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| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Test-retest reliability of resting-state EEG in young and older adults |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Psychophysiology |
| Publisher | Wiley-Blackwell Publishing, Inc. |
| Geographical Reach | international |
| ISSN | 0048-5772 |
| Volume | 60 |
| Number | 7 |
| Page Range | e14268 |
| Date | 2023 |
| Abstract Text | 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. |
| Digital Object Identifier | 10.1111/psyp.14268 |
| PubMed ID | 36894751 |
| Other Identification Number | merlin-id:23904 |
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