Aphasia is a common and debilitating communication disorder caused by damage to the language regions
of the brain, most often from stroke. Impairments in the production of naturalistic language (also referred to as
discourse or connected speech) are ubiquitous in aphasia and cause significant health-related disability. Given
how integral naturalistic language production is to all human interaction, advancing our understanding of
impaired naturalistic language production in aphasia is of high priority for all key stakeholders: individuals with
aphasia, clinicians, and researchers.
Despite its importance, our understanding of naturalistic language production in aphasia is limited.
Specifically, two key questions remain unanswered: (1) How do salient features (e.g., abandoned utterances,
grammatical omissions, phonemic paraphasias) of impaired naturalistic language production map onto neural
characteristics, such as lesion location or extent? (2) How do features change over time? Although emerging
evidence has yielded promising insights, challenges related to both the measures used and the individuals
studied are barriers to advancing our knowledge on these topics. The goal of the proposed project is to
address the limitations in the current literature by leveraging a novel measure of naturalistic language
production in aphasia and applying it to a large and ongoing longitudinal study (R01 DC013270) using
advanced analytic techniques. Specifically, we will score naturalistic language samples from ~225 individuals
with aphasia across four time points over the first year of stroke recovery using a psychometrically robust
measure I developed called the Auditory-Perceptual Rating of Connected Speech in Aphasia (APROCSA).
Scores on three core dimensions of impaired naturalistic language production will serve as outcome measures.
In Aim 1, we will characterize the neural correlates of naturalistic language production in acute aphasia by
building a series of complementary multiple linear and support vector regression models to evaluate relations
between naturalistic language impairment and structural brain damage, where lesion-delineated brain scans
will be used to predict performance on the three APROCSA dimensions.
In Aim 2, we will quantify patterns and predictors of naturalistic language production recovery in aphasia by
measuring (1) the trajectory of behavioral change on the three APROCSA dimensions and (2) the influence of
lesion location and extent on change, using a powerful approach called latent growth curve modeling.
The impact of the proposed project will be an explanatory brain-behavior model of naturalistic language
production in aphasia that improves clinicians’ ability to develop prognoses, provide informed education, and
benchmark performance on an everyday language skill. This proposal will also provide essential mentorship for
developing a translational research program that applies tools from cognitive neuroscience and quantitative
methods to the study of naturalistic language production and other clinically relevant areas in aphasia.