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连接、纤维束、分形及其他:神经外科网络与连接性研究实用指南

Connections, Tracts, Fractals, and the Rest: A Working Guide to Network and Connectivity Studies in Neurosurgery.

作者信息

Hart Michael G, Romero-Garcia Rafael, Price Stephen J, Santarius Thomas, Suckling John

机构信息

Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.

Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom; Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.

出版信息

World Neurosurg. 2020 Aug;140:389-400. doi: 10.1016/j.wneu.2020.03.116. Epub 2020 Apr 2.

Abstract

Brain mapping and connectomics can probe networks that span the entire brain, producing a diverse range of outputs for probing specific clinically relevant questions. The potential for understanding the effect of focal lesions on brain function, cognition, and plasticity abounds, any one of which would likely yield more effective and safer neurosurgical strategies. However, the possibilities of advanced magnetic resonance imaging and connectomics have been somewhat underused in neurosurgery, arising from actual or perceived difficulties in either application or analysis. The present review builds on previous work describing the theoretical attractions of connectomics to deliberate on the practical details of performing high-quality connectomics studies in neurosurgery. First, the data and methods involved in deriving connectomics models will be considered, specifically for the purpose of determining the nature of inferences that can be made subsequently. Next, a selection of key analysis methods will be explored using practical examples that illustrate their effective implementation and the insights that can be gleaned. The principles of study design will be introduced, including analysis tips and methods for making efficient use of available resources. Finally, a review of the best research practices for neuroimaging studies will be discussed, including principles of open access data sharing, study preregistration, and methods for improving replicability. Ultimately, we hope readers will be better placed to appraise the current connectomics studies in neurosurgery and empowered to develop their own high-quality studies, both of which are key steps in realizing the true potential of connectomics and advanced neuroimaging analyses in general.

摘要

脑图谱和连接组学能够探测贯穿整个大脑的网络,产生各种各样的输出结果,以探究特定的临床相关问题。了解局灶性病变对脑功能、认知和可塑性的影响具有很大潜力,其中任何一个方面都可能产生更有效、更安全的神经外科手术策略。然而,先进的磁共振成像和连接组学在神经外科中的应用潜力在一定程度上未得到充分发挥,这是由于在应用或分析方面实际存在或被认为存在的困难。本综述基于之前描述连接组学理论吸引力的工作,深入探讨在神经外科中开展高质量连接组学研究的实际细节。首先,将考虑推导连接组学模型所涉及的数据和方法,特别是为了确定随后能够做出的推断的性质。接下来,将通过实际例子探索一系列关键分析方法,这些例子展示了它们的有效实施以及能够获得的见解。将介绍研究设计的原则,包括分析技巧和有效利用现有资源的方法。最后,将讨论神经影像学研究的最佳研究实践,包括开放获取数据共享原则、研究预注册以及提高可重复性的方法。最终,我们希望读者能够更好地评估当前神经外科中的连接组学研究,并能够开展自己的高质量研究,这两者都是实现连接组学和一般先进神经影像学分析真正潜力的关键步骤。

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