Mobile Brain-Body Imaging (MoBI) dual-tasking datasets (response inhibition while walking): Young adults

Combining walking with a demanding cognitive task is traditionally expected to elicit decrements in gait and/or cognitive task performance. However, it was recently shown that, in a cohort of young adults, most participants improved performance when walking was added to performance of a Go/NoGo response inhibition task. The present study aims to extend these previous findings to an older adult cohort, to investigate whether this improvement when dual-tasking is observed in healthy older adults. Mobile Brain/Body Imaging (MoBI) was used to record electroencephalographic (EEG) activity, three-dimensional (3D) gait kinematics and behavioral responses in the Go/NoGo task, during sitting or walking on a treadmill, in 34 young adults and 37 older adults. Increased response accuracy during walking, independent of age, was found to correlate with slower responses to stimuli (r = 0.44) and with walking-related EEG amplitude modulations over frontocentral regions (r = 0.47) during the sensory gat..., This dataset was collected using the Mobile Brain-Body Imaging modality, involving synchronous recordings of 3 data streams: 1) EEG (BioSemi Inc., Amsterdam, The Netherlands) 2) Behavioral responses to the designed Go/NoGo task (Presentation, Neurobehavioral Systems Inc., Berkeley, CA, USA) 3) Full-body kinematics (OptiTrack, NaturalPoint, Inc., Corvallis, OR, USA). To record these 3 data streams in a time-synchronized manner, the Lab Streaming Layer (LSL: https://labstreaminglayer.org/#/) was used. The data included are raw, except for the behavior-related logfiles, for which both raw and processed versions are provided (see README file for details)., The .mat files in the \"LSLData\" subfolders require MATLAB (MathWorks Inc., Natick, MA, USA) to open. An open-source alternative to open them is using Python (see https://www.askpython.com/python/examples/mat-files-in-python) The .set and .fdt files in the \"EEGstruct_Raw\" subfolders require EEGLAB, which is an open-source MATLAB toolbox for electrophysiological signal processing and analysis (https://sccn.ucsd.edu/eeglab/index.php). Alternatively, they can be opened using MNE, which is an open-source MATLAB toolbox for electrophysiological signal processing and analysis (https://mne.tools/dev/generated/mne.io.read_raw_eeglab.html). The .txt and .log files in the \"Logiles_Raw\" and \"Logfiles_Processed\" subfolders can be opened using any text editor. The metadata.xlsx file can be opened using Microsoft Excel. Alternatively, LibreOffice (https://www.libreoffice.org/), which is free and open-source, can be used. , # Title of Dataset Mobile Brain-Body Imaging (MoBI) dual-tasking datasets (response inhibition while walking): Young adults ## Description of the data and file structure This Drayd dataset contains multimodal MoBI data, collected from young adults while performing the 1-back Go/NoGo response inhibition task and concurrently walking on a treadmill. The data is organized as follows: ``` |-- 010705001 | |-- LSLData | | |-- 010705001.mat | |-- Logfiles_Raw | | |-- GoNoGo_010705001.txt | | |-- mainExperScript_010705001.log | | |-- motion_state_010705001.txt | | |-- Training_GoNoGo_010705001.txt | |-- Logfiles_Processed | | |-- GoNoGo_010705001_processed.txt | | |-- mainExperScript_010705001_processed.txt | |-- EEGstruct_Raw | | |-- 010705001.set | | |-- 010705001.fdt |-- 010705002 | |-- LSLData | | |-- 010705002.mat | |-- Logfiles_Raw | | |-- GoNoGo_010705002.txt | | |-- mainExperScript_010705002.log | |...传统观点认为，将行走与高要求认知任务相结合，会导致步态和/或认知任务表现下降。但近期一项针对年轻成年人队列的研究显示，当受试者在完成Go/NoGo响应抑制任务（Go/NoGo response inhibition task）时加入行走任务，多数参与者的任务表现反而提升。本研究旨在将该既往发现推广至老年成年人队列，以探究健康老年群体中是否也存在双任务（dual-tasking）范式下的表现改善现象。本研究使用移动脑体成像（Mobile Brain/Body Imaging, MoBI）技术，记录了34名年轻成年人与37名老年成年人在坐姿或跑步机行走状态下完成Go/NoGo任务时的脑电图（electroencephalographic, EEG）活动、三维（three-dimensional, 3D）步态运动学数据与行为反应数据。研究发现，无论年龄如何，行走状态下的响应准确率提升均与刺激响应延迟（相关系数r=0.44）以及感觉门控阶段额中央脑区与行走相关的脑电波幅调制（相关系数r=0.47）存在相关性…… 本数据集采用移动脑体成像模态采集，包含三路同步记录的数据： 1. 脑电图（EEG）设备：BioSemi公司（荷兰阿姆斯特丹） 2. 定制Go/NoGo任务的行为反应数据：采用Presentation设备（美国加州伯克利Neurobehavioral Systems公司） 3. 全身运动学数据：OptiTrack设备（美国俄勒冈州科瓦利斯NaturalPoint公司）。 为实现三路数据的时间同步采集，本研究使用了实验室流层（Lab Streaming Layer, LSL，https://labstreaminglayer.org/#/）技术。 本次公开的数据均为原始数据，仅行为相关日志文件同时提供原始与处理后版本（详细说明请参阅README文件）。 "LSLData"子文件夹中的.mat格式文件需使用MATLAB软件（美国马萨诸塞州纳提克MathWorks公司）打开，开源替代方案为使用Python读取（参考https://www.askpython.com/python/examples/mat-files-in-python）。 "EEGstruct_Raw"子文件夹中的.set与.fdt格式文件需使用EEGLAB工具箱打开——EEGLAB是一款开源的MATLAB脑电信号处理与分析工具箱（https://sccn.ucsd.edu/eeglab/index.php）；也可使用MNE工具箱打开，MNE同样是开源的脑电信号处理与分析工具箱（https://mne.tools/dev/generated/mne.io.read_raw_eeglab.html）。 "Logiles_Raw"与"Logfiles_Processed"子文件夹中的.txt与.log格式文件可通过任意文本编辑器打开。 metadata.xlsx文件可使用Microsoft Excel打开，开源免费替代方案为LibreOffice（https://www.libreoffice.org/）。 # 数据集标题 移动脑体成像（MoBI）双任务数据集（行走时的响应抑制任务）：年轻成年人队列 ## 数据与文件结构说明 本Drayd数据集包含多模态MoBI数据，采集自完成1回溯（1-back）Go/NoGo响应抑制任务并同时在跑步机上行走的年轻成年人。 数据组织形式如下： |-- 010705001 | |-- LSLData | | |-- 010705001.mat | |-- Logfiles_Raw | | |-- GoNoGo_010705001.txt | | |-- mainExperScript_010705001.log | | |-- motion_state_010705001.txt | | |-- Training_GoNoGo_010705001.txt | |-- Logfiles_Processed | | |-- GoNoGo_010705001_processed.txt | | |-- mainExperScript_010705001_processed.txt | |-- EEGstruct_Raw | | |-- 010705001.set | | |-- 010705001.fdt |-- 010705002 | |-- LSLData | | |-- 010705002.mat | |-- Logfiles_Raw | | |-- GoNoGo_010705002.txt | | |-- mainExperScript_010705002.log | |...