Chernykh Mariia, Zyma Ihor, Vodianyk Bohdan, Subin Yaroslav, Seleznov Ivan, Popov Anton, Kiyono Ken
Department of Physiology and Anatomy, Educational and Scientific Center "Institute of Biology and Medicine", Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.
School of Engineering, University of Málaga, Málaga, Spain.
Front Hum Neurosci. 2025 Jun 18;19:1571477. doi: 10.3389/fnhum.2025.1571477. eCollection 2025.
Cognitive disturbances following COVID-19 have been widely reported, yet the neural dynamics underpinning such phenomena remain incompletely understood. This exploratory study examined cortical neurodynamics using electroencephalographic (EEG) analysis in three groups: individuals with severe COVID-19 (Group S), individuals recovered from moderate COVID-19 (Group M), and healthy controls (Group H). EEG recordings were obtained during the resting state and exposure to three odorants-ammonia (trigeminal), isoamyl acetate (olfactory), and mountain pine (mixed)-to assess reactivity under different sensory conditions. Power Spectral Density (PSD) and detrended moving average (DMA) analyses were applied to quantify both spectral power and long-range temporal correlations, respectively. Group S showed consistently elevated -band PSD and -scaling exponent values across all conditions, indicative of globally rigid and hyperexcitable dynamics. Group M exhibited partially recovered oscillatory patterns, including α3 enhancements, without statistically significant stimulus-driven modulation. Group H maintained physiologically typical EEG responses with limited olfactory reactivity. While these results suggest differential patterns of neurodynamic adaptation and rigidity among groups, interpretations regarding cognitive status remain tentative due to the absence of behavioral or neuropsychological testing. The findings underscore the utility of DMA as a complementary EEG analysis tool and provide a basis for hypothesis-driven research on post-COVID cortical reorganization. Future studies incorporating direct cognitive measures are essential to validate EEG-based biomarkers of brain function.
新型冠状病毒肺炎(COVID-19)后的认知障碍已被广泛报道,但支撑此类现象的神经动力学仍未完全明了。这项探索性研究使用脑电图(EEG)分析,对三组人群的皮质神经动力学进行了研究:患有重症COVID-19的个体(S组)、从中度COVID-19康复的个体(M组)和健康对照者(H组)。在静息状态以及暴露于三种气味剂——氨(三叉神经刺激)、乙酸异戊酯(嗅觉刺激)和山松(混合刺激)——期间进行EEG记录,以评估不同感觉条件下的反应性。分别应用功率谱密度(PSD)分析和去趋势移动平均(DMA)分析来量化频谱功率和长程时间相关性。S组在所有条件下均显示出频段PSD和标度指数值持续升高,表明整体动力学僵硬且兴奋性过高。M组表现出部分恢复的振荡模式,包括α3增强,且无统计学上显著的刺激驱动调制。H组保持生理上典型的EEG反应,嗅觉反应性有限。虽然这些结果表明各组之间存在神经动力学适应和僵硬的不同模式,但由于缺乏行为或神经心理学测试,关于认知状态的解释仍具有不确定性。这些发现强调了DMA作为一种补充性EEG分析工具的实用性,并为COVID-19后皮质重组的假设驱动研究提供了基础。纳入直接认知测量的未来研究对于验证基于EEG的脑功能生物标志物至关重要。