# Neural Computations Underlying Cancellation of the Vestibular Consequences of Voluntary Movement

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2022 · $532,209

## Abstract

Project Summary: This research program is motivated by three goals. First, we will establish the neural
mechanisms that underlie the brain's ability to estimate and cancel self-generated vestibular (inner ear
balance) input during active movement. Second, we will determine how the vestibular cerebellum learns to
adapt to changes in the relationship between expected and actual sensory input to maintain stabile perception
and accurate behavior. Third, we will assess how reward-motivation signals influence circuit performance.
 The brain's ability to distinguish sensory stimuli that are the result of self-generated (i.e., active) versus
unexpected or externally generated (i.e., passive) stimulation is vital to ensuring perceptual stability and
accurate motor control. Notably, in the vestibular system, the same central neurons that receive afferent input
also send direct projections to motor centers to control balance and posture via the vestibular-spinal reflex.
This reflex is essential for providing robust postural responses to unexpected vestibular stimuli, yet is counter-
productive when the goal is to make active head movements. Accordingly, it is advantageous to suppress this
pathway during active self-motion. Over the past two decades, we have made excellent progress toward
identifying where brain makes the distinction between reafferent (i.e., active) and exafferent (i.e., passive)
vestibular signals. Specifically, while the responses of vestibular afferents remain robust (and equivalent)
regardless of whether stimulation is active or passive, neurons at the next stage of processing in the vestibular
nuclei are significantly less responsive to active self-motion. In addition, we have shown that this suppression
only occurs when sensory feedback matches that expected based on the motor command (e.g., during normal
active movements). In the proposed research, we will address several fundamental questions that remain open
regarding the computations that the brain performs to ensure stable perception and accurate motor control
during self-motion. First, experiments in Aim 1 will investigate how the brain computes the vestibular
cancellation signal that eliminates actively generated signals from early sensory processing. We predict that
the cerebellar cortex plays an essential role in computing the mismatch between expected and actual
vestibular input to compute a cancellation signal. Aim 2 will determine how the cerebellum learns to interpret
active motion as self-generated when the relationship between the actual and expected sensory feedback is
altered. These experiments will provide insight into the error-based mechanisms that ensure calibration of the
vestibular reafference suppression mechanism is maintained. Finally, in Aim 3 we will determine whether and
how motivation modulates cerebellum-mediated vestibular reafference suppression. Combined, these studies
will (1) determine the source of the vestibular reafference cancellation signal, (2...

## Key facts

- **NIH application ID:** 10434677
- **Project number:** 5R01DC018061-04
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Kathleen E Cullen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $532,209
- **Award type:** 5
- **Project period:** 2019-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10434677

## Citation

> US National Institutes of Health, RePORTER application 10434677, Neural Computations Underlying Cancellation of the Vestibular Consequences of Voluntary Movement (5R01DC018061-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10434677. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*