Agnihotri Sandeep Kumar, Cai Jiang
Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai 519031, China.
Brain Sci. 2024 Jul 29;14(8):767. doi: 10.3390/brainsci14080767.
Transcranial electrical brain stimulation techniques like transcranial direct current (tDCS) and transcranial alternating current (tACS) have emerged as potential tools for treating neurological diseases by modulating cortical excitability. These techniques deliver small electric currents to the brain non-invasively through electrodes on the scalp. tDCS uses constant direct current which weakly alters the membrane voltage of cortical neurons, while tACS utilizes alternating current to target and enhance cortical oscillations, though the underlying mechanisms are not fully understood more specifically. To elucidate how tACS perturbs endogenous network dynamics, we simulated spiking neuron network models. We identified distinct roles of the depolarizing and hyperpolarizing phases in driving network activity towards and away from the strong nonlinearity provided by pyramidal neurons. Exploring resonance effects, we found matching tACS frequency to the network's endogenous resonance frequency creates greater entrainment. Based on this, we developed an algorithm to determine the network's endogenous frequency, phase, and amplitude, then deliver optimized tACS to entrain network oscillations. Together, these computational results provide mechanistic insight into the effects of tACS on network dynamics and could inform future closed-loop tACS systems that dynamically tune stimulation parameters to ongoing brain activity.
经颅直流电刺激（tDCS）和经颅交流电刺激（tACS）等经颅电刺激技术已成为通过调节皮层兴奋性来治疗神经系统疾病的潜在工具。这些技术通过头皮上的电极将小电流无创地输送到大脑。tDCS使用恒定直流电，微弱地改变皮层神经元的膜电压，而tACS利用交流电来靶向并增强皮层振荡，不过其具体潜在机制尚未完全明确。为了阐明tACS如何干扰内源性网络动力学，我们模拟了脉冲神经元网络模型。我们确定了去极化和超极化阶段在驱动网络活动趋向和远离由锥体神经元提供的强非线性方面的不同作用。通过探索共振效应，我们发现使tACS频率与网络的内源性共振频率匹配会产生更大的同步。基于此，我们开发了一种算法来确定网络的内源性频率、相位和幅度，然后提供优化的tACS以同步网络振荡。这些计算结果共同为tACS对网络动力学的影响提供了机制性见解，并可为未来根据持续的脑活动动态调整刺激参数的闭环tACS系统提供参考。
