SPECTRAL PARAMETERIZATION 8 well as the reliability of the SpecParam model to fit across a nonrestricted frequency range.…”

“…All techniques and measurement instruments require good psychometrics to be useful for understanding individual or group differences, yet little is known about the psychometric properties of EEG following parameterization techniques. As measures of EEG activity in the absence of parameterization (i.e., total periodic activity; Gasser et al 1985;Popov et al 2023) has traditionally been employed to assess psychometric properties of EEG, only recently the psychometric properties of periodic activity been assessed following parameterization (i.e., parameterized periodic activity; Levin et al 2020;Pathania et al 2021) while also focusing on aperiodic activity (Levin et al 2020;Pathania et al 2021;Popov et al 2023;Trondle et al 2023;Webb et al 2023). This is PSYCHOMETRIC ANALYSIS OF SPECTRAL PARAMETERIZATION 4 integral to our understanding of EEG correlates of neural activity, as aperiodic activity conflates all periodic activity in each frequency band.…”

Sensorimotor brain-computer interface performance depends on signal-to-noise ratio but not connectivity of the mu rhythm in a multiverse analysis of longitudinal data

“…Therefore, on average, task-related modulation of the mu rhythm may not have a cumulative effect across many sessions. In addition, Popov et al (2023) have also reported an excellent (ICC = 0.83) test-retest reliability of the periodic component of the alpha power in the sensorimotor regions. While this finding goes in line with the absence of longitudinal changes in SNR in the analyzed dataset, there still was a within-subject effect of SNR on BCI performance.…”

Pallidal Recordings in Chronically Implanted Dystonic Patients: Mitigation of Tremor-Related Artifacts

“…Second, we used relatively short recordings, with lengths ranging from one to four minutes. Nevertheless, this was considered sufficient to calculate power and coherence measurements, as Popov et al have observed good to excellent test-retest reliability of resting-state power and coherence in a large sample based on recordings that were just 100 s long [ 71 ]. Potential biases of coherence on recording length [ 72 ] were not addressed here, as all statistical comparisons were performed within subjects on data of the same length.…”