个体阿尔法频率的发展变化:在公众参与活动期间记录脑电图数据。

Imaging neuroscience (Cambridge, Mass.) Pub Date : 2023-08-10 eCollection Date: 2023-08-01 DOI:10.1162/imag_a_00001
Christopher Turner, Satu Baylan, Martina Bracco, Gabriela Cruz, Simon Hanzal, Marine Keime, Isaac Kuye, Deborah McNeill, Zika Ng, Mircea van der Plas, Manuela Ruzzoli, Gregor Thut, Jelena Trajkovic, Domenica Veniero, Sarah P Wale, Sarah Whear, Gemma Learmonth
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引用次数: 0

摘要

认知神经成像实验的统计能力通常很低。低样本量可以降低检测到真实效果(假阴性)的可能性,并增加偶然检测到不存在效果(假阳性)的风险。在这里,我们记录了我们利用一种相对未探索的方法收集大样本量进行简单脑电图(EEG)研究的经验:在公众参与和外联活动期间记录社区中的EEG。我们在当地科学节上收集了346名参与者(189名女性,年龄在6-76岁之间)的数据,为期6天,共计29小时。α活动(6-15 Hz)是从30秒的信号中过滤出来的,该信号是从放置在枕中线(Oz)和脑内(Iz)之间的单个电极记录的,同时参与者闭着眼睛休息。共获得289个高质量数据集。使用这种基于社区的方法,我们能够复制基于实验室的对照研究结果:个体α频率(IAF)在儿童时期增加,在28.1岁时达到10.28 Hz的峰值频率,在中老年时再次减慢。总α功率线性下降,但非周期性调整的α功率在使用寿命内没有变化。非周期性斜率和截距在最年轻的参与者中最高。通过多维疲劳量表测量,这些脑电图指标与自我报告的疲劳之间没有关联。最后,我们为希望在公众参与和外联环境中收集脑电图数据的研究人员提出了一系列重要考虑因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Developmental changes in individual alpha frequency: Recording EEG data during public engagement events.

Developmental changes in individual alpha frequency: Recording EEG data during public engagement events.

Developmental changes in individual alpha frequency: Recording EEG data during public engagement events.

Developmental changes in individual alpha frequency: Recording EEG data during public engagement events.

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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