Neurotech
ë
ç
ñ
k
ïdë
Examining Neurotech's Efﬁcacy and Safety
2023/10/02 v1.2

ëv

ø
ø
b

CONTENTS

01

Can neurofeedback training
improve motor performance?

02

Can neurofeedback training
improve sleep quality?

03

Can neurofeedback training
enhance attentional functions?

04

Can neurofeedback training
enhance memory aptitudes?

05

Can non-invasive brain stimulation
improve motor task performance?

06

Can non-invasive brain stimulation
improve sleep quality?

07

Can non-invasive brain stimulation
enhance attentional functions?

08

Can non-invasive brain stimulation
enhance memory aptitudes?

09

Is EEG a biomarker of relaxation?

10

Is EEG a biomarker of stress level?

11

Is EEG a biomarker of attention level?

12

Is EEG a biomarker of certain
emotion categories?

01

Basic knowledge of EEG

03Adverse events reported
in the use of Neurotech

02

Design and role of placebosin Neurotech

Preface
This evidence book is written for those interested in thescientific evidence of the efficacy and safety of Neurotech. In recent years, "Neurotechnology," commonlyreferred to as "Neurotech," has been rapidly growing.
Neurotech is the technology that aims to estimate andregulate the state of the human brain. Brochures forsuch products make enticing claims such as "improved
athletic performance," "improved memory," or "visualized emotions." However, is there any scientific basis forthese claims? Are there any potential risks for ordinary
consumers using such products?

tions, with the remaining eight to be released after thesystematic reviews are completed.
This book was developed by an Evidence Evaluation
Committee composed of twelve researchers specializing in neuroscience. The systematic reviews were conducted by a systematic review team of more than 20
researchers and graduate students under the supervision of the Evidence Evaluation Committee. To improvethe book's impartiality and comprehensibility, thesystematic review process, the correctness of the contents of this book, and the transparency of the disclosure of conflicts of interest were reviewed by an External
Review Board consisting of various experts. For basic
knowledge of Neurotech, please refer to the alreadypublished Neurotech Guidebook [2].

The efficacy and safety of Neurotech products available
to the general public are still not fully understood. Manyof these products lack a solid scientific foundation andoften rely on a few academic papers to support theirclaims [1]. However, citing several papers does not guarantee the reliability of their effectiveness and safety. The
product lacks proper scientific evidence if the quality ofthe trials conducted in cited papers is poorly designed.
Unfortunately, it can be challenging for general consumers to accurately grasp the certainty of the claimed
efficacy.

BrainTechë bøøk
ブレインテックのいまを知ろう！
2022/06/15 v0.07

BrainTechçëïdëñ kTo address these concerns, we have compiled theevidence book to provide the public with an accurate
overview of the efficacy and safety of Neurotech. The

ブレイン・テック エビデンスブック

2022/09/01 v0.1

Building trust in Neurotech
Step1.

Ensureproduct safety
andinformation
disclosure

Can I trust this?

Step 2.

Accumulatescientiﬁcevidence offunctionality

Güïd

ëv

bøø

<Guidebook>- For those interested in Neurotech products.
- Created by a committee of researchers, physicians,
industry persons who are well-versed in the field of
neuroscience.
- Provides correct knowledge and perspectives thatare currently available as well as information on
how to approach Neurotech.
<Evidence Book>- For Neurotech users and providers of products andservices.
- Created by an evidence evaluation committee
consisting of researchers specializing in neuroscience.
- Summarizes the effectiveness and safety of Neurotech based on the results of systematic reviews.

This book provides straightforward answers, especiallyin the headline section of each question, to make it
understandable for general consumers. The appendix
summarizes the foundational knowledge required tounderstand this book. For those with scientific and technical expertise–such as business people promoting thesales or development of Neurotech products andservices, as well as researchers and medical personnel–this book contains specialized information. Whilesome parts may be complex for ordinary consumers,
we believe the scientific perspective acquired throughthis book will help mitigate potential drawbacks andhealth risks associated with the use of Neurotech products. We hope this book fosters a scientific understanding of Neurotech and supports its development as areliable technology.

Step 3.

Demonstrate
producteﬃcacy inwell-designed
trialsIʼm convinced!

Consumer Neurotech products are a developing technology with varying
levels of reliability. In this book, we investigated the scientific basis for
Neurotech functional claims, which corresponds to Step 2 in the above chart.

contents are based on the results of systematic reviews,
which examine the scientific evidence related to theeffects often claimed for Neurotech products and thesafety of their usage. In this book, we have posted 12questions about the commonly claimed effects of Neurotech products, such as "Can neurofeedback training
improve motor performance?" We have answered
these questions based on the results of systematic
reviews. The first edition contains answers to four ques-

October 2023
By Evidence Evaluation Committee

1Preface

Disclaimer: Please read carefully
The authors of this book have carefully checked that the matters and analysis described are accurate. Furthermore, its
contents have been verified by an external review board consisting of professionals in medicine, neuroscience, law, andexperts in medical publishing and neuroethics. However, the accuracy of the content cannot be completely guaranteed due toa number of uncertain factors, including future technological developments, the unique complexity of researching the brain,changes in social circumstances, differences in opinions due to individual perspectives, differences in physical characteristics
and usage conditions of the consumers, and revisions to the legal framework. Consequently, we assume no responsibility forany health hazards or legal issues that may arise from the usage of this book. Please note that the positive statements in thisbook do not serve as scientific evidence for specific products with functional claims. In a similar fashion, the absence ofevidence supporting functionality based on literature reviews in this book does not imply that products claiming such functionality lack a scientific foundation. We kindly request that the readers refrain from referring to this book regarding Neurotech
intended for minors or for medical purposes, such as the diagnosis or treatment of illnesses, as these areas fall outside thescope of this book.

This evidence book was produced as part of the "Liberation from Biological Limitations via Physical, Cognitive and Perceptual Augmentation (Project Manager Ryota Kanai)" project for Goal 1 of the Cabinet Office Moonshot Research andDevelopment Program, "Overcoming limitations of body, brain, space and time" by 2050. The funders, Japan Science andTechnology Agency and the Cabinet Office, are not involved in any part of this book.

2

Can neurofeedback training
improve motor performance?

RQ1
Answer

The use of neurofeedback for seven days or more possibly improves motor performance.
However, due to the limited number of research, it is currently unclear to what extent andin what categories of motor performance these effects occur.
When healthy adults* engage in neurofeedback training for seven days or longer, their motor
performance possibly improves immediately after training. However, due to the small number ofstudies, evidence is too premature to draw any definite conclusion on the specific category of
motor performance (e.g., balance, endurance) and to what extent it is effective. In addition, theoptimal frequency and duration of daily training necessary to achieve an effect have yet to be
fully clarified.
*In this RQ, healthy adults were defined as those aged 18-64 years who had not been diagnosed with any physical,
mental, or neurological disorder or disease at the time of participation in the experiment.

