Bristol Centre for Complexity Sciences, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK.
Eur J Neurosci. 2012 Jul;36(2):2229-39. doi: 10.1111/j.1460-9568.2012.08105.x.
A key pathology in the development of Parkinson's disease is the occurrence of persistent beta oscillations, which are correlated with difficulty in movement initiation. We investigated the network model composed of the subthalamic nucleus (STN) and globus pallidus (GP) developed by A. Nevado Holgado et al. [(2010) Journal of Neuroscience, 30, 12340-12352], who identified the conditions under which this circuit could generate beta oscillations. Our work extended their analysis by deriving improved analytic stability conditions for realistic values of the synaptic transmission delay between STN and GP neurons. The improved conditions were significantly closer to the results of simulations for the range of synaptic transmission delays measured experimentally. Furthermore, our analysis explained how changes in cortical and striatal input to the STN-GP network influenced oscillations generated by the circuit. As we have identified when a system of mutually connected populations of excitatory and inhibitory neurons can generate oscillations, our results may also find applications in the study of neural oscillations produced by assemblies of excitatory and inhibitory neurons in other brain regions.
帕金森病发展过程中的一个关键病理学特征是持续β振荡的发生,这与运动起始困难有关。我们研究了由 A. Nevado Holgado 等人开发的由丘脑底核(STN)和苍白球(GP)组成的网络模型[(2010)《神经科学杂志》,30,12340-12352],他们确定了该电路在什么条件下可以产生β振荡。我们的工作通过推导出 STN 和 GP 神经元之间突触传递延迟的实际值的改进分析稳定性条件,扩展了他们的分析。改进后的条件与实验测量的突触传递延迟范围内的模拟结果更接近。此外,我们的分析解释了皮质和纹状体对 STN-GP 网络的输入变化如何影响电路产生的振荡。正如我们已经确定了相互连接的兴奋性和抑制性神经元群体的系统如何产生振荡一样,我们的结果也可能在研究其他脑区由兴奋性和抑制性神经元集合产生的神经振荡方面得到应用。