Using Real-time Functional Magnetic Resonance Imaging (fMRI) Neurofeedback and Motor Imagery to Enhance Motor Timing and Precision in Cerebellar Ataxia
Phase: NA
Conditions: Cerebellar Ataxia, Spinocerebellar Ataxias, Cerebellar Degeneration
Sponsor: Johns Hopkins University

Title: Using Real-time fMRI Neurofeedback and Motor Imagery to Enhance Motor 
Timing and Precision in Cerebellar Ataxia 
 
NCT #: NCT05436262 
 
Document Date: 07/21/2023

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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Version 4 Dated:  01/2021 
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JHM IRB - eForm A – Protocol 
 
 
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1. 
Abstract 
a. Provide no more than a one page research abstract briefly stating the problem, the 
research hypothesis, and the importance of the research. 
 
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. 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. 
This proposal represents the first of its kind in the treatment of CA, with the potential to 
dramatically improve motor rehabilitation outcomes.  
 
2. 
Objectives (include all primary and secondary objectives) 
 
Primary Objectives 
Aim 1: Use rtfMRI-NF and motor imagery to train CA participants to improve motor accuracy. 
• Aim 1.1: Train CA participants (N=30) to engage neural regions during motor imagery 
that are associated with overt finger tapping at slow (1 Hz) and fast (4 Hz) speeds.  
• Aim 1.2: Correlate motor imagery skill (i.e., slider bar distance from target) with overt 
tapping performance.  

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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• Aim 1.3: Evaluate the relations between overt tapping accuracy and neurological 
symptoms as well as motor imagery skill with offline assessments of motor imagery 
ability. 
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: Translate rtfMRI-NF learning into at-home therapy strategies for continued training.  
• Aim 2.1: Examine whether motor imagery strategies from rtfMRI-NF 
training translate into successful at-home therapy training 
• Aim 2.2: Compare motor imagery performance during rtfMRI NF with at-home motor 
imagery benefits.  
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. 
 
Exploratory 
Aim 3: Design next-generation approaches to rtfMRI-NF. The data from Aim 1 will be analyzed 
to optimize the future rtfMRI experiments in the CA population. We will examine whether the 
NF session can be streamlined to deliver more accurate NF in shorter sessions. To enable future 
studies to operate within an experimental medicine frame work we will examine three major 
questions. Aim 3.1 Are there group differences in CA versus healthy controls? Aim 3.2 Are 
healthy models of motor imagery viable for CA participant NF? Aim 3.3 Can the NF session be 
streamlined to deliver more accurate NF in more efficient sessions?  
  
3. 
Background (briefly describe pre-clinical and clinical data, current experience with 
procedures, drug or device, and any other relevant information to justify the research) 
 
 
Preliminary Data: 
We will apply rtfMRI-NF imagery training to people with cerebellar ataxia (CA), a movement 
disorder that results from progressive cerebellar degeneration. CA individuals experience poor 
balance, difficulty walking, severe hand tremors, abnormal eye movements, and slurred speech. 
A key function of the cerebellum is to orchestrate the fine timing and sequencing of motor 
functions [3]. The cerebellum recognizes spatial and temporal relationships for feedforward 
predictions [4-7] and then compares the predicted versus actual outcomes and adjusts its output 
to the cortex [6, 8, 9]. CA signs, therefore, fundamentally reflect a disruption in timing ability. 
Without a known cure, current treatments include palliative pharmacology and physical, 
occupational, and speech therapies to strengthen muscles and counteract the symptoms of disease 
progression [10]. While these treatments can slow the rate of motor loss, they focus on physical 
manifestations and do not target the underlying neural mechanisms involved, thereby missing the 

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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root cause. Moreover, not all treatments are equally 
effective for each patient due to the heterogeneity of 
symptom presentations. We hypothesize that if patients 
could learn to “exercise” their own motor brain 
networks directly, they could optimize their 
rehabilitation.  
 
The National Ataxia Foundation released a report in 
January 2021 describing the three symptoms that 
mattered most to those with CA: lack of balance, 
impaired mobility, and decreased fine motor skills in 
the hand. Uncoordinated hand movements make it 
difficult to perform activities of daily living, such as 
writing, typing, eating, drinking, holding a razor or 
toothbrush, etc. Fine motor skills, therefore, represent 
an important target for therapeutic intervention and can 
reasonably be tested in laboratory and MRI settings.  
 
We compared performance of CA participants (N=17) 
and healthy controls (N=17) matched for age, sex, and 
education levels on a task that involved finger tapping 
in time with a visual cue that flashed at 1, 2, 3, and 4 
Hz (Figure 1). Performance feedback was provided as a 
slider bar that moved to the left as participants tapped too slow and to the right as they tapped too 
fast. We anticipated that CA participants would be able to use the external cues of the slider bar 
to correct tapping errors in real time, rather than rely on internal models of timing intervals. 
 
Tapping accuracy, measured by root-mean-squared error (RSME) relative to target, was 
impaired at all tapping rates. Relative to controls, the CA group’s tapping speed was too slow at 
4 Hz, and too fast at 1 Hz. Tapping too fast at 1 Hz suggest an inability to control movements to 
slow down. Over/undershoot corrections in finger movements likely averaged out and masked 
group differences in speed 2 and 3 Hz, but were revealed in the slow (1 Hz) and fast (4 Hz) 
conditions. In CA, higher symptom severity, as measured by the International Cooperative 
Rating Scale (ICARS), was associated with slower tapping and greater error magnitude. 
Together, these results suggested that accuracy and speed are dissociable measures, with 
accuracy being the more sensitive measure of motor impairment in CA. Moreover, the 1 and 4 
Hz conditions represented especially interesting tapping rates to study given the contrasting 
behaviors at each speed.  
 
