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Abstract：
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.
摘要：
作为一种新颖的测量大脑活动自发波动的不规则性和复杂性的方法，在过去的十年中，脑熵（BEN）在静息状态功能磁共振成像（rs-fMRI）研究中引起了很多关注。先前的研究表明其与认知和心理功能有关。虽然大多数先前的研究假设BEN在扫描会话期间大致是静止的，大脑,即使在它的静止状态，是一个高度动态的系统。这种动态可以通过一系列与认知和心理过程相关的重复出现的全脑模式来表征。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。我们采用了滑动窗口方法，从包含812名年轻健康成年人的HCP（人类Connectome项目）rs-fMRI数据集中得出全脑功能网络的动态脑熵（dBEN）。通过k均值聚类方法将dBEN进一步聚类成4个重复出现的BEN状态。一个BEN状态的分数窗口(FW)和平均停留时间(MDT)，以极低的整体BEN为特征，被发现与一般认知能力呈负相关(即，认知灵活性，抑制控制，和处理速度)。另一个BEN州,以位于DMN中的中间总体BEN和低内部状态BEN为特征，ECN,和SAN的一部分，其FW,MDT与上述认知能力呈正相关。我们的研究结果促进了我们对BEN动力学的潜在机制的理解，并为临床人群的未来研究提供了潜在的框架。
