Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Cognitive Science, Johns Hopkins University, Baltimore, MD, USA.
Department of Hearing and Speech Sciences, University of Maryland, College Park, MD, USA.
Cortex. 2017 Oct;95:119-135. doi: 10.1016/j.cortex.2017.08.003. Epub 2017 Aug 10.
A major challenge in understanding the origin of clinical symptoms in neuropsychological impairments is capturing the complexity of the underlying cognitive structure. This paper presents a practical guide to path modeling, a statistical approach that is well-suited for modeling multivariate outcomes with a multi-factorial origin. We discuss a step-by-step application of such a model to the problem of nonfluency in aphasia. Individuals with aphasia are often classified into fluent and nonfluent groups for both clinical and research purposes, but despite a large body of research on the topic, the origin of nonfluency remains obscure. We propose a model of nonfluency inspired by the psycholinguistic approach to sentence production, review several bodies of work that have independently suggested a relationship between fluency and various elements in this model, and implement it using path modeling on data from 112 individuals with aphasia from the AphasiaBank. The results show that word production, comprehension, and working memory deficits all contribute to nonfluency, in addition to syntactic impairment which has a strong and direct impact on fluency. More generally, we demonstrate that a path model is an excellent tool for exploring complex neuropsychological symptoms such as nonfluency.
理解神经心理障碍临床症状的起源面临的一个主要挑战是捕捉潜在认知结构的复杂性。本文介绍了路径建模的实用指南,这是一种统计方法,非常适合对具有多因素起源的多维结果进行建模。我们讨论了将此类模型应用于失语症非流畅性问题的分步方法。患有失语症的个体通常会因临床和研究目的而分为流畅和非流畅组,但尽管对此主题进行了大量研究,非流畅性的起源仍然不清楚。我们提出了一种受心理语言学句子生成方法启发的非流畅性模型,回顾了一些独立表明流畅性与该模型中各种元素之间存在关系的研究,并使用来自 AphasiaBank 的 112 名失语症患者的数据通过路径建模实现了该模型。结果表明,除了对流畅性有直接且强烈影响的句法障碍外,词生成、理解和工作记忆缺陷也会导致非流畅性。更一般地说,我们证明路径模型是探索非流畅性等复杂神经心理症状的绝佳工具。