 
Figure 1. Finger tapping speed and accuracy in 
CA. Top row: The CA group showed impaired 
accuracy at 1, 2 (trend), 3, and 4 Hz. Bottom 
row: The CA group tapped too fast at 1 Hz and 
too slow at 4 Hz. Yellow= group means. Error 
bars denote standard error [1]. 

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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We conducted a follow-up study to explore whether the feedback from the slider bar improved or 
degraded tapping behavior. We found that both groups slowed their tapping speed in the absence 
of continuous feedback, but the CA group’s tapping accuracy deficits persisted. Based on the 
differences between 1 and 4 Hz, we speculate that 4 Hz may be close to the tapping limits of CA 
participants, but 1 Hz represents a trainable target for improving motor timing from paced visual 
feedback. Thus, this application’s focus on 1 and 4 Hz builds on a foundation of preliminary data 
and aims to tease apart deficits in production from those of top-down feedback processing.  
We conducted an fMRI pilot study to identify neural activity patterns associated with right-
handed finger tapping in CA participants 
(N=10) versus matched healthy controls 
(N=6). The task used in the scanner was the 
same as that described above. Participants 
completed 16 total blocks of tapping, with 
one frequency presented per block, and 
each frequency (1, 2, 3, or 4 Hz) presented 
four times. At 1 Hz, the CA group 
hyperactivated cortical motor regions (e.g., 
right M1) and hypoactivated anterior 
cerebellar regions (Lobules V-VI). At 4 Hz, 
the CA group again hyperactivated cortical 
motor regions (Figure 2). 
 
Group differences in the cerebellar regions 
were mitigated by increased cerebellar 
recruitment in the CA group (relative to 1 
Hz). However, instead of recruiting the 
right anterior cerebellum only (ipsilateral to 
the finger tapping hand), the CA group 
recruited the anterior cerebellum bilaterally 
(Figure 3).  
 
These results suggest that the CA group 
recruited cortical motor regions more than 
controls regardless of speed and 
performance. The CA group’s cerebellar 
activity was abnormal at both speeds, but 
showed different patterns of activity. These 
results demonstrated the feasibility of 
conducting fMRI research using this task in 
CA participants, and also pointed to M1 and 
the cerebellum as potential targets for 
rtfMRI-NF training.  
 
Motor imagery can be an important 
rehabilitation tool for people with 
movement disorders [2]. Loss of motor 
Figure 2. Neural correlates of finger tapping at 1 Hz. FMRI 
contrasts for tapping at 1 Hz minus rest were compared between 
groups. Activations in red/yellow = tapping-related in the CA 
group. Activations in blue = tapping-related in the controls. The CA 
group hyperactivated cortical motor regions (e.g., right primary 
motor cortex, M1) and hypoactivated cerebellar regions (lobes V-
VI). Activations, p <0.005. Right = right.  
Figure 3. Within-group results for tapping at 4 Hz. 
FMRI contrasts for tapping at 4 Hz revealed bilateral 
recruitment of the anterior cerebellum in the CA group 
that was ipsilateral in controls. Activations in 
red/yellow = tapping-related. Activations in blue = rest-
related. Activations, p <0.001. Right = right.  

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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function following injury can be regained through neural reorganization, but motor execution is 
not always possible or safe. Numerous clinical studies have indicated that motor imagery 
improves motor performance, especially when used as an adjuvant treatment with physical 
practice [11]. 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 process. 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. For example, NF can be presented as a slider bar to indicate the degree to which a 
motor imagery strategy is working. Moreover, rtfMRI-NF may provide a quantifiable, objective 
marker of motor imagery performance, since the degree of NF control is proportional to the 
success of imagery to engage relevant brain regions. 
 
We will combine rtfMRI-NF with imagery to facilitate 
motor network (“exercise”) to improve function in CA. 
We will use support vector machines (SVMs) to 
extract motor imagery patterns and perform rtfMRI-NF 
as pioneered by LaConte [12, 13] (Figure 4). The SVM 
is first trained on an individual’s fMRI patterns while 
performing a simple motor task (e.g., finger tapping in 
sync with a flashing visual cue). SVM is then used to 
provide neurofeedback during a subsequent task (e.g., 
motor imagery of finger tapping). Information about 
the brain’s activity during motor imagery is relayed 
back to the person in the form of an “error signal” (i.e., 
distance from a target on a slider bar). Participants can 
use this neurofeedback to learn strategies for motor 
imagery that implicitly steer their brain towards 
optimal patterns of neural activity. As the participant 
changes their mental strategy, neurofeedback indicates 
whether the new strategy is working.  
 
RtfMRI-NF is safe, can be performed even when 
physical movement is severely impaired, and targets 
the underlying neural responses directly rather than the 
downstream physical signs. Although alternative cheaper and more portable imaging modalities 
may ultimately be adapted if this line of research garners success, fMRI is currently the best 
general purpose, whole-brain, non-invasive technology available for human research. Thus, the 
benefit of rtfMRI is that while this application optimally explores motor imagery’s therapeutic 
potential, it simultaneously addresses a critical need to better delineate motor control and 
imagery circuitry in CA. Since rtfMRI-NF is a relatively new technology [14], research is only 
beginning to explore its clinical uses. Most clinical studies to date have been conducted in 
psychiatric populations [15-26] which have reported symptom reductions in association with NF 
modulation of brain networks. 
 
