Preschool College, Luoyang Normal University, Luoyang 471000, China; Center for Psychological Sciences, Zhejiang University, Hangzhou 310027, China.
Center for Psychological Sciences, Zhejiang University, Hangzhou 310027, China.
J Affect Disord. 2025 Jan 15;369:1099-1107. doi: 10.1016/j.jad.2024.10.066. Epub 2024 Oct 21.
Brain entropy (BEN) is a novel measure for irregularity and complexity of brain activities, which has been used to characterize abnormal brain activities in many brain disorders including attention-deficit/hyperactivity disorder (ADHD). While most research assumes BEN is stationary during scan sessions, the brain in resting state is also a highly dynamic system. The BEN dynamics in ADHD has not been explored.
We used a sliding window approach to derive the dynamical brain entropy (dBEN) from resting-state functional magnetic resonance imaging (rfMRI) dataset that includes 98 ADHD patients and 111 healthy controls (HCs). We identified 3 reoccurring BEN states. We tested whether the BEN dynamics differ between ADHD and HC, and whether they are associated with ADHD symptom severity.
One BEN states, characterized by low overall BEN and low within-state BEN located in SMN (sensorimotor network) and VN (visual network), its FW (fractional window) and MDT (mean dwell time) were increased in ADHD and positively correlated with ADHD severity; another state characterized by high overall BEN and low within-state BEN located in DMN (default mode network) and ECN (executive control network), its FW and MDT were decreased in ADHD and negatively correlated with ADHD severity.
The window length of dBEN analysis can be further optimized to suit more datasets. The co-variation between dBEN and other dynamical brain metrics was not explored.
Our findings revealed abnormal BEN dynamics in ADHD, providing new insights into clinical diagnosis and neuropathology of ADHD.
脑熵（BEN）是一种衡量大脑活动不规则性和复杂性的新指标，已被用于描述包括注意缺陷多动障碍（ADHD）在内的许多脑部疾病中的异常大脑活动。虽然大多数研究假设在扫描过程中 BEN 是静止的，但静息状态下的大脑也是一个高度动态的系统。ADHD 中的 BEN 动力学尚未得到探索。
我们使用滑动窗口方法从包括 98 名 ADHD 患者和 111 名健康对照者（HC）的静息态功能磁共振成像（rfMRI）数据集推导出动态脑熵（dBEN）。我们确定了 3 种反复出现的 BEN 状态。我们测试了 ADHD 和 HC 之间的 BEN 动力学是否存在差异，以及它们是否与 ADHD 症状严重程度有关。
一种 BEN 状态的特点是总体 BEN 低，位于 SMN（感觉运动网络）和 VN（视觉网络）的内部状态 BEN 低，其 FW（分数窗口）和 MDT（平均停留时间）在 ADHD 中增加，与 ADHD 严重程度呈正相关；另一种状态的特点是总体 BEN 高，位于 DMN（默认模式网络）和 ECN（执行控制网络）的内部状态 BEN 低，其 FW 和 MDT 在 ADHD 中降低，与 ADHD 严重程度呈负相关。
dBEN 分析的窗口长度可以进一步优化，以适应更多的数据集。dBEN 与其他动态大脑指标之间的共变关系尚未得到探索。
我们的研究结果揭示了 ADHD 中异常的 BEN 动力学，为 ADHD 的临床诊断和神经病理学提供了新的见解。
