Maximizing and predicting sentence processing treatment outcomes in aphasia

NIH RePORTER · NIH · R56 · $679,287 · view on reporter.nih.gov ↗

Abstract

Abstract Agrammatic aphasia (agrammatism), an acquired language disorder, affects the ability to produce and comprehend sentences and significantly impacts the ability to communicate. The choice of the most efficacious and cost-effective treatment for specific language impairments (including agrammatism) is a major challenge for clinicians, as is the ability to formulate prognostic statements about the effects of treatment, based on individuals' language and neural profiles. Advances in understanding the effects of treatment for sentence processing deficits are therefore important for providing optimal intervention. The present proposal builds on previous work showing that Treatment of Underlying Forms (TUF, [1-2]), a metalinguistic approach focused explicitly on improving sentence processing abilities in agrammatic aphasia, results in strong acquisition and generalization effects (see [1], for review), changes in on-line sentence processing as identified in visual world eyetracking studies [3-6], and adaptive neuroplasticity as measured by shifts in BOLD signal derived from functional neuroimaging [7-8]. The overarching goal of the proposed studies is to refine TUF to maximize its efficacy and boost treatment outcomes to ultimately increase its clinical use. We propose a set of studies that test the effects of early treatment components of TUF to identify those that are most critical for successful outcomes (Aim 1, Study 1), compare the relative effects of TUF and Verb Network Strengthening Treatment (VNeST) on offline, online and neural processing (Aim 2, Study 2), and examine the effects of noninvasive neurostimulation (i.e., high-definition, transcranial direct current stimulation (HD- tDCS)) as an adjunct to TUF (Aim 3, Study 3). In addition, we will use multimodal neuroimaging and behavioral data to examine the factors underlying successful treatment outcomes and develop algorithms for predicting responsiveness to treatment based on these variables (Aim 4, Study 4).

Key facts

NIH application ID
10412434
Project number
1R56DC019157-01A1
Recipient
NORTHWESTERN UNIVERSITY
Principal Investigator
CYNTHIA K THOMPSON
Activity code
R56
Funding institute
NIH
Fiscal year
2021
Award amount
$679,287
Award type
1
Project period
2021-08-01 → 2022-07-31