Li Qiang, Wang Hanxuan, Zhang Rui
The Medical Big Data Research Center, Northwest University, Xi'an, 710127 China.
The Health Science Center, Xi'an Jiaotong University, Xi'an, 710049 China.
Cogn Neurodyn. 2025 Dec;19(1):17. doi: 10.1007/s11571-024-10207-9. Epub 2025 Jan 9.
Insomnia, as a common sleep disorder, is the most common complaints in medical practice affecting a large proportion of the population on a situational, recurrent or chronic basis. It has been demonstrated that, during wakefulness, patients with insomnia exhibit increased EEG power in theta, beta, and gamma band. However, the relevant mechanisms underlying such power changes are still lack of understanding. In this paper, by combining the neural computational model with the real EEG data, we focus on exploring what's behind the EEG power changes for insomniac. We first develop a modified Liley model, named FSR-Liley, by respectively considering the fast and slow synaptic responses in inhibitory neurons along with the one-way projection between them. Then we introduce a parameter selection and evaluation method based on Markov chain Monte Carlo algorithm and Wasserstein distance, by which the sensitive parameters are selected automatically, and meanwhile, the optimal values of selected parameters are evaluated. Finally, through combining with EEG data, we determine the sensitive parameters in FSR-Liley and accordingly provide the mechanistic hypotheses: (1) decrease in , corresponding to the input from the thalamus to cortical inhibitory population with fast synaptic response, leads to the increased theta and beta power; (2) decrease in , corresponding to the projection from cortical excitatory population to inhibitory population with fast synaptic response, causes the increased gamma power. The results in this paper provide insights into the mechanisms of EEG power changes in insomnia and establish a theoretical foundation to support further experimental research.
失眠作为一种常见的睡眠障碍,是医学实践中最常见的主诉,在情境性、复发性或慢性基础上影响着很大一部分人群。已经证明,在清醒状态下,失眠患者在θ波、β波和γ波频段的脑电图功率增加。然而,这种功率变化背后的相关机制仍不清楚。在本文中,通过将神经计算模型与实际脑电图数据相结合,我们专注于探索失眠患者脑电图功率变化背后的原因。我们首先通过分别考虑抑制性神经元中的快速和慢速突触反应以及它们之间的单向投射,开发了一种改进的Liley模型,称为FSR-Liley。然后我们引入了一种基于马尔可夫链蒙特卡罗算法和瓦瑟斯坦距离的参数选择和评估方法,通过该方法自动选择敏感参数,同时评估所选参数的最优值。最后,通过与脑电图数据相结合,我们确定了FSR-Liley中的敏感参数,并据此提出了机制假设:(1) 对应于从丘脑到具有快速突触反应的皮质抑制性群体的输入的 减少,导致θ波和β波功率增加;(2) 对应于从皮质兴奋性群体到具有快速突触反应的抑制性群体的投射的 减少,导致γ波功率增加。本文的结果为失眠脑电图功率变化的机制提供了见解,并为支持进一步的实验研究奠定了理论基础。