ORIGINAL RESEARCH
published: 12 February 2021
doi: 10.3389/fnhum.2021.637401

A Study on the Effect of Mental
Practice Using Motor Evoked
Potential-Based Neurofeedback
Daiki Matsuda 1 , Takefumi Moriuchi 1 , Yuta Ikio 1 , Wataru Mitsunaga 1 , Kengo Fujiwara 1 ,Moemi Matsuo 1 , Jiro Nakamura 2 , Tomotaka Suzuki 3 , Kenichi Sugawara 3 andToshio Higashi 1*
1Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan, 2 Department of Occupational Therapy,
Nagasaki Memorial Hospital, Nagasaki, Japan, 3 Faculty of Health and Social Work, Division of Physical Therapy, Kanagawa
University of Human Services, Yokosuka, Japan

Edited by:
Ryouhei Ishii,
Osaka Prefecture University, Japan
Reviewed by:
Akiyoshi Matsugi,
Shijonawate Gakuen University, Japan
Hisato Sugata,
Oita University, Japan*Correspondence:
Toshio Higashi
higashi-t@nagasaki-u.ac.jp
Specialty section:
This article was submitted toBrain Imaging and Stimulation,a section of the journal
Frontiers in Human Neuroscience
Received: 03 December 2020
Accepted: 11 January 2021
Published: 12 February 2021
Citation:
Matsuda D, Moriuchi T, Ikio Y,
Mitsunaga W, Fujiwara K, Matsuo M,
Nakamura J, Suzuki T, Sugawara K
and Higashi T (2021) A Study on the
Effect of Mental Practice Using Motor
Evoked Potential-Based
Neurofeedback.
Front. Hum. Neurosci. 15:637401.
doi: 10.3389/fnhum.2021.637401

This study aimed to investigate whether the effect of mental practice (motor
imagery training) can be enhanced by providing neurofeedback based on transcranial
magnetic stimulation (TMS)-induced motor evoked potentials (MEP). Twenty-four healthy,
right-handed subjects were enrolled in this study. The subjects were randomly allocatedinto two groups: a group that was given correct TMS feedback (Real-FB group) and agroup that was given randomized false TMS feedback (Sham-FB group). The subjects
imagined pushing the switch with just timing, when the target circle overlapped a crossat the center of the computer monitor. In the Real-FB group, feedback was provided tothe subjects based on the MEP amplitude measured in the trial immediately preceding
motor imagery. In contrast, the subjects of the Sham-FB group were provided with afeedback value that was independent of the MEP amplitude. TMS was applied when
the target, moving from right to left, overlapped the cross at the center of the screen,
and the MEP amplitude was measured. The MEP was recorded in the right first dorsalinterosseous muscle. We evaluated the pre-mental practice and post-mental practicemotor performance in both groups. As a result, a significant difference was observed in
the percentage change of error values between the Real-FB group and the Sham-FB
group. Furthermore, the MEP was significantly different between the groups in the 4th
and 5th sets. Therefore, it was suggested that TMS-induced MEP-based neurofeedback
might enhance the effect of mental practice.
Keywords: mental practice, motor evoked potential, neurofeedback, transcranial magnetic stimulation, motor
imagery training

INTRODUCTION
With the progress in brain imaging technology in recent years, mechanisms in the brain that havebeen treated as black boxes are gradually being clarified. In particular, even when the brain isdamaged, such as in cerebrovascular disorders, it has been proven that plastic brain changes, asa consequence of training, do occur. In recent years, attention has been focused on rehabilitation
based on knowledge of the mechanisms in the brain. Under such circumstances, mental practice(i.e., motor imagery training) is one of the means of rehabilitation acting in complement tomovement therapy; mental practice is a method of repeatedly reproducing motor imagery.

