可穿戴式脑磁图数据记录在人体行走

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Meaghan E. Spedden , George C. O’Neill , Timothy O. West , Tim M. Tierney , Stephanie Mellor , Nicholas A. Alexander , Robert Seymour , Jesper Lundbye-Jensen , Jens Bo Nielsen , Simon F. Farmer , Sven Bestmann , Gareth R. Barnes
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引用次数: 0

摘要

大规模全身运动过程中大脑活动的非侵入性时空成像是运动神经科学领域的一个重要方法论挑战。在这里,我们提出了一个使用新的成像方式-光泵脑磁图(OP-MEG)记录的数据集,以记录人类行走过程中的大脑活动。参与者(n=3)执行视觉引导的步进任务,要求精确放置足部,同时记录双轴和三轴OP-MEG和腿部肌肉活动(肌电图,EMG)。该数据集还包括每个参与者的结构MRI和足部运动学。这个多模态数据集为OPM数据的方法论开发和测试(例如,运动相关的干扰抑制)、受试者内分析和探索性分析提供了资源,为进一步研究人类行走的神经控制工作提供了假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wearable MEG data recorded during human stepping
Non-invasive spatiotemporal imaging of brain activity during large-scale, whole body movement is a significant methodological challenge for the field of movement neuroscience. Here, we present a dataset recorded using a new imaging modality – optically-pumped magnetoencephalography (OP-MEG) – to record brain activity during human stepping. Participants (n=3) performed a visually guided stepping task requiring precise foot placement while dual-axis and triaxial OP-MEG and leg muscle activity (electromyography, EMG) were recorded. The dataset also includes a structural MRI for each participant and foot kinematics. This multimodal dataset offers a resource for methodological development and testing for OPM data (e.g., movement-related interference rejection), within-subject analyses, and exploratory analyses to generate hypotheses for further work on the neural control of human stepping.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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