Oscillatory neural activity in the cortico-basal ganglia-thalamocortical (CBGTC) loop is associated with the motor state of a subject, but also with the availability of modulatory neurotransmitters. For example, increased low-frequency oscillations in Parkinson’s disease (PD) are related to decreased levels of dopamine and have been proposed as biomarkers to adapt and optimize therapeutic interventions, such as deep brain stimulation. Using neural oscillations as biomarkers require differentiating between changes in oscillatory patterns associated with parkinsonism vs. those related to a subject’s motor state. To address this point, we studied the correlation between neural oscillatory activity in the motor cortex and striatum and varying degrees of motor activity under normal and parkinsonian conditions. Using rats with bilateral or unilateral 6-hydroxydopamine lesions as PD models, we correlated the motion index (MI)—a measure based on the physical acceleration of the head of rats—to the local field potential (LFP) oscillatory power in the 1–80 Hz range. In motor cortices and striata, we observed a robust correlation between the motion index and the oscillatory power in two main broad frequency ranges: a low-frequency range [5.0–26.5 Hz] was negatively correlated to motor activity, whereas a high-frequency range [35.0–79.9 Hz] was positively correlated. We observed these correlations in both normal and parkinsonian conditions. In addition to these general changes in broad-band power, we observed a more restricted narrow-band oscillation [25–40 Hz] in dopamine-denervated hemispheres. This oscillation, which seems to be selective to the parkinsonian state, showed a linear frequency dependence on the concurrent motor activity level. We conclude that, independently of the parkinsonian condition, changes in broad-band oscillatory activities of cortico-basal ganglia networks (including changes in the relative power of low- and high-frequency bands) are closely correlated to ongoing motions, most likely reflecting he operations of these neural circuits to control motor activity. Hence, biomarkers based on neural oscillations should focus on specific features, such as narrow frequency bands, to allow differentiation between parkinsonian states and physiological movement-dependent circuit modulation.

中文翻译：

---

皮质-纹状体振荡与生理和帕金森病患者的运动活动水平相关

皮质-基底节-丘脑皮质 (CBGTC) 回路中的振荡神经活动与受试者的运动状态有关，但也与调节性神经递质的可用性有关。例如，帕金森病 (PD) 中低频振荡的增加与多巴胺水平降低有关，并已被提议作为生物标志物来适应和优化治疗干预，例如深部脑刺激。使用神经振荡作为生物标志物需要区分与帕金森病相关的振荡模式的变化与与受试者运动状态相关的振荡模式的变化。为了解决这一点，我们研究了运动皮层和纹状体中的神经振荡活动与正常和帕金森病条件下不同程度的运动活动之间的相关性。使用双侧或单侧 6-羟基多巴胺病变的大鼠作为 PD 模型，我们将运动指数 (MI)（一种基于大鼠头部物理加速度的测量）与 1– 局部场电位 (LFP) 振荡功率相关联。 80 赫兹范围。在运动皮层和纹状体中，我们观察到运动指数和振荡功率在两个主要频率范围内的强相关性：低频范围 [5.0-26.5 Hz] 与运动活动呈负相关，而高频范围[35.0–79.9 Hz] 呈正相关。我们在正常和帕金森病条件下都观察到了这些相关性。除了宽带功率的这些一般变化之外，我们还在多巴胺去神经支配的半球中观察到了更受限的窄带振荡 [25-40 Hz]。这种振荡，这似乎对帕金森状态有选择性，显示出对并发运动活动水平的线性频率依赖性。我们得出结论，独立于帕金森病，皮质基底节网络宽带振荡活动的变化（包括低频段和高频段相对功率的变化）与正在进行的运动密切相关，最有可能反映了他这些神经回路的运作来控制运动活动。因此，基于神经振荡的生物标志物应侧重于特定特征，例如窄频带，以区分帕金森病状态和生理运动依赖的电路调制。皮质基底节网络宽带振荡活动的变化（包括低频段和高频段相对功率的变化）与正在进行的运动密切相关，最有可能反映了这些神经回路控制运动活动的操作。因此，基于神经振荡的生物标志物应侧重于特定特征，例如窄频带，以区分帕金森病状态和生理运动依赖的电路调制。皮质基底节网络宽带振荡活动的变化（包括低频段和高频段相对功率的变化）与正在进行的运动密切相关，最有可能反映了这些神经回路控制运动活动的操作。因此，基于神经振荡的生物标志物应侧重于特定特征，例如窄频带，以区分帕金森病状态和生理运动依赖的电路调制。