Figure 4. Rt-fMRI NF and support vector machine 
learning (SVM). SVM learning: Inside the MRI, 
participants finger tap in sync with a flashing crosshair as 
a slider bar indicates tapping accuracy (right = too fast, 
left = too slow). FMRI data are preprocessed 
online and classified via SVM. RtfMRI-NF: During motor 
imagery, a slider bar indicates whether imagery 
strategies are successfully engaging brain regions as 
predicted by SVM classifiers. Thus, rtfMRI-NF guides the 
participant toward engaging motor networks through 
motor imagery [2].   

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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Only a handful of rtfMRI-NF studies have been conducted in neurologic conditions. In three 
stroke studies, participants (N=15 total) were able to modulate brain networks to improve motor 
and visuomotor function [27-30]. In three studies of Parkinson’s disease (PD), [31-33] results 
have been encouraging. Tinaz et al. (2018) found that eight PD patients were able to modulate 
connectivity between the insula and prefrontal cortex, which was the a priori target of interest; 
however, the modulation had no effect on motor function. A slightly larger PD study by 
Subramanian et al. (2016) compared rtfMRI-NF training plus at-home motor training (N=13) to 
at-home motor training only (N=13). The rtfMRI-NF a priori region of interest was the 
supplementary motor area (SMA) based on earlier findings that NF training to modulate the 
SMA correlated with reduction in PD motor symptoms (N=10) [31]. They replicated successful 
modulation of the SMA using rtfMRI-NF, and motor function improved by 20%. They reported 
trend-level correlations between NF success and motor function improvements. Moreover, 
improvements in the rtfMRI-NF group were 2-fold greater than in the exercise-only group (who 
did not show clinically relevant change), yet this group difference did not reach statistical 
significance. The authors suggested that studies with larger sample sizes are warranted. It is also 
notable that PD participants were guided to engage their SMA, even though additional regions 
were determined to upregulate with NF training, including the frontal lobe, anterior cingulate, 
basal ganglia, and cerebellum. Thus, our proposed agnostic, whole-brain classifier approach may 
be advantageous. 
 
In general, due to the novelty of the rtfMRI-NF methodology as applied to clinical populations, 
methods have varied across studies, and there is still much to learn about how to optimize 
procedures. Nevertheless, rtfMRI-NF holds great potential as a motor rehabilitation tool. The 
proposed project will pursue this line of research by using rtfMRI-NF and motor imagery to train 
CA participants to engage their motor network and improve motor function. We will also test the 
feasibility of translating this training into at-home therapy. We will use rtfMRI-NF data collected 
here to develop next-generation approaches to machine learning-based rtfMRI-NF that will 
inform future protocols. 
 
 
4. 
Study Procedures 
a. Study design, including the sequence and timing of study procedures  
(distinguish research procedures from those that are part of routine care). 
 
To address the objectives listed above, we plan to sample patients with cerebellar ataxia. For 
participants with cerebellar ataxia, this will be comprised of: 1) a screening phone call, 2) 
medical record review, 3) one study visit conducted by one of Dr. Marvel’s research staff, which 
will be comprised of both remote, in-person activities, and neuroimaging as detailed below.  
 
The specific study procedures are as follows: 
 
First, a screening phone call will be placed to assess eligibility for participants with cerebellar 
ataxia. The screening phone call will involve the use of screening scripts to identify if patients 
are eligible and willing to participate in the research. Furthermore, screening will check for two 
issues 1) clinical appropriateness and 2) MRI Safety. The only screening test that must be done 
in-person after consent is obtained is a pre-MRI pregnancy test. Patients with cerebellar ataxia 

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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will also specifically be asked for permission to review their medical records prior to the study 
visit to confirm eligibility. We will examine patient records in EPIC for additional medical 
information that may contain relevant study variables.  
 
Next, the first study visit will be coordinated and performed by one of Dr. Marvel’s research 
staff. This will involve a) written informed consent, b) interviewer-administered clinical history 
questionnaires, c) participant-administered surveys, d) neuropsychological testing, and e) MRI 
imaging at the Kennedy Krieger Institute. 
 
Teleconsent will be used as opposed to in-person consenting when possible to reduce 
unnecessary in-person encounters, as described in Section 15, Q1 of the eIRB application. 
Telemedicine visits will be substituted for portions of in-person visits (e.g., the consent process 
and the interviewer-administered clinical history questionnaires) when possible. Prior to 
initiating telemedicine for study visits the study team will explain to the participant, what a 
telemedicine visit entails and confirm that the study participant is in agreement and able to 
proceed with this method. Telemedicine acknowledgement will be obtained in accordance with 
the Guidance for Use of Telemedicine in Research. In the event telemedicine is not deemed 
feasible, the study visit will proceed as an in-person visit. Telemedicine visits will be conducted 
using HIPAA compliant method approved by the Health System and within licensing 
restrictions. 
 
Following informed consent, standardized instruments will be administered by a trained 
interviewer. Completion of these standardized instruments takes approximately 35 minutes. 
 
 
 
 
 
o Anxiety: The Hamilton Anxiety Scale (HAM-A) is a 14-item scale, scored from 0 (not 
present) to 4 (severe), that measures psychological and somatic symptoms associated 
with anxiety [34]. A score of less than 17 indicates mild anxiety, 18-24 mild to moderate 
severity and 25-30 as moderate to severe anxiety.   
o Depression: The Hamilton Depression Scale (Ham-D) is a 17-item scale, scored with a 0-
3 Likert scale measuring presence and severity of depression [35]. A score of 10-13 
indicates mild to moderate depression, and scores greater than 17 as moderate to severe 
depression. 
 