Background and Purpose
There is growing interest in neurofeedback training (NFT) as a potential alternative to general motor training anda method to enhance the effectiveness of mental imagery. Several studies have reported positive effects of NFT
on golf putting and fine motor skills [3,4], while a meta-analysis revealed no significant impact of NFT on motor
performance among athletes [5]. This prompts the question, how safely and reliably can NFT improve motor performance in healthy adults?

Results - Safety
The safety of NFT could not be determined due to the limited number of studies discussing potential adverse
events. To date, no adverse events have been reported. Out of the 33 studies that utilized NFT to enhance
motor performance in healthy adults, only five studies (with a total of 129 subjects) assessed adverse events.
Thus, it was not possible to draw conclusive statements regarding the safety of NFT. However, it is worth notingthat none of the five studies focusing on adverse events reported negative effects.

Results - Effectiveness
Number of studies(Number of subjects)● The use of NFT for seven days or more may improve
motor performance (Fig. 1A). However, the scientific evidence supporting this claim is insufficient,given the risk of bias in the results and the limited
number of subjects in the studies conducted.

Effect size
(Standardized mean difference)(A) Intervention duration● The effectiveness of NFT on specific motor performance, such as movement accuracy, reaction time,
hand dexterity, whole body balance, and endurance, could not be adequately evaluated due to an
insufficient number of studies (Fig. 1B).

Less than one week

5(169)

Over one week

11(205)(B) Motor performance measure● The effects of NFT on motor performance may becomparable to those of non-NFT motor training
methods such as mental practice (Fig. 1C). However, considering the total number of subjects in thestudies conducted to date and the inconsistency of
the results, scientific evidence remains inconclusive.

Accuracy3(59)Reaction time3(45)Hand dexterity

6(185)

Other

4(85)

(C) Control conditions
General training other than NFT

3(55)Placebo8(219)

No intervention

5(100)-2● Four studies repeatedly assessed motor performance after NFT. Further research is needed toconfirm the duration of the training effects. Also,
the training intervals required to maintain or
improve performance need to be revealed.

0Ineffective

2

4Effective

Figure 1. Results of the effectiveness assessment. (A) Effects of intervention
duration. (B) Differences in effects by the targeted motor performance. (C)Superiority of NFT by control conditions.

3Can neurofeedback training improve motor performance?

(A) Daily NFT duration grouped byStudy characteristics

the length of the intervention period● Intervention period (Fig. 2A): Thirteen studies
lasted only one day, four studies lasted from two toseven days, five studies lasted from eight days tofour weeks, and 11 studies lasted longer than fourweeks. The longest training time per day was 90
minutes, and the shortest was six minutes. There
was no apparent trend that suggested a shorter
training time per day was associated with longer
training periods.

100: Mean ± s.d.

Daily NFT duration（min.）

RQ1● Intervention frequency: Daily for training periods ofless than four days and every two to seven days forlonger periods.

80

60

40

20

0

ay
1d

● Methods to measure brain activity for NFT: EEG (26studies), fMRI (3 studies), MEG (2 studies), andfNIRS (2 studies).

2-

ks
ks
ays
ee
ee
7d
4w
4w
r
e
Ov
ays
8d

Length of intervention period● Channels recorded for EEG-based NFT (Fig. 2B): Of
the 26 studies, 11 recorded EEG from the central
region (C3, Cz, and C4). The subsequent mostcommon measurement was from the parietal
region (Pz: 5 studies).

(B) EEG recording channels utilized in NFT studies● Frequency band(s) targeted by EEG-based NFT
study (Fig. 2C): The most common frequency band
used for NFT was alpha (14 studies), followed bytheta (12 studies) and beta (12 studies). 11 studies
used a combination of theta, alpha, and/or beta. In
addition, nine studies used a component called
sensorimotor rhythm (SMR)#1 , and four studies
used the power ratio between theta and beta oscillations.

Fpz
F7

T3

F3

Fz

F4

C3

Cz

C4

P3

Pz

P4

T5

O1

● Types of control condition: Placebo (18 studies), nointervention (10 studies), and general motor training other than NFT (8 studies). Placebos usedmethods such as feedback of previously recorded
brain activity of others or random information similar to brain activity.
● Targeted motor performance: Movement accuracy
such as shooting and golf putting (8 studies), hand
dexterity (8 studies), reaction time#2 (8 studies),whole body balance (2 studies), and endurance (2studies).

F8

T4

T6

O2

: None:３-4 studies: 1 study: 7-8 studies(C) EEG components targets by NFT studies
Theta
Alpha
Beta
SMR
0

5
10
Number of studies: Single

15: Multiple

Figure 2. Study characteristics.

4

RQ1

Can neurofeedback training improve motor performance?

Systematic review processes● Five databases were used to search for studies that conducted NFT to improve motor
performance in healthy adults aged 18-64
years [6].
● 2,325 papers found through our search andother sources were screened according topredetermined inclusion criteria. The 33
selected articles were used to summarize
the characteristics of studies conducted todate.
● Of the 33 papers, 13 were randomized controlled trials that could calculate effect sizes
related to motor performance and had a low
to moderate risk of bias. These papers wereused for statistical analyses to evaluate theeffectiveness of NFT.

Records identified throughdatabase searching (2307 studies)

Additional records identified
through other sources (18 studies)

Records screened bytitle and abstract (2325 studies)

Main inclusion criteria
for article screening

Records excluded(2213 studies)

Full-text articles assessed
for eligibility (112 studies)- Healthy adults aged 18-64 years- Controlled trials- NFT was conducted- Motor performance
was measured

Records excluded(79 studies)

Studies included in the qualitative
summary and safety assessment(33 studies)
Records excluded(20 studies)

Studies included in the assessmentof effectiveness (13 studies)

Inclusion criteria
for effectiveness assessment- Randomized controlled trials- Data available for effect size
calculation- Low to moderate risk of bias
in the results

Figure 3. Flowchart of the systematic review process.

Keywords#1. Sensorimotor rhythm (SMR): SMR refers to the EEG component around 12-15 Hz measured from the central
region. Previous studies considered the SMR signal sources as the primary motor cortex, which sends themuscle the command "Move," and the primary somatosensory cortex, which is adjacent to the primary motor
cortex and receives muscle and skin sensory information [7].
#2. Reaction time: Reaction time is the time between receiving a cue and beginning movement, like responding to
the cue "on your mark, get set, go!".

5Can neurofeedback training
improve sleep quality?

RQ2
AnswerDue to the limited amount of research, there is currently no evidence to support the claimthat neurofeedback improves sleep quality in healthy adults.
Currently, there is insufficient scientific evidence to determine if neurofeedback training can
improve the sleep quality of healthy adults. Few studies have been conducted on this topic, andthe effectiveness and safety of neurofeedback for enhancing sleep quality are still being investigated. Further research is needed to better understand the specific aspects of sleep that canpotentially benefit from neurofeedback. In the meantime, if the reader wants to improve their
sleep quality, we recommend following the sleep guidelines for health promotion provided bysleep science experts and the Ministry of Health, Labour, and Welfare [8].
*In this RQ, healthy adults were defined as those aged 18 years or older who had not been diagnosed with any physical, mental, or neurological disorder or disease at the time of participation in the experiment.

