Wang Kun, Wei Aili, Fu Yu, Wang Tianhui, Gao Xiujie, Fu Bo, Zhu Yingwen, Cui Bo, Zhu Mengfu
Institute of Medical Support Technology, Academy of Military Science of Chinese PLA, Tianjin, China.
Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China.
Front Neuroinform. 2022 Aug 23;16:968907. doi: 10.3389/fninf.2022.968907. eCollection 2022.
Rhythmic light flickers have emerged as useful tools to modulate cognition and rescue pathological oscillations related to neurological disorders by entrainment. However, a mechanistic understanding of the entrainment for different brain oscillatory states and light flicker parameters is lacking. To address this issue, we proposed a biophysical neural network model for thalamocortical oscillations (TCOs) and explored the stimulation effects depending on the thalamocortical oscillatory states and stimulation parameters (frequency, intensity, and duty cycle) using the proposed model and electrophysiology experiments. The proposed model generated alpha, beta, and gamma oscillatory states (with main oscillation frequences at 9, 25, and 35 Hz, respectively), which were successfully transmitted from the thalamus to the cortex. By applying light flicker stimulation, we found that the entrainment was state-dependent and it was more prone to induce entrainment if the flicker perturbation frequency was closer to the endogenous oscillatory frequency. In addition, endogenous oscillation would be accelerated, whereas low-frequency oscillatory power would be suppressed by gamma (30-50 Hz) flickers. Notably, the effects of intensity and duty cycle on entrainment were complex; a high intensity of light flicker did not mean high entrainment possibility, and duty cycles below 50% could induce entrainment easier than those above 50%. Further, we observed entrainment discontinuity during gamma flicker stimulations with different frequencies, attributable to the non-linear characteristics of the network oscillations. These results provide support for the experimental design and clinical applications of the modulation of TCOs by gamma (30-50 Hz) light flicker.
节律性光闪烁已成为通过同步来调节认知并挽救与神经系统疾病相关的病理性振荡的有用工具。然而，对于不同脑振荡状态和光闪烁参数的同步机制尚缺乏了解。为了解决这个问题，我们提出了一个用于丘脑皮质振荡（TCOs）的生物物理神经网络模型，并使用该模型和电生理实验探索了取决于丘脑皮质振荡状态和刺激参数（频率、强度和占空比）的刺激效果。所提出的模型产生了α、β和γ振荡状态（主要振荡频率分别为9、25和35Hz），这些振荡状态成功地从丘脑传递到了皮质。通过应用光闪烁刺激，我们发现同步是状态依赖性的，并且如果闪烁扰动频率更接近内源性振荡频率，则更易于诱导同步。此外，内源性振荡会加速，而γ（30 - 50Hz）闪烁会抑制低频振荡功率。值得注意的是，强度和占空比对同步的影响很复杂；高光闪烁强度并不意味着高同步可能性，并且低于50%的占空比比高于50%的占空比更容易诱导同步。此外，我们在不同频率的γ闪烁刺激期间观察到同步的不连续性，这归因于网络振荡的非线性特征。这些结果为通过γ（30 - 50Hz）光闪烁调节TCOs的实验设计和临床应用提供了支持。
