# Dynamic Neural Mechanisms of Audiovisual Speech Perception

> **NIH NIH U01** · BAYLOR COLLEGE OF MEDICINE · 2020 · $1,061,698

## Abstract

Project Summary/Abstract
Speech perception is inherently multisensory: when conversing with someone that we can see,
our brains combine auditory information from the voice with visual information from the face.
Speech perception lies at the heart of our interactions with other people and is thus one of our
most important cognitive abilities. However, there is a large gap in our knowledge about this
uniquely human skill because most experimental techniques available in humans suffer from
poor spatiotemporal resolution. In order to remedy this gap, we will examine the neural
mechanisms of audiovisual speech perception using intracranial recording (iEEG) in humans.
Audiovisual speech perception occurs in the posterior superior temporal gyrus and sulcus
(pSTG) Understanding the dynamics of the neural computations within pSTG at the mesoscale
(neurons organized into columns and patches) has been impossible in humans. We propose to
leverage two technical innovations within the fast-changing field of iEEG to study them for the
first time: first, high-resolution intracranial electrode grids, which allow for recording from a
cortical volume hundreds of times smaller than the electrodes in standard iEEG grids; second,
NeuroGrids that record single-neuron activity from a non-penetrating film of electrodes placed
on the cortical surface. Our causal inference model requires the existence of distinct auditory,
visual and audiovisual speech representations. Aim 1 will search for these representations in
pSTG. Aim 2 will examine low-frequency oscillations in pSTG to determine their role in
multisensory speech perception. If successful, the Aims will provide a comprehensive account of
the neural mechanisms of multisensory speech perception, including the long-standing mystery
of the perceptual benefit of visual speech.

## Key facts

- **NIH application ID:** 10016852
- **Project number:** 5U01NS113339-02
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Michael S Beauchamp
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,061,698
- **Award type:** 5
- **Project period:** 2019-09-15 → 2020-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10016852

## Citation

> US National Institutes of Health, RePORTER application 10016852, Dynamic Neural Mechanisms of Audiovisual Speech Perception (5U01NS113339-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10016852. Licensed CC0.

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