School of Electrical, Electronic and Communications Engineering, University College Dublin, Ireland.
IEEE Trans Neural Syst Rehabil Eng. 2013 Mar;21(2):244-53. doi: 10.1109/TNSRE.2013.2241791.
Growing evidence suggests that synchronized neural oscillations in the cortico-basal ganglia network may play a critical role in the pathophysiology of Parkinson's disease. In this study, a new model of the closed loop network is used to explore the generation and interaction of network oscillations and their suppression through deep brain stimulation (DBS). Under simulated dopamine depletion conditions, increased gain through the hyperdirect pathway resulted in the interaction of neural oscillations at different frequencies in the cortex and subthalamic nucleus (STN), leading to the emergence of synchronized oscillations at a new intermediate frequency. Further increases in synaptic gain resulted in the cortex driving synchronous oscillatory activity throughout the network. When DBS was added to the model a progressive reduction in STN power at the tremor and beta frequencies was observed as the frequency of stimulation was increased, with resonance effects occurring for low frequency DBS (40 Hz) in agreement with experimental observations. The results provide new insights into the mechanisms by which synchronous oscillations can arise within the network and how DBS may suppress unwanted oscillatory activity.
越来越多的证据表明，皮质-基底节网络中的同步神经振荡可能在帕金森病的病理生理学中发挥关键作用。在这项研究中，使用新的闭环网络模型来探索网络振荡的产生和相互作用，以及通过深部脑刺激（DBS）来抑制它们。在模拟多巴胺耗竭的条件下，通过超直接通路增加增益会导致皮层和丘脑底核（STN）中不同频率的神经振荡相互作用，从而导致新的中间频率的同步振荡出现。进一步增加突触增益会导致皮层驱动整个网络的同步振荡活动。当将 DBS 添加到模型中时，随着刺激频率的增加，观察到 STN 在震颤和β频率处的功率逐渐降低，低频 DBS（40 Hz）会产生共振效应，这与实验观察结果一致。研究结果为同步振荡如何在网络中产生以及 DBS 如何抑制不需要的振荡活动提供了新的见解。
