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基于连接组学的病灶-症状映射(CLSM):一种用于映射神经功能的新方法。

Connectome-based lesion-symptom mapping (CLSM): A novel approach to map neurological function.

机构信息

Department of Neurology, Medical University of South Carolina, Charleston, SC, USA.

Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.

出版信息

Neuroimage Clin. 2017 Aug 24;16:461-467. doi: 10.1016/j.nicl.2017.08.018. eCollection 2017.

DOI:10.1016/j.nicl.2017.08.018
PMID:28884073
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5581860/
Abstract

Lesion-symptom mapping is a key tool in understanding the relationship between structure and function in neuroscience as it can provide objective evidence about which regions are for a given process. Initial limitations with this approach were largely overcome by voxel-based lesion-symptom mapping (VLSM), a method introduced in the early 2000s, which allows for a whole-brain approach to study the association between damaged areas and behavioral impairment by applying an independent statistical test at every voxel. By doing so, this technique eliminated the need to predefine regions of interest or classify patients into groups based on arbitrary cutoff scores. VLSM has nonetheless its own limitations; chiefly, a bias towards recognizing cortical necrosis/gliosis but with poor sensitivity for detecting injury along long white matter tracts, thus ignoring cortical disconnection, which can per se lead to behavioral impairment. Here, we propose a complementary method that, instead, establishes a statistical relationship between the strength of connections between all brain regions of the brain (as defined by a standard brain atlas) and the array of behavioral performance seen in patients with brain injury: connectome-based lesion-symptom mapping (CLSM). Whole-brain CLSM therefore has the potential to identify key connections for behavior independently of a priori assumptions with applicability across a broad spectrum of neurological and psychiatric diseases. We propose that this approach can further our understanding of brain-structure relationships and is worth exploring in clinical and theoretical contexts.

摘要

病灶-症状映射是理解神经科学中结构与功能关系的关键工具,因为它可以为特定过程的特定区域提供客观证据。这种方法最初存在一些局限性,主要是基于体素的病灶-症状映射 (VLSM) 方法在 21 世纪初得到了引入,从而克服了这些局限性。这种方法允许通过在每个体素上应用独立的统计检验,采用全脑方法来研究受损区域与行为障碍之间的关联,从而消除了根据任意截断分数预先定义感兴趣区域或对患者进行分类的需要。然而,VLSM 也有其自身的局限性;主要是,它偏向于识别皮质坏死/胶质增生,但对检测长白质束损伤的敏感性较差,从而忽略了皮质中断,而皮质中断本身可能导致行为障碍。在这里,我们提出了一种互补的方法,即建立大脑所有区域之间连接强度与脑损伤患者行为表现数组之间的统计关系:基于连接组的病灶-症状映射 (CLSM)。因此,全脑 CLSM 有可能独立于先验假设,识别出与行为相关的关键连接,适用于广泛的神经和精神疾病。我们提出,这种方法可以进一步加深我们对大脑结构关系的理解,值得在临床和理论背景下进行探索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e18c/5581860/8e6eee033c71/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e18c/5581860/a8170dd3169f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e18c/5581860/8e6eee033c71/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e18c/5581860/a8170dd3169f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e18c/5581860/8e6eee033c71/gr2.jpg

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