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全脑层fMRI的获取和处理方法-VASO和BOLD:肯舒数据集

Kenshu Koiso^1,2, Anna K Müller¹, Kazuaki Akamatsu²

¹Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, NL.

|April 10, 2025

概括

研究人员开发了新的全脑层fMRI方法和协议,用于可靠的定向大脑连接分析. 这项工作提供了工具和数据集,以推进认知神经科学研究中的层级fMRI应用.

科学领域:

神经成像是一种神经成像.
认知神经科学认知神经科学
系统神经科学系统神经科学

背景情况:

层级fMRI为皮层网络中的定向神经信息流分析提供了潜力.
之前的研究证明了层级fMRI的原理证明,但缺乏可靠性和可重复性数据.
对于全脑层fMRI数据集的既定预处理方法目前无法使用.

研究的目的:

开发和验证用于神经科学研究中的常规全脑层fMRI的工具.
为了提高信号噪声比 (tSNR) 的效率和层级fMRI的测试-重新测试可靠性.
提供一个全面的数据集,用于对未来层级fMRI方法的发展进行基准测试.

主要方法:

开发并验证了全脑层fMRI的公开可用的序列,采集协议和处理管道.
在9名参与者中获得了超过60小时的扫描数据,以确保协议的稳定性.
创建了Kenshu数据集,包含20小时的多模式全脑层fMRI数据,来自于一个参与者在看电影时.

主要成果:

建立了可靠和可重复的全脑层fMRI协议,以最大限度地提高SNR效率.
证明了全脑层fMRI对各种认知神经科学分析的适用性,包括连接性和表示相似性.
在广泛的扫描会话中验证了开发的协议.

结论:

开发的工具和协议为常规的全脑层fMRI测量铺平了道路.
肯舒数据集是推进层级fMRI方法和应用的宝贵资源.
这项工作有助于对整个大脑的定向功能连接进行常规测量.

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