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首页> 外文期刊>Cortex: A Journal Devoted to the Study of the Nervous System and Behavior >A network underlying human higher-order motor control: Insights from machine learning-based lesion-behaviour mapping in apraxia of pantomime
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A network underlying human higher-order motor control: Insights from machine learning-based lesion-behaviour mapping in apraxia of pantomime

机译:一种网络底层高阶电机控制:从基于机器学习的病变行为映射的洞察力在Pantomime的Apraxia中的洞察

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摘要

Neurological patients with apraxia of pantomime provide us with a unique opportunity to study the neural correlates of higher-order motor function. Previous studies using lesion-behaviour mapping methods led to inconsistent anatomical results, reporting various lesion locations to induce this symptom. We hypothesised that the inconsistencies might arise from limitations of mass-univariate lesion-behaviour mapping approaches if our ability to pantomime the use of objects is organised in a brain network. Thus, we investigated apraxia of pantomime by using multivariate lesion behaviour mapping based both on support vector regression and sparse canonical correlations in a sample of 130 left-hemisphere stroke patients. Both multivariate methods identified multiple areas to underlie high-order motor control, including inferior parietal lobule, precentral gyrus, posterior parts of middle temporal cortex, and insula. Further, long association fibres were affected, such as the superior longitudinal fascicle, inferior occipito-frontal fascicle, uncinated fascicle, and superior occipito-frontal fascicle. The findings underline the benefits of multivariate lesion-behaviour mapping in brain networks and provide new insights into the brain networks underlying higher-order motor control. (C) 2019 Elsevier Ltd. All rights reserved.
机译:神经系统患者患有少女的脂肪酸症,为我们提供了研究高阶电机功能的神经相关的独特机会。以前的研究采用病变行为映射方法导致不一致的解剖结果,报告各种病变位置以诱导这种症状。我们假设如果我们在大脑网络中组织了使用对象的统治能力,则可能会因大规模单变量的病变行为 - 行为映射方法的限制而产生不一致。因此,我们通过使用多元病变行为映射来研究哑剧的牺牲品,这对于130左半球中风患者的样本中的支持向量回归和稀疏规范相关性。两种多变量方法都确定了多次高阶电机控制的多个区域,包括较低的顶叶叶片,前术转象,中间时颞皮质的后部和insula。此外,长期结合纤维受到影响,例如优越的纵向束性,较差的枕骨 - 正面雄蕊,未透露的纺织品和优质枕骨 - 额相束。该研究结果强调了大脑网络中多元病变行为映射的好处,并为高阶电机控制底层脑网络提供了新的见解。 (c)2019年elestvier有限公司保留所有权利。

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