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Updated: Jul 4, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

在BOLD fMRI中识别功能白质网络

Alexa L Eby, Lucas W Remedios, Michael E Kim

bioRxiv : the preprint server for biology

|February 8, 2024

概括

休息状态功能性MRI信号在白质中,经常被忽视,揭示大脑活动模式. 这些发现为阿尔茨海默氏症等神经系统疾病提供了潜在的早期标志物.

科学领域:

神经成像是一种神经成像.
白物质功能连接功能连接

背景情况:

静止状态BOLD-fMRI中的白质信号越来越被认为是大脑活动的指标.
了解这些信号可以了解大脑生理学和潜在的神经疾病早期标志物,如阿尔茨海默病.

研究的目的:

用静态fMRI数据调查白质内功能性大脑网络.
识别白质活动的稳定集群及其解剖和功能相关物.

主要方法:

使用了OASIS-3数据集,包括来自711名受试者的休息状态fMRI数据 (2,026张图像).
应用等级聚类到白物质内的声素级时间序列相关性.
使用Dice系数在扫描对扫描和主体对主体交叉验证中评估集群稳定性.

主要成果:

在4,9,13,18和24等级的功能集群中确定了局部最大稳定性.
较低的层次对应于明确定义的解剖叶.
更高层次的层次映射到功能区域,包括运动和记忆区域,在额叶,叶,叶和叶有显著覆盖.

结论:

使用静止状态fMRI的等级聚类揭示了白质内稳定的功能网络.
这些功能性白质网络显示了解剖学和功能相关性,可能作为神经疾病的生物标志物.

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