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一种用于基底神经节-丘脑-皮质振荡活动的动力学模型及其在帕金森病中的意义。

A dynamical model for the basal ganglia-thalamo-cortical oscillatory activity and its implications in Parkinson's disease.

作者信息

Navarro-López Eva M, Çelikok Utku, Şengör Neslihan S

机构信息

School of Mathematics and Computer Science, Faculty of Science and Engineering, University of Wolverhampton, Alan Turing Building, Wulfruna Street, Wolverhampton, WV1 1LY UK.

Biomedical Engineering Department, Boğaziçi University, 34342 Beşiktaş, Istanbul Turkey.

出版信息

Cogn Neurodyn. 2021 Aug;15(4):693-720. doi: 10.1007/s11571-020-09653-y. Epub 2020 Nov 25.

Abstract

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.

摘要

我们提议通过一种新颖的基底神经节、皮层和丘脑网络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调节所有基底神经节核团活动中的影响、基底神经节 - 丘脑 - 皮层回路的自组织神经元相互依存活动以及皮层下背景振荡的产生。黑质致密部神经元产生的多巴胺量的变化在帕金森病的发病以及基底神经节动作选择中均起着关键作用。我们对这些多巴胺诱导的关系进行建模,帕金森状态被解释为与基底神经节 - 丘脑 - 皮层网络振荡活动模式的不同节律相关的自发涌现行为。这些结果具有重要意义,原因如下:(1)神经群体基于经过精心设计以具有电生理现实反应的单神经元模型构建;(2)我们的模型独特地将皮层下结构中的振荡活动变化、基底神经节中的多巴胺水平以及与帕金森状态兼容的病理性同步神经元模式联系起来,这仍然是一个未解决的问题,对于更好地理解疾病进展至关重要。

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