# Individual differences in brain networks supporting speech understanding in patients with cochlear implants

> **NIH NIH R01** · WASHINGTON UNIVERSITY · 2022 · $587,705

## Abstract

Abstract
Listeners with hearing impairment can often understand spoken language, but with increased effort, taking
cognitive resources away from other processes such as attention and memory. An important challenge is
therefore to understand how the brain copes with a degraded speech signal and the cognitive processes that
are most critical to successful comprehension. Adult listeners with cochlear implants are a unique group in
which to investigate effortful listening: They have typically adapted to auditory deprivation for a period of years
of profound hearing loss, followed by some degree of hearing restoration following implantation. Following
increased auditory input due to cochlear implantation, the degree to which individual listeners are able to
successfully recognize speech, especially in the presence of background noise, is extremely variable. Previous
attempts to explain this variability in the context of underlying patterns of brain activity have been unsuccessful,
in large part because the technical challenges associated with neuroimaging in the presence of an implanted
medical device have prevented adequate localization of neural responses to speech. The goal of our research
is to understand the cognitive systems that support speech recognition in listeners with cochlear implants and
to use knowledge about these systems to improve behavioral outcomes. We do so using converging evidence
from behavioral measures and functional brain imaging. We make use of high-density diffuse optical
tomography (HD-DOT), a form of optical brain imaging that produces anatomically-localized indices of regional
cortical activity. We will map the brain networks supporting speech comprehension in listeners with cochlear
implants, which we expect to differ from those engaged by listeners with good hearing. We will then evaluate
the degree to which neural markers of effortful listening can predict individual differences in speech recognition
success in the presence of background noise. Together the findings will help ground our understanding of
cochlear implant-aided speech recognition in a neuroanatomically-constrained framework and develop more
accurate outcome measures.

## Key facts

- **NIH application ID:** 10366520
- **Project number:** 1R01DC019507-01A1
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Jonathan E Peelle
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $587,705
- **Award type:** 1
- **Project period:** 2021-12-03 → 2022-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10366520

## Citation

> US National Institutes of Health, RePORTER application 10366520, Individual differences in brain networks supporting speech understanding in patients with cochlear implants (1R01DC019507-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10366520. Licensed CC0.

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