文章基本信息

标题：A resource for assessing dynamic binary choices in the adult brain using EEG and mouse-tracking
本地全文：下载
作者：Kun Chen ; Ruien Wang ; Jiamin Huang 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-10
DOI：10.1038/s41597-022-01538-5
语种：English
出版社：Nature Publishing Group
摘要：We present a dataset combining high-density Electroencephalography (HD-EEG, 128-channels) and mouse-tracking intended as a resource for examining the dynamic decision process of semantics and preference choices in the human brain . The dataset includes resting-state and task-related (food preference choices and semantic judgments) EEG acquired from 31 individuals (ages: 18–33) . Along with the dataset, we also provided the preliminary microstate analysis of resting-state EEG and the ERPs, topomap, and time-frequency maps of the task-related EEG . We believe that the simultaneous mouse- tracking and EEG recording would crack the core components of binary choices and further index the temporal dynamics of decision making and response hesitation . This publicly available dataset could support the development of neural signal processing methods in motor EEG, thus advancing research in both the decision neuroscience and brain-computer interface (BCI) applications .