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帕金森病中的异常学习:关于运动徐缓的神经计算研究。

Aberrant learning in Parkinson's disease: A neurocomputational study on bradykinesia.

机构信息

Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy.

出版信息

Eur J Neurosci. 2018 Jun;47(12):1563-1582. doi: 10.1111/ejn.13960. Epub 2018 Jun 12.

DOI:10.1111/ejn.13960
PMID:29786160
Abstract

Parkinson's disease (PD) is a neurodegenerative disorder characterized by a progressive decline in motor functions, such as bradykinesia, caused by the pathological denervation of nigrostriatal dopaminergic neurons within the basal ganglia (BG). It is acknowledged that dopamine (DA) directly affects the modulatory role of BG towards the cortex. However, a growing body of literature is suggesting that DA-induced aberrant synaptic plasticity could play a role in the core symptoms of PD, thus recalling for a "reconceptualization" of the pathophysiology. The aim of this work was to investigate DA-driven aberrant learning as a concurrent cause of bradykinesia, using a comprehensive, biologically inspired neurocomputational model of action selection in the BG. The model includes the three main pathways operating in the BG circuitry, that is the direct, indirect and hyperdirect pathways, and use a two-term Hebb rule to train synapses in the striatum, based on previous history of rewards and punishments. Levodopa pharmacodynamics is also incorporated. Through model simulations of the Alternate Finger Tapping motor task, we assessed the role of aberrant learning on bradykinesia. The results show that training under drug medication (levodopa) provides not only immediate but also delayed benefit lasting in time. Conversely, if performed in conditions of vanishing levodopa efficacy, training may result in dysfunctional corticostriatal synaptic plasticity, further worsening motor performances in PD subjects. This suggests that bradykinesia may result from the concurrent effects of low DA levels and dysfunctional plasticity and that training can be exploited in medicated subjects to improve levodopa treatment.

摘要

帕金森病(PD)是一种神经退行性疾病,其特征是运动功能逐渐下降,如运动迟缓,这是由于基底神经节(BG)内黑质纹状体多巴胺能神经元的病理性去神经支配引起的。人们已经认识到,多巴胺(DA)直接影响 BG 对皮质的调节作用。然而,越来越多的文献表明,DA 诱导的异常突触可塑性可能在 PD 的核心症状中发挥作用,从而需要对其病理生理学进行“重新概念化”。这项工作的目的是使用 BG 中动作选择的综合、受生物启发的神经计算模型,研究 DA 驱动的异常学习作为运动迟缓的并发原因。该模型包括在 BG 电路中起作用的三个主要途径,即直接途径、间接途径和超直接途径,并使用双项赫布规则根据以前的奖励和惩罚历史来训练纹状体中的突触。还纳入了左旋多巴药效动力学。通过对交替手指敲击运动任务的模型模拟,我们评估了异常学习对运动迟缓的作用。结果表明,在药物治疗(左旋多巴)下进行训练不仅提供了即时的益处,而且还提供了持续的延迟益处。相反,如果在左旋多巴疗效消失的情况下进行训练,可能会导致皮质纹状体突触可塑性出现功能障碍,从而进一步恶化 PD 患者的运动表现。这表明运动迟缓可能是由于 DA 水平降低和功能障碍性可塑性的并发影响所致,并且在接受药物治疗的患者中可以利用训练来改善左旋多巴的治疗效果。

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