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Conversely, TMS is a method that can evaluate brain activity
during motor imagery, like to be using fMRI and NIRS. The
motor evoked potential (MEP) is widely used as an evaluation of
M1 excitability, and the MEP amplitude (peak-to-peak) has beenreported to be significantly higher during motor imagery than incontrol conditions in several previous studies (Fadiga et al., 1998;
Facchini et al., 2002; Munzert et al., 2009).
It has been reported that a greater MEP amplitude isassociated with greater motor imagery (Williams et al., 2012)and more vivid kinesthetic motor imagery (Ohno et al., 2011;
Ikeda et al., 2012; Moriuchi et al., 2020). Based on the above,it is possible that results similar to the results of feedback
performed by fMRI and NIRS can be obtained even when
feedback using TMS is performed. Compared to fMRI and NIRS,TMS equipment is relatively inexpensive and easy to move, so
there are few restrictions; as such, we thought that it would
be useful for increasing opportunities for neurofeedback inclinical situations.
Therefore, the purpose of this study was to verify whether M1
excitability can be promoted by feedback to the subject with the
MEP amplitude (peak-to-peak) induced by TMS as an index.

Motor imagery is the execution of a mental action in astate where there is no clear movement or muscle activation(Mizuguchi et al., 2014). It has been reported that in motor
imagery, activation in the brain is recognized to be almost similar
to the actual action, without the accompanying movement.
Specifically, studies using positron emission tomography (PET)and magnetic resonance imaging (fMRI) have reported thatthe premotor area, supplementary motor area, cingulate, andparietal cortex are activated during these mental exercises (Porroet al., 1996, 2000; Deiber et al., 1998; Lotze et al., 1999;
Gerardin et al., 2000; Ehrsson et al., 2003; Hanakawa et al.,
2003; Jackson et al., 2003; Kuhtz-Buschbeck et al., 2003; Dechentet al., 2004; Meister et al., 2004). In addition, activation of
the primary motor cortex (M1) has been reported by studies
using electroencephalography (EEG) and transcranial magnetic
stimulation (TMS) (Pfurtscheller and Neuper, 1997; Hollinger
et al., 1999; Caldara et al., 2004; Mattia et al., 2004). Mental
practice does not require special machines or devices, andsubjects can easily work on it without any time or space
restrictions. Furthermore, since it can be carried out without
actual movement, it can be applied to patients who do not havethe capacity to perform voluntary exercise and minimize dangers
such as risk of falling (Dietrich, 2008). In fact, there is also areport, using randomized controlled trials, that demonstrates theeffect of mental practice on the improvement of upper limb
paralysis in stroke patients (Page et al., 2009; Nilsen et al., 2012;
Park and Lee, 2015). Furthermore, a systemic review showedthat mental practice is an effective intervention for upper limb
dysfunction in stroke patients (Langhorne et al., 2009).
However, although evidence has been shown for the effect ofmental practice, it is not widely used in clinical settings. The
reason for this is that since motor imagery is processed in thebrain, it is difficult to objectively evaluate how clearly the subject
undertakes motor imagery as a task, from the viewpoint of thetherapist. Therefore, it is difficult to give accurate feedback during
practice. To address this problem, attempts to evaluate brain
activity in motor imagery using brain imaging technology andprovide feedback to the subject in real-time, have been reported(Broetz et al., 2010; Ang et al., 2011; Pichiorri et al., 2015; Mehler
et al., 2019). For example, a previous study measured the change
in cerebral blood flow rate in a motor-related region (right dorsal
region of the premotor cortex), as a blood oxygenation leveldependent signal using fMRI. Through feedback to participants,
it was possible to perform mental practice while maintaining
increased motor imagery ability; as a result, the study reported
an improvement in performance (Hui et al., 2014). In addition,oxygenated hemoglobin signals in the premotor area, on the
opposite side, were recorded with motor imagery using nearinfrared spectroscopy (NIRS); we performed the measurements
by dividing participants in to the real-FB group (feedback of thecorrect amount of cerebral blood flow change to the subject) andthe sham-feedback group (feedback of a false cerebral blood flowchange). The real-FB group showed that the self-assessment scalescores for kinesthetic motor imagery were higher than those of
the Sham-feedback group (Mihara et al., 2012). However, theabovementioned neuroimaging equipment is expensive, highly
restrictive, and possibly difficult to widely use in the clinic.

