ABSTRACT

Background:

A clinical diagnosis of primary progressive aphasia relies on behavioral characteristics and patterns of atrophy to determine a variant: logopenic; nonfluent/agrammatic; or semantic. The dual stream model is a contemporary paradigm that has been applied widely to understand brain-behavior relationships; however, applications to neurodegenerative diseases like primary progressive aphasia are limited.

Aims

The primary aim of this study is to determine if the dual stream model can be applied to a neurodegenerative disease, such as primary progressive aphasia, using both behavioral and neuroimaging data.

Methods & Procedures:

We analyzed behavioral and neuroimaging data to apply a multivariate classification tool (support vector machines) to determine if the dual stream model extends to primary progressive aphasia. Sixty-four individuals with primary progressive aphasia were enrolled (26 logopenic variant, 20 nonfluent/agrammatic variant, and 18 semantic variant) and administered four behavioral tasks to assess three linguistic domains (naming, repetition, and semantic knowledge). We used regions of interest from the dual stream model and calculated the cortical volume for gray matter regions and white matter structural volumes and fractional anisotropy. We applied a multivariate classification tool (support vector machines) to distinguish variants based on behavioral performance and patterns of atrophy.

Outcomes & Results:

Behavioral performance discriminates logopenic from semantic variant and nonfluent/agrammatic from semantic variant. Cortical volume distinguishes all three variants. White matter structural volumes and fractional anisotropy primarily distinguish nonfluent/agrammatic from semantic variant. Regions of interest that contribute to each classification in cortical and white matter analyses demonstrate alignment of logopenic and nonfluent/agrammatic variants to the dorsal stream, while the semantic variant aligns with the ventral stream.

Conclusions:

A novel implementation of an automated multivariate classification suggests that the dual stream model can be extended to primary progressive aphasia. Variants are distinguished by behavioral and neuroanatomical patterns and align to the dorsal and ventral streams of the dual stream model.

Application of the dual stream model to PPA

中文翻译：

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双流模型在神经退行性疾病中的应用：来自原发性进行性失语症多变量分类工具的证据

摘要

背景：

原发性进行性失语症的临床诊断依赖于行为特征和萎缩模式来确定变异：语言减少；不流利/语法不通；或语义。双流模型是一种当代范式，已广泛应用于理解大脑行为关系；然而，在原发性进行性失语症等神经退行性疾病中的应用有限。

目标

本研究的主要目的是利用行为和神经影像数据确定双流模型是否可以应用于神经退行性疾病，例如原发性进行性失语症。

方法和程序：

我们分析了行为和神经影像数据，应用多元分类工具（支持向量机）来确定双流模型是否扩展到原发性进行性失语症。招募了 64 名原发性进行性失语症患者（26 名语言缺失变体、20 名不流利/语法不通变体和 18 名语义变体），并执行四项行为任务来评估三个语言领域（命名、重复和语义知识）。我们使用双流模型中的感兴趣区域，并计算灰质区域的皮质体积和白质结构体积以及分数各向异性。我们应用多元分类工具（支持向量机）来根据行为表现和萎缩模式来区分变异。

结果与成果：

行为表现将语词匮乏与语义变体区分开来，将不流利/语法不通与语义变体区分开来。皮质体积区分了所有三种变体。白质结构体积和分数各向异性主要区分非流利/语法不通和语义变体。有助于皮质和白质分析中每个分类的感兴趣区域表明，语词减少和非流利/语法变体与背侧流的对齐，而语义变体与腹侧流的对齐。

结论：

自动多变量分类的新颖实现表明双流模型可以扩展到原发性进行性失语症。变体通过行为和神经解剖学模式来区分，并与双流模型的背侧和腹侧流对齐。

双流模型在PPA中的应用