Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke.

Ajay D Halai,Anna M Woollams,Matthew A Lambon Ralph

doi:10.1016/j.nicl.2017.10.037

Abstract

In order to gain a better understanding of aphasia one must consider the complex combinations of language impairments along with the pattern of paraphasias. Despite the fact that both deficits and paraphasias feature in diagnostic criteria, most research has focused only on the lesion correlates of language deficits, with minimal attention on the pattern of patients' paraphasias. In this study, we used a data-driven approach (principal component analysis - PCA) to fuse patient impairments and their pattern of errors into one unified model of chronic post-stroke aphasia. This model was subsequently mapped onto the patients' lesion profiles to generate the triangulation of language-cognitive impairments, naming errors and their neural correlates. Specifically, we established the pattern of co-occurrence between fifteen error types, which avoids focussing on a subset of errors or the use of experimenter-derived methods to combine across error types. We obtained five principal components underlying the patients' errors: omission errors; semantically-related responses; phonologically-related responses; dysfluent responses; and a combination of circumlocutions with mixed errors. In the second step, we aligned these paraphasia-related principal components with the patients' performance on a detailed language and cognitive assessment battery, utilising an additional PCA. This omnibus PCA revealed seven unique fused impairment-paraphasia factors: output phonology; semantics; phonological working memory; speech quanta; executive-cognitive skill; phonological (input) discrimination; and the production of circumlocution errors. In doing so we were able to resolve the complex relationships between error types and impairments. Some are relatively straightforward: circumlocution errors formed their own independent factor; there was a one-to-one mapping for phonological errors with expressive phonological abilities and for dysfluent errors with speech fluency. In contrast, omission-type errors loaded across both semantic and phonological working memory factors, whilst semantically-related errors had the most complex relationship by loading across four factors (phonological ability, speech quanta, executive-cognitive skills and circumlocution-type errors). Three components had unique lesion correlates: phonological working memory with the primary auditory region; semantics with the anterior temporal region; and fluency with the pre-central gyrus, converging with existing literature. In conclusion, the data-driven approach allowed derivation of the triangulation of deficits, error types and lesion correlates in post-stroke aphasia.

Highlights

The most common cause of aphasia is stroke, with approximately 30% of cases suffering from language problems in the acute phase and 20% chronically (Berthier, 2005; Engelter et al, 2006)
We found that six categories contributed less than 2% of the total errors and the variance within each of these error types were less than 1.5%
This outcome probably reflects the level of inter-correlations between the paraphasia types (Table 1) and motivates the use of a principal component analysis (PCA) approach to extract the clustering of the error types

Summary

Introduction

The most common cause of aphasia is stroke, with approximately 30% of cases suffering from language problems in the acute phase and 20% chronically (Berthier, 2005; Engelter et al, 2006). Bates et al, 2003; Butler et al, 2014; Corbetta et al, 2015; Halai et al, 2017; Lacey et al, 2017; Mirman et al, 2015a; Mirman et al, 2015b). Given their importance in aphasiology, the key purpose of the current study was to assimilate the patterns of patients' paraphasias thereby generating the much broader lesion-symptomerror mapping for post-stroke aphasia, for the first time.

Objectives

Methods

Results

Conclusion