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MATERIALS AND METHODS
Subjects
A power analysis using G-power revealed a requisite sample sizeof 22 (with an effect size of 0.4 and significance level of p <0.05, power of 0.8). A total of 24 healthy subjects (14 men and
10 women; mean age, 22.4 ± 3.4 years) were enrolled in the
study. All participants provided written informed consent, andall were right-handed (as indicated by self-report). None of thesubjects reported neurological impairment or contraindications
to TMS. The study was approved by the local ethics committee ofNagasaki University Graduate School of Biomedical Sciences. All
experimental procedures were conducted in accordance with the
Declaration of Helsinki (World Medical Association, 2013).
To reveal the effect of TMS feedback, all participants wererandomly allocated to either the real-feedback group (Real-FB)(n = 12; a group given a right MEP amplitude) or the shamfeedback group (Sham-FB) (n = 12; a group given a non-related
value of MEP amplitude).

Experimental Set-Up
Subjects were seated on a reclining chair 80 cm away froma computer monitor (19-inch, resolution 1,024 × 768 pixels,
refresh frequency 60 Hz) and were instructed to keep both hands
in a pronated position on a horizontal board attached to thechair’s armrest. They were instructed to keep the right forearmas still and relaxed as possible while paying attention to the visual
stimuli presented on the monitor. The position of the right index
finger was adjusted, as shown in Figure 1, so that the switch could
be pressed by the abduction movement.

Experimental Task
The motor imagery task was conducted as shown in Figure 1. The
timing of the TMS trigger needs to stimulate at the same point as
the action, during motor imagery. Therefore, in the present study,

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FIGURE 1 | Experimental set-up and task. Seventy-five images were continuously reproduced, and magnetic stimulation was applied at the time of the 38th frame atwhich the cursor overlapped with the target point. At the time when the cursor overlapped with the target point, we instructed the participant to press the button byindex finger abduction.

arrival of a cursor to the target point. Subjects obtained feedbackof the obtained MEP amplitude values. Figure 2A shows themonitor of the neuro-feedback system used in the present study.
We set the level meter, at the bottom of the monitor, which
could reflect the corticospinal excitability during motor imagery.
A value of 100% indicated corticospinal excitability in the resting
condition. This level meter was represented by a scale from0 to 200%, where every 10% indicated the relative change incorticospinal excitability during motor imagery (Figure 2B). A
previous study reported that the difference in vividness for motor
imagery affected corticospinal excitability (Moriuchi et al., 2020).
Therefore, if subjects can imagine something vividly, the value ofthe level meter reaches over 100%. On the other hand, if subjects
cannot imagine vividly, the value of the level meter will be equal
to or <100%.
Corticospinal excitability was assessed in the program andimmediately displayed on the level meter. For the Real-FB group,
the level meter provided the real value of each trial. However,for the Sham-FB group, the level meter randomly provided a
non-related value of the actual corticospinal excitability. The
bar displayed by the program is set to vary randomly between
0 and 200%. Therefore, it is considered that it was displayednearly evenly for the Sham-FB group. The subjects were provided
with sufficient prior explanation by the experimenter about themechanism of the level meter used for feedback. In addition, we
explained that the closer to Good, the better the motor imagery,and the closer to Poor, the worse the motor imagery.