The following neuropsychological instruments will be administered at the study visit. We may 
also video the neurological exams (ICARS) for subsequent scoring by the study team. Video 
recording is especially helpful if there is ambiguity about neurological signs, and we want to get 
another study team member’s consensus rating. The complete battery takes approximately 120 
minutes to complete.  
Standardized Instrument 
Approximate Time 
(minutes) 
Hamilton Anxiety Scale (HAM-A) 
15 
Hamilton Depression Scale (HAM-D)  
20 
Neuropsychological Instrument 
Approximate Time 
(minutes) 

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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o Visual and Kinesthetic Imagery: The Kinesthetic and Visual Imagery Questionnaire 
(KVIQ-20), is a 20-item scale that is designed for patients who may have reduced 
mobility, difficulty standing, or performing certain movements due to neurological 
complications or disease progression [36]. The questionnaire assesses 10 items for visual 
imagery rated on a 1 (no image) to 5 (image as clear as seeing) and 10 items for 
kinesthetic imagery rated on a 1 (no sensation) to 5 (as intense as executing the action) 
scale.  
o Pre-morbid Function: An estimate of pre-morbid intellectual functioning will be 
measured using the Wide Range Achievement Test – 4th Edition, Reading subtest 
(WRAT-4) [37]. The WRAT-4 Reading is a standardized test requiring word decoding 
through letter identification and the ability to read increasingly complex words out of 
context. Age-referenced standardized scores will be calculated and converted to 
normalized T scores for analyses. Cognitive decline will be determined comparing 
neuropsychological test performance to estimated pre-morbid functioning on the WRAT-
4 Reading. Specifically, obtaining two or greater standard deviations below the WRAT-4 
Reading score on two or more neuropsychological tests will characterize cognitive 
decline.  
o Cognitive Impairment: The cerebellar cognitive affective/Schmahmann syndrome scale 
(CCAS-Scale), is a screening battery designed to test for disturbances in high functioning 
domains in patients with cerebellar damage including: executive, visual-spatial, 
linguistic, and affect regulation [38]. The total possible raw score is 120, with a pass/fail 
measure where 0 (normal), 1 (possible CCAS), 2, (probable CCAS), and 3 (definite 
CCAS).  
o Ataxia assessment: The International Cooperative Ataxia Rating Scale (ICARS), 
quantifies neurological impairments rated on an ordinal scale from 0-100. The ICARS 
assesses 19 items, with 4 subscales: posture and gait disturbance, kinetic function, speech 
disorder, and oculomotor disorders [39].  
 
When the neuropsychological testing portion of the visit is completed, they will then be trained 
on a cognitive task that will be administered inside the MRI. If they are a woman of childbearing 
age, they will be given a urine drug pregnancy test. If the pregnancy test is positive, they will be 
removed from the study and PHI and any data collected thus far will be destroyed. After training 
and pregnancy test if needed, they will be escorted to the F.M. Kirby Research Center across the 
street, which houses the MRI scanner. Participants will be asked to arrive 1 hour before the MRI 
scan is scheduled to begin. Total time spent in the scanner will be approximately < 1 hour, and 
Kinesthetic and Visual Imagery Questionnaire 
(KVIQ-20) 
45 
Wide Range Achievement Test (WRAT-IV)  
30 
Cerebellar Cognitive Affective/Schmahmann 
Syndrome Scale (CCAS-Scale) 
15 
International Cooperative Ataxia Rating Scale 
(ICARS) 
30 

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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we will reserve 1 full hour to allow time to get in and out of the scanner for this movement 
disordered population.  
 
 
 
 
 
 
 
 
 
Participants will perform an overt tapping test as a baseline measure of online task performance. 
Therapy begins the next day and lasts for 21 days (participants complete at least 5 days per week 
to accommodate scheduling conflicts). A final measure of overt tapping will be performed the 
day after therapy ends. Participants will be randomly assigned to one of three training conditions. 
Group 1, imagery only; Group 2, overt tapping only; and Group 3, imagery plus overt tapping. 
During imagery, participants will view the task while imagining that they are finger tapping in 
time with the flashing cursor, using the imagery strategies identified during their rtfMRI-NF 
session. During overt tapping, participants will finger tap in time with the flashing cue.  
 
Participants will be instructed to find a quiet room with minimal distractions and remain in a 
comfortable seated position with their hands resting on the keyboard. All tests include blocks of 
trials in which either 1 or 4 Hz cues are presented. In the baseline and final measures, a session 
will consist of one 4-minute test comprised of 12 blocks; each frequency will be presented six 
times. In the 3-week therapy component, a session will consist of two 2-minute tests comprised 
of six blocks each; each frequency will be presented three times per block. In all sessions, 
frequency blocks will be pseudorandomized such that the first block will always be the 1 Hz 
frequency, and the same frequency will be presented in no more than three consecutive blocks. 
All blocks begin with 5 seconds of rest, followed by 15 seconds of the flashing cue. After 
completion of their experience for the day (e.g, vividness of imagery, perceived tapping 
precision, etc.).  
 
 
BASELINE MEASURE 
3 WEEKS OF AT-HOME THERAPY 
CONDITIONS 
FINAL 
MEASURE 
Overt tapping 
(4 min) 
Daily log  
(3 min) 
Imagery  
(4 min) 
Overt tapping  
(4 min) 
Imagery + 
overt 
tapping  
(2 + 2 min) 
Daily 
log  
(3 min) 
Overt 
tapping 
(4 min) 
Daily 
log  
(3 min) 
Group 1 
(n=10) 
X 
X 
X 
 
 
X 
X 
X 
Group 2 
(n=10) 
X 
X 
 
X 
 
X 
X 
X 
Group 3 
(n=10) 
X 
X 
 
 
X 
X 
X 
X 
 
b. Study duration and number of study visits required of research participants. 
 
