Dataset Information

WORD LEARNING IN APHASIA: TREATMENT IMPLICATIONS AND STRUCTURAL CONNECTIVITY ANALYSES

ABSTRACT:

Objective

Of current interest in aphasia research is the relevance of what we can learn from studying word learning ability in aphasia. In a preliminary study, we addressed two issues related to the novel word learning ability of individuals with aphasia. First, as word learning engages large-scale cognitive-linguistic systems (language skills, verbal short-term memory (STM), other memory and executive functions), we probed whether novel word learning practice in three people with aphasia could stimulate these language-related systems. Second, as lesion correlates affecting word learning in aphasia remain unclear, we examined whether the structural integrity of the left arcuate fasciculus (AF) in the same three individuals is related to outcomes of novel word learning practice.

Method

To stimulate word learning systems, our three participants practiced for 4 weeks with an explicit novel word – novel referent word learning task, adopted from the Ancient Farming Equipment learning paradigm (Laine & Salmelin, 2010). The participants’ progress on receptive and expressive novel word learning was followed up, and their language and verbal STM abilities as well as single-session novel word learning (Learning to Name Aliens by Gupta, Martin, Abbs, Schwartz & Lipinski, 2006) were tested before and after the practice period. To address the second question, we analyzed the participants’ structural MRI scans with respect to the integrity of the left AF and its overlap with the lesion areas.

Results

All participants showed some receptive word learning in the trained task, as well as improvements in verbal STM span at posttest. Two of the three participants also showed improved performance on some of the language outcome measures. One participant with partially spared left AF, especially temporo-parietal connections, exhibited better word learning performance than the other two who had larger damage and disconnection of the AF.

Conclusions

While the present results are preliminary, they open the possibility that novel word learning practice in aphasia may stimulate remaining word learning mechanisms in aphasia, and thereby influence language and verbal STM abilities. These results also suggest that preservation of novel word learning ability in aphasia in part depends on the integrity of the left arcuate track.

SUBMITTER: Coran M

PROVIDER: S-EPMC7802821 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:Focal brain damage caused by stroke can result in aphasia and advances in cognitive neuroscience suggest that impairment may be associated with network-level disorder rather than just circumscribed cortical damage. Several studies have shown meaningful relationships between brain-behaviour using lesions; however, only a handful of studies have incorporated in vivo structural and functional connectivity. Patients with chronic post-stroke aphasia were assessed with structural (n = 68) and functional (n = 39) MRI to assess whether predicting performance can be improved with multiple modalities and if additional variance can be explained compared to lesion models alone. These neural measurements were used to construct models to predict four key language-cognitive factors: (i) phonology; (ii) semantics; (iii) executive function; and (iv) fluency. Our results showed that each factor (except executive ability) could be significantly related to each neural measurement alone; however, structural and functional connectivity models did not explain additional variance above the lesion models. We did find evidence that the structural and functional predictors may be linked to the core lesion sites. First, the predictive functional connectivity features were found to be located within functional resting-state networks identified in healthy controls, suggesting that the result might reflect functionally specific reorganization (damage to a node within a network can result in disruption to the entire network). Second, predictive structural connectivity features were located within core lesion sites, suggesting that multimodal information may be redundant in prediction modelling. In addition, we observed that the optimum sparsity within the regularized regression models differed for each behavioural component and across different imaging features, suggesting that future studies should consider optimizing hyperparameters related to sparsity per target. Together, the results indicate that the observed network-level disruption was predicted by the lesion alone and does not significantly improve model performance in predicting the profile of language impairment.