Amy Romanello, Nina von Schwanenflug, Michelle Franka, Friedemann Paul, Harald Prüss, Stephan Krohn, Carsten Finke
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引用次数: 0
Abstract
Functional connectivity (FC) quantifies the temporal coherence of blood-oxygen-level-dependent (BOLD) signals across brain regions. Recently, the information-theoretic "complexome" framework has linked FC to coinciding "complexity drops": transient moments in which regional BOLD signals simultaneously become regular. Here, we replicate this relationship in an independent dataset and extend the framework by (a) integrating it with signal cofluctuation analysis; (b) extending the previous binary concept of simultaneous complexity drops to a continuous, threshold-free calculation based on a temporal unwrapping procedure; (c) providing evidence of clinical relevance in the model disease of anti-N-methyl-D-aspartate-receptor encephalitis; and (d) deriving a new measure of pairwise dissimilarity in local BOLD patterns. This "index of pattern incongruency" (IPI) explains clinically relevant FC reductions and maps onto distinct associations with cognition beyond FC. These findings show that global FC is closely related to local patterns within underlying BOLD signals, strengthening the link between complexity dynamics and the brain's functional organization as a large-scale network.
功能连通性(FC)量化了脑区血氧水平依赖性(BOLD)信号的时间一致性。最近,信息论的“复杂体”框架将FC与重合的“复杂性下降”联系起来:区域BOLD信号同时变得有规则的瞬间。在这里,我们在一个独立的数据集中复制这种关系,并通过(a)将其与信号共波动分析相结合来扩展框架;(b)将先前的同时复杂性下降的二元概念扩展为基于时间展开过程的连续的无阈值计算;(c)提供抗n -甲基- d -天冬氨酸受体脑炎模型疾病的临床相关性证据;(d)推导出局部BOLD模式成对不相似性的新度量。这种“模式不一致指数”(IPI)解释了临床相关的FC减少,并映射出与FC之外的认知的独特关联。这些发现表明,全局FC与潜在BOLD信号中的局部模式密切相关,从而加强了复杂性动力学与大脑功能组织作为一个大规模网络之间的联系。