多发性硬化症中EEG信号的多重分形组织
Multifractal organization of EEG signals in Multiple Sclerosis
AI总结：
本研究对多发性硬化症患者的EEG信号进行多重分形分析，发现信号多重分形程度与残疾水平显著相关，与病程无关，提示其是疾病进展的标志，可能源于神经元代偿机制。
摘要：
量化脑信号的复杂/多重分形组织对于充分理解大脑过程和结构至关重要。在本研究中，我们对一项受控多发性硬化症（MS）研究中获得的脑电图（EEG）数据进行了多重分形分析，重点关注多重分形程度、病程与残疾水平之间的相关性。我们的结果揭示了时间序列复杂性与多发性硬化症进展之间存在显著对应关系，分别通过标度指数和扩展残疾状态量表（EDSS）进行量化。具体而言，在部分脑区中，高残疾水平患者的时间序列表现出充分发展的多重分形性和低持续性，而对照组和低EDSS患者的信号则以持续性和单分形性为特征。对EEG信号间互相关性的分析支持了这些结果，其中EDSS>1的患者组与EDSS≤1的患者联合对照组之间的差异最为显著。研究未观察到多重分形性与病程之间存在关联，这表明数据的多重分形组织是疾病进展的标志。观察到的EEG信号复杂性/多重分形性被假设为神经元代偿的结果——即在大脑结构发生退行性变的情况下优化神经过程。由于本研究采用多重分形形式体系来量化复杂性，且目前关于与代偿相关的皮层重组的静息态EEG证据较为匮乏，因此该研究具有高度相关性。
英文摘要：
Quantifying the complex/multifractal organization of the brain signals is crucial to fully understanding the brain processes and structure. In this contribution, we performed the multifractal analysis of the electroencephalographic (EEG) data obtained from a controlled multiple sclerosis (MS) study, focusing on the correlation between the degree of multifractality, disease duration, and disability level. Our results reveal a significant correspondence between the complexity of the time series and multiple sclerosis development, quantified respectively by scaling exponents and the Expanded Disability Status Scale (EDSS). Namely, for some brain regions, a well-developed multifractality and little persistence of the time series were identified in patients with a high level of disability, whereas the control group and patients with low EDSS were characterised by persistence and monofractality of the signals. The analysis of the cross-correlations between EEG signals supported these results, with the most significant differences identified for patients with EDSS $> 1$ and the combined group of patients with EDSS $\leq 1$ and controls. No association between the multifractality and disease duration was observed, indicating that the multifractal organisation of the data is a hallmark of developing the disease. The observed complexity/multifractality of EEG signals is hypothetically a result of neuronal compensation -- i.e., of optimizing neural processes in the presence of structural brain degeneration. The presented study is highly relevant due to the multifractal formalism used to quantify complexity and due to scarce resting-state EEG evidence for cortical reorganization associated with compensation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