Task 
Approximate Time 
(minutes) 
Training on cognitive test (outside the scanner beforehand) 
10 
MPRAGE 
6 
Overt tapping 
12 
Motor imagery 
12 
Overt tapping 
12 

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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Each participant will have 1 in-person study visit (day 1) that will take about 3-4 hours. Days 2-
23 of the study will consist of at-home therapy 5x weekly that may take up to 10 minutes to 
complete. At-home therapy includes a baseline online measure and log (7 minutes), group 
designated tasks (See table below) and log (7 minutes), and a final online measure and log (7 
minutes). The total duration of the study is 2 years of data collection and analyses (allowing up 
to 3 additional years of data analyses).   
 
General Study Protocol 
Event 
Tasks Completed 
Duration 
Screening 
(phone) 
Clinical appropriateness 
15-20 minutes 
 
Screening 
(In-person) 
Consent*, pre-MRI pregnancy test 
25-30 minutes 
In-person 
visit 
Task orientation 
10-15 minutes 
MRI: Anatomical scan and rtfMRI-NF 
1 hour (42 min 
active MRI) 
Questionnaires*, assessments*, neurological exam, at-home 
instructions 
2 hours 
 
At-home 
therapy 
Baseline online measure & log 
7 minutes 
Training according to group assignment: Group 1 = motor 
imagery only, Group 2 = overt tapping only, Group 3 = motor 
imagery plus overt tapping (& daily logs) 
7 minutes per 
day for 3 
weeks 
Final online measure & log 
7 minutes 
* When feasible, these tasks will be conducted by phone 
 
c. Blinding, including justification for blinding or not blinding the trial, if applicable. 
N/A 
 
d. Justification of why participants will not receive routine care or will have current 
therapy stopped. 
N/A 
 
e. Justification for inclusion of a placebo or non-treatment group. 
N/A 
 
f. Definition of treatment failure or participant removal criteria. 
N/A 
 
g. Description of what happens to participants receiving therapy when study ends or if a 
participant’s participation in the study ends prematurely. 
N/A 
h. If biological materials are involved, please describe all the experimental procedures 
and analyses in which they will be used.  

 
Date: 07/21/2023 
Principal Investigator: Cherie Marvel, PhD 
Application Number: IRB00300264 
 
 
 
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N/A 
 
5. 
Inclusion/Exclusion Criteria 
 
Study population 
For the current study, we propose to recruit a total of N=30 adult participants with cerebellar 
ataxia. Participants with cerebellar ataxia will be recruited through the Johns Hopkins Ataxia 
Center. Dr. Rosenthal (Co-I and Ataxia Center Director) oversees the Ataxia Center’s new 
patient registry that will provide an additional source of recruitment. The Ataxia Center in 2019, 
saw 110 new patients and 243 follow-up visits.  
 
Inclusion criteria: 18-100 years of age, at least 8th grade education, right-handedness, clinical 
diagnosis of progressive, degenerative cerebellar ataxia by a movement disorder specialist 
(cerebellar ataxia of unknown etiology, and spinocerebellar ataxias with and without genetic 
confirmation).  
 
Exclusion criteria: History of Axis I psychiatric disorders (including alcohol and drug 
dependence), severe or unstable medical disorder, non-ataxia related neurological disorders, such 
as stroke or epilepsy, history of head injury that resulted in a loss of consciousness greater than 5 
minutes and/or neurological sequelae, any condition that is contraindicated for the MRI 
environment (e.g., metal in the body, pacemaker, claustrophobia), or currently pregnant, and 
clinical diagnosis of multiple system atrophy (MSA, due to the disruption of the central 
autonomic network) or Friedrich’s ataxia (FA, due to extensive involvement of the spinal cord 
and loss of sensory fibers in the peripheral nerves). MSA and FA differ substantially from other 
forms of CA and would greatly complicate interpretation of the data. Eligible subjects may be 
asked to refrain from medications that affect the central nervous system that would also make 
data difficult to interpret (e.g., sedatives) for an appropriate period of time prior to scanning. 
Participants will be excluded if they do not have a home computer with internet available to 
complete the 3-week at-home component of the study protocol.  
 
6. 
Drugs/ Substances/ Devices 
a. The rationale for choosing the drug and dose or for choosing the device to be used. 
N/A 
b. Justification and safety information if FDA approved drugs will be administered for 
non-FDA approved indications or if doses or routes of administration or participant 
populations are changed. 
N/A 
c. Justification and safety information if non-FDA approved drugs without an IND will 
be administered.  
N/A 
 
7. 
Study Statistics 
a. Primary outcome variable. 
 
1) Overt tapping accuracy improvements will be analyzed by comparing the mean accuracy on 
overt tapping between baseline and final measures (pre- and post- NF) to compute a delta 

 
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measure that will indicate magnitude of accuracy improvement at each frequency (1 and 4 
Hz). This will be analyzed using paired t-tests within frequency conditions.  
 
2) At-home overt tapping accuracy improvements will be analyzed by comparing the mean 
accuracy on overt tapping between baseline and final measures at home (pre- and post- 3-week 
at-home therapy training) to compute a delta measure that will indicate magnitude of accuracy 
improvement at each frequency (1 and 4 Hz). This will be analyzed using paired t-tests within 
frequency conditions. As a follow-up analysis of improvement during the 3-week therapy (for 
training Groups 2 and 3 who perform daily overt tapping exercises), the mean accuracy of overt 
tapping at both frequencies will be measured for each session and compared using repeated 
measures ANOVAs and post-hoc t-tests as appropriate.  
 
b. Secondary outcome variables. 
 
