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Detection of Transient Inter-regional Coupling in fMRI Time Series: A New Method Combining Inter-subjects Synchronization and Cluster-Analyses

机译:fMRI时间序列中瞬时区域间耦合的检测:受试者间同步和聚类分析相结合的新方法

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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.
机译:我们提出了一种分析功能磁共振成像时间序列的新方法。目的是使用完全数据驱动的方法来识别大脑区域之间区域间耦合的功能相关的瞬时“突发”。我们使用受试者之间的同步(即呈现相同感觉输入的不同受试者的时间序列之间的相关性)来隔离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行方式显示此类同步活动的区域分组在一起。最后,第二个聚类分析确定了功能磁共振成像信号的模式,这些模式在不同的瞬态之间一致地重复。分析的最终输出是一组网络,这些网络在时间序列的特定窗口上始终显示功能相关的fMRI信号的瞬态模式。重要的是,fMRI信号在属于同一网络的不同区域之间可能会有所不同。这种新方法特别适合于在fMRI期间使用自然刺激研究多组分控制过程。

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