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计算神经生物学是转化神经科学的有用工具:以共济失调为例。

Computational neurobiology is a useful tool in translational neurology: the example of ataxia.

机构信息

Department of Medicine, Mayo Clinic Rochester, MN, USA.

Departments of Neurology and Neuroscience, University of Connecticut Health Center Farmington, CT, USA.

出版信息

Front Neurosci. 2015 Jan 21;9:1. doi: 10.3389/fnins.2015.00001. eCollection 2015.

Abstract

Hereditary ataxia, or motor incoordination, affects approximately 150,000 Americans and hundreds of thousands of individuals worldwide with onset from as early as mid-childhood. Affected individuals exhibit dysarthria, dysmetria, action tremor, and diadochokinesia. In this review, we consider an array of computational studies derived from experimental observations relevant to human neuropathology. A survey of related studies illustrates the impact of integrating clinical evidence with data from mouse models and computational simulations. Results from these studies may help explain findings in mice, and after extensive laboratory study, may ultimately be translated to ataxic individuals. This inquiry lays a foundation for using computation to understand neurobiochemical and electrophysiological pathophysiology of spinocerebellar ataxias and may contribute to development of therapeutics. The interdisciplinary analysis suggests that computational neurobiology can be an important tool for translational neurology.

摘要

遗传性共济失调,或运动协调障碍,影响了大约 15 万名美国人和全球数十万在儿童中期以后发病的个体。受影响的个体表现出构音障碍、运动失调、动作震颤和交替运动障碍。在这篇综述中,我们考虑了一系列源自与人类神经病理学相关的实验观察的计算研究。对相关研究的调查说明了将临床证据与来自小鼠模型和计算模拟的数据相结合的影响。这些研究的结果可能有助于解释在小鼠中的发现,并且经过广泛的实验室研究后,最终可能转化为共济失调患者。这项研究为使用计算方法来理解脊髓小脑共济失调的神经生物化学和电生理学病理生理学奠定了基础,并可能有助于治疗方法的开发。跨学科分析表明,计算神经生物学可以成为转化神经学的重要工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/4300942/f5f6a664498c/fnins-09-00001-g0001.jpg

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