Imaging NeuroscienceNeurosciencePeer-reviewed journal article
Developmental changes in individual alpha frequency: Recording EEG data during public engagement events
Christopher TurneriD, Satu BaylaniD, Martina BraccoiD, Gabriela CruziD, Simon HanzaliD, Marine Keime, Isaac Kuye, Deborah C. McNeill, Zika NgiD, Mircea van der PlasiD, Manuela RuzzoliiD, Gregor ThutiD, Jelena TrajkoviciD, Domenica VenieroiD, Sarah P. Wale, Sarah Whear, Gemma LearmonthiD
Abstract
Statistical power in cognitive neuroimaging experiments is often very low. Low sample size can reduce the likelihood of detecting real effects (false negatives) and increase the risk of detecting non-existing effects by chance (false positives). Here we document our experience of leveraging a relatively unexplored method of collecting a large sample size for simple electroencephalography (EEG) studies: by recording EEG in the community during public engagement and outreach events. We collected data from 346 participants (189 females, age range 6-76 years) over 6 days, totalling 29 hours, at local science festivals. Alpha activity (6-15 Hz) was filtered from 30 seconds of signal, recorded from a single electrode placed between the occipital midline (Oz) and inion (Iz) while participants rested with their eyes closed. A total of 289 good quality datasets were obtained. Using this community-based approach, we were able to replicate controlled, lab-based findings: IAF increased during childhood, reaching a peak frequency of 10.28 Hz at 28.1 years old, and slowed again in middle and older age. Total alpha power decreased linearly, but the aperiodic-adjusted alpha power did not change over the lifespan. Aperiodic slopes and intercepts were highest in the youngest participants. There were no associations between these EEG indexes and self-reported fatigue, measured by the Multidimensional Fatigue Inventory. Finally, we present a set of important considerations for researchers who wish to collect EEG data within public engagement and outreach environments.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 32
- FWCI
- 4.80
- Field percentile
- top 4%
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