Novel Brain Signal Feedback Paradigm to Enhance Motor Learning After Stroke
Phase: NA
Conditions: Stroke
Sponsor: VA Office of Research and Development

 
 
 
 
ID: N2192-P Novel Brain Signal Feedback Paradigm to Enhance Motor Learning After 
Stroke 
4/22/2019 
 
 

 
Problem.  Stroke (795,000/year in the US and 30 million existing stroke survivors in the 
world) damages brain neural structures that control coordinated upper limb movement.  To most 
effectively target the brain damage, interventions should be directed so as to restore brain 
control serving coordination of peripheral neuromuscular function.  Currently, there is a lack of a 
transformative intervention strategy.  Existing evidence shows that limited efficacy is exhibited in 
response to neural rehabilitation that is only peripherally-directed (limbs e.g.) or only directed at 
the brain.  One limitation of existing non-invasive direct brain stimulation methods is that the 
exogenously applied stimuli are more gross than the known existing endogenous brain neural 
networks and activation patterns.  Therefore, it is reasonable to consider engaging and 
retraining existing brain function after stroke, i.e., neural feedback in a closed-loop, real-time 
paradigm, such that the stroke survivor receives information regarding brain activation, and 
uses that neural feedback in order to re-learn brain control of more normal coordinated 
movement.  One name for such a neural feedback system is brain-computer interface (BCI); 
new types of BCI systems have been tested for motor training (e.g., EEG, MEG); however, 
either these systems were invasive (implanted) or they have not shown clinically efficacious 
results in motor recovery.   
Rationale.  In contrast, real time functional magnetic resonance imaging (rtfMIR) has 
recently shown the advantage of precisely identifying the location of brain activity for a variety of 
cognitive and emotional tasks; but though precise in its location of brain function, rtfMRI is not 
practical in terms of cost and feasibility during motor learning that requires sitting and engaging 
the upper limb in complex motor tasks across multiple sessions.  In contrast to rtfMRI, real time 
functional near-infrared spectroscopy (rtfNIRS) is not as spatially precise as rtfMRI, but rtfNIRS 
is a low-cost, portable solution to provide brain neural feedback during motor learning.  
Therefore, we will capitalize on the unique advantages of each, by utilizing them in a hybrid, 
sequential motor learning protocol.  Through rtfMRI-guided learning, followed by more repetitive 
rtfNIRS learning, we will engage the brain to enhance the effective signals for motor control.  In 
order to utilize Hebbian principles of learning, we will engage simultaneously both central 
effective signals (through neural feedback) and peripheral affective signals, by employing 
neural-triggered functional electrical stimulation (FES) assisted coordination practice, which 
produces peripherally-induced affective signals from muscle and joint receptors.  Thus, this 
combination intervention engages central nervous system, motor effective pathway training 
along with induction of affective signal production (FES-assisted practice), all of which will be 
implemented within the framework of evidence-based motor learning principles. 
 
Aim and Hypothesis.   
This study aims to develop and test an innovative protocol for recovery of wrist extension after 
stroke, using a combination of rtfMRI, rtfNIRS, FES, and motor learning. 
Aim I. Test the innovative coordination training protocol of combination rtfMRI/rtfNIRS central 
neural feedback and peripherally-directed, neurally-triggered FES-assisted coordination practice 
implemented within a framework of motor learning principles. 
Hypothesis 1. Chronic stroke survivors will show significant improvement in upper limb function 
in response to the combined rtfMRI/rtfNIRS central neural feedback; peripherally-directed FES-
assisted coordination practice of wrist and finger extension; and whole arm/hand motor learning 
(Primary measure: Pre-/post-treatment change score in Arm Motor Abilities Test - function 
domain (AMAT - F); secondary measure: Pre/post-treatment change score in Fugl-Meyer upper 
limb coordination. 
 
Methods 
Design 

Single cohort feasibility test of new intervention protocol employing rtfMRI and rtfNIRS, FES, 
and motor learning for motor learning following chronic stroke. 
 