Background and Purpose
Various methods are available to maintain good sleep and improve its quality, such as moderate exercise
during the day, avoiding bright lights at night, maintaining a regular sleep schedule, and going to bed whensleepy [8]. Neurofeedback training (NFT) has recently emerged as another potential method to improve
sleep quality [9]. So, how safely and reliably can NFT be expected to improve sleep quality in healthy adults
without sleep disturbances?

Results - Safety
Assessing the safety of NFT is currently difficult as no studies reported any potential adverse events.
While four studies have investigated the impact of NFT on sleep quality in healthy adults, none of themprovided information about any associated adverse events linked to the intervention.

Results - Effectiveness● Studies on the effectiveness of NFT haveshown varying results. Currently, no scientificevidence supports the claim that NFT
improves sleep quality in healthy adults (Fig.
1A). One reason for this uncertainty could be
attributed to the inconsistent methods#1 used
to assess sleep quality.
● The impact of NFT on daytime napping andnighttime sleep (Fig. 1B) and the differences inthe effects of different EEG components usedin NFT (Fig. 1C) cannot be determined due tothe insufficient amount of research.
● Additionally, the required training durationand hours per day for NFT to affect sleep
remains unknown.

Number of studies

Effect size

(Number of subjects)(Standardized mean difference)(A) All studies

4(115)(B) Time point of evaluation
Daytime napping3(93)Nighttime sleep2(48)(C) Frequency band(s) targetedby EEG-based NFT
Sigma

3(75)

Alpha/theta

1(40)
-4

-3

-2 -1

0

1

Ineffective

2

3

4

5

Effective

Figure 1. Results of the effectiveness assessment. (A) Overall effects. (B) Comparison
between daytime nap and nighttime sleep. (C) Comparison in frequency band(s) targetedby EEG-based NFT.

6

RQ2

Can neurofeedback training improve sleep quality?

Study characteristics(A) EEG recording channels utilized in NFT studies● Intervention period: Varying widely, from one day
to ten or more.

Fp1● Intervention duration: Ranges from 24 to 90 minutes per day.

F7

● Channels recorded for EEG-based NFT (Fig. 2A): Allstudies measured EEG from the central area (Cz,
C3, C4).

T3

T5

Fp2

F3

Fz

F4

C3

Cz

C4

P3

Pz

P4

O1

● Frequency band(s) targeted by EEG-based NFT
study (Fig. 2B): Power in the sigma frequency band
and a combination of power in alpha and theta
frequency bands were used.

F8

T4

T6

O2

: None: 1 study: 2 studies● Types of control conditions: All four studies used
placebos, with feedback based on non-EEG datalike a heartbeat, EEG components not utilized in
NFT, and EEG data from others.

(B) EEG components targeted by NFT● Timing of sleep quality assessment: Three studies
were assessed during daytime naps, and two were
evaluated during nighttime sleep.

Theta

Alpha

Sigma

0

1

2

Number of studies: Single

Figure 2. Study characteristcs.

7: Multiple

3

RQ2

Can neurofeedback training improve sleep quality?

Systematic review processes● Four databases were used to search forstudies that conducted NFT to improve sleep
quality in healthy adults 18 years of age andolder [10].

Records identified throughdatabase searching (1285 studies)● 1,285 papers found through our search werescreened according to predetermined inclusion criteria. The four articles selected as aresult were used to summarize the main
characteristics of studies to date.

Records screened bytitle and abstract (827 studies)
Records excluded(796 studies)

Full-text articles assessed
for eligibility (31 studies)● These studies were used for statisticalanalyses to evaluate the effectiveness of NFT.
● To assess these papers, we employed widely
accepted sleep quality indices, including the
proportion and duration of N3 sleep stages#2, the amplitude of sleep EEG#3 (like sigma
and delta waves), sleep efficiency#4 , sleep
latency#5, and wake time after sleep onset#6.

Additional records identified
through other sources (0 studies)

Main inclusion criteria
for article screening- Healthy adults
aged over 17 years- Controlled trials- NFT was conducted- Sleep quality was measured

Records excluded(27 studies)

Studies included in the qualitative
summary and safety assessment(4 studies)
Records excluded(0 studies)

Studies included in the assessmentof effectiveness (4 studies)

Inclusion criteria
for effectiveness assessment- Randomized controlled trials- Data available for effect size
calculation- Low to moderate risk of bias
in the results

Figure 3. Flowchart of the systematic review process.

Keywords#1. Methods for assessing sleep quality: Currently, it is evaluated through various indices [11]. Through polysomnography and actigraphy, evaluations can be conducted based on objective indicators such as sleep EEG and sleep
latency. On the other hand, subjective sleepiness is also evaluated through questionnaires or interviews. Sleep
quality is then evaluated based on an integration of these results. However, there has yet to be a consensus
among experts on a standard approach for evaluating sleep quality.
#2. Sleep Stages: Sleep is categorized into two main stages: non-REM and REM sleep. Non-REM sleep is then subdivided into three stages, referred to as N1, N2, and N3. N1 denotes the state of dozing off, while N3 represents astate of deep sleep. During N3, external sounds are less likely to wake an individual up.
#3. Sleep EEG: Theta oscillations are commonly observed during the initial stage of non-REM sleep, known as N1. As
one progresses to N2, sleep spindles are present, indicating a deeper stage of sleep. The presence of sleep
spindles is a reliable indicator of stable sleep. The deepest non-REM stage, N3, is characterized by slow waves
with a frequency of 0.5 to 4 Hz.
#4. Sleep efficiency: It refers to the proportion of time spent in any of the sleep stages, including non-REM (N1, N2,
N3) and REM sleep, out of the total time spent in bed.
#5. Sleep latency: This refers to the time from turning the light off to the first onset of any stage of sleep.
#6. Wake time after sleep onset: It is the amount of time between falling asleep and getting up that is consideredbeing awake.

8

Can neurofeedback training
enhance attentional functions?

RQ3
AnswerIt likely enhances attentional performance, but whether its effects are greater than thoseof other general training methods remains unclear.
Attentional functions are classified into three elements: "executive control" (also called the central
executive), which focuses on what needs to be done in the present moment and staying focusedon the task at hand; "spatial orientation," which directs attention toward the intended target; and"arousal," which creates and maintains an appropriate state of readiness [12]. After neurofeedback
training, healthy adults* likely experience immediate improvement in executive control and spatial orientation. While these observed effects are greater than those of doing nothing, it remains
unclear whether they surpass those of placebos and general training methods, such as meditation or tasks mimicking playing video games (e.g., Tetris or Concentration). Note that the effects
of neurofeedback on Attention-Deficit Hyperactivity Disorder (ADHD) have already been summarized elsewhere [13] and are not within the scope of this review.
*In this RQ, healthy adults were defined as those aged 18-65 years who had not been diagnosed with any physical,
mental, or neurological disorder or disease at the time of participation in the experiment.

