ArticleImaging neuroscience (Cambridge, Mass.)2023
Developmental changes in individual alpha frequency: Recording EEG data during public engagement events.
Article in Imaging neuroscience (Cambridge, Mass.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Electrophysiological correlates of cognitive reserve in healthy older adults at different cognitive states.Cognitive, affective & behavioral neuroscience · 2026Article
- An Exploratory Age-Adjusted Model of Individual Alpha Peak Frequency in Healthy Older Adults: A FOOOF-Based Spectral Parametrization Study.European journal of investigation in health, psychology and education · 2026Article
- Widening participation in cognitive neuroscience: a mixed-methods study of age-related motivators, barriers and attitudes towards imaging methods.BMC medical research methodology · 2026Article
- Lifespan development of EEG alpha and aperiodic component sources is shaped by the connectome and axonal delays.National science review · 2026Article
- How to Improve the Reliability of Aperiodic Parameter Estimates in M/EEG: A Method Comparison.Psychophysiology · 2026Article
- Alpha oscillations are dysrhythmic in Fragile X syndrome.bioRxiv : the preprint server for biology · 2026Article
- A meta-analysis of periodic and aperiodic electrophysiological features in Parkinson's disease.Brain communications · 2026Review
- How to Improve the Reliability of Aperiodic Parameter Estimates in M/EEG: A Method Comparison and Recommendations for Best Practices.bioRxiv : the preprint server for biology · 2025Article
- Neural Correlates of Restless Legs Syndrome (RLS) Based on Electroencephalogram (EEG)-A Mechanistic Review.International journal of molecular sciences · 2025Review
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- Multi-centre normative brain mapping of intracranial EEG lifespan patterns in the human brain.Brain structure & function · 2025Article
- No significant relationship found between spontaneous motor tempo, heartbeat, and individual alpha frequency: an analysis of internal tempos.Scientific reports · 2025Article
- Article
- Age differences in motivation drive performance during the sustained attention to response task.PloS one · 2025Article
- Pilot Study of Personalized Transcranial Magnetic Stimulation with Spectral Electroencephalogram Analyses for Assessing and Treating Persons with Autism.Journal of personalized medicine · 2024Article
- Brain health in diverse settings: How age, demographics and cognition shape brain function.NeuroImage · 2024Article
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Authors and funding
17 authors.
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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 the 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: individual alpha frequency (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.
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