As a novel measure for irregularity and complexity of the spontaneous fluctuations of brain activities, brain entropy (BEN) has attracted much attention in resting-state functional magnetic resonance imaging (rs-fMRI) studies during the last decade. Previous studies have shown its associations with cognitive and mental functions. While most previous research assumes BEN is approximately stationary during scan sessions, the brain, even at its resting state, is a highly dynamic system. Such dynamics could be characterized by a series of reoccurring whole-brain patterns related to cognitive and mental processes. The present study aims to explore the time-varying feature of BEN and its potential links with general cognitive ability. We adopted a sliding window approach to derive the dynamical brain entropy (dBEN) of the whole-brain functional networks from the HCP (Human Connectome Project) rs-fMRI dataset that includes 812 young healthy adults. The dBEN was further clustered into 4 reoccurring BEN states by the k-means clustering method. The fraction window (FW) and mean dwell time (MDT) of one BEN state, characterized by the extremely low overall BEN, were found to be negatively correlated with general cognitive abilities (i.e., cognitive flexibility, inhibitory control, and processing speed). Another BEN state, characterized by intermediate overall BEN and low within-state BEN located in DMN, ECN, and part of SAN, its FW, and MDT were positively correlated with the above cognitive abilities. The results of our study advance our understanding of the underlying mechanism of BEN dynamics and provide a potential framework for future investigations in clinical populations.

中文翻译：

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静息状态下的大脑熵动力学

作为一种测量大脑活动自发波动的不规则性和复杂性的新方法，脑熵（BEN）在过去十年中在静息态功能磁共振成像（rs-fMRI）研究中引起了广泛关注。先前的研究表明它与认知和心理功能有关。虽然大多数先前的研究都假设 BEN 在扫描期间大致静止，但大脑即使在静止状态也是一个高度动态的系统。这种动态的特征可以是一系列与认知和心理过程相关的重复出现的全脑模式。本研究旨在探讨 BEN 的时变特征及其与一般认知能力的潜在联系。我们采用滑动窗口方法从包含 812 名年轻健康成年人的 HCP（人类连接组计划）rs-fMRI 数据集中推导出全脑功能网络的动态脑熵 (dBEN)。通过 k 均值聚类方法将 dBEN 进一步聚类为 4 个重复出现的 BEN 状态。一种 BEN 状态的分数窗口 (FW) 和平均停留时间 (MDT) 以总体 BEN 极低为特征，被发现与一般认知能力（即认知灵活性、抑制控制和处理速度）呈负相关。另一种BEN状态，其特征是总体BEN处于中等水平，状态内BEN处于低水平，位于DMN、ECN和SAN的部分区域，其FW和MDT与上述认知能力呈正相关。我们的研究结果增进了我们对 BEN 动力学潜在机制的理解，并为未来临床人群的研究提供了潜在的框架。