Background and Purpose
There is growing interest in Neurofeedback Training (NFT) as a training method to enhance attentional
functions. For example, several studies have reported the effectiveness of NFT in improving attentional
functions by using specific EEG components such as sensorimotor rhythm (SMR) or beta [14,15]. However,contrasting reports suggested that NFT might only change brain activity and did not affect behavioral
aspects such as correct response rate or reaction time [16]. Then, what types of attentional functions can
NFT reliably enhance in healthy adults, and to what extent?

Results - Safety
The safety of NFT could not be determined due to the limited number of studies discussing adverse
events. To date, no adverse events have been reported. Out of the 41 studies that utilized NFT to
improve attentional functions in healthy adults, only two studies with a total of 124 subjects assessed
adverse events. These studies did not indicate any serious adverse events that necessitated medical intervention or other unfavorable circumstances.

9

RQ3

Can neurofeedback training enhance attentional functions?

Results - Effectiveness● NFT may enhance attentional functions (Fig. 1A).
● Among attentional functions, NFT showed
effects on executive control, such as decreased
reaction time when alternating between two
types of judgments [17] (Fig. 1B).
● Effects on spatial orientation were also observed.
However, the scientific evidence supporting thisclaim is insufficient due to the risk of bias in the
results and the total number of subjects in thestudies (Fig. 1B).

Effect size
(Standardized mean difference)(A) All studies

16(569)(B) Attentional functions
Executive control

12(408)Spatial orientation

6(214)

Arousal7(149)(C) Control conditions
General training other than NFT

2(73)Placebo8(184)

No intervention

7(252)● No effect of NFT on arousal was found (Fig. 1B).
● Few studies compared the effects of NFT toother general attentional training methods, suchas meditation or tasks mimicking Tetris or Concentration, making it unclear whether NFT has
advantages (Fig. 1C).

Number of studies(Number of subjects）

- 1.5

-1

- 0.5

0

0.5

Ineffective

1

1.5

2

Effective

Figure 1. Results of the effectiveness assessment. (A) Overall effects. (B) Differencesin effects by attentional functions. (C) Superiority of NFT by control conditions.

● The difference in the enhancement of attentional
functions between NFT and placebo remains
unknown (Fig. 1C).
● Only two studies assessed the effect of NFT on
attentional functions over time. Thus, the duration of the training effect is not evident. Nor
could we determine the training intervals
required to maintain or improve the performance.

10

Can neurofeedback training enhance attentional functions?

Study characteristics(A) EEG components targeted by NFT● Intervention period and duration: Three studies
lasted only one day, four studies from two to sevendays, 15 studies from eight days to four weeks, and13 studies longer than that, the longest being
about 13.5 weeks; the duration of training per day
was about five minutes in one study, 10 to 20 minutes in eight studies, about 20 to 60 minutes in 20
studies, and longer than that in five studies, thelongest being 136 minutes.

Theta
Alpha
Beta
SMR
0

5

10

15

Number of studies● Intervention frequency: Our survey of studies conducting NFT for three or more days revealed thatseven studies performed it daily, four studies performed it four to five days a week, 12 studies performed it two to three days a week, and sevenstudies performed it less than two days a week.

: Single: Multiple

0
Ex
or
ec
ie
ut
nt
ive
at
io
co
n
nt
Sp
r
o
at
l
＋
ia
co
ar
lo
nt
ou
rie
ro
sa
l＋
nt
a
l
sp
tio
at
n
＋
ia
lo
ar
rie
ou
nt
sa
at
l
io
n＋
ar
ou
sa
l

● Channels recorded for EEG-based NFT (Fig. 2A):
There were 24 studies in the central region (C3, Cz,
C4), 12 in the frontal region (F3, Fz, F4), 11 in theparietal region (P3, Pz, P4), 7 in the occipital region(O1, Oz, O2), and 5 in the frontal pole (Fp1, Fpz,
Fp2).

10

Ar
ou
sa
l

● Methods to measure brain activity: EEG (33 studies), fMRI (4 studies), NIRS (3 studies), and MEG (1study).

20

Ex
ec
ut
ive

co
nt
ro
l＋

sp
at
ia
l

Number of studies(B) Target attentional functions of NFT

Ex
ec
ut
ive
co
nt
Sp
ro
at
l
ia
lo
rie
nt
at
io
n

● Frequency band(s) targeted by EEG-based NFT
study (Fig. 2B): Theta and beta frequencies werethe most commonly utilized (13 studies), often
combined together. Alpha waves were individuallyused in more than half of the studies (6 out of 11).
SMR was used in 10 studies, and only 2 studies
incorporated event-related potentials, including
P300.

Ex
ec
ut
ive

RQ3

(C) EEG recording channels utilized in NFT studies

Fp1● Types of control conditions: Placebos (8 studies),
no intervention (7 studies), and general training
methods other than NFT (2 studies). The feedback
for the placebo included brain activity from
non-target regions, EEG components of other individuals, or random information unrelated to brain
activity.

F7

T3

T5

Fp2

F3

Fz

F4

C3

Cz

C4

P3

Pz

P4

O1

● Targeted attentional functions (Fig. 2C): Executive
control (25 studies), spatial orientation (13 studies),and arousal (19 studies), with some studies targeting multiple attentional functions.

T4

T6

O2

: None: 4-6 studies: 1-3 studies: More than 6 studies

Figure 2. Study characteristics.

11

F8

RQ3

Can neurofeedback training enhance attentional functions?

Systematic review processes● Six databases were used to search for studies that conducted NFT to enhance attentional functions in healthy adults aged 18-65
years [18].
● 3,337 papers found through our search werescreened according to predetermined inclusion criteria. The 41 articles selected as aresult were used to summarize the main
characteristics of studies to date.
● Of the 41 papers, 15 were randomized controlled trials that could gather numerical dataon attentional functions and had a low risk ofbias in the results. These studies were used
for statistical analyses to evaluate the effectiveness of NFT.

Records identified throughdatabase searching (3337 studies)

Records screened bytitle and abstract (3337 studies)
Records excluded(3159 studies)

Full-text articles assessed
for eligibility (178 studies)

Additional records identified
through other sources (0 studies)

Main inclusion criteria
for article screening- Healthy adults
aged 18-65 years- Controlled trials- NFT was conducted- Attentional function
was measured

Records excluded(137 studies)

Studies included in the qualitative
summary and safety assessment(41 studies)
Records excluded(26 studies)

Studies included in the assessmentof effectiveness (15 studies)

Inclusion criteria
for effectiveness assessment- Randomized controlled trials- Data available for effect size
calculation- Low to moderate risk of bias
in the results

Figure 3. Flowchart of the systematic review process.

12

RQ4

Can neurofeedback training
enhance memory aptitudes?

Answer Systematic review is in progress. Please wait for the answer.

13

RQ5

Can non-invasive brain stimulation
improve motor task performance?

