Neuroscience and Aphasia Research Unit, School of Psychological Sciences, Zochonis Building, University of Manchester, Brunswick Street, Manchester, M13 9PL, UK.
Neuroscience and Aphasia Research Unit, School of Psychological Sciences, Zochonis Building, University of Manchester, Brunswick Street, Manchester, M13 9PL, UK
Brain. 2014 Dec;137(Pt 12):3248-66. doi: 10.1093/brain/awu286. Epub 2014 Oct 27.
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.
脑卒中后失语症是一种多维障碍，患者的表现反映了多种行为连续体的变化。我们提出了一种新的方法来分离慢性失语症患者表现的主要方面，并分离其神经基础。我们使用主成分分析从 31 名慢性脑卒中失语症患者在大量详细行为评估中的表现中提取潜在的核心因素。旋转后的主成分分析揭示了三个关键因素，我们根据在每个成分上加载最强的测试共同元素将其命名为语音、语义和执行/认知。语音因素解释了最大的方差，其次是语义因素，然后是执行认知因素。使用主成分分析使这些三个因素的得分正交，因此非常适合在基于体素的相关性分析高分辨率结构扫描中用作同时连续的预测因子。语音处理能力与左侧后颞叶包括 Heschl 回、后中颞叶和上颞叶以及上颞叶下的白质有关。语义因素与左侧前中颞叶和其下方的颞叶干有关。执行认知因素与任何特定区域的结构完整性没有选择性相关，这与支持执行功能的区域广泛分布和多功能性质相符。确定的语音和语义区域与其他方法（如功能神经影像学和神经刺激）突出的区域非常吻合。使用主成分分析可以比使用原始评估分数或诊断分类更稳健和有选择性地描述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独特的、正交的行为成分。因此，除了提高我们对脑卒中后失语症的损伤-症状映射的理解外，相同的方法还可以用于阐明其他神经障碍中的大脑-行为关系。