1) The relation between imagery accuracy and tapping accuracy with supplemental assessments 
of imagery and motor symptoms will be analyzed using non-parametric correlation tests, such as 
Spearman’s rank-order correlation coefficient test, because of the ordinal values in the KVIQ and 
ICARS assessments. Mean imagery accuracy and tapping accuracy scores from the final MRI 
assessment will be compared separately to the KVIA an ICARS.   
 
2) The relation between brain activity during imagery NF and overt tapping improvements will 
be analyzed using Pearson correlations between the mean of region of interest activity (minus 
rest) during NF training and the RSME delta scores.   
 
3) The influence of ancillary measures on overt tapping and motor imagery accuracy will be 
analyzed using non-parametric correlation tests (e.g., Spearman’s rank) because of the ordinal 
values in the HAM-A, HAM-D, CCAS, and WRAT assessments. Mean imagery accuracy and 
tapping accuracy scores from the final MRI assessment will be compared separately to each of 
the assessments.   
 
c. Statistical plan including sample size justification and interim data analysis. 
 
We plan to enroll 30 participants in this study. The sample size was determined through a power 
analyses using G*Power 3.1.9.2 software [40]. Because motor imagery, with or without rtfMRI-
NF, has never been used as a treatment approach for people with cerebellar ataxia (CA), as 
proposed here, our power analyses are extrapolated from information we have obtained that 
in three prior studies that support the premise and feasibility of Aim 1, which is to use rtfMRI-
NF and motor imagery to train CA participants to improve motor accuracy.  
 
In our first study, the behavioral RSME deficits exhibited by cerebellar ataxia participants while 
performing the same overt tapping task as proposed in Aim 1 was quite robust at both 1 Hz and 4 
Hz conditions (relative to controls, N=17 per group) [1]. Applying these data to our model 
revealed that a sample size of at least 12 participants per group yielded at least 82% power at 
the .05 level, one-tailed, to reject the null hypothesis of no differences between groups, based on 
an effect size of at least .79 (large). Although the proposed study will not include healthy 

 
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controls, at least 12 CA participants should be sufficient to elicit RSME 
performance impairments.  
 
In our second study, a functional MRI study of CA participants and healthy controls while 
performing the same overt tapping task as proposed in Aim 1 revealed several brain regions that 
differed between groups at the 1 Hz and 4 Hz conditions (N=6 controls, N=10 
ataxia): notably, right M1 and right cerebellar lobe V. Contrast values (1 Hz tapping – rest) for 
these regions were computed, using atlas-based boundaries [41, 42] for CA participants and 
healthy controls separately and entered into analyses. For the M1 region of interest 
(ROI), a sample size of at least 13 participants per group yielded 82% power at the .05 level, 
two-tailed, to reject the null hypothesis of no difference between groups at the 1 Hz condition, 
based on an effect size of 1.2 (large). For cerebellar lobe V, a sample size of at least 
9 participants per group yielded 83% power at the .05 level, two-tailed, to reject the null 
hypothesis of no difference between groups. Similarly, strong between-group differences were 
revealed at the 4 Hz condition for the M1 ROI. Atlas-based contrast values (4 Hz tapping – rest) 
for M1 were computed for each group and entered into analyses. A sample size of at 
least 8 participants per group yielded 84% power at the .05 level, two-tailed, to reject the null 
hypothesis of no difference between groups at the 4 Hz condition, based on an effect size of 
1.6 (large). However, group differences for cerebellar lobe V, not were significant in our fMRI 
study at the 4 Hz condition because the CA group was able to recruit this region vigorously in 
this tapping condition. Given the low number of participants per group in 
the functional MRI pilot study, additional brain ROIs were identified by trending between-group 
differences and entered into the model: left premotor cortex and bilateral 
lobes VIIB. For these ROIs, a sample size of 19-29 participants per group yielded at least 80% 
power at the .05 level, two-tailed, to reject the null hypothesis of no group differences, based on 
an effect size of at least .78 (large). These measures are conservative given that the ROIs were 
atlas-based rather than task-based (i.e., the ROI boundaries included voxels that did not differ 
between groups). Thus, a sample size of 29 would be expected to reveal neural activation 
abnormalities in a number of regions within the cortex and cerebellum in CA participants.    
 
In our third study, rtfMRI-NF was applied to healthy adults (N=17) while performing the overt 
tapping and imagery tasks proposed in Aim 1. Results revealed that several brain regions 
engaged during motor imagery positively correlated with RSME improvements: bilateral M1, 
right premotor cortex and the SMA. Atlas-based contrast values (motor imagery – rest) for these 
ROIs were computed. Entering into the model the correlation value and standard 
deviations between the mean contrast values per ROI and mean RSME “delta” revealed that a 
sample size of 17 – 22 participants yielded at least 81% power at the .05 level, one-tailed, to 
reject the null hypothesis of no linear relationship between motor imagery activation and RSME 
improvements.   
 
Taken together, we propose to enroll N=30 CA participants into this study. This N will be 
overpowered for some aspects of the study, such as tapping accuracy. However, we are also 
taking into consideration that the rtfMRI-NF data was based on healthy controls, and we 
anticipate greater variability in rtfMRI-NF training in the CA participants. Moreover, a sample 
size of 30 will allow us some room to make additional comparisons with the at-home therapy 
data (Aim 2) and exploratory MRI data analyses (Aim 3).   

 
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Sample size may be underpowered for the some of the proposed comparisons across aims.   
The amount of motor imagery necessary to improve overt tapping performance in CA patients is 
unknown. We modeled our power analysis parameters to target Aim 1. However, 
we will compare the neuroimaging data with at-home therapy performance variables 
(Aim 2) and will use the data from Aim 1 to conduct exploratory analyses to improve future 
protocols (Aim 3). The current sample size may be too small to detect significant results on all 
comparisons. Nevertheless, we consider the data we collect here to be highly informative for 
future studies and will serve as pilot data (and power analyses) for future grant applications.     
  