Subjects 
Subject criteria as follows: 
• 
Cognition sufficiently intact to give valid informed consent to participate.* 
• 
Sufficient endurance to participate in rehabilitation sessions. 
• 
Ability to follow 2 stage commands. 
• 
Medically Stable 
• 
Age > 21 years. 
• 
Impaired upper limb function as follows: impaired ability to flex and extend the wrist. 
• 
At least 5 degrees of wrist flexion and extension of the wrist. 
• 
Passive ROM of wrist extension of at least 20 degrees. 
• 
At least 6 months post stroke. 
Exclusion Criteria: 
• 
Metal implants, pacemaker, claustrophobia, inability to operate the MRI patient call 
button or any other contraindications for MRI. 
• 
Acute or progressive cardiac (including cardiac arrhythmias), renal, respiratory, 
neurological disorders or malignancy. 
• 
Active psychiatric diagnosis or psychological condition, or active drug/alcohol abuse. 
• 
Lower motor neuron damage or radiculopathy. 
• 
More than one stroke. 
• 
Pregnancy (discontinued from the study, if a woman becomes pregnant). 
 * The combined scores for the Aid to Capacity Evaluation (ACE) and Mini-Mental Status 
Examination (MMSE) as follows: 
o 
MMSE 24-30 + the ACE score that states 'definitely capable' OR 
MMSE 17 - 23 + the ACE score that states 'probably capable' 
 
Intervention 
 
Intervention:  Neural Feedback Training and Motor Learning 
  
Real-time fMRI neural feedback training.   
Figure 1 provides a schematic of our rtfMRI system.  
MRI signal is transmitted to a second computer 
running Turbo Brain Voyager (Brain Innovation, 
Maastricht, Netherlands) to analyze data and provide 
feedback signal.  We will use our custom software, to 
provide feedback to the rtfMRI user (MATLAB; 
Mathworks Inc., Natick, MA, USA).  Feedback values 
are transmitted to a laptop running Presentation 
software to display an updated feedback image to 
the participant.  Lag between MRI acquisition and 
feedback presentation is (2-3s, current system).   
 The subject is first scanned during wrist extension 
and then wrist flexion.  The directions to the subject 
are communicated through Presentation software 
synched with the scanner.  Figure 2 shows  
what the subjects sees, while inside the scanner, in 
terms of directions to perform either wrist flexion or wrist extension (white background panels).  
Off-line analyses are conducted to ascertain baseline brain activation patterns.  Next, the 
subject uses real time fMRI neural feedback for re-training wrist extension, during which he/she 
Figure 1.  Real Time fMRI Schematic:  Closed 
Loop Feedback Training Paradigm 

also sees the far right panel in Figure 2 (black background panel), which shows a ‘thermometer’ 
that reflects, for  example, whether the BOLD signal is being upregulated by the subject, during 
wrist extension.    
 
Real time fNIRS neural 
feedback training. Each 
participant’s structural MRI is 
loaded into a neuronavigation 
system (Brainsight TMS 
neuronavigation software, 
Rogue Research Inc.) in which 
a fiducial manipulandum is 
localized in 3D space via 
“stereoscopic” infrared 
cameras, co-registered to the 
3D structural MRI. Attaching the 
manipulandum to the fNIRS 
optode array transfers co-
registration of optode 
placements to the subject’s 
structural MRI.  The optode 
array is attached to a 24-
channel Hitachi ETG-4000 fNIRS 
instrument (Figure 3, schematic 
of our rtfNIRS system).  We will 
use our custom software 
(Matlab; Mathworks Inc., Natick, 
MA, USA) to acquire the fNIRS 
signal from the user, analyze in 
real time, and present feedback, 
utilizing the thermometer 
feedback consistent with the 
rtfMRI feedback provided.  
Feedback values are transmitted 
to a laptop running Presentation 
software to display an updated 
feedback image to the 
participant. 
 FES.  The rtfNIRS system 
acquires brain signal, which 
serves to identify when FES is 
triggered for wrist extension-
assist coordination practice.  We are using the Motionstim 8 stimulator (MEDEL GmbH, 
Hamburg, Germany). Two unipolar electrodes of oval shape (4x6 cm) are placed on the wrist 
extensors and wrist flexors (PW, 300µs; frequency, 20 Hz - 30 Hz; amplitude, adjusted for 
comfort).  
 Motor learning with FES (no brain neural feedback).  The motor learning training is based, 
of course, on assessment of muscle strength, coordination, muscle tone, and functional task 
performance.  As in standard clinical practice, from this assessment, a clear understanding is 
derived by the treating therapist, regarding the impairments underlying the deficits identified, as 
well as the compensatory strategies employed.  The motor learning program begins at the 
Figure 2.  Visual Directions for rtfMRI-BCI User  
(Seen in the Scanner During Training of Brain Activation) 
 
