Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates

Abstract

Background Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. Objective To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Methods 25 behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high resolution MRI was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. Results The principal components analysis yielded four dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. Conclusions An extensive clinical aphasia assessment identifies four independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual’s specific pattern of deficits and preserved abilities.

Dissociation between Frontal and Temporal-Parietal Contributions to Connected Speech in Acute Stroke

“…These results overlap but are not synonymous with regions associated with fluency via LBM analyses in chronic stroke (Yourganov et al, 2016;Halai et al, 2017;Lacey et al, 2017;Halai et al, 2018;cf. Borovsky et al, 2007) and brain atrophy in patients with primary progressive aphasia Rogalski et al, 2011).…”

“…Third, we conducted detailed quantitative analyses to independently assess the content and structure of spontaneous speech using the rigorous quantitative production analysis (QPA) approach (Saffran et al, 1989;Rochon et al, 2000;Gordon, 2006;Wilson et al, 2010). Fourth, because single behavioral measures may consist of multiple cognitive components, we applied PCA to extract the underlying cognitive components across the QPA measures Butler et al, 2014;Mirman et al, 2015a;Lacey et al, 2017). Lastly, we applied support vector regression (SVR) based multivariate LBM which considers the pattern of all voxels as a single model to predict a behavioral outcome.…”

“…Significant findings controlling for the effect of lesion size were from a PCA-LBM analysis which included not only the connected speech measures but other production and cognitive measures. In these subsequent analyses, fluency related factors were primarily associated with the frontal lobe (Halai et al, 2017;Lacey et al, 2017;Halai et al, 2018).…”

A multivariate lesion symptom mapping toolbox and examination of lesion‐volume biases and correction methods in lesion‐symptom mapping

“…These measures were chosen to sample across a range of lesion effect sizes and potential anatomical loci. Participants were drawn from other studies examining lesion-behavior relationships (Lacey, Skipper-Kallal, Xing, Fama, & Turkeltaub, 2017; Xing et al, 2016; Xing, Lacey, Skipper-Kallal, Zeng, & Turkeltaub, 2017). All participants provided written informed consent and all studies were approved by the Georgetown University IRB.…”

On the generalizability of post‐stroke proportional recovery

“…The ability to reflect recovery is dependent upon what specialized behavioral, cognitive or sensory domain is tested. Differing neural substrates and behaviors are targeted across varied language assessments [21]. Further, no single test, irrespective of validity, can provide a complete picture of language capacity.…”