Answer Systematic review is in progress. Please wait for the answer.

14

RQ6

Can non-invasive brain stimulation
improve sleep quality?

Answer Systematic review is in progress. Please wait for the answer.

15

RQ7

Can non-invasive brain stimulation
enhance attentional functions?

Answer Systematic review is in progress. Please wait for the answer.

16

RQ8

Can non-invasive brain stimulation
enhance memory aptitudes?

Answer Systematic review is in progress. Please wait for the answer.

17

RQ9

Is EEG a biomarker of relaxation?

Answer

The amplitude of alpha oscillations in EEG possibly indicates the level of relaxation,
depending on where they are measured. However, interpreting the results requires
caution.
For healthy adults*, the amplitude of alpha oscillations in the frontopolar region may indicate
their level of relaxation. However, alpha oscillations measured from other areas or other EEG
components (such as delta, theta, beta, gamma, and other indices) do not indicate relaxation.
These results suggest that although the common belief that alpha oscillations signify a level ofrelaxation may be partially correct, using alpha oscillations as a biomarker of relaxation requires
careful consideration. In actuality, the amplitude of alpha oscillations is influenced not only by thelevel of relaxation but also by several other factors, including sleepiness, fatigue, and attention[19-23]. Additionally, It should be noted that gold standards of a relaxation index#1 have yet to beestablished.
*In this RQ, healthy adults were defined as those aged 18-65 years who had not been diagnosed with any physical,
mental, or neurological disorder or disease at the time of participation in the experiment.

Background and Purpose
Within the general public, alpha oscillations in EEG are often equated with a relaxed state, as seen in products like "alpha oscillation-producing music CDs" marketed for relaxation effects. Some researchers also
believe that alpha oscillations become stronger when we relax. However, there is no consensus on therelationship between relaxation indices and various EEG components, including alpha oscillations.
Primarily because the definition of relaxation varies among studies and includes subjective and objective
measures, such as autonomic nervous system#2 measures obtained from electrocardiograms (ECGs). So, towhat extent are EEG measurements and relaxation actually related?

Results - Safety
EEG measurements are widely considered safe, so EEG could be a safe way to evaluate relaxationlevels. EEG measures weak electrical signals through electrodes placed on the scalp and does not induce
electric currents in the head. Skin rashes may occasionally develop from the tape used to attach electrodes,
but the risk is comparable to that of using adhesive bandages on the skin. While the studies reviewed did
not include any safety statements, it is generally believed that no inherent adverse events are associatedwith EEG measurement.
Number of studies(Number of subjects)

Results - Validity

Coefficient correlation(A) Intensity of alpha oscillations
All studies
Prefrontal region
Frontal region
Central region
Parietal region
Occipital region●A strong positive correlation of r = 0.74 was foundbetween relaxation indices and the amplitude ofalpha oscillations in the frontopolar region (Fig. 1A).
●A weak positive correlation of around r = 0.2 was also
found between relaxation indices and the amplitudeof alpha oscillations in the frontal and central regions(Fig. 1A).

17(541)
3(53)
6(229)
7(250)
5(104)
7(210)(B) Intensity of other EEG components●No significant correlation was found between relaxation indices and the amplitude of alpha oscillations in
the parietal and occipital regions (Fig. 1A).
●No significant correlations were found between relaxation indices and delta, theta, beta, and gamma oscillations, as well as other EEG indices (Fig. 1B).

Delta
Theta
Beta
Gamma

3(51)
8(143)
7(145)
2(16)Alpha/beta ratio2(51)Relative gamma

3(24)
-1

- 0.5

Negativecorrelation

0No
correlation

0.5

1

Positivecorrelation

Figure 1. Results of the validity assessment. (A) Correlation between the intensityof alpha oscillations and relaxation indices. (B) Correlation between the intensityof other EEG components and relaxation index.

18

Is EEG a biomarker of relaxation?
Study characteristics(A) EEG recording channels● Proportions of EEG recording channels (Fig. 2A): Measurements from the frontal region (F3, F4) were themost common (21 studies), followed by occipital (O1: 19;
O2: 20 studies) and central (C3: 15; C4: 16 studies)regions. More than 10 studies were recorded from thefrontopolar (Fp1, Fp2) and parietal (P3, P4) regions,
respectively.

Fp1
F7

T3

● EEG frequency bands (Fig. 2B): Alpha oscillations werethe most commonly used EEG index (27 studies),
followed by theta and beta (14 studies for each). A few
studies used delta and gamma oscillations.

Fp2

F3

Fz

F4

C3

Cz

C4

P3

Pz

P4

T5

O1

● EEG feature components (Fig. 2C): Most studies used
power or normalized power for each frequency band. A
few studies used power ratios between multiple
frequency bands or asymmetries in oscillatory power
between the left and right hemispheres.

F8

T4

T6

O2

: 4-9 studies: 15-19 studies: 10-14 studies: More than 20 studies(B) EEG frequency bands
Delta● Types of relaxation indices (Fig. 2D): ECG-related indiceswere the most frequently used, including heart rate, lowfrequency (LF, typically 0.05-0.15 Hz) power, highfrequency (HF, typically 0.15-0.4 Hz) power, and LF/HF
ratio. Many subjective measures of the level of relaxation were also used, such as the Profile of Mood State(POMS) test. Some studies used salivary indices such as
the cortisol test.

Theta
Alpha
Beta
Gamma
Others

0

5

10
15
20
Number of studies

2530(C) EEG feature components
Power & amplitude

OthersPower

Power asymmetry

Normalized power

Coherence

Delta
Theta

Frequency

Amplitude

ERP

Current source density

Alpha
Beta

MicrostateAppearance ofspecific activity

Gamma
OthersOthers0510α/β power ratio

15
20
25
Number of studies3035

γ / (θ＋α) power ratio
α / θ power ratio

0

5

10

15
20
25
30
Number of studies

35(D) Types of relaxation indices
Relaxation level, Relaxation feeling

Questionnaire

POMS

OthersHeart rate

ECG indices

RQ9

SDNN

R-R interval

RMSSD

CSI

OthersNormalized

HiF

Normalized

LF

Not normalized

Not normalized

LF/HF

Cortisol

SalivaOthersSkin conductanceBlood pressure
Respiration rate

0

1

2

3

4

5

6

7

8

Number of studies
Figure 2. Study characteristics.

19

9

10

11

12

13

14

15

RQ9

Is EEG a biomarker of relaxation?

Systematic review processes● Five databases were used to search for studies that measured EEG and relaxation indices(e.g., ECG-related indices associated withparasympathetic nervous system activity andsubjective indices of relaxation) in healthy
adults aged 18-65 years [24].

