# Auditory brain-computer interface for communication

> **NIH NIH F32** · BROWN UNIVERSITY · 2020 · $74,810

## Abstract

Project Summary
 A fundamental end-goal of brain-computer interfaces (BCI) is to enable communication in individuals
with severe motor paralysis. BCIs decode the neural signals and accomplish the intended goal via an effector,
such as a computer cursor or a robotic limb. The BCI user relies on the realtime feedback of the effector's
performance to modulate their neural strategy to control the external device. To date, this feedback is
predominantly visual. However patients with the most severe paralysis resulting from amyotrophic lateral
sclerosis (ALS), some forms of stroke and traumatic brain injuries can have severe visual impairments
including oculomotor fatigue, nystagmus and ophthalmoparesis - that make the reliable use of a visual-based
BCI impossible. This puts a premium on developing novel solutions that can leverage sensory modalities that
are intact. In this research, I will develop and test the feasibility of an auditory-based interface to establish BCI
control in motor-impaired patients with severe neurological insults
 In Aim 1, I propose to implement a novel paradigm using auditory cues in lieu of visual signals, and test
its feasibility in controlling an effector (ie, computer cursor) to perform a cued target-acquisition task in healthy
participants. This will validate the range of parameter values of the four tested auditory input signals: 1)
frequency, 2) amplitude, 3) spatial azimuth and 4) spatial elevation. This approach is distinct from most binary
class auditory BCI solutions, since it relies on both the natural ability of humans to localize sounds, and the
ability to associate new tones to a virtual space, thus allowing a truly multi-class auditory approach. In Aim 2, I
propose to implement the auditory interface into the realtime xPC used for visual presentation in clinical trial
participants with intracortical BCIs, and test their performance on the cued target-acquisition task. Although
much success has been demonstrated in this task using visual feedback, this auditory approach will permit BCI
use by people with visual impairments further compounding their paralysis. Finally in Aim 3, I will test the
feasibility of BrainGate BCI users to utilize an auditory BCI speller to perform a copy-typing task and free-
typing task.
 The accomplishment of the goals of this research will be a critical step towards enabling severely
paralyzed individuals with visual impairments to re-establish communication independently, continuously and
reliably.

## Key facts

- **NIH application ID:** 9851289
- **Project number:** 5F32MH118709-02
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Daniel James Thengone
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $74,810
- **Award type:** 5
- **Project period:** 2018-12-01 → 2021-08-17

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9851289

## Citation

> US National Institutes of Health, RePORTER application 9851289, Auditory brain-computer interface for communication (5F32MH118709-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9851289. Licensed CC0.

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