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脑疾病的连接组学

The connectomics of brain disorders.

机构信息

Monash Clinical and Imaging Neuroscience, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia 3168.

Melbourne Neuropsychiatry Centre and Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia 3053.

出版信息

Nat Rev Neurosci. 2015 Mar;16(3):159-72. doi: 10.1038/nrn3901.

Abstract

Pathological perturbations of the brain are rarely confined to a single locus; instead, they often spread via axonal pathways to influence other regions. Patterns of such disease propagation are constrained by the extraordinarily complex, yet highly organized, topology of the underlying neural architecture; the so-called connectome. Thus, network organization fundamentally influences brain disease, and a connectomic approach grounded in network science is integral to understanding neuropathology. Here, we consider how brain-network topology shapes neural responses to damage, highlighting key maladaptive processes (such as diaschisis, transneuronal degeneration and dedifferentiation), and the resources (including degeneracy and reserve) and processes (such as compensation) that enable adaptation. We then show how knowledge of network topology allows us not only to describe pathological processes but also to generate predictive models of the spread and functional consequences of brain disease.

摘要

大脑的病理性改变很少局限于单一部位;相反,它们通常通过轴突途径传播,影响其他区域。这种疾病传播的模式受到基础神经结构极其复杂但高度组织化的拓扑结构的限制;即所谓的连接组。因此,网络组织从根本上影响大脑疾病,基于网络科学的连接组学方法是理解神经病理学的重要组成部分。在这里,我们考虑了大脑网络拓扑结构如何塑造对损伤的神经反应,强调了关键的适应不良过程(如失联络、跨神经元变性和去分化),以及使适应成为可能的资源(包括冗余和储备)和过程(如代偿)。然后,我们展示了对网络拓扑结构的了解不仅使我们能够描述病理过程,而且还可以生成大脑疾病传播和功能后果的预测模型。

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