# Using real-time fMRI neurofeedback and motor imagery to enhance motor timing and precision in cerebellar ataxia

> **NIH NIH R21** · JOHNS HOPKINS UNIVERSITY · 2022 · $275,666

## Abstract

7. PROJECT SUMMARY
Motor imagery, especially when used as an adjuvant treatment with physical practice, promises to be a powerful
tool for improving function in individuals with movement disorders. Yet, due to its very nature, motor imagery
cannot be directly observed. This makes it difficult to assist and evaluate a patient's motor imagery efforts. Brain
activity associated with motor imagery is, however, observable through neuroimaging. Moreover, with the recent
development of technologies like real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF),
motor imagery “behavior” can be displayed to both the patient and the clinician. We hypothesize that if patients
could learn to “exercise” their own motor brain networks directly, they could optimize their
rehabilitation. In this proposal, we seek to examine the feasibility of applying rtfMRI-NF imagery training to
individuals with cerebellar ataxia (CA), a movement disorder that results from progressive cerebellar
degeneration. Current treatments can slow the rate of motor loss through methods such as physical therapy and
core strengthening, but they focus on physical manifestations and do not target the underlying neural
mechanisms involved, thereby missing the root cause. In addition to evaluating the feasibility of motor imagery
rtfMRI-NF in CA, we will examine the utility of additional at-home therapy, subsequent to the rtfMRI session.
Finally, we will use the rtfMRI-NF data for offline analyses for brain mapping, machine learning, and simulating
additional rtfMRI approaches to develop future iterations of rtfMRI-NF protocols. Thus, future work aims to
establish refined experimental medicine frameworks by identifying neural underpinnings (NF targets) of motor
accuracy, and testing whether engaging these targets, through NF, improves motor performance. As outlined in
the proposal, Aim 1 will use rtfMRI-NF during motor imagery to train CA participants to improve motor accuracy.
Thirty CA participants will receive NF during motor imagery in an experiment in which we hypothesize that 1) CA
participants will be able to control a NF interface; 2) imagery skill will be positively correlated to improvements in
overt tapping accuracy; and 3) overt tapping accuracy will correlate with neurological signs, whereas motor
imagery skill will correlate with assessed motor imagery ability. Aim 2 will translate rtfMRI-NF learning into at-
home therapy strategies for three weeks of continued training in which we hypothesize that 1) continued practice
with imagery strategies will lead to additional improvements in motor timing and precision, and 2) performance
during rtfMRI-NF training will positively correlate with at-home motor imagery performance. In an exploratory
Aim 3, we will examine three primary questions to establish future experimental medicine designs. Specifically,
these question are 1) Are there group-level differences in fMRI activity in CA versus healthy controls?; 2) Are
healthy...

## Key facts

- **NIH application ID:** 10354246
- **Project number:** 1R21NS125546-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** STEPHEN M LACONTE
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $275,666
- **Award type:** 1
- **Project period:** 2021-12-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10354246

## Citation

> US National Institutes of Health, RePORTER application 10354246, Using real-time fMRI neurofeedback and motor imagery to enhance motor timing and precision in cerebellar ataxia (1R21NS125546-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10354246. Licensed CC0.

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