Dataset Information

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

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.

SUBMITTER: Halai AD

PROVIDER: S-EPMC5683039 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Halai Ajay D AD Woollams Anna M AM Lambon Ralph Matthew A MA

NeuroImage. Clinical 20171106

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 th ...[more]

PMID: 29159059

Similar Datasets

Project description:Aphasia is an acquired disorder caused by damage, most commonly due to stroke, to brain regions involved in speech and language. While language impairment is the defining symptom of aphasia, the co-occurrence of non-language cognitive deficits and their importance in predicting rehabilitation and recovery outcomes is well documented. However, people with aphasia (PWA) are rarely tested on higher-order cognitive functions, making it difficult for studies to associate these functions with a consistent lesion correlate. Broca's area is a particular brain region of interest that has long been implicated in speech and language production. Contrary to classic models of speech and language, cumulative evidence shows that Broca's area and surrounding regions in the left inferior frontal cortex (LIFC) are involved in, but not specific to, speech production. In this study we aimed to explore the brain-behaviour relationships between tests of cognitive skill and language abilities in thirty-six adults with long-term speech production deficits caused by post-stroke aphasia. Our findings suggest that non-linguistic cognitive functions, namely executive functions and verbal working memory, explain more of the behavioural variance in PWA than classical language models imply. Additionally, lesions to the LIFC, including Broca's area, were associated with non-linguistic executive (dys)function, suggesting that lesions to this area are associated with non-language-specific higher-order cognitive deficits in aphasia. Whether executive (dys)function - and its neural correlate in Broca's area - contributes directly to PWA's language production deficits or simply co-occurs with it, adding to communication difficulties, remains unclear. These findings support contemporary models of speech production that place language processing within the context of domain-general perception, action and conceptual knowledge. An understanding of the covariance between language and non-language deficits and their underlying neural correlates will inform better targeted aphasia treatment and outcomes.

Project description:Identifying the neural changes that support recovery of cognitive functions after a brain lesion is important to advance our understanding of human neuroplasticity, which, in turn, forms the basis for the development of effective treatments. To date, the preponderance of neuroimaging studies has focused on localizing changes in average brain activity associated with functional recovery. Here, we took a novel approach by evaluating whether cognitive recovery in chronic stroke is related to increases in the differentiation of local neural response patterns. This approach is supported by research indicating that, in the intact brain, local neural representations become more differentiated (dissimilar) with learning (Glezer et al., 2015). We acquired fMRI data before and after 21 individuals received approximately 12 weeks of behavioral treatment for written language impairment due to a left-hemisphere stroke. We used Local-Heterogeneity Regression Analysis (Purcell and Rapp, 2018) to measure local neural response differentiation associated with written language processing, assuming that greater heterogeneity in the pattern of activity across adjacent neural areas indicates more well-differentiated neural representations. First, we observed pre to post-treatment increases in local neural differentiation (Local-Hreg) in the ventral occipital-temporal cortex of the left hemisphere. Second, we found that, in this region, higher local neural response differentiation prior to treatment was associated with less severe written language impairment, and that it also predicted greater future responsiveness to treatment. Third, we observed that changes in neural differentiation were systematically related to performance changes for trained and untrained items. Fourth, we did not observe these brain-behavior relationships for mean BOLD responses, only for Local-Hreg. Thus, this is the first investigation to quantify changes in local neural differentiation in the recovery of a cognitive function and the first to demonstrate the clear behavioral relevance of these changes. We conclude that the findings provide strong support for the novel hypothesis that the local re-differentiation of neural representations can play a significant role in functional recovery after brain lesion.

Project description:Neuropsychological assessment, brain imaging and computational modelling have augmented our understanding of the multifaceted functional deficits in people with language disorders after stroke. Despite the volume of research using each technique, no studies have attempted to assimilate all three approaches in order to generate a unified behavioural-computational-neural model of post-stroke aphasia. The present study included data from 53 participants with chronic post-stroke aphasia and merged: aphasiological profiles based on a detailed neuropsychological assessment battery which was analysed with principal component and correlational analyses; measures of the impairment taken from Dell's computational model of word production; and the neural correlates of both behavioural and computational accounts analysed by voxel-based correlational methodology. As a result, all three strands coincide with the separation of semantic and phonological stages of aphasic naming, revealing the prominence of these dimensions for the explanation of aphasic performance. Over and above three previously described principal components (phonological ability, semantic ability, executive-demand), we observed auditory working memory as a novel factor. While the phonological Dell parameter was uniquely related to phonological errors/factor, the semantic parameter was less clear-cut, being related to both semantic errors and omissions, and loading heavily with semantic ability and auditory working memory factors. The close relationship between the semantic Dell parameter and omission errors recurred in their high lesion-correlate overlap in the anterior middle temporal gyrus. In addition, the simultaneous overlap of the lesion correlate of omission errors with more dorsal temporal regions, associated with the phonological parameter, highlights the multiple drivers that underpin this error type. The novel auditory working memory factor was located along left superior/middle temporal gyrus and ventral inferior parietal lobe. The present study fused computational, behavioural and neural data to gain comprehensive insights into the nature of the multifaceted presentations in aphasia. Our unified account contributes enhanced knowledge on dimensions explaining chronic post-stroke aphasia, the variety of factors affecting inter-individual variability, the neural basis of performance, and potential clinical implications.

