Capturing multidimensionality in stroke aphasia: mapping principal behavioural components to neural structures.
Capturing multidimensionality in stroke aphasia: mapping principal behavioural components to neural structures.
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DOI：
10.1093/brain/awu286
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发表时间：
2014-12
期刊：
影响因子：
--
通讯作者：
Woollams AM
中科院分区：
文献类型：
--
作者：
Butler RA;Lambon Ralph MA;Woollams AM
Butler等人将31例慢性卒中失语患者的行为缺陷与潜在的神经结构联系起来。使用主成分分析，他们减少了一个神经心理电池到三个独立的维度：语音，语义和执行认知。语音和语义处理分别与背侧和腹侧通路的完整性有关，中风失语症是一种多维疾病，其中患者的个人资料反映了沿着多个行为连续体的变化。我们提出了一种新的方法来分离慢性失语症的主要方面的性能和隔离其神经基础。主成分分析被用来提取核心因素的表现与慢性中风失语症的31名参与者在一个大的，详细的电池的行为评估。旋转的主成分分析揭示了三个关键因素，我们标记为语音，语义和执行/认知的基础上，在测试中的共同元素，加载最强烈的每个组件。语音因素解释的变异最多，其次是语义因素，然后是执行认知因素。主成分分析的使用使得参与者在这三个因素上的得分正交，因此非常适合用作基于体素的高分辨率结构扫描相关方法分析中的同时连续预测因子。语音加工能力与左侧后外侧裂周区（包括Heschl's gyrus，后中回、上级颞回和上级颞沟）以及后上级颞回下方的白色有关。语义因素是唯一相关的左前颞中回和下方的颞干。执行认知因素没有选择性地与任何特定区域的结构完整性相关，这可能是预期的，因为支持执行功能的区域具有广泛分布和多功能的性质。所确定的语音和语义领域与其他方法，如功能性神经成像和神经刺激所强调的一致。主成分分析的使用使我们能够比使用原始评估分数或诊断分类更稳健和选择性地表征参与者行为表现的神经基础，因为主成分分析提取了统计上唯一的正交行为成分。因此，除了提高我们对中风失语症的病变-症状映射的理解外，同样的方法可以用于澄清其他神经系统疾病中的脑-行为关系。
Butler et al. relate behavioural deficits in 31 patients with chronic stroke aphasia to underlying neural structures. Using principal components analysis, they reduce a neuropsychological battery to three independent dimensions: phonological, semantic and executive-cognition. Phonological and semantic processing are linked to dorsal and ventral pathway integrity, respectively Stroke aphasia is a multidimensional disorder in which patient profiles reflect variation along multiple behavioural continua. We present a novel approach to separating the principal aspects of chronic aphasic performance and isolating their neural bases. Principal components analysis was used to extract core factors underlying performance of 31 participants with chronic stroke aphasia on a large, detailed battery of behavioural assessments. The rotated principle components analysis revealed three key factors, which we labelled as phonology, semantic and executive/cognition on the basis of the common elements in the tests that loaded most strongly on each component. The phonology factor explained the most variance, followed by the semantic factor and then the executive-cognition factor. The use of principle components analysis rendered participants’ scores on these three factors orthogonal and therefore ideal for use as simultaneous continuous predictors in a voxel-based correlational methodology analysis of high resolution structural scans. Phonological processing ability was uniquely related to left posterior perisylvian regions including Heschl’s gyrus, posterior middle and superior temporal gyri and superior temporal sulcus, as well as the white matter underlying the posterior superior temporal gyrus. The semantic factor was uniquely related to left anterior middle temporal gyrus and the underlying temporal stem. The executive-cognition factor was not correlated selectively with the structural integrity of any particular region, as might be expected in light of the widely-distributed and multi-functional nature of the regions that support executive functions. The identified phonological and semantic areas align well with those highlighted by other methodologies such as functional neuroimaging and neurostimulation. The use of principle components analysis allowed us to characterize the neural bases of participants’ behavioural performance more robustly and selectively than the use of raw assessment scores or diagnostic classifications because principle components analysis extracts statistically unique, orthogonal behavioural components of interest. As such, in addition to improving our understanding of lesion–symptom mapping in stroke aphasia, the same approach could be used to clarify brain–behaviour relationships in other neurological disorders.
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影响因子：
2
作者：
Ardila, A
通讯作者：
Ardila, A
影响因子：
5.7
作者：
Andersen, Sarah M.;Rapcsak, Steven Z.;Beeson, Pelagie M.
通讯作者：
Beeson, Pelagie M.
影响因子：
4.2
作者：
Geva, Sharon;Baron, Jean-Claude;Jones, P. Simon;Price, Cathy J.;Warburton, Elizabeth A.
通讯作者：
Warburton, Elizabeth A.
DOI：
10.1073/pnas.0509550103
发表时间：
2006-05-02
影响因子：
11.1
作者：
Badre, D;Wagner, AD
通讯作者：
Wagner, AD
影响因子：
11.2
作者：
Catani, M;Jones, DK;Ffytche, DH
通讯作者：
Ffytche, DH