Department of Health Technologies, School of Information Technology, Tallinn University of Technology, 5 Ehitajate Rd, 19086, Tallinn, Estonia.
Sci Rep. 2023 Apr 18;13(1):6307. doi: 10.1038/s41598-023-33364-z.
Mental disorders have an increasing tendency and represent the main burden of disease to society today. A wide variety of electroencephalographic (EEG) markers have been successfully used to assess different symptoms of mental disorders. Different EEG markers have demonstrated similar classification accuracy, raising a question of their independence. The current study is aimed to investigate the hypotheses that different EEG markers reveal partly the same EEG features reflecting brain functioning and therefore provide overlapping information. The assessment of the correlations between EEG signal frequency band power, dynamics, and functional connectivity markers demonstrates that a statistically significant correlation is evident in 37 of 66 (56%) comparisons performed between 12 markers of different natures. A significant correlation between the majority of the markers supports the similarity of information in the markers. The results of the performed study confirm the hypotheses that different EEG markers reflect partly the same features in brain functioning. Higuchi's fractal dimension has demonstrated a significant correlation with the 82% of other markers and is suggested to reveal a wide spectrum of various brain disorders. This marker is preferable in the early detection of symptoms of mental disorders.
精神障碍的发生率呈上升趋势,是当今社会的主要疾病负担。大量的脑电图(EEG)标志物已被成功用于评估精神障碍的不同症状。不同的 EEG 标志物已被证明具有相似的分类准确性,这引发了它们是否独立的问题。本研究旨在验证以下假设:不同的 EEG 标志物部分揭示了反映大脑功能的相同 EEG 特征,因此提供了重叠的信息。评估 EEG 信号频带功率、动力学和功能连接标记物之间的相关性表明,在对 12 种不同性质的标记物进行的 66 次(56%)比较中,有 37 次存在统计学显著相关性。大多数标记物之间的相关性表明标记物中存在相似的信息。所进行的研究结果证实了以下假设:不同的 EEG 标志物部分反映了大脑功能中的相同特征。Higuchi 的分形维数与 82%的其他标记物具有显著相关性,表明它可以揭示各种大脑障碍的广泛谱。该标志物更适合早期检测精神障碍的症状。