Records identified throughdatabase searching (3295 studies)

Additional records identified
through other sources (0 studies)

Records screened bytitle and abstract (3295 studies)

Main inclusion criteria
for article screening● 3,295 papers found during our search werescreened according to predetermined inclusion criteria. Then, 39 articles were selected
to summarize the main characteristics ofstudies conducted to date.
● Of the 39 papers, 30 provided correlation
values between EEG and relaxation indicesand had a low to moderate risk of bias in the
results. These studies were used for statistical analyses to evaluate the validity of EEG
indices.
● Two primary types of relaxation indices exist:
subjective indices obtained through questionnaires and ECG-related indices. Becausesome indices increase as relaxation deepens
while others decrease, adjustments weremade to ensure the value consistently rises
as relaxation increases. For instance, thesigns of subjective indices like nervousness
and heart rate were reversed, as smaller
values indicate a more relaxed state.

Records excluded(2942 studies)

Full-text articles assessed
for eligibility (353 studies)
Records excluded(314 studies)

Studies included in the qualitative
summary and safety assessment(39 studies)
Records excluded(9 studies)

Studies included in
the validity assessment (30 studies)- Healthy adults
aged 18-65 years- Measurements of EEG
and relaxation indices- Not in a sleep or
unconscious state- Correlation values areavailable or can be calculated
Exclusion criteria
for assessment of validity- Unreliable correlations- High risk of bias in the results- No frequency
domain EEG indicesFigure 3. Flowchart of the systematic review process.

Keywords#1. Relaxation index: Relaxation is generally defined as a state of parasympathetic dominance. Quantitative measures of relaxation include subjective measures (questionnaires), ECG-related, and saliva-related, with different
studies using different measures.
#2. Autonomic nervous system: This refers to the nervous system that controls involuntary functions such as breathing, sweating, and temperature regulation, as well as metabolism. It supports our bodies by balancing the sympathetic nervous system that predominates in quiet "rest and digest" conditions and the parasympathetic nervous system that drives the "fight or flight" response in stressful situations.

20

RQ10

Is EEG a biomarker of stress level?

Answer Systematic review is in progress. Please wait for the answer.

21

RQ11

Is EEG a biomarker of attention level?

Answer Systematic review is in progress. Please wait for the answer.

22

RQ12

Is EEG a biomarker of certain
emotion categories?

Answer Systematic review is in progress. Please wait for the answer.

23

Appendix

1

Basic knowledge of EEG

Types and frequencies of EEG
Since the physiological significance of EEG rhythms
differs depending on their frequency, it is believedthat the state of brain activity can be roughly determined by examining the changes in signal amplitude at each frequency range (Table1). However, it
is not easy to make a one-to-one match between
EEG frequencies and the functions they reflect.
Moreover, the criteria for the frequencies thatdelimit wave types are not always consistent. For
instance, an 8 Hz wave can be classified as either
alpha or theta, given that it may reflect function
and states associated with both. It is also known
that the relationship between EEG rhythms andfunctions varies slightly with age, gender, and exercise habits [25-27].

Electroencephalograms (EEGs) are waveform signals that reflect the electrical activity in the brain.
EEG recording is done using an electroencephalograph. The recorded EEG contains multiple oscillations with a constantly changing waveform (seeFig.1). These oscillations are classified based on
their frequency, indicating their rhythm's speed.
Frequency refers to the number of times a wave
repeats in one second; for example, if it repeats ten
times per second, its frequency is 10 Hz. The typesof oscillations in EEG are classified from lowest(fewer waves) to highest frequency as delta, theta,alpha, beta, and gamma (Table1). Delta and theta
oscillations, which have lower frequencies, are classified as slow waves, while beta and gamma oscillations, which have higher frequencies, are classified
as fast waves, with alpha oscillations serving as theintermediate. The amplitudes of alpha and slow
waves are larger than those of fast waves (Fig.1).

Table 1. Types of waveforms in EEG and their functions and states *

EEG

Delta
（0.5-4 Hz)
Theta（4-8 Hz)Gamma(over 30 Hz)

Frequencies

Functions and states

Delta

0.5-4 HzIt is observed during deep sleep.

Theta

4-8 Hz

It is believed to be associatedwith cognitive function andconcentration.

Alpha

8-13 HzIt is believed to be related torelaxation and visual function.

Beta

13-30 HzIt is known to be associatedwith motor function.

Gamma

Over 30Hz

It is believed to be associatedwith various functions, including
higher cognitive functions andmeditation.

＋
＋

Alpha
（8-13 Hz)Beta
（13-30 Hz)

Types

＋
＋
50 uV
1s

Figure 1. EEG and the multiple waves that make up an EEG. An EEG is asuperimposed figure of multiple waves oscillating at various rhythms.

*The functions and states that each wave is believed to reflect are only
generalizations. Please refer to the corresponding Review Question for an
explanation of whether the theta oscillations actually indicate a concentration or
the alpha oscillations indicate a level of relaxation.

24

Appendix

1

Basic knowledge of EEG

EEG electrode position: International 10-20 system
The International 10-20 system uses letters of thealphabet to denote the location of recording electrodes on the head. For instance, "Fp'' represents
the frontal pole, the most anterior part of the head,
while "F" refers to the group of electrodes locatedin the frontal region. Among the electrodes locatedon the line connecting the front of the left andright ears (preauricular points), "C" located in thecentral region mainly corresponds to the areaaround the motor cortex, and "T" located in thetemporal region corresponds to the area aroundthe auditory cortex. The "P" in the parietal region
corresponds to the posterior parietal cortex, andthe "O" in the occipital region corresponds to thevisual cortex and other areas. It is important tonote that the measurement position and numberof electrodes may differ depending on the electroencephalogram used.

The International 10-20 System is a universal standard for electrode placement, which outlines the
positions and names of electrodes. This ensuresthat EEG recording electrodes are placed equidistantly on the scalp (Fig. 2). This system enables EEG
measurement from approximately the same brain
region, regardless of head size, and ensures thatthe recording electrodes are consistently placedwhen measuring EEG from the same person. However, EEG recordings from the scalp do not exclusively reflect activity from the brain region directly
under the recording electrode. Since brain activity
is measured through multiple tissues and substances (including the skull, dura mater, and cerebrospinal fluid), the resulting EEG contains a mixture of activity from various brain regions.

(A) Head position of each electrode symbol in the(B) Head position of each electrode symbol insagittal plane (head viewed from the side)

the horizontal plane (head viewed from above)

C

F

Fp1

Fp2

P
Fp

F7

T

F3

O
T3

C3

T5

25

F4

P3

Pz

F8

C4

Cz

O1

Figure 2. Electrode positions based on the International 10-20 system.

Fz

P4

O2

T4

T6

2

Design and role of placebos in Neurotech
results, making the evaluation of the drug's efficacy
more reliable.

In general, when conducting clinical trials to test
the effectiveness of a drug, participants are allocated into two groups. One group receives the actual
medication, while the other group receives a placebo that looks and tastes like the actual drug but
does not contain the active therapeutic ingredient.
The aim is to compare changes in symptoms
between the two groups. However, why is it
important to administer the placebo under suchcircumstances? One may argue that it is enough tocompare the group that receives the drug with thegroup that does not.