Project description:The clinical profiles of individuals with post-stroke aphasia demonstrate considerable variation in the presentation of symptoms. Recent aphasiological studies have attempted to account for this individual variability using a multivariate data-driven approach (principal component analysis) on an extensive neuropsychological and aphasiological battery, to identify fundamental domains of post-stroke aphasia. These domains mainly reflect phonology, semantics and fluency; however, these studies did not account for variability in response to different forms of connected speech, i.e. discourse genres. In the current study, we initially examined differences in the quantity, diversity and informativeness between three different discourse genres, including a simple descriptive genre and two naturalistic forms of connected speech (storytelling narrative, and procedural discourse). Subsequently, we provided the first quantitative investigation on the multidimensionality of connected speech production at both behavioural and neural levels. Connected speech samples across descriptive, narrative, and procedural discourse genres were collected from 46 patients with chronic post-stroke aphasia and 20 neurotypical adults. Content analyses conducted on all connected speech samples indicated that performance differed across discourse genres and between groups. Specifically, storytelling narratives provided higher quantities of content words and lexical diversity compared to composite picture description and procedural discourse. The analyses further revealed that, relative to neurotypical adults, patients with aphasia, both fluent and non-fluent, showed reduction in the quantity of verbal production, lexical diversity, and informativeness across all discourses. Given the differences across the discourses, we submitted the connected speech metrics to principal component analysis alongside an extensive neuropsychological/aphasiological battery that assesses a wide range of language and cognitive skills. In contrast to previous research, three unique orthogonal connected speech components were extracted in a unified model, reflecting verbal quantity, verbal quality, and motor speech, alongside four core language and cognitive components: phonological production, semantic processing, phonological recognition, and executive functions. Voxel-wise lesion-symptom mapping using these components provided evidence on the involvement of widespread cortical regions and their white matter connections. Specifically, left frontal regions and their underlying white matter tracts corresponding to the frontal aslant tract and the anterior segment of the arcuate fasciculus were particularly engaged with the quantity and quality of fluent connected speech production while controlling for other co-factors. The neural correlates associated with the other language domains align with existing models on the ventral and dorsal pathways for language processing.

Project description:Listening to vocal music has been recently shown to improve language recovery in stroke survivors. The neuroplasticity mechanisms supporting this effect are, however, still unknown. Using data from a three-arm single-blind randomized controlled trial including acute stroke patients (N=38) and a 3-month follow-up, we set out to compare the neuroplasticity effects of daily listening to self-selected vocal music, instrumental music, and audiobooks on both brain activity and structural connectivity of the language network. Using deterministic tractography we show that the 3-month intervention induced an enhancement of the microstructural properties of the left frontal aslant tract (FAT) for the vocal music group as compared to the audiobook group. Importantly, this increase in the strength of the structural connectivity of the left FAT correlated with improved language skills. Analyses of stimulus-specific activation changes showed that the vocal music group exhibited increased activations in the frontal termination points of the left FAT during vocal music listening as compared to the audiobook group from acute to 3-month post-stroke stage. The increased activity correlated with the structural neuroplasticity changes in the left FAT. These results suggest that the beneficial effects of vocal music listening on post-stroke language recovery are underpinned by structural neuroplasticity changes within the language network and extend our understanding of music-based interventions in stroke rehabilitation.Significance statementPost-stroke language deficits have a devastating effect on patients and their families. Current treatments yield highly variable outcomes and the evidence for their long-term effects is limited. Patients often receive insufficient treatment that are predominantly given outside the optimal time window for brain plasticity. Post-stroke vocal music listening improves language outcome which is underpinned by neuroplasticity changes within the language network. Vocal music listening provides a complementary rehabilitation strategy which could be safely implemented in the early stages of stroke rehabilitation and seems to specifically target language symptoms and recovering language network.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets