# Maximizing and predicting sentence processing treatment outcomes in aphasia

> **NIH NIH R56** · NORTHWESTERN UNIVERSITY · 2021 · $679,287

## 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 organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** CYNTHIA K THOMPSON
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $679,287
- **Award type:** 1
- **Project period:** 2021-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10412434

## Citation

> US National Institutes of Health, RePORTER application 10412434, Maximizing and predicting sentence processing treatment outcomes in aphasia (1R56DC019157-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10412434. Licensed CC0.

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