When testing the efficacy of Neurotech products, it
is recommended to compare it to a placebo condition, as is done in drug efficacy studies. In noninvasive brain stimulation, electrodes placed on thescalp are often used to stimulate the brain. To
mimic the stimulus being tested, a sham stimulation is used as a placebo condition (Fig.1A). The
typical placebo stimulus lasts for a few seconds toa few dozen seconds, after which no stimulus isgiven (Fig.1B). This method provides the subject
with a sensation similar to that of actual stimulation, even though not enough stimulation is actually delivered. Suppose veritable stimulation is more
effective than placebo stimulation. In that case, itmeans that sustained stimulation is necessary toin du c e c h an ges in m otor per for man c e an dmemory and that the stimulated sensation alone
cannot induce such changes.

If a comparison is made without a placebo, it is
impossible to rule out the possibility that the psychological comfort of taking the drug may have atherapeutic effect. Therefore, when placebo-controlled trials are conducted, participants areunaware of whether they receive a veritable drug
or a placebo. Even physicians administering the
drug/placebo and evaluators assessing the drug's
efficacy can have unconscious assumptions that
may affect the accuracy of the drug's assessment.
That's why clinical trials are conducted in the double-blind manner, that is a trial with physicians,
evaluators, and participants not knowing whether agiven subject takes a medication containing anactive ingredient or a placebo. This approach
reduces the risk of unconscious assumptions fromthose involved in the trial that would influence theTime(B) Placebo 1.
Subjects receive a brief stimulation
to the same brain regions as A.

Stimulation
intensity

Stimulation
intensity(A) Veritable stimulation.
Subjects receive sustained
stimulation to the brain regions
associated with specific functions.

Other placebos stimulate brain regions that are
different from those associated with specific functions and performance (Fig.1C). If actual stimulation is highly effective compared to this placebo, itmeans that stimulation to a particular brain regionis essential for inducing changes in function andperformance.

Time

Figure 1. Schematic diagram of noninvasive brain stimulation and its placebo condition.

26(C) Placebo 2.
Subjects receive sustained
stimulation to a brain region
different from A.
Stimulation
intensity

AppendixTimeAppendix

2

Design and role of placebos in Neurotech

and performance. This method measures brain
activity in the same way as the first and second placebos. Still, it differs in feeding back the brain activity index, validating more precisely the importanceof feeding back brain activity in specific brain
regions and at the particular frequency of EEG
activity [28].

Placebos in Neurofeedback Training (NFT) modify
the feedback information in various ways, as shownin Fig. 2B-E. The first placebo (Fig.2B) provides subjects with random information that resembles
brain activity. The second placebo (Fig.2C) presents
subjects with biometric information other thanbrain activity, such as heart rate. If veritable neurofeedback is more effective than these placebos,
this indicates that feedback of brain activity information, such as EEG, is crucial in inducing changes
in functions and performance.

The fourth placebo (Fig.2E) is a method wherebrain activity indices identical to veritable neurofeedback are calculated from the previously
recorded brain activity of others, such as EEG, andpresented to subjects. If veritable neurofeedback ismore effective than this placebo, it suggests that
regulating brain activity through neurofeedback is
crucial in inducing changes in function and performance.

The third placebo (Fig.2D) gives subjects brain
activity indices calculated from non-target brain
regions and other components. If veritable neurofeedback is highly effective compared to this placebo, it proves that feedback of the targeted brain
activity is essential in inducing changes in function

Schematic diagram of neurofeedback and its placebo condition(A) Veritable neurofeedback.
Subjects are presented with brain activity
that is thought to be associated witha specific function or performance.

(B) Placebo with feedback of random
information similar to brain activity.
Subjects are presented with information
based on randomly generated numbers.

(D) Placebo with feedback of other brain activity.
Subjects are presented with brain activity not thought tobe associated with specific functions, e.g., activity in brain
regions different from veritable neurofeedback.

(C) Placebo with feedback of otherbiometric information. Subjects arepresented with biometric information otherthan brain activity, such as heart rate
and respiratory rate.

(E) Placebo with feedback of another person's brain activity.
Subjects are presented with brain activity based on previously
recorded data of others.

Figure 2. Schematic diagram of neurofeedback and its placebo condition.

27

Appendix

3

Adverse events reported
in the use of Neurotech
the subjects. Using noninvasive brain stimulation
not following these guidelines may result in ahigher risk of adverse events.

An adverse event is an undesired medical event,other than the intended effect, that occurs during
or after using Neurotech products [29] . Take theexample of antihypertensive drugs. The intended
effect of antihypertensive medications is to lower
blood pressure at an appropriate level. To this end,
some antihypertensive drugs dilate blood vessels
or suppress the sympathetic nervous system. However, dilating blood vessels may cause the body tofeel hot, and suppressing the sympathetic nervous
system too much may cause bradycardia. In addition, some people may feel dizzy if their bloodpressures drop too low or they experience allergic
reactions.

Serious adverse events are adverse events that fallunder the following (1) to (6) [29].
(1) Those leading to death.
(2) Those potentially leading to death.
(3) Those requiring hospitalization or prolonged
hospitalization for treatment.
(4) Those causing permanent or significant disability or dysfunction.
(5) Those transmitted to the next generation ofchildren or grandchildren as a congenital disease or abnormality.
(6) Those judged to be medically significant in addition to the above.

Occurrences other than the targeted effect are
called adverse events. We also define occurrences
as adverse events even if they are not assumed tobe directly related to the use of the Neurotech
product but occurred during a study to determine
the effectiveness of a Neurotech product (e.g.,when a participant catches a cold and is hospitalized in a study period).

Possible non-serious adverse events that may becaused by the methods investigated in this bookinclude (1) temporary fatigue, (2) sick feeling, (3)pain or burning sensation at the site of stimulations, (4) headache, (5) dizziness or nausea, and (6)drowsiness [32]. Note that adverse events not only
vary to individuals but also may vary depending on
the physical condition of the day and the patient's
mental state, such as tension level, and do notalways occur.

Accumulating research data is now beginning toreveal which usage of Neurotech products or typesof participants is more likely to have adverse eventswith Neurotech products. Table1 shows theadverse events mentioned in the studies examinedin the development of the evidence book. Please
be aware that studies using noninvasive brain stimulation are conducted following the guidelines
published by the relevant academic societies [30,31]
and are planned with consideration of the safety of

A similar term to adverse events is side effects.
These refer to harmful effects on the user that may
have occurred directly due to using the Neurotech
products [29].

28Appendix

3

Adverse events reported in the use of Neurotech

Table 1. Adverse events reported in papers selected for each RQ

Intervention methods

Number of papers mentioning
the presence or absenceof adverse events

Serious adverse events

Non-serious adverse events

RQ1

Neurofeedback

5 of 33 papers

No occurrence

No occurrence

RQ2

Neurofeedback

0 of 4 papers

UnclearUnclear

RQ3

Neurofeedback

2 of 41 papers

No occurrence

No evaluation

RQ4

Neurofeedback

Under investigation

RQ5

Non-invasive brain stimulation

Under investigation

RQ6

Non-invasive brain stimulation

Under investigation

RQ7

Non-invasive brain stimulation

Under investigation

RQ8

Non-invasive brain stimulation

Under investigation

RQ9

EEG measurement

1 of 39 papers

No evaluation

No occurrence

RQ10

EEG measurement

Under investigation

RQ11

EEG measurement

Under investigation

RQ12

EEG measurement

Under investigation29

Supplementary Information
Evidence Book Creation Process
members, who conduct the content audit of thedeliverables, were selected from those with no conflict of interest in the Moonshot Kanai Project.