we adopted the coincidence timing task, which involved pressing
the button through index finger abduction, coinciding with thearrival of a cursor, running on a straight forward line from thestart point. In the performance evaluation of this experiment, theabduction switch was pressed with the index finger touching the
button, such that the abduction angle was very small. The starting
point was to the right of the monitor and the target point was in
the middle of the screen.
The experimental video was made from 75 individual JPEG
files, from the starting point to the end point, and shown insuccession to obtain the animation effect, which was presented ata speed of 33.3 ms/frame. The timing of the coincidence with thearrival of the cursor to the target point was the 38th file. Based on
the above, the circle reached the target in 1.27 s, and the distancefrom the start position to the target was 12.5 cm on the monitor.
One set (20 trials) was used for performance evaluation.
An experimental movie was played where a black cross in thecenter of a white screen was presented. After the warning signal(beeping sound), the cursor ran on a straight line at a constant
speed from the starting point, to the target point. Subjects wererequired to pay attention to the movement of the cursor on themonitor and to press the button with index finger abduction,
when the cursor arrived at the target point. The experimental
program used in the present study was a custom-made programby LabVIEW systems (LabVIEW, National Instruments, USA).

Mental Practice
Mental practice with motor imagery was conducted for fivesets with 20 trials per set. Therefore, the total number of trials
was 100. Subjects were instructed to kinesthetically imagine thecoincidence timing task as if they were actually performing the
movement, and subsequently recall the sense of the fingertip,
muscle strength, and the sound when they pressed the button.

TMS and MEP Recording
Surface EMG signals were amplified and filtered at a bandwidthof 5–3,000 Hz using a digital signal processor (Neuropack Sigma
MEB-5504, Nihon Kohden; Tokyo, Japan). Analog outputs froma single processor were digitized at a sampling rate of 2,000 Hz
and saved to a computer for offline analysis using an A/D
converter (PowerLab16/30, AD Instruments, Sydney, Australia).
At the beginning of the experiment, we identified the optimal
TMS coil position for evoking MEPs in the right FDI (theTMS Feedback
We used MEP induced by TMS during motor imagery forneurofeedback. The TMS trigger was set at the timing of the

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FIGURE 2 | TMS feedback. (A) Motor evoked potential (MEP) amplitudes compared with baseline were feedback visually on each trial. (A) shows the level meter
displayed to the subject when providing feedback. This is represented by a graduation that ranges from 0 to 200%, in 10% increments. The value in the motor
imagery task, compared with the MEP at rest, is displayed. (B) If the MEP amplitude size during the motor imagery task is <100% compared with that in the control(at rest) MEP amplitude size, the level meter is displayed in red; if the MEP amplitude is over 100%, the level meter is displayed in blue.

on how far the target point and the cursor deviated, when thesubjects pressed the switch button in the coincidence timing
task. Subjects were given 20 trials and we evaluated how many
images were displaced with respect to where the target point
and the cursor coincided. Calculation of the number of errors
was incorporated into the program and could be performed
automatically. The maximum value of the error was 37, which
was calculated from the target point.
To rate the vividness of the subjects’ motor imagery, thesubjects were asked to complete a self-evaluation test on a visual
analog scale (VAS). Subjects marked a location on a 100-mm
horizontal line, the two ends of which were labeled “0 = None atall” and “100 = Very vivid image,” according to the vividness of
the imagery they imagined (Martin and Ulrike, 2006; Ikeda et al.,2012).

hotspot). TMS was delivered to the left M1 hotspot, marked witha pen on a swimming cap covering the scalp of each subject.
TMS employed a 70 mm figure-eight coil connected to a magnetic
stimulator (Magstim 200, Magstim, UK). The coil was placed
tangentially to the scalp with its handle pointing backward androtated ∼45◦ away from the mid-sagittal line. Care was taken to
maintain the same coil position relative to the scalp throughout
the experiment. The resting motor threshold (MT) was definedas the lowest stimulus intensity that evoked a MEP of at least 50µV in amplitude, in the right FDI, in five out of 10 trials. The test
stimulus intensity was set at 110–130% of the resting MT. The
mean amplitude of the control MEP for the FDI was 0.5∼1.0 mV.
Throughout the experiments, subjects were instructed to avoid
inadvertent movements that could give rise to background EMG
activity. For each muscle in each trial, the 20 ms period preceding
TMS triggering was checked for background EMG activity.

