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Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study

机译:全脑连接动力学反映了任务特定和个人特定调制:多任务研究

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Functional connectivity (FC) has been widely used to study the functional organization of temporally correlated and spatially distributed brain regions. Recent studies of FC dynamics, quantified by windowed correlations, provide new insights to analyze dynamic, context-dependent reconfiguration of brain networks. A set of reoccurring whole-brain connectivity patterns at rest, referred to as FC states, have been identified, hypothetically reflecting underlying cognitive processes or mental states. We posit that the mean FC information for a given subject represents a significant contribution to the group-level FC dynamics. We show that the subject-specific FC profile, termed as FC individuality, can be removed to increase sensitivity to cognitively relevant FC states. To assess the impact of the FC individuality and task-specific FC modulation on the group-level FC dynamics analysis, we generate and analyze group studies of four subjects engaging in four cognitive conditions (rest, simple math, two-back memory, and visual attention task). We also propose a model to quantitatively evaluate the effect of two factors, namely, subject-specific and task-specific modulation on FC dynamics. We show that FC individuality is a predominant factor in group-level FC variability, and the embedded cognitively relevant FC states are clearly visible after removing the individual's connectivity profile. Our results challenge the current understanding of FC states and emphasize the importance of individual heterogeneity in connectivity dynamics analysis.
机译:功能连接(FC)已被广泛用于研究时间上相关和空间分布的脑区的功能组织。最近对窗口相关性量化的FC动态的研究提供了新的见解来分析脑网络的动态,上下文相关重新配置。已经确定了一系列重新忽视的全脑连接模式,称为FC态,假设反映了潜在的认知过程或精神状态。我们对给定主题的平均FC信息表示对组级FC动态的显着贡献。我们表明,可以去除作为FC个性称为FC个性的特定主题的FC型材,以提高对认知相关的FC态的敏感性。为了评估FC个性和任务特定的FC调制对集团级FC动力学分析的影响,我们生成和分析了四个主题的组研究,参与了四个认知条件(休息,简单的数学,反复记忆和视觉注意任务)。我们还提出了一种模型来定量评估两个因素的效果,即对FC动态的主题特定和任务特定调制。我们表明,FC个性是组级FC变异性的主要因素,并且在移除个人的连接配置文件后,嵌入的认知相关的FC状态清晰可见。我们的成果挑战目前对FC态的理解,并强调各种异质性在连通动力学分析中的重要性。

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