Figure VV.  Panels with white background show directions for waiting (+), 
preparing to move, and move.  Panel with black background shows real time 
feedback regarding whether there was successful activation of targeted brain 
region. 
Figure 3. Real-time fNIRS Neurofeedback System With BCI-Triggered 
FES. 

‘challenge point’ of the learner, as in any learning plan of any type.  FES is used to assist in 
practicing more coordinated movements, until volitional capability recovers sufficiently for 
productive movement practice.  This assessment and treatment plan procedure are standard 
clinical neuro-rehabilitation practice, for which therapists are trained in their professional 
education.  
Specific motor task assessment for initiation of motor learning for a given task.  Prior to 
assigning a motor task within the motor learning program, the motor task is assessed for the 
following characteristics:   
What percent of the normal range of movement is executed, volitionally and independently; 
What percent of the motor task is executed with the support of verbal or tactile facilitation; 
What percent of the normal range of movement is executed, along with a motor assist device; 
Is a normal level of effort expended during the task (versus holding breath; abnormally tensing 
uninvolved muscles); 
Are motor compensatory strategies employed during execution of the entire duration of the 
motor task; 
Are motor compensatory strategies employed during execution of a portion of the motor task; 
How many repetitions of the motor task can be performed in a row, with only a ‘beat’ in 
between, before the motor task is performed in an uncoordinated or incorrect fashion. 
These assessments determine at which point in the coordination hierarch, the learner will begin.  
Progression of the motor learning program through the hierarchy of difficulty, is dependent upon 
iterative assessment, as is the case in standard clinical practice. 
Herarchy of motor task difficulty.  The hierarchy of motor task difficulty has been developed 
and used successfully in prior work.  Motor task difficulty is progressed using a purposeful 
approach.  In order to illustrate treatment progression for the Motor Learning Protocol, it is first 
important to understand the hierarchy of difficulty for the motor tasks underlying upper limb 
functional deficits after stroke.  We use a schema of increasingly difficult motor tasks that was 
developed and used successfully in prior work.  This hierarchy of task difficulty provides 
guidance for the starting point for training a given functional deficit or coordination deficit, as well 
as guidance for treatment progression of the motor tasks and task components that are 
impaired after stroke.  
 Training muscle activation within-synergy.  For one who is unable to activate a given 
muscle in any body position, the first treatment goal is to facilitate and elicit muscle activation on 
demand.  In a severely paretic muscle, activation is first elicited within a synergistic mass 
pattern, because in our prior work, we found that this is the easiest condition under which to 
obtain volitional muscle activation.  In this case, we begin with the subject in the sidelying 
position with the involved limb, uppermost, and supported on an exercise board in the horizontal 
plane.  The limb is positioned within a synergistic pattern for the start position.  The clinician 
provides minimal assistance, withdrawing external manual or device assistance as soon as the 
patient begins to regain volitional control during practice.  As the subject recovers the ability to 
control muscle activation, motor task practice is progressed to more difficult body positions.  
 Training isolated single joint movement within-synergy .  For training single joint 
movement, the subject practices isolated movement with the limb positioned so that the 
movement is practiced within a synergistic limb position. 