Statistical methods that will be used with respect to each outcome measure:   
In general, comparisons between measures with continuous variables (e.g., accuracy) 
within participants will be conducted using paired-tests, repeated-measures ANOVAs, and post-
hoc t-tests as appropriate. Pearson correlations will be run between continuous variables (e.g., 
motor imagery accuracy and delta scores). Non-parametric tests will be used when assessments 
that with ordinal values (ICARS, KVIQ, mood, and cognitive ancillary measures) are included.  
 
d. Early stopping rules. 
N/A 
 
8. 
Risks 
a. Medical risks, listing all procedures, their major and minor risks and expected 
frequency. 
 
Risks/Benefits 
The following relevant risk/benefit considerations and potential ethical issues may arise as part 
of the proposed study. Any adverse events will be promptly reported to the IRB. As this is not an 
intervention study, participants will be informed as part of the consent process that their medical 
care will not be affected or altered by their decision to participate in this research. There are no 
financial risks to the participant.   
 
MRI: Screening of participants will consist of checks for contraindications to MRI scanning. 
Urine pregnancy testing will be conducted on-site for women of child bearing age. Currently 
pregnant participants will be excluded. There are no known significant risks for an MRI exam. 
Subjects, may, however, experience mild discomfort by the noise made by the magnet during the 
procedure, bothered by feelings of claustrophobia, or anxiety. There is a risk that the subject may 
become bored or fatigued with cognitive testing while in the scanner.  
 
EMG: The EMG will be utilized to determine whether participants are moving their finger 
muscles during the imagery condition in the MRI scanner, in which they are not supposed to do 
so. To apply the surface electrodes on the participant’s arm, skin prepping gel similar to a gentle 
exfoliating cream will first be applied and rubbed onto the participant's skin in order to remove 
any dead skin. There is a risk that subjects may not like the feeling of the cream or that their skin 
will become slightly irritated. The risks of the electrodes are the same as those of applying a 
band-aid on someone's arm: subjects may be uncomfortable with the adhesive feeling of the 
electrodes, and the electrodes might feel similar to ripping off a band-aid when taken off.  

 
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Incidental findings: Participants may feel anxious due to the outcome of the MRI examination if 
an abnormality is detected by the neuroradiologist. Female participants of child bearing age may 
become anxious if a pregnancy test screen is positive.  
 
Behavioral testing: There is a risk that participants may become fatigued or bored while 
performing these tasks.  
 
Mood and neurological assessments: Participants may feel uncomfortable or anxious while 
discussing their mood states with the study team. During the neurological exam, CA participants 
will be asked to stand, walk, and perform other motor functions while sitting, which may create a 
fall risk or sense of frustration if the participant has difficulty performing the tasks. 
 
Confidentiality: 
Despite all precautions, there is a very small risk that identifying information may be revealed. In 
addition to the study team, the IRB may access personal identifying information during routine 
monitoring.  
 
b. Steps taken to minimize the risks. 
 
MRI: Participants who report previous experiences of claustrophobia will also be excluded. All 
participants will be supplied with ear protection during MRI scanning to reduce noise exposure. 
If at any time the participant becomes fatigued during cognitive testing, they will have the 
opportunity to take a break or if needed discontinue the scan. To reduce the risk of dizziness and 
nausea, subjects will be instructed to enter and exit the MRI scanner slowly and to limit 
movement while in the MRI scanner. 
 
EMG: To minimize the risk of any discomfort or skin irritation from the skin prepping gel, it will 
be applied carefully and gently to the subject’s arm. It will be made sure that the participant is 
comfortable with the electrodes when they are put on, and care will be taken when they will be 
removed in order to minimize any discomfort and skin irritation. If the participant becomes 
uncomfortable during recording, then the electrodes can be removed early. If the participant has 
highly sensitive skin or would not like to go through with the EMG, then an EMG recording does 
not have to be obtained. 
 
Incidental findings: All MRI structural scans will be read by a neuroradiologist within two-
weeks of acquisition. In the event of an incidental finding, the PI and Co-I (Dr. Liana Rosenthal) 
will be contacted immediately. Participants will be contacted by the Co-I (or neuroradiologist, as 
determined by group discussion) to notify them of the findings via telephone. Dr. Rosenthal can 
then refer the participant for follow-up care. Participants, upon written permission, may have the 
MRI findings sent to their primary care physician (PCP). Pregnancy test results will be delivered 
on the day of the MRI scan in person. If positive, study participation will end. If the participant is 
anxious or distraught from the test results, Dr. Rosenthal will be on hand to assess the need for 
immediate or follow-up medical care and can refer accordingly.  
 

 
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Behavioral testing: Prior to testing, participants will be reminded that study participation is 
voluntary and can be stopped at any time. Participants will receive ample opportunities to rest 
and take breaks as needed between tests.  
 
Mood and neurological assessments: If the participant becomes anxious or upset while 
discussing mood states, the experimenter will take a break from questioning until the participant 
is ready to continue. The participant may discontinue at any time. If the participant exhibits signs 
of extreme duress, or is found to have severe depression or endorse suicidal ideation, we will 
involve Dr. Rosenthal for consultation on the matter, engage their PCP, and/or escort them to the 
Emergency Department as appropriate. To minimize risk of falls during the neurological exam, 
we will have two experimenters present to assist with balance. If the participant or the 
experimenter decides that standing or walking will be too risky, that component of the 
neurological exam will be omitted.  
 