Experimental Procedure

Evaluation

We conducted 20 trials of performance evaluation of actual
movement in both groups (pre-evaluation). We then measured
the MEP amplitude at rest. Subsequently, motor imagery trainingof pressing the switch, was carried out to ensure vividness of

An assessment of performance and vividness for motor imagery
was conducted before and after the intervention of mental
practice using TMS feedback. Performance assessment was based

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FIGURE 4 | MEP amplitude change in each set during the motor imagery task.
Changes in MEP amplitude (mean ± SE) for each feedback group. *p < 0.05.

FIGURE 3 | Change in motor performance. Percentage change in the error
values (mean ± SE) in each feedback group. *p < 0.05.

TABLE 1 | Error value and percentage change of error values for each group.

Real-FB group

Sham-FB group

Pre

Post

Error value

42.3 ± 15.9

38.9 ± 16.9

Percentage changes of error
value

90.4 ± 16.6

Error value

35.2 ± 11.8

Percentage changes of error
value

126.3 ± 27.6

43.8 ± 15.2

FIGURE 5 | Background EMG amplitude in each set during the motor imagery
task. Changes in root mean square of the background EMG amplitude (mean± SE) for each feedback group.

the motor imagery of the subject, and the VAS was used toevaluate the vividness of the subjective motor imagery (preevaluation). We then performed a motor imagery task as amental practice using TMS feedback across five sets (total 100
trials), with 20 trials being one set. After the experimental task,
both groups were again evaluated by VAS (post-evaluation), andthe performance evaluation of actual movement was conducted
for 20 trials (post-evaluation). The two groups were compared
and analyzed.

(Real-FB vs. Sham-FB), and “trial sets” (rest, 1st−5th sets). The
background EMG activities (with each TMS trial data represented
as the root-mean-square (RMS) amplitude of the 20 ms prior
to the TMS trigger) of right FDI muscles were analyzed using
two-way repeated-measure ANOVA, with the factors “group”(Real-FB vs. Sham-FB), and “trial sets” (rest, 1st−5th sets). Whena main or interaction effect was found in “trial sets,” a post-hoc
analysis was conducted using Dunnett’s test. On the other hand,
if the main or interaction effects was found in “group,” anindependent t-test was performed to examine group differences
for each set.
In all analyses, a p-value of < 0.05 was considered statisticallysignificant. All analyses were performed using statistical analysis
software (SPSS version 22.0, IBM, USA).

Data and Statistical Analysis
We compared performance improvement (percentage change oferror values), MEP, and changing vividness of motor imagery(percentage change of VAS scores) between the Real-FB group
and Sham-FB group. The error value and VAS score were
calculated using the following equation: [(the error value of 20
trial or VAS score of the post-test—the error value of 20 trial
or VAS score of the pre-test)/the error value of 20 trial or VAS
score of the pre-test × 100+100]. An independent t-test wasused to examine group differences in performance improvement.
Furthermore, if a background EMG was found, the data ofthe trial were rejected. The MEP amplitude (peak-to-peak) was
measured in every trial. The data were analyzed statistically using
two-way analysis of variance (ANOVA), with the factors “group”

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RESULTS
Change in Motor PerformanceFirst, a two-way ANOVA was performed in a total of 20 trials
using the error value for each trial. The results of the two-way

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MEP-Based Neurofeedback for Mental Practiceconfirmed that p = 0.458; the observed covariance matrix of thedependent variable was equal between the two groups. Figure 5
shows the changes in the RMS background EMG amplitude(in both groups. The two-way ANOVA showed no significant
main effect and interaction for “trial sets” and “group” of the
background EMG.

Change in the Vividness (VAS) of
Subjective Motor Imagery
Figure 6 shows the change in VAS (± standard error) inboth groups. The results of the two-way ANOVA showedno significant interaction between groups and trials. A Box’s
M test confirmed that p = 0.736; the observed covariancematrix of the dependent variable was equal between the twogroups. Furthermore, there was no significant difference inthe percentage change in VAS scores; however, there wasa tendency for improvement in the Real-FB group’s VAS
score in the “evaluation point” (p = 0.059). Table 2 shows
the VAS score and percentage change of VAS values ofeach groups.

