fMRI时间序列中瞬态区域间耦合检测:一种结合主体间同步和聚类分析的新方法

Cécile Bordier, E. Macaluso
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引用次数: 1

摘要

提出了一种新的功能磁共振成像时间序列分析方法。目的是利用完全数据驱动的方法,识别与功能相关的大脑区域间耦合的短暂“爆发”。我们使用被试间同步(即不同被试的时间序列之间的相关性)来分离fMRI时间序列中的相关瞬变。接下来,我们应用第一个聚类分析,将以并发方式显示这种同步活动的区域分组在一起。最后,第二个聚类分析确定了fMRI信号在不同瞬态中一致重复的模式。分析的最终输出是一组网络,这些网络显示功能相关的fMRI信号的瞬态模式,在时间序列的特定窗口上保持一致。重要的是,fMRI信号可以在属于同一网络的不同区域之间有所不同。这种新方法特别适合于在功能磁共振成像中使用自然刺激来研究多组分控制过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Transient Inter-regional Coupling in fMRI Time Series: A New Method Combining Inter-subjects Synchronization and Cluster-Analyses
We present a new method for the analysis of fMRI time series. The aim is to identify functionally-relevant transient "bursts" of inter-regional coupling between brain areas, using a fully data-driven approach. We use inter-subjects synchronization (i.e. correlation between time series of different subjects who are presented with the same sensory input) to isolate relevant transients in the fMRI time series. Next, we apply a first cluster analysis to group together areas that show such synchronized activity in a concurrent manner. Finally, a second cluster analysis identifies patterns of the fMRI signal that repeat consistently across the different transients. The final output of the analysis is a set of networks that show transient patterns of functionally relevant fMRI signal, consistently over specific windows of the time series. Importantly, the fMRI signal can differ between different areas belonging to the same network. This new approach is particularly suited to investigate multi-components control processes using naturalistic stimuli during fMRI.
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