Confidentiality:  
• Subjects will be notified that they have passed or failed the screening directly in-person 
or by telephone. In the event of a screen failure, all documents containing the 
participant’s personal health information will be destroyed. All participants will be 
assigned a code number to protect confidentiality in lieu of participant names. The code 
key which includes participant names will be kept separate from clinical data obtained 
such as MRI, neurological scores, and assessments. Names and contact information will 
be stored in a locked cabinet in Dr. Marvel’s laboratory. Research staff that are IRB 
approved for this study will have access to this cabinet. Data will be stored on a secure 
REDCap database with password protections that will be accessible to study team 
members only. Publication of results will include only de-identified data.  
 
Data Collected in the Study : 
This research study will include outside collaborators for data analysis; however, this is not a 
multisite study. The collaborating site, led by Dr. Stephen LaConte at Virginia Tech (VT) Fralin 
Biomedical Research Institute, will obtain an independent, non-overlapping IRB protocol for this 
project because of the separate and distinct protocols that will be carried out at each 
site. Participant recruitment, testing, and all data collection will occur solely at Johns Hopkins. 
Defacing MRI data: 
All study-related data containing PHI, including structural MRI data, will be securely transferred 
from the Kirby Center to Johns Hopkins OneDrive. On OneDrive, structural MRI data will be 
accessed by an IT-supported lab computer in the Psychiatric Neuroimaging Core to complete the 
defacing using Pydeface software. The software registers structural images to a custom template 
and uses the template space to remove all facial features from the structural MRI scan. Header 
editing software is used to identify header fields and remove all data from Dicom header fields 
containing PHI. Defacing and header stripping is verified using OsiriX MD Dicom viewer 
software. We will examine the de-faced images to ensure that the facial soft tissue has been 
removed successfully. 
Defaced MRI data will be copied to Enterprise NAS for image processing and analysis.  

 
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Data Storage, Access, and Analysis: 
Non-MRI related PHI and LDS data will remain on OneDrive and will be accessed via 
SafeDesktop. Additional LDS information will be stored on a JH IT-managed Network Attached 
Storage (NAS) via space allocated through the JHU Psychiatric Neuroimaging Core. 
 
Data Sharing with Virginia Tech: 
After verification, MRI and related data in the form of a limited data set (LDS), will be shared 
with non-Hopkins collaborators at VA Tech using a folder on OneDrive that is separate from the 
folder with PHI. LDS may include the date of birth, age in years or months, and date of MRI 
scan. Dr. LaConte’s server is behind the VA Tech firewall and adheres to high PHI-protected 
security standards to safeguard data. We will share MRI and MRI-task behavioral data to VA 
Tech for analysis only. VA Tech may also be consulted during MRI scans to assist with technical 
errors for the real-time neurofeedback equipment; however, they will not be directly interacting 
with research subjects or learn their identity.   
 
c. Plan for reporting unanticipated problems or study deviations. 
 
In the event of an adverse event or serious adverse event that requires medical or professional 
intervention, the neurologist on the project, Dr. Liana Rosenthal, will be available to assess the 
level of attention required for immediate medical care. This may consist of escort to the ED or 
referral for follow-up medical care with the participant’s primary care physician or specialist. 
Furthermore, all events will be reported within 24 hours of the investigator becoming aware of 
the event to the IRB. Other unanticipated problems will be reported to the IRB within 2 weeks 
after the investigator becomes aware of the problem.  
 
d. Legal risks such as the risks that would be associated with breach of confidentiality. 
 
Every effort will be made to keep the information in the study confidential: (1) subjects will be 
assigned a code number and the code number only will be used to identify the scanning 
information, cognitive and behavioral information, or the clinical information that will be 
analyzed; (2) the computers on which the data will be stored are password protected on a secure 
server behind the Hopkins firewall; (3) written documents concerning the study will be kept in 
locked cabinets within locked personnel areas; (4) all personnel involved in the study have 
completed the appropriate HIPAA training and are fully aware of the need for confidentiality.  
 
e. Financial risks to the participants. 
 
These procedures will be performed at no cost to the subjects. 
 
9. 
Benefits 
a. 
Description of the probable benefits for the participant and for society. 
 
Cerebellar ataxia participants may not directly benefit as a result of study participation. Data 
collected from this study may provide important future directions to improve protocols that could 
in turn benefit cerebellar ataxia patients in the future. Motor imagery, guided by rtfMRI-NF, may 
provide a novel, safe approach to “exercising” the motor circuitry and providing a new 

 
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rehabilitation tool for individuals with cerebellar ataxia. Moreover, this methodology may 
transfer to treatment for other movement disorders.   
 
10. 
Payment and Remuneration 
a. 
Detail compensation for participants including possible total compensation, 
proposed bonus, and any proposed reductions or penalties for not completing the 
protocol. 
 
Participants will be given $100 for completing the study. Participants will be paid by gift card at 
the end of the study. Participants will be provided a parking voucher at the first visit (East 
Baltimore campus).  
 
If participants are from out of town, we may be able to provide one night of complimentary hotel 
lodging at Residence Inn Baltimore at the Johns Hopkins Medical Campus if needed, along with 
transportation to and from the hotel and our scanning facility if needed. Funds are limited and 
will be applied as needed but cannot be extended to all participants. 
If a participant leaves the study early, or is dropped from the study by the principal investigator 
for not complying with the procedures listed in this consent form, he or she will only be paid for 
the parts of the study that he or she has completed. The study will not reimburse for, or replace, a 
gift card that has been lost, stolen, or expired.  
 
11. 
Costs 
a. 
Detail costs of study procedure(s) or drug (s) or substance(s) to participants and 
identify who will pay for them. 
N/A 
 
 
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