FIGURE 6 | Percentage change in VAS score. Percentage change in the VAS
score (mean ± SE) in each feedback group.

DISCUSSIONANOVA for “group” (Real-FB vs. Sham-FB) and “evaluation
point” (pre-evaluation vs. post-evaluation) showed that there
were significant main effects for “group” and “evaluation point”
and a significant interaction. A Box’s M test confirmed that p =0.556; the observed covariance matrix of the dependent variable
was equal between the two groups.
Figure 3 shows the motor performance (± standard error)change in both groups. A significant difference was observed in
the percentage change of the error values between the Real-FB
group and the Sham-FB group. The motor performance uses theerrors in 20 trials, thus, a lower value means a better performance.
The percentage change in error values was 100% or less in the
Real-FB group and 100% or more in the Sham-FB group. In otherwords, this shows that the timing error decreased in the Real-FB
group and increased in the Sham-FB group. Table 1 shows theerror value and percentage change of error values, in each group.

The purpose of this study was to clarify whether the effectof mental practice is enhanced when providing neurofeedback
based on TMS-induced MEP as an index. In order to clarify
the effect of TMS feedback, we divided the subjects into twogroups; the Real-FB group which received a feedback MEP
amplitude as an index and the Sham-FB group which received
feedback values not related to MEP amplitude. The two groups
were then compared, and a significant difference was observedin the percentage change of error values between the RealFB group and the Sham-FB group. Furthermore, the MEP was
significantly different between the groups in the 4th and 5th
sets. On the other hand, there were no significant differences
found in VAS scores. However, there was an improvement
tendency between pre- and post-mental practice in the RealFB group.

Change in Motor Performance

Change in MEP Amplitude During Mental
Practice

In this study, we used the coincidence timing task, which
involved pressing a button by index finger abduction. As a result,
there were significant differences in the percentage change oferror values. Shenghong et al. (2020) reported that the effectof neurofeedback training during simple motor imagery was
only significant in the real-feedback group but not in thesham group. Moreover, the previous study used real-time fMRI
neurofeedback-guided motor imagery based on contralateral
M1 hand area blood oxygen level dependent (BOLD) signals
in healthy subjects and found positive correlations between
contralateral M1 activation and performance changes in the
motor imagery task as an isometric force precision grip task
(Blefari et al., 2015). In other words, subjects with stronger
contralateral M1 activation during motor imagery may benefit
more from mental practice. These findings support the resultof the present study that performance was improved byusing MEP amplitude and reflected the excitability of the

Subjects in the Real-FB group had a >100% MEP compared torest MEP, with the 1st set corresponding to 116/240 trials, 2nd
set corresponding to 142/240 trials, 3rd set corresponding to
125/240 trials, 4th set corresponding to 136/240 trials, and 5th set
corresponding to 164/240 trials. Among individuals, individuals
achieved more than 100% of MEP compared to rest MEP in
about 30/100–80/100 trials. Figure 4 shows the change in themean MEP amplitude (± standard error) in both groups. The
two-way ANOVA showed a significant main effect for “trial sets”
and “group.” Dunnett’s post-hoc test revealed that there was asignificant difference between the rest set and the 5th set of MEPs.
Moreover, an unpaired t-test between groups of Real-FB group
and Sham-FB group found no significant difference in the MEP
amplitude at rest, but a significant difference was observed in
MEP amplitudes in the 4th and 5th sets (p < 0.01). A Box’s M test

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Poor feedback, even though the motor imagery was performedin the Sham-FB group. In addition, there is a possibility that thetiming of the motor imagery may be questionable, or anxiety may
have been caused whereby the motor imagery may not have beencreated; it is thought that MEP decreased due to confusion.
Based on the above observations, it was suggested that
the MEP amplitude-based feedback used in this study could
maintain high MEP during MI and may enhance the effect ofmental practice.

TABLE 2 | VAS score and percentage change of VAS values of each groups.