 Training isolated single joint movement, out-of-synergy .  The motor task goal is to 
achieve isolated single joint movement with the non-moving limb joints positioned in out of 
synergy positions.  As capability improves, the subject is progressed to more difficult positions. 
 Training multiple joint movement out-of-synergy .  The motor task goal is volitional control 
of multiple joint movements, out-of-synergy.   
 Training alternating joint movements .  In parallel with training described above, training 
can be conducted for control of alternating flexion and extension movement control.  The initial 
practice position can be sidelying.  The task is to alternate flexion and extension movements at 
a single joint, with the other limb joints in static neutral position.   
 Task Component Practice .   When the movements from above are sufficiently coordinated, 
actual task component practice can begin.  Task components can be progressed through a 
variety of body positions (e.g., sitting/standing) and through more difficult conditions (different 
object weights and shapes, faster speed performance). 
 Full Functional Task Practice .  Full task practice is undergone, as soon as the subject is 
able to practice with closer-to-normal coordination of task components.   If necessary, each 
component is practiced separately, just before integrating the components into the whole task 
practice.  During training, particular attention is allocated to the sequencing and grading of 
muscle contractions.  
Criteria for progression of motor task difficulty.  The criteria for progressing motor task 
difficulty described in this section has been developed and used successfully in prior work.  Our 
protocol utilizes the following clinical practice paradigm: ‘test-treat-test’ within a given session, 
as well as a ‘re-test’ procedure at the beginning of the subsequent session.  Standard clinical 
practice procedures of assessment, along with the assessment description provided above, 
provide information regarding the subject’s need for intervention at a specific level of motor task 
difficulty, the immediate response to intervention (within the session), and the carry-over effect 
between sessions.  These standard clinical practice procedures are applied in the clinical testing 
and training of each task component within a given session.  The subject’s ability, to 
demonstrate carry-over between the two sessions serves as the criterion for progression to the 
next level of difficulty for practice of a given task or movement component.  This information is 
not a formal outcome measure; rather, it is used to make treatment progression decisions, 
consistent with standard clinical rehabilitation practice. This information serves as criteria upon 
which to progress the functional training practice.   
 Motor task progression is standardized according to these specific guidelines. The motor task 
is progressed to a more difficult level if specific criteria are met, according to criteria derived 
from our past work. 
 
Measures 
  
Primary Measure, Aim 1, Hypothesis 1.  Function. The AMAT-F, a measure of 13 
complex, coordinated tasks used in everyday living (coordination of movement during functional 
tasks).  The AMAT is reported as being sensitive to change, specifically for stroke survivors; 
with high inter-rater, test-re-test reliability; and high homogeneity of scores on the test 
dimension of movement coordination within a function task.  Minimum clinically important 
difference (MCID) is .44 points, indicating that an improvement of at least .44 points is clinically 
significant.   
  
Secondary measure.  Impairment.  Coordination of isolated joint movement control will 
be assessed using the upper limb motor subscale of the Fugl-Meyer Coordination Scale (FM), 
measuring isolated coordinated movements of single or multiple upper extremity joints.  The FM 
is a sensitive, reliable and valid measure.  The MCID for the FM scale is 4.25 points, indicating 
that an improvement of at least 4.25 points is clinically significant.   
 
Data Interpretation:  Inspection of Descriptive Data  

 
Response to the innovative neural feedback combined treatment will be tested using the AMAT-
F as primary measure (pre-/post-treatment comparison) and FM as secondary measure.  Due to 
the small sample size we will inspect descriptive data for any trend or gain that is clinically 
significant. 
 
