# Neurophysiological Mechanisms of Speech Intelligibility in Noise - A Quantitative Framework

> **NIH NIH F31** · PURDUE UNIVERSITY · 2020 · $44,546

## Abstract

Project Summary/Abstract
Communicating in noisy environments with many sound sources places enormous demands on the auditory
system. Successfully extracting target speech information in such scenarios requires a combination of precise
cochlear transduction and neural coding of sound information, and effective downstream cognitive processes
that use the encoded information to segregate and selectively process the target speech of interest. Speech-in-
noise problems (e.g., in old age or hearing loss) can thus arise from impaired “bottom-up” coding of
information, or from declines in cognitive ability. Although the existence of these two components is well
recognized, there is currently no integrative framework for quantifying the relative contributions of each to
speech intelligibility in noise, and for identifying which aspect is deficient in an individual who is experiencing
listening problems. The specific aims of this proposal are designed to address this gap by measuring the
neurophysiological representation of envelope information and investigating how that varies with both “bottom-
up” manipulations and “top-down” manipulations in the same individuals. First, envelope coding in the
brainstem and cortex will be directly measured using electroencephalography (EEG). The EEG metrics will
then be linked to perceptual intelligibility by examining how they covary as the speech is presented with
different levels and types of background noise, and how they covary across individuals (Aim 1). Next, for the
same individuals, the effect of attentional focus on the same envelope coding measures as Aim 1 will be
examined by keeping the input speech mixture constant and manipulating which speech source is the focus of
selective attention (Aim 2). This approach helps isolate the top-down component. Importantly, conducting all
intelligibility and EEG measurements in the same individual subjects allows us to leverage individual
differences and use regression techniques to characterize the relative contributions of bottom-up and top-down
mechanisms to performance. Finally, for the speech-noise mixtures used in Aim 1, we will calculate the same
envelope coding metrics at the output of a computational auditory-nerve model (Aim 3). Key mechanisms of
cochlear dysfunction will be incorporated into the model to characterize their effects on envelope coding of
speech in noise. By comparing “model” (Aim 3) and “neural” metrics (Aims 1 and 2), we will test whether
cochlear mechanisms can account for the individual differences in bottom-up coding. The knowledge gained
through the proposed set of experiments will be foundational in the development of objective diagnostics and
interventions tailored for the specific nature of speech-in-noise problems that an individual patient is
experiencing. Project completion will also provide the applicant with training in computational modeling,
psychophysical and EEG experiment design, data collection, analysis, and interpretation, a...

## Key facts

- **NIH application ID:** 9985088
- **Project number:** 5F31DC017381-03
- **Recipient organization:** PURDUE UNIVERSITY
- **Principal Investigator:** Vibha Viswanathan
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $44,546
- **Award type:** 5
- **Project period:** 2018-09-01 → 2021-08-08

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9985088

## Citation

> US National Institutes of Health, RePORTER application 9985088, Neurophysiological Mechanisms of Speech Intelligibility in Noise - A Quantitative Framework (5F31DC017381-03). Retrieved via AI Analytics 2026-06-03 from https://api.ai-analytics.org/grant/nih/9985088. Licensed CC0.

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