Real-FB group

Sham-FB group

Pre

Post

Score (mm)70.2 ± 12.3

80.4 ± 17.8

Percentage changes of VAS
value (%)

114.6 ± 25.2

Score (mm)71.3 ± 11.0

Percentage changes of VAS
value (%)

98.0 ± 25.2

70.0 ± 14.6

Change in Vividness of Subjective Motor
Imagery
corticospinal tract including the M1. However, we examined
the short-term performance change in only 100 trials. In
previous studies on the effectiveness of mental practice,researchers examined the effect of mental practice on shortterm performance change with the hand sequence task, mostof which examined the effects within weeks to months(Yasushi et al., 2010; Frenkel et al., 2014; Avanzino et al.,2015; Di Rienzo et al., 2015). Therefore, we think it isnecessary to verify the long-term intervention effects of feedback
using TMS.

In this study, subjective motor imagery vividness was evaluatedusing the VAS. As a result, there was no significant differencein the percentage change in VAS score. However, there was an
improvement tendency between pre- and post-mental practice in
the Real-FB group.
A feedback study using NIRS reported by Mihara et al.
(2012) showed that subjective motor imagery vividness was
significantly higher in the Real-FB group than in the ShamFB group. Unfortunately, although there was a tendency, we
could not show a statistically significant difference in thisstudy. However, as mentioned above, there was a significant
difference between the two groups in the MEP amplitudein the motor imagery task. In the Real-FB group, a high
MEP was maintained in the 5th set, and it was reported that
MEP is highly related to the vividness of subjective motor
imagery (Moriuchi et al., 2020). Therefore, we consideredthat a tendency to improve in the Real-FB group VAS
score was observed. Moving forward, we think that it isnecessary to examine long-term intervention effects as well as
performance changes.

Change in MEP Amplitude During Mental
Practice
In this study, there were significant main effects in “trial sets” and“group”; there was a significant difference between rest and the
5th set of MEPs in the Real-FB group. Moreover, a significant
difference was observed in MEP amplitudes at the 4th and 5th
sets (p < 0.01).
Therefore, it was suggested that M1 excitability during mental
practice is kept higher in the Real-FB group than in the ShamFB group. Such a result may have been obtained potentiallybecause in the Real-FB group, true feedback of M1 excitability
in motor imagery is accurate feedback. As in the present study,
Mihara et al. used NIRS to assess brain activity feedback near thecontralateral premotor cortex during motor imagery in a real-FB
group. They reported that cerebral cortex activity was increased
centered on the contralateral premotor cortex but decreased
near the dorsolateral parietal association cortex. Furthermore,
operant conditioning, which provides the size of MEP feedback,shows that participants can self-modulate their own brain state(for example, by providing feedback according to the MEP size,
MEP could be increased for UP training sessions and conversely
decreased for DOWN training sessions) (Kathy et al., 2018). In
this study, we thought that the MEP during MI in the Real-FB
group could be maintained at a high value by feedback of the
MEP as a bar.
In contrast, in the Sham-FB group, it is thought that confusion
occurred because it was difficult to judge the correctness of the
motor imagery itself through introspection of the motor imagery
and the gap of the feedback result. Mihara et al. (2012) reported
that under sham conditions, subjects could feel uncertain andlose confidence in kinesthetic imagery with incorrect feedback,which could mislead the subjects. In this study, it is possible thatthe feedback was not stable, such as in the form of Good or

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Limitations
Referring to the study of Mihara et al. (2012), we compared
two groups, the Real-FB group that received feedback on
the MEP amplitude as an index and the Sham-FB groupthat received feedback values that were not related to the
MEP amplitude. However, this study design does not show
the difference in effect from the case where feedback is not
given. Searching for studies that verified the effects of otherneurofeedback, we found that studies that set groups that do notprovide feedback, as a control group (deCharms et al., 2005),
or those that adopted a region other than the target region,or a signal from a third party for feedback of the sham-FB
group (Subramanian et al., 2011; Sitaram et al., 2012; Younget al., 2014), have also been reported. Taking these reports
into consideration, setting a group to not receive feedback
as a control group, could have shown an effect of feedback
using TMS on mental practice. In addition, as mentioned
above, this study merely examined the effect of short-term
mental practice on healthy subjects. In the future, to clarify
effective methods of mental practice in rehabilitation, it isnecessary to investigate the change in performance by longterm intervention settings and examinations for stroke patients,for example.

