看电影时脑功能网络的同步高振幅共同波动

Jacob C. Tanner, Joshua Faskowitz, Lisa Byrge, Daniel P. Kennedy, Olaf Sporns, Richard F. Betzel
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引用次数: 0

摘要

最近的研究表明,功能连接可以分解为其精确的帧贡献,揭示短暂的、不频繁的和高振幅的时间点,即“事件”。事件对时间平均连接模式的贡献不成比例,提高了可识别性和大脑行为关联,并且它们的表达差异与内源性激素波动和自闭症有关。在这里,我们探讨的是被试观看电影时的事件特征。使用两个独立获取的图像数据集,参与者被动地观看电影,我们发现事件在个体之间同步,基于同步水平,可以分为三种不同的类型:在电影之间的边界同步的,在电影期间同步的,以及根本不同步的。我们发现,与其他类别相比,边界事件表现出更大的振幅,明显的共波动模式和时间传播。我们表明,潜在的边界事件1是一种特定的共涨落模式,涉及控制和突出系统的激活以及视觉系统的失活。另一方面,在电影期间同步的事件显示出一种与电影刺激时间锁定的共同波动模式。最后,我们发现受试者的时变大脑网络在这些同步事件中是最相似的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synchronous high-amplitude co-fluctuations of functional brain networks during movie-watching
Abstract Recent studies have shown that functional connectivity can be decomposed into its exact frame-wise contributions, revealing short-lived, infrequent, and high-amplitude time points referred to as “events.” Events contribute disproportionately to the time-averaged connectivity pattern, improve identifiability and brain-behavior associations, and differences in their expression have been linked to endogenous hormonal fluctuations and autism. Here, we explore the characteristics of events while subjects watch movies. Using two independently-acquired imaging datasets in which participants passively watched movies, we find that events synchronize across individuals and based on the level of synchronization, can be categorized into three distinct classes: those that synchronize at the boundaries between movies, those that synchronize during movies, and those that do not synchronize at all. We find that boundary events, compared to the other categories, exhibit greater amplitude, distinct co-fluctuation patterns, and temporal propagation. We show that underlying boundary events1 is a specific mode of co-fluctuation involving the activation of control and salience systems alongside the deactivation of visual systems. Events that synchronize during the movie, on the other hand, display a pattern of co-fluctuation that is time-locked to the movie stimulus. Finally, we found that subjects’ time-varying brain networks are most similar to one another during these synchronous events.
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