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A Study of the Midbrain Network for Covert Attentional Orienting in Cervical Dystonia Patients using Dynamic Causal Modelling

机译:动态因果模型研究中度神经网络对宫颈肌张力障碍患者隐性注意定向的研究

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Understanding the neuronal network dynamics underlying the third most common movement disorder, cervical dystonia, can be achieved using dynamic causal modelling. Current literature establishes structures of the midbrain network for covert attentional orienting as dysfunctional in patients with cervical dystonia. One of these structures is the superior colliculus, for which it is hypothesised that deficient GABAergic activity therein causes cervical dystonia. To understand the role that this node plays in cervical dystonia, various connectivity models of the midbrain network were compared under the influence of a loom-recede visual stimulus fMRI paradigm. These models included the thalamus and striatum, crucial nodes in the direct/indirect pathways for motor movement and inhibition. The parametric empirical Bayes approach was used to quantify the difference in connection strengths across the winning models between patients and controls. Our findings demonstrated greater modulation by a looming stimulus event on the strength of connection from the striatum to the superior colliculus in patients. These results offer new means to understanding the pathophysiology of cervical dystonia.
机译:可以使用动态因果模型来了解第三大常见运动障碍(即颈肌张力障碍)的神经网络动态。当前的文献建立了中脑网络的结构,用于在宫颈肌张力障碍患者中隐蔽地注意定向为功能障碍。这些结构之一是上丘,据推测,其中的GABA能活性不足会引起宫颈肌张力障碍。为了了解该节点在子宫颈肌张力障碍中的作用,在织机后视觉刺激fMRI范例的影响下,比较了中脑网络的各种连通性模型。这些模型包括丘脑和纹状体,是运动运动和抑制的直接/间接途径中的关键节点。参数化经验贝叶斯方法用于量化患者和对照组之间获胜模型之间连接强度的差异。我们的发现表明,迫在眉睫的刺激事件对患者纹状体与上丘之间的连接强度产生了更大的调节作用。这些结果为了解宫颈肌张力障碍的病理生理学提供了新的手段。

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