C.  Recruitment and Informed Consent 
The subjects to be enrolled in this study will be recruited (using posted flyers) from:  the MR 
VA Medical Center and the broader community.  Newspaper ads will be used to alert potential 
participants to the study.  Both the flyer and the newspaper ad will be approved by the UF/VA 
IRB.  Candidates will be consented for the study only after the IRB approves the consent form 
for the study.  The full IRB will approve the study materials, including the consent form.   
If the patient is interested in learning more about the study, research staff  will provide 
additional information.  Patients admitted to the study will provide written  informed consent.  
The informed consent process will include a scheduled meeting time with the potential 
candidate and family member/caregiver/significant other. The meeting will be held in a room in 
which everyone can sit in chairs, see and hear each other clearly, and feel no reason to hurry.  
During the meeting the following will occur:  verbal description of the study, including all content 
in the consent form; demonstration of the baclofen pump, and all the rehabilitation technologies; 
meeting a participating patient (if we have a participant who is available and has expressed a 
willingness to meet the potential participant); time for questions throughout each portion of the 
informed consent process and a time for questions at the end of the session.  After the first 
information session, the blank consent form will be provided to the study candidate to take 
home for several days.  The research staff phone number will be provided to the patient and 
family.  Questions will be answered by phone.  Follow-up information sessions will be 
scheduled, as requested by the candidate/family members, or as needed by the research staff 
member.    An appointment will be scheduled if the candidate expresses continued interest in 
the study.   Remaining questions will be answered.  Additionally, the candidate will be queried 
about understanding the study.  That is, the candidate will be asked to describe the study in 
his/her own words.  In order to be accepted into the study, the candidate will be required to 
express understanding of each point in the consent form.  If the candidate then agrees to enter 
the study, he/she will sign the consent form in the presence of a witness, the investigator will 
sign the consent form, and a copy of the consent form will be provided to the subject.   
 
D.  Potential Risks 
1. Device malfunction – There is a risk that the commercially available surface FES system will 
fail to operate properly.  
2. Electrical safety - There is a possibility of a shock hazard or of electrical burn. 
3.  Fatigue or muscle soreness. 
4.  Breach of confidentiality of subject identification. 
5.  Fatigue or discomfort during rtfNIRS neural feedback. 
6.  Fatigue and anxiety during rtfMRI neural feedback or MRI testing. 
E.  Protection Against Risks 
Because of the actions taken to minimize risks, the likelihood of the above risks is low.     
 
1. Device malfunction - There is the risk that the FES system will fail to operate properly.  

The stimulator is commercially available and used routinely in clinical practice.  It was designed 
with safeguards in place that limit the stimulus amplitude, pulse width, and frequency.   
2. Electrical safety - There is a possibility of a shock hazard or of electrical burn with the use of 
an electrical stimulation system.  The stimulus level is fixed within a threshold precluding shock 
hazzard.  Levels for the ranges of stimulation amplitude and pulsewidth that are used, are 
always used within the comfort of the subject.  These comforable levels are not great enough to 
cause tissue damage.  The treating therapist monitors the skin surface after a given session.     
 
3.  Fatigue or muscle soreness.  For many stroke survivors, muscles in the involved limbs have 
not been used for a number of months or years.  As with any deconditioned muscle, re-
conditioning can create some muscle soreness.  We have found in our prior work that we can 
preclude muscle soreness by finely incrementing the start-up of the exercise.  We routinely do 
not have reports of any muscle soreness from our subjects.  Fatigue can occur in subjects. 
Therefore, we have found that a finely incremented progression is best for activity level, 
including exercise.  The therapist on the study is highly experienced at assessing non-verbal 
communication and querying subjects as to their fatigue level.  The therapist is committed to 
providing a training protocol that is within the capability of a given subject, and providing 
frequent rests and a balanced session in order to achieve this. 
 
