一个高分辨率的7特斯拉静态fMRI数据集,优化用于研究皮质下皮层
Josephine M Groot1,2, Steven Miletic1,3, Scott J S Isherwood1
1Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, the Netherlands.
Data in brief
|July 24, 2024
概括
这项研究提供了来自56名健康成年人的高分辨率全脑静止状态fMRI数据. 先进的7特斯拉成像协议增强了皮质下血液氧气水平依赖的信号检测,用于详细的脑力学研究.
科学领域:
- 神经成像是一种神经成像.
- 人类大脑动态 人类大脑动态
- 磁共振成像是一种磁共振成像技术.
背景情况:
- 了解自发大脑活动需要对皮质和皮质下区域进行全脑成像.
- 先进的功能磁共振成像 (fMRI) 技术对于详细的人类大脑研究至关重要.
研究的目的:
- 为了呈现高分辨率的全脑静止状态fMRI (rs-fMRI) 数据,在7特斯拉获得.
- 提供针对皮下血液氧气水平依赖 (BOLD) 信号分析优化的数据.
主要方法:
- 从56名健康成年人获得了7特斯拉的rs-fMRI数据,具有1.5毫米的同位素分辨率.
- 使用多频段回声平面成像 (EPI) 具有较短的回声时间,以提高BOLD灵敏度.
- 收集了用于噪声校正的并发生理数据,并将数据格式化为脑成像数据结构 (BIDS).
主要成果:
- 获得了高质量的全脑fMRI数据,空间分辨率优异.
- 该协议显示了最佳的BOLD灵敏度,特别是在皮层下区域.
- 功能和结构数据被共同注册并使用fMRIPrep进行预处理,以便共享数据.
结论:
- 提出的7 Tesla rs-fMRI数据集为研究人类大脑动态提供了宝贵的资源.
- 数据的高空间分辨率和优化下皮层灵敏度有助于进行详细的调查.
- 这一数据集支持神经科学和脑成像领域的广泛研究应用.
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