We propose to investigate brain electrophysiological alterations associated with Parkinson’s disease through a novel adaptive dynamical model of the network of the basal ganglia, the cortex and the thalamus. The model uniquely unifies the influence of dopamine in the regulation of the activity of all basal ganglia nuclei, the self-organised neuronal interdependent activity of basal ganglia-thalamo-cortical circuits and the generation of subcortical background oscillations. Variations in the amount of dopamine produced in the neurons of the substantia nigra pars compacta are key both in the onset of Parkinson’s disease and in the basal ganglia action selection. We model these dopamine-induced relationships, and Parkinsonian states are interpreted as spontaneous emergent behaviours associated with different rhythms of oscillatory activity patterns of the basal ganglia-thalamo-cortical network. These results are significant because: (1) the neural populations are built upon single-neuron models that have been robustly designed to have eletrophysiologically-realistic responses, and (2) our model distinctively links changes in the oscillatory activity in subcortical structures, dopamine levels in the basal ganglia and pathological synchronisation neuronal patterns compatible with Parkinsonian states, this still remains an open problem and is crucial to better understand the progression of the disease.

我们建议通过基底神经节、皮质和丘脑网络的新型自适应动力学模型来研究与帕金森病相关的脑电生理改变。该模型独特地统一了多巴胺在所有基底神经节核活动调节中的影响、基底神经节-丘脑-皮质回路的自组织神经元相互依赖活动以及皮质下背景振荡的产生。黑质致密部神经元中产生的多巴胺量的变化是帕金森病发作和基底神经节动作选择的关键。我们模拟这些多巴胺诱导的关系，帕金森状态被解释为与基底神经节-丘脑-皮质网络的振荡活动模式的不同节律相关的自发性突发行为。这些结果很重要，因为：（1）神经群体建立在单神经元模型上，这些模型经过精心设计，具有电生理学上的真实反应，（2）我们的模型将皮层下结构的振荡活动的变化与多巴胺水平明显联系起来在与帕金森状态兼容的基底神经节和病理同步神经元模式中，这仍然是一个悬而未决的问题，对于更好地了解疾病的进展至关重要。