Mapping human brain lesions and their functional consequences.

Mapping human brain lesions and their functional consequences.
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绘制人脑病变及其功能后果。

DOI:
10.1016/j.neuroimage.2017.10.028
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发表时间:
2018-01-15
期刊:
影响因子:
5.7
通讯作者:
Rorden C
Rorden C
中科院分区:
医学1区
文献类型:
--
作者:
Karnath HO;Sperber C;Rorden C

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神经科学通过检查脑损伤和随后的行为障碍之间的关系来推断脑功能的历史悠久。与相关方法相比,这种方法的主要优点是它可以告诉我们某个大脑区域是否是给定认知功能所必需的。此外,基于病变的分析为临床缺陷提供了独特的见解。在过去的十年中,统计体素为基础的病变行为映射(VLBM)成为一个强大的方法来了解人类大脑的架构。这篇综述说明了VLBM如何提高我们对功能性脑结构的认识,以及它是如何固有地受到其质量单变量方法的限制。最近开发的各种方法似乎是对传统VLBM的补充。本文概述了这些新方法,包括使用专门的成像方式,结合结构成像与规范的连接体数据,以及结构成像数据的多变量分析。我们认为这些新方法是对传统VLBM的补充,而不是取代传统VLBM,为回答相关问题提供了协同工具。最后,我们讨论了这些方法在认知神经科学和临床应用中的潜力。
Neuroscience has a long history of inferring brain function by examining the relationship between brain injury and subsequent behavioral impairments. The primary advantage of this method over correlative methods is that it can tell us if a certain brain region is necessary for a given cognitive function. In addition, lesion-based analyses provide unique insights into clinical deficits. In the last decade, statistical voxel-based lesion behavior mapping (VLBM) emerged as a powerful method for understanding the architecture of the human brain. This review illustrates how VLBM improves our knowledge of functional brain architecture, as well as how it is inherently limited by its mass-univariate approach. A wide array of recently developed methods appear to supplement traditional VLBM. This paper provides an overview of these new methods, including the use of specialized imaging modalities, the combination of structural imaging with normative connectome data, as well as multivariate analyses of structural imaging data. We see these new methods as complementing rather than replacing traditional VLBM, providing synergistic tools to answer related questions. Finally, we discuss the potential for these methods to become established in cognitive neuroscience and in clinical applications.
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