论文标题
对运动障碍的深度刺激：探索计算网络模型中频率依赖性功效
Deep brain stimulation for movement disorder treatment: Exploring frequency-dependent efficacy in a computational network model
论文作者
论文摘要
提出了基底神经节（BG）网络的大规模计算模型来描述包括深脑刺激（DBS）的运动障碍。这个复杂网络的模型考虑了基底神经节网络的四个区域：丘脑核（STN）作为DBS的目标区域，Globus Pallidus，PARS Externa和Pars Interna（GPE-GPI）（GPE-GPI）和丘脑（THA）。通过假设降低多巴胺能输入并相应的抑制性或对GPE和GPI的抑制作用来模拟帕金森氏症的情况。可以得出宏观数量，该量与丘脑反应密切相关，从而导致运动程序保真度。可以证明，根据对GPE和GPI的不同水平的纹状体投影，这些宏观数量的动力学从正常条件转移到帕金森氏症。在STN上模拟DBS会影响整个网络的动力学，将丘脑活性提高到接近正常水平，同时与正常和帕金森氏症动力学不同。使用上述宏观量，该模型提出的最佳DBS频率范围在130 Hz以上。
A large scale computational model of the basal ganglia (BG) network is proposed to describes movement disorder including deep brain stimulation (DBS). The model of this complex network considers four areas of the basal ganglia network: the subthalamic nucleus (STN) as target area of DBS, globus pallidus, both pars externa and pars interna (GPe-GPi), and the thalamus (THA). Parkinsonian conditions are simulated by assuming reduced dopaminergic input and corresponding pronounced inhibitory or disinhibited projections to GPe and GPi. Macroscopic quantities can be derived which correlate closely to thalamic responses and hence motor programme fidelity. It can be demonstrated that depending on different levels of striatal projections to the GPe and GPi, the dynamics of these macroscopic quantities switch from normal conditions to parkinsonian. Simulating DBS on the STN affects the dynamics of the entire network, increasing the thalamic activity to levels close to normal, while differing from both normal and parkinsonian dynamics. Using the mentioned macroscopic quantities, the model proposes optimal DBS frequency ranges above 130 Hz.
