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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/26362
Title: Characterizing Population EEG Dynamics throughout Adulthood
Authors: Hashemi A
Pino LJ
Moffat G
Mathewson KJ
Aimone C
Bennett PJ
Schmidt LA
Sekuler AB
Department: Psychology, Neuroscience & Behaviour
Keywords: Big Data;EEG;Muse;age;alpha frequency;mindfulness;Adolescent;Adult;Aged;Aged, 80 and over;Aging;Brain;Brain Waves;Electroencephalography;Female;Humans;Judgment;Male;Meditation;Middle Aged;Mindfulness;Neuropsychological Tests;Sex Characteristics;Signal Processing, Computer-Assisted;Young Adult
Publication Date: Nov-2016
Publisher: Society for Neuroscience
Abstract: For decades, electroencephalography (EEG) has been a useful tool for investigating the neural mechanisms underlying human psychological processes. However, the amount of time needed to gather EEG data means that most laboratory studies use relatively small sample sizes. Using the Muse, a portable and wireless four-channel EEG headband, we obtained EEG recordings from 6029 subjects 18-88 years in age while they completed a category exemplar task followed by a meditation exercise. Here, we report age-related changes in EEG power at a fine chronological scale for δ, θ, α, and β bands, as well as peak α frequency and α asymmetry measures for both frontal and temporoparietal sites. We found that EEG power changed as a function of age, and that the age-related changes depended on sex and frequency band. We found an overall age-related shift in band power from lower to higher frequencies, especially for females. We also found a gradual, year-by-year slowing of the peak α frequency with increasing age. Finally, our analysis of α asymmetry revealed greater relative right frontal activity. Our results replicate several previous age- and sex-related findings and show how some previously observed changes during childhood extend throughout the lifespan. Unlike previous age-related EEG studies that were limited by sample size and restricted age ranges, our work highlights the advantage of using large, representative samples to address questions about developmental brain changes. We discuss our findings in terms of their relevance to attentional processes and brain-based models of emotional well-being and aging.
URI: http://hdl.handle.net/11375/26362
metadata.dc.identifier.doi: https://doi.org/10.1523/eneuro.0275-16.2016
ISSN: 2373-2822
2373-2822
Appears in Collections:Psychology, Neuroscience & Behaviour Publications

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