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CONCLUSION

Clinical Implications
Mental practice using fMRI and NIRS is considered to be difficult
to perform in clinical terms from the viewpoint of constraint
and mobility. We hypothesized that performing mental practiceusing TMS would be more feasible to use in clinical settings. As aresult of this study, a significant difference was observed in thepercentage change of error values between the Real-FB groupand the Sham-FB group. Furthermore, there was a significant
difference between the rest set and the 5th set of MEPs. Recent
studies on mental practice using neurofeedback have reported
that accurate feedback of brain status can maintain high vividnessof motor imagery and performance improvement was observed.
Similar to these findings, in this study, maintenance of increased
MEP amplitude was observed in the Real-FB group comparedwith the resting amplitude. It seems that mental practice could
be performed while maintaining the vividness of the high motor
imagery corrected by feedback of M1 excitability; mental practiceusing TMS seems to be effective. In this study, we examined only
the short-term effects; however, we will consider that a similar
performance improvement as in fMRI and NIRS studies would
be observed by verifying the long-term effects.
In addition, changes in M1 excitability are also being evaluatedin various TMS-based studies at all stages from the acute phaseto the chronic stage, after stroke (Cicinelli and Traversa, 1997;
Escudero et al., 1998; Delvaux et al., 2003; van Kuijk et al., 2008;
McDonnell and Stinear, 2017; Mooney et al., 2020). In otherwords, although there are restrictions such as consciousness level,
since the MEP amplitude can be derived at any stage after stroke,
we consider that neurofeedback using MEP amplitude can beused at any stage of stroke. Regarding the use of this method in aclinical setting, we couldn’t verify the effect of giving feedback inpatients only with the results of this study, so we considered that
this method is inadequate for use in a clinical setting. However,it was suggested that giving real feedback could maintain theincreased MEP amplitude, compared with the resting amplitude
in healthy subjects; therefore, with mental practice while giving
real feedback using TMS, mental practice can be carried out
while maintaining higher motor imagery vividness, which may
be recognized as an improvement in function.

Feedback using MEP amplitude, induced by TMS as an index,
suggested the possibility of enhancing the effect of mental
practice because enhanced M1 excitability during mental practice
was observed. Thus, in future studies, it is necessary to verify
the comparison with the control group and long-term effects
of intervention.

DATA AVAILABILITY STATEMENTThe original contributions presented in the study are includedin the article/supplementary material, further inquiries can bedirected to the corresponding author/s.

ETHICS STATEMENT
The studies involving human participants were reviewed
and approved by The local ethics committee of Nagasaki
University Graduate School of Biomedical Sciences. The
patients/participants provided their written informed consent toparticipate in this study.

AUTHOR CONTRIBUTIONS
DM, TH, and KS conceived and designed the experiments.
TM, DM, YI, KF, and WM performed the experiments. TM,
MM, and TH analyzed the data. TS and JN created theexperimental program. DM, TM, and TH drafted the manuscript.
All authors contributed to the article and approved the finalized
submitted version.

FUNDING
This work was partly supported by a Early-Career Scientists
from the Japan Society for the Promotion of Science (Grant No.
JP18K17675).

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Conflict of Interest: The authors declare that the research was conducted in theabsence of any commercial or financial relationships that could be construed as apotential conflict of interest.
Copyright © 2021 Matsuda, Moriuchi, Ikio, Mitsunaga, Fujiwara, Matsuo,
Nakamura, Suzuki, Sugawara and Higashi. This is an open-access article distributed
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