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

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...

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Main Authors: Ajay D. Halai, Anna M. Woollams, Matthew A. Lambon Ralph
Format: Article
Language:English
Published: Elsevier 2018-01-01
Series:NeuroImage: Clinical
Online Access:http://www.sciencedirect.com/science/article/pii/S2213158217302802
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spelling doaj-77148f6192384f1fa4ccace77c2dfab42020-11-24T21:57:37ZengElsevierNeuroImage: Clinical2213-15822018-01-0117465473Triangulation of language-cognitive impairments, naming errors and their neural bases post-strokeAjay D. Halai0Anna M. Woollams1Matthew A. Lambon Ralph2Correspondence to: A. D. Halai, Neuroscience and Aphasia Research Unit, Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Zochonis Building, University of Manchester, Brunswick Street, Manchester M13 9PL, UK.; Neuroscience and Aphasia Research Unit, University of Manchester, UKNeuroscience and Aphasia Research Unit, University of Manchester, UKCorresponding author.; Neuroscience and Aphasia Research Unit, University of Manchester, UKIn 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. Keywords: Naming errors, Semantic, Phonology, Speech production, Principal component analysis, Lesion-mappinghttp://www.sciencedirect.com/science/article/pii/S2213158217302802
collection DOAJ
language English
format Article
sources DOAJ
author Ajay D. Halai
Anna M. Woollams
Matthew A. Lambon Ralph
spellingShingle Ajay D. Halai
Anna M. Woollams
Matthew A. Lambon Ralph
Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke
NeuroImage: Clinical
author_facet Ajay D. Halai
Anna M. Woollams
Matthew A. Lambon Ralph
author_sort Ajay D. Halai
title Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke
title_short Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke
title_full Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke
title_fullStr Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke
title_full_unstemmed Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke
title_sort triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke
publisher Elsevier
series NeuroImage: Clinical
issn 2213-1582
publishDate 2018-01-01
description 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. Keywords: Naming errors, Semantic, Phonology, Speech production, Principal component analysis, Lesion-mapping
url http://www.sciencedirect.com/science/article/pii/S2213158217302802
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