All ETDs from UAB

Advisory Committee Chair

Jerzy P Szaflarski

Advisory Committee Members

Kristina M Visscher

David C Knight

Jarred W Younger

Gitendra Uswatte

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) College of Arts and Sciences


The advent of advanced neuroimaging techniques has enabled unprecedented insights into the neurobiology of language recovery after stroke. Current theories of language recovery after stroke, however, are limited by their dependence on the results of small imaging studies that have typically focused on only single imaging modalities. This likely contributes to discrepancies in the literature regarding critical topics such as how each hemisphere contributes to residual language abilities, whether different compensatory mechanisms are engaged by patients with different amounts of left hemispheric damage, whether poor long-term outcomes are primarily due to a loss of local cortical function or result from disruptions of inter-regional communication, and how the networks recruited for residual language processing relate to residual brain structure. This dissertation aimed to test the predictions of current theories and address discrepancies in the literature using multimodal (functional MRI, structural MRI, diffusion-weighted MRI) neuroimaging data obtained from 43 chronic left hemispheric stroke patients and 43 age, handedness, and sex-matched controls. The following studies (1) test predictions of current theory regarding the contributions of canonical brain language networks to long-term language outcomes after stroke, identify a core set of regions supporting broad aspects of residual language function, and show that extensive damage to canonical networks leads to the recruitment non-canonical right hemispheric regions for semantic processing, (2) show that damage to “bottleneck” regions where multiple long-range white matter tracts converge, particularly in the posterior temporo-parietal white matter, strongly predicts long-term impairments in multiple language domains, and (3) show that the preservation of posterior temporo-parietal cortex and the underlying deep white matter is associated with preserved/restored task-evoked activation in canonical language networks. Our findings support the emphasis of current theory on the importance of canonical language network function for successful recovery, and indicate that specific right hemispheric regions are recruited to compensate after left hemispheric damage. They also demonstrate the preservation of cortical and white matter convergence zones in posterior temporo-parietal areas likely play an important role in successful language recovery, potentially by enabling the preservation/restoration of function in canonical language networks.



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