Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States.
Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States.
J Comput Neurosci. 2022 Aug;51(3):361-380. doi: 10.1007/s10827-023-00853-z. Epub 2023 Jun 2.
Parkinson's disease (PD) and animal models of PD feature enhanced oscillations in several frequency bands in the basal ganglia (BG). Past research has emphasized the enhancement of 13-30 Hz beta oscillations. Recently, however, oscillations in the delta band (0.5-4 Hz) have been identified as a robust predictor of dopamine loss and motor dysfunction in several BG regions in mouse models of PD. In particular, delta oscillations in the substantia nigra pars reticulata (SNr) were shown to lead oscillations in motor cortex (M1) and persist under M1 lesion, but it is not clear where these oscillations are initially generated. In this paper, we use a computational model to study how delta oscillations may arise in the SNr due to projections from the globus pallidus externa (GPe). We propose a network architecture that incorporates inhibition in SNr from oscillating GPe neurons and other SNr neurons. In our simulations, this configuration yields firing patterns in model SNr neurons that match those measured in vivo. In particular, we see the spontaneous emergence of near-antiphase active-predicting and inactive-predicting neural populations in the SNr, which persist under the inclusion of STN inputs based on experimental recordings. These results demonstrate how delta oscillations can propagate through BG nuclei despite imperfect oscillatory synchrony in the source site, narrowing down potential targets for the source of delta oscillations in PD models and giving new insight into the dynamics of SNr oscillations.
帕金森病(PD)和 PD 的动物模型在基底神经节(BG)中表现出几个频带的增强振荡。过去的研究强调了 13-30 Hz 贝塔振荡的增强。然而,最近,在 PD 小鼠模型的几个 BG 区域中,已经确定了 delta 波段(0.5-4 Hz)的振荡是多巴胺损失和运动功能障碍的一个强有力的预测指标。特别是,在黑质网状部(SNr)中的 delta 振荡被证明可以导致运动皮层(M1)的振荡,并在 M1 损伤下持续存在,但尚不清楚这些振荡最初是在哪里产生的。在本文中,我们使用计算模型来研究 delta 振荡如何由于来自苍白球外部(GPe)的投射而在 SNr 中产生。我们提出了一种网络架构,该架构包含来自振荡 GPe 神经元和其他 SNr 神经元的 SNr 抑制。在我们的模拟中,这种配置产生的模型 SNr 神经元的放电模式与体内测量的模式相匹配。特别是,我们看到了在 SNr 中自发出现的近反相活动预测和非活动预测的神经元群体,这些群体在基于实验记录的 STN 输入的包含下仍然存在。这些结果表明,尽管在源站点存在不完美的振荡同步性,delta 振荡如何在 BG 核中传播,缩小了 PD 模型中 delta 振荡源的潜在目标,并为 SNr 振荡的动力学提供了新的见解。