Agnihotri Sandeep Kumar, Cai Jiang, Wang Zhen
Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, 519031, Guangdong, China.
Heliyon. 2024 Dec 7;10(24):e41034. doi: 10.1016/j.heliyon.2024.e41034. eCollection 2024 Dec 30.
Transcranial electrical stimulation (tES), including transcranial alternating current stimulation (tACS) and transcranial direct current stimulation (tDCS), is widely studied for its potential to modulate brain oscillations and connectivity, offering treatment options for neurological disorders like Alzheimer's, Parkinson's, and insomnia. In this study, we focus on investigating the efficacy of tACS and tDCS in entraining intrinsic cortical network oscillations through a computational model.
We developed a 2D computational cortical neuron model with 2000 neurons (1600 pyramidal and 400 inhibitory), based on the Izhikevich neuron model. The network was structured to generate low-frequency oscillations, particularly within the delta (4 Hz) range. Both tACS and tDCS were simulated to assess their effect on network synchronization. An algorithm was employed to extract the network's intrinsic frequency and align stimulation frequencies accordingly.
Our model successfully generated 4 Hz oscillations, characteristic of delta waves, associated with sleep states. t-ACS stimulation enhanced the power of the 4 Hz frequency, achieving effective synchronization with the intrinsic network dynamics. In contrast, tDCS failed to increase the power of 4 Hz oscillations and disrupted the excitatory-inhibitory balance of the network, reducing connectivity and synchronization. Our results demonstrate that tACS effectively enhances network synchronization and maintains excitatory-inhibitory balance by aligning with the network's intrinsic oscillatory frequency. In contrast, tDCS disrupts these dynamics, reducing connectivity and failing to entrain the target frequency. These findings suggest that tACS may hold greater potential for applications requiring precise network synchronization, while tDCS may have distinct but more limited efficacy in influencing oscillatory activity.
The study demonstrates the superior efficacy of tACS over tDCS in enhancing the synchronization of cortical networks by entraining intrinsic frequencies. Future research may extend this model by incorporating long-term plasticity mechanisms to better understand tES effects over longer time scales.
经颅电刺激(tES),包括经颅交流电刺激(tACS)和经颅直流电刺激(tDCS),因其调节脑振荡和连接性的潜力而受到广泛研究,为阿尔茨海默病、帕金森病和失眠等神经系统疾病提供了治疗选择。在本研究中,我们专注于通过计算模型研究tACS和tDCS在诱导内在皮质网络振荡方面的功效。
我们基于Izhikevich神经元模型开发了一个具有2000个神经元(1600个锥体神经元和400个抑制性神经元)的二维计算皮质神经元模型。该网络被构建为产生低频振荡,特别是在δ(4Hz)范围内。对tACS和tDCS进行了模拟,以评估它们对网络同步的影响。采用一种算法提取网络的固有频率,并相应地调整刺激频率。
我们的模型成功产生了与睡眠状态相关的、具有δ波特征的4Hz振荡。t-ACS刺激增强了4Hz频率的功率,实现了与内在网络动力学的有效同步。相比之下,tDCS未能增加4Hz振荡的功率,破坏了网络的兴奋-抑制平衡,降低了连接性和同步性。我们的结果表明,tACS通过与网络的固有振荡频率对齐,有效地增强了网络同步并维持了兴奋-抑制平衡。相比之下,tDCS破坏了这些动力学,降低了连接性,并且未能诱导目标频率。这些发现表明,tACS在需要精确网络同步的应用中可能具有更大的潜力,而tDCS在影响振荡活动方面可能具有独特但更有限的功效。
该研究证明了tACS在通过诱导固有频率增强皮质网络同步方面优于tDCS。未来的研究可以通过纳入长期可塑性机制来扩展该模型,以更好地理解tES在更长时间尺度上的影响。