4.  Breach of confidentiality of subject identification.  Our research data becomes anonymous 
after the subject is enrolled and assigned a study number.  Our clinical data contains identifiers.  
We maintain separate files of clinical data and research data.  We will take the following 
measures to ensure the confidentiality of subject identification:  
a)     A subject will be assigned a subject code number upon enrollment into the study; 
b)     Identifying information will be maintained in a spreadsheet that can be accessed only 
by the study PI (password protected);  
c)      In research data, the subject will be identified by the subject code number assigned at 
study entry;  
d)    Clinical records that contain identifying information (including questionnaires and video) 
will be maintained in a room that is locked and in a locked shelf, with key access only by the 
therapist who provides daily training for the subject.    
d)     Informed consents are stored in a room that is locked, and in a locked file cabinet with 
key access only by the two research team members assigned to maintain the consent files 
and human subjects protection records. 
e)    The data will be maintained in accordance with VA policy.   
5.  rtfNIRS neural feedback.  For fNIRS experiments, the fNIRS equipment has a CE 
certification and obeys the near infrared spectrum and power that is allowed under university 
and federal regulations.   This is a non-invasive method of acquiring brain signal from the 
surface of the head.  Application of fNIRS headset and optodes are relatively quicker compared 
to other methods such as electroencephalography (EEG), and so, less intrusive to the user.  
The fNIRS headset can become uncomfortable for some, if worn too long.  The patient will be 
instructed that if he/she becomes fatigued or uncomfortable during rtfNIRS neural feedback 
training, we should discontinue the session.  To preclude this situation, we will maintain cap-
wearing to less than 40 minutes.  Our team is well-experienced at discerning fatigue and 
discomfort and will encourage patients to discontinue at any sign of fatigue or discomfort. 
6.  rtfMRI neural feedback and testing.  In the MR scanner, some participants may 
experience some anxiety at being inside the ‘tube’ of the MRI environment, and thus will be 
closely monitored for signs of anxiety. MR scanners produce noise as part of the image creation 
process, and thus all subjects will have their hearing protected by earplugs and/or headphones, 

and head positioner that also serves to reduce ambient noise. All scanning techniques involve 
only non-invasive recording techniques, and the instrumentation meets all relevant safety 
standards. The structural and functional pulse sequences used in our protocols are 
manufacturer-provided, and include inherent control of specific absorption rate (SAR) – 
prevention of exposure to radio energy above FDA accepted limits. All our scans fall well below 
FDA SAR limits. To ensure confidentiality, all references to specific individuals are removed 
from files stored on computer volumes, and subjects are assured of complete confidentiality of 
all scan materials.  
 Importance of the Knowledge to be Gained 
Stroke is one of the principal causes of morbidity and mortality in adults in the developed 
world and the leading cause of disability in all industrial countries. Stroke survivors can suffer 
several neurological deficits or impairments, such as hemiparesis, communication disorders, 
cognitive deficits or disorders in visuo-spatial perception. These impairments have an enormous 
impact on patient’s life and considerable cost for health and social services. Even after 
completing standard rehabilitation, more than half (50-60%) still experience some degree of 
motor impairment, and are at least partly dependent on others in their activities of daily living..  
Although some innovative rehabilitation strategies have shown potential in randomized 
control trials, available rehabilitation methods do not restore normal or close to normal motor 
function and quality of life in many patients.  Traditional approaches towards motor rehabilitation 
of patients after stroke have utilized limb motor training, and more recently, limb training 
expected to produce experience-dependent plasticity that would control more normal motor 
function.  More recently, some have explored the use of more direct stimulation of the brain with 
technologies such as tDCS and TMS.  Research has shown that neither of these methods 
applied separately are optimally suited for movement recovery after stroke. Therefore, we are 
proposing an integrative approach, combining a novel BCI neural feedback approach, together 
with more traditional experience-dependent limb training. 
There has been great interest in brain-computer interface (BCI) technology to help 
improve the quality of life and restore motor function in people with motor disabilities. Over the 
past 15 years, an increasing number of BCI systems have been developed. All of these systems 
record, decode, and ultimately translate some measurable neurophysiological signal into an 
effector action or behavior. Noninvasive signal recording approaches have used 
electroencephalography (EEG), magnetoencephalography (MEG), blood-oxygen-level 
dependent functional MRI, and near infrared spectroscopy.  However, these systems have 
either not been applied or not been clinically efficacious in producing motor recovery after 
stroke.    
Early results in the application of BCI technology for recovery of motor function are 
promising, though mixed. Our preliminary results and that of others have shown that individuals 
who have had a stroke could gain control of specific features in EEG signals and MEG signals, 
and real-time fMRI signals.  We recorded EEG activity while the patients performed a reaching 
task with affected arm, before and after a motor learning regimen.  EEG signal amplitude and 
latency measures showed improvements during the preparation phase of the reaching task. We 
showed that healthy individuals and subcortical stroke patients can acquire control of the activity 
in the ventral Premotor Cortex (vPMC) through instrumental training, and that has a beneficial 
effect on motor cortical facilitation and also motor performance in a pinch-force task.  However, 
others found in a randomized controlled trial, that BCI did not have an additive effect beyond 
robotic training, according to motor function measures.  Given the need for more efficacious 
interventions and the promising, but mixed results from early studies of BCI, it is important to 
develop and test more sophisticated BCI systems for motor learning after stroke, a more precise 

