Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/35634
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dc.contributor.authorTurner, Christopheren_UK
dc.contributor.authorBaylan, Satuen_UK
dc.contributor.authorBracco, Martinaen_UK
dc.contributor.authorCruz, Gabrielaen_UK
dc.contributor.authorHanzal, Simonen_UK
dc.contributor.authorKeime, Marineen_UK
dc.contributor.authorKuye, Isaacen_UK
dc.contributor.authorMcNeill, Deborahen_UK
dc.contributor.authorNg, Zikaen_UK
dc.contributor.authorvan der Plas, Mirceaen_UK
dc.contributor.authorRuzzoli, Manuelaen_UK
dc.contributor.authorThut, Gregoren_UK
dc.contributor.authorTrajkovic, Jelenaen_UK
dc.contributor.authorVeniero, Domenicaen_UK
dc.contributor.authorWale, Sarah P.en_UK
dc.contributor.authorWhear, Sarahen_UK
dc.contributor.authorLearmonth, Gemmaen_UK
dc.date.accessioned2023-12-03T01:02:42Z-
dc.date.available2023-12-03T01:02:42Z-
dc.date.issued2023-08-10en_UK
dc.identifier.urihttp://hdl.handle.net/1893/35634-
dc.description.abstractStatistical 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.en_UK
dc.language.isoenen_UK
dc.publisherMIT Pressen_UK
dc.relationTurner C, Baylan S, Bracco M, Cruz G, Hanzal S, Keime M, Kuye I, McNeill D, Ng Z, van der Plas M, Ruzzoli M, Thut G, Trajkovic J, Veniero D, Wale SP, Whear S & Learmonth G (2023) Developmental changes in individual alpha frequency: Recording EEG data during public engagement events. <i>Imaging Neuroscience</i>, 1, pp. 1-14. https://doi.org/10.1162/imag_a_00001en_UK
dc.rights© 2023 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.en_UK
dc.titleDevelopmental changes in individual alpha frequency: Recording EEG data during public engagement eventsen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1162/imag_a_00001en_UK
dc.citation.jtitleImaging Neuroscienceen_UK
dc.citation.issn2837-6056en_UK
dc.citation.issn2837-6056en_UK
dc.citation.volume1en_UK
dc.citation.spage1en_UK
dc.citation.epage14en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderThe Wellcome Trusten_UK
dc.author.emailgemma.learmonth@stir.ac.uken_UK
dc.citation.date10/08/2023en_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationSorbonne Universityen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationBasque Science Foundationen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Nottinghamen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationPsychologyen_UK
dc.identifier.wtid1940726en_UK
dc.contributor.orcid0000-0003-4061-4464en_UK
dc.date.accepted2023-08-10en_UK
dcterms.dateAccepted2023-08-10en_UK
dc.date.filedepositdate2023-11-29en_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorTurner, Christopher|en_UK
local.rioxx.authorBaylan, Satu|en_UK
local.rioxx.authorBracco, Martina|en_UK
local.rioxx.authorCruz, Gabriela|en_UK
local.rioxx.authorHanzal, Simon|en_UK
local.rioxx.authorKeime, Marine|en_UK
local.rioxx.authorKuye, Isaac|en_UK
local.rioxx.authorMcNeill, Deborah|en_UK
local.rioxx.authorNg, Zika|en_UK
local.rioxx.authorvan der Plas, Mircea|en_UK
local.rioxx.authorRuzzoli, Manuela|en_UK
local.rioxx.authorThut, Gregor|en_UK
local.rioxx.authorTrajkovic, Jelena|en_UK
local.rioxx.authorVeniero, Domenica|en_UK
local.rioxx.authorWale, Sarah P.|en_UK
local.rioxx.authorWhear, Sarah|en_UK
local.rioxx.authorLearmonth, Gemma|0000-0003-4061-4464en_UK
local.rioxx.projectProject ID unknown|The Wellcome Trust|en_UK
local.rioxx.freetoreaddate2023-11-29en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/all-rights-reserved|2023-11-29|en_UK
local.rioxx.filenameDevelopmental changes in individual alpha frequency Recording EEG data.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source2837-6056en_UK
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