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健康成年人视觉认知动机研究的同步脑电图-功能近红外光谱数据集。

A simultaneous EEG-fNIRS dataset of the visual cognitive motivation study in healthy adults.

作者信息

Phukhachee Tustanah, Angsuwatanakul Thanate, Iramina Keiji, Kaewkamnerdpong Boonserm

机构信息

Computer Engineering Department, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand.

College of Biomedical Engineering, Rangsit University, Pathum Thani 12000, Thailand.

出版信息

Data Brief. 2024 Feb 27;53:110260. doi: 10.1016/j.dib.2024.110260. eCollection 2024 Apr.

DOI:10.1016/j.dib.2024.110260
PMID:38533112
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10964074/
Abstract

This article described a publicly available dataset of the visual cognitive motivation study in healthy adults. To gain an in-depth understanding and insights into motivation, Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) were measured simultaneously at shared locations while participants performed a visual cognitive motivation task. The participants' choices in the cognitive motivation task were recorded. The effects of their motivation were identified in the recognition test afterward. This dataset comprised EEG and fNIRS data from sixteen healthy adults (age: 21- 37 years; 14 males and 2 females) during the cognitive motivation task with visual scenic stimuli. In addition, the motivation and the corresponding motivation effect were also provided. This dataset provides understanding and analyzing opportunities for the process of attention and decision while the brain undergoes an induced motivated state and its effect on the recognition performance.

摘要

本文描述了一个公开可用的健康成年人视觉认知动机研究数据集。为了深入理解和洞察动机,在参与者执行视觉认知动机任务时,在共享位置同时测量脑电图(EEG)和功能近红外光谱(fNIRS)。记录参与者在认知动机任务中的选择。随后在识别测试中确定他们动机的影响。该数据集包括16名健康成年人(年龄:21 - 37岁;14名男性和2名女性)在视觉场景刺激的认知动机任务期间的EEG和fNIRS数据。此外,还提供了动机及相应的动机效果。该数据集为大脑处于诱发的动机状态时的注意力和决策过程及其对识别性能的影响提供了理解和分析机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/258d/10964074/35323c6e5ef1/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/258d/10964074/65db10770392/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/258d/10964074/069788e57679/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/258d/10964074/35323c6e5ef1/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/258d/10964074/65db10770392/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/258d/10964074/069788e57679/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/258d/10964074/35323c6e5ef1/gr3.jpg

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Sensors (Basel). 2022 Aug 5;22(15):5865. doi: 10.3390/s22155865.
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Multiscale Entropy as a New Feature for EEG and fNIRS Analysis.多尺度熵作为脑电图和功能近红外光谱分析的新特征
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