brain neural feedback system (Aim 1). 
Motor recovery after stroke is reported to be associated with structural and functional 
changes, such as neurite outgrowth in the peri-legional regions , increased synaptogenesis, 
increased axonal sprouting, and increased excitability of neurons. One way to capitalize on the 
advantages of different technologies is to combine those that provide unique motor learning 
practice advantages; in this manner, the shortcomings of a single technology can be 
compensated, as well.  We have used this strategy in prior work in order to satisfy the motor 
learning principle of practicing movements that are as close to normal as possible, which may 
guide newly sprouting axons to the appropriate cortical regions.  One promising combination of 
technologies is BCI for brain signal neural feedback and functional electrical stimulation (FES) 
for movement-assistance practice and affective feedback.  There is some promising work 
showing that FES and motor learning can produce clinically significant gains.  In prior work, we 
showed the feasibility of BCI integration with functional electrical stimulation.  Given the need 
and the advantages of each of the technologies of BCI and FES, along with the specificity of 
motor learning, it is critical to test the response to such a combined intervention protocol, 
according to motor recovery (Aim I).  
 DATA AND SAFETY MONITORING 
The major portion of the study will be conducted at the, the Malcom Randall Gainesville 
Veterans Affairs Medical Center.  One type of data acquisition and training will be conducted at 
the University of Florida, McKnight Brain Institute, MRI Core Facility:  MRI, fMRI data acquisition 
and real time fMRI training.   
Subject health data and progression of upper limb function capability will be monitored 2 
– 5 days per week by the therapist providing the intervention protocol.  A Clinical Team meeting 
will be held once per week to review subject health data and any changes in functional 
capability.  Membership of the Clinical Board includes the study PI, the physical therapist on the 
study, the engineer on the study.  
 
The study engineer will maintain a de-identified database of outcome measures.    
Individual subject data will be reviewed by the study team every two weeks.   
 
The study data is subject to review and/or audit by the Research Compliance Officer of 
the Medical Center, who is independent of the study.  The time of the full study review is 
selected at random, but will occur at least once during the proposed work.  Consent forms are 
reviewed annually by the Research Compliance Officer of the Medical Center.  The IRB 
provides oversight of human protections issues for all studies conducted at the Medical Center.  
The currently proposed study will comply with the IRB regulations and procedures.  The study 
will not begin until IRB approval is awarded.  The study will submit patient data and summary 
findings to the IRB on an annual basis.  If an adverse event occurs, it will be reported directly to 
the IRB within 24 hours, and all IRB procedures will be followed.   
ADDITIONAL TOPICS 
Inclusion of Women and Minorities 
Women and minorities are represented above the percentages of the national population at one 
or more of the referring medical centers.  For the last 48 subjects recruited into our research 
studies, 16% were women and 23% were minorities.  Men, women, minorities, and majority will 
be recruited using the same criteria.   
End of Human Subjects and Protection Document