休息期间的高分辨率EEG数据集和在左下视野的局部视觉刺激
Takayuki Onojima1,2,3, Keiichi Kitajo1,4,5
1Rhythm-based Brain Information Processing Unit, CBS-TOYOTA Collaboration Center, RIKEN Center for Brain Science, Japan.
Data in brief
|January 21, 2026
概括
已有健康成年人观看视觉刺激的高时间分辨率电脑电图 (EEG) 数据. 这一数据集可以研究视觉处理,事件相关潜力和大脑活动横向化.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 生物医学工程 生物医学工程
背景情况:
- 脑电图 (EEG) 对于研究大脑活动至关重要.
- 了解视觉处理需要高时间分辨率的数据.
- 像BIDS这样的标准化数据格式提高了数据共享和可重复性.
研究的目的:
- 提供健康成年人的高时间分辨率EEG数据集.
- 促进对视觉唤起潜力和大脑侧面化的研究.
- 为EEG数据提供可重复的分析管道.
主要方法:
- 收集了来自8名健康成年人的10,000赫兹EEG数据.
- 使用了64通道的actiCAP微型系统和Bittium NeurOne特斯拉放大器.
- 在眼睛开放休息和局部视觉刺激期间记录的数据 (棋盘模式).
主要成果:
- 根据大脑成像数据结构 (BIDS v1.9.0) 组织的数据集.
- 包括带有全面元数据的原始BrainVision文件.
- 为不同的对比度提供行为反应和事件注释.
结论:
- 该数据集支持对早期视觉唤起潜力的详细分析.
- 能够调查振荡相位对齐和半球横向化.
- MNE-Python脚本促进可重现的事件相关潜力和时间频率分析.
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