The "Liberation from Biological Limitations via
Physical, Cognitive and Perceptual Augmentation"(Project Manager: Ryota Kanai, Representative
Organization: Advanced Telecommunications
Research Institute International, hereinafterreferred to as "Moonshot Kanai Project"), an R&D
project under Moonshot Goal 1 of the Moonshot
Research & Development Program, established the"BMI Usage Guideline Development Committee"(now, the Guidebook Development Committee) in
July 2021 and started its activities to develop "BMI
Usage Guideline" [2]. The development committee
first conducted a preliminary survey on the sales
status of Neurotech products for general consumers in Japan and abroad and whether they areaccompanied by scientific evidence. The survey
revealed that although the number of products isincreasing, most have not been sufficiently verified
for their efficacy and safety. As a result, we thoughtthat the development of the BMI Usage Guideline
was not appropriate at this time due to the lack ofreliable sources.

To create the evidence book, NTT Data Institute ofManagement Consulting, Inc., commissioned by
the development committee, first conducted amarket survey of the effectiveness widely advocated for Neurotech products. Next, based on the
results, the Evidence Evaluation Committee established 12 review questions (RQs) that should be
scrutinized for effectiveness, safety, and reliability.
Each RQ was assessed by systematic review (SR)and meta-analysis by two Evidence Evaluation
Committee members and at least two SR members. Upon completion of the SR, an external
review was conducted by the SR external review
board using an SR evaluation tool called AMSTAR2[33]. If any issues were raised during this external
review, SR processes were revised until the SR
external review board approved that all the steps
had been appropriately conducted. After completing an external review of the SR process, the two
Evidence Evaluation Committee members were
responsible for compiling answers of the RQ. Additionally, volunteer SR members wrote appendicesthat provide complementary information to help
read through the evidence book.

Meanwhile, from the perspective of preventing
health hazards, the committee members considered that conducting a comprehensive survey ofthe efficacy and safety of Neurotech products andsharing the current results with the general public
is worthwhile. In addition, to promote the sounddevelopment of the Neurotech market, the same
information should be shared with businesses thatdevelop and provide such products and those considering entering the Neurotech market. Therefore,
the Guidebook Development Committee has decided to produce two books: a "Guidebook" aimed at
informing the general public about the current
status of Neurotech and an "Evidence Book" summarizing the scientific evidence on the effectiveness and safety of Neurotech. To ensure the integrity of the evidence search results, more than 60%of the members of the Evidence Evaluation Committee, who are responsible for the creation of the
Evidence Book, and all of the external review board

Once a draft of the evidence book was ready, it
underwent its first external review by medical
science experts. For this review, a modified versionof AGREEⅡ[34], originally developed to evaluate thequality of clinical practice guidelines, was used.
Based on the results, the text was revised and thenreviewed from a legal perspective by jurists andattorneys. The revised text was further polishedafter a second external review by all evidence bookexternal review board members. The external
review results and responses from the Evidence
Evaluation Committee members can be found at
the end of the Japanese version of the evidence
book [2].

30Supplementary Information

Future Revision Plans
Neurotech Guidebook. In contrast to the first version of the guidebook, which was written for thegeneral public, the second version will be written
for the private sector and those interested in developing and selling Neurotech products or incorporating them into their own businesses. The second
version will emphasize responsible product development, sales, and application. For instance, it will
include information on how to ensure the safety of
Neurotech products. This will involve distinguishing
between device safety (electrical and mechanical)
and biological safety (effects on the body and psychological state). Additionally, it will outline theneed for monitoring potential side effects, such as
headaches, dizziness, and anxiety, for an appropriate period. The guidebook will also highlight theimportance of conducting unbiased studies toassure product effectiveness and the methodology
for designing such studies.

The evidence book will be published in three separate editions. The first edition includes the answers
to four of the 12 RQs. The second edition, planned
to be available in May 2024, will have the answers
to additional five RQs. The third edition will haveanswers to all the 12 RQs and will be available in
December 2024. In addition, we plan to update theevidence book every three to five years to reflect
the latest research status regarding Neurotech's
effectiveness, safety, and reliability. To do so, we
have begun discussions with related academic
societies and international organizations to establish a system to update this document even after
the Moonshot Kanai Project ends in 2025. We
believe that consistently providing reliable information to the public will lead to building public trust in
Neurotech.
Moreover, the Guidebook Development Committee
is currently working on the second version of theManagement of COI
Conflict of interest (COI) is divided into economic
COI, which is related to financial relationships andacquisition of research funds with specific companies/organizations, and COI, such as academic COI(research activities and expertise) that are non-economic in nature (hereinafter referred to as "academic COI"). In addition to personal COI, financial
and academic COI with educational institutions
such as universities and other academic organizations, such as academic societies, to which thecommittee members belong may also affectevidence book development [35] . Therefore, theGuidebook Development Committee formulated amethod of managing COI before developing theevidence book under the Minds Manual for Guideline Development 2020 ver. 3.0 [35] and published aguideline regarding COI [2]. Specifically, the members of the Evidence Evaluation Committee, Systematic Review Team, Secretariat, and External
Review Boards are obliged to report their financial
COI for the three years prior to their appointment.

Apart from this, they are also requested to declareacademic COI for the three years prior to the startof the systematic review. In addition, we ask themto report both financial and academic COIs during
the previous year if any COI exceeds our set standards. Suppose it is found that there is an error inpreviously self-reported information. In that case,they must notify the secretariat and promptly file arevised report.
Based on the COI declarations submitted by members, we checked for conflicts of interest and, if
any, evaluated whether a management plan wasnecessary. The declaration criteria for economic
and academic COI are published on the website. In
addition, the declarations' contents will be madepublic at the same time as the evidence book is
published. Through these efforts, we are striving toensure that the content of the evidence book isneutral and appropriate and to earn society's trustin the use of Neurotech.

31

References(Blue indicates systematic review papers written by the members of the Evidence Evaluation Committee to derive answers
to RQs.)[1] McCall IC, Lau C, et al., Neuron. 2019;102(4):728-731.
[2] Moonshot Research and Development Program from the Japan Science and Technology Agency Internet of Brains.
Retrieved July 21, 2023; from https://brains.link/en/braintech_guidebook[3] Cheng MY, Huang CJ, et al., J Sport Exerc Psychol. 2015;37(6):626-636.
[4] Ota Y, Takamoto K, et al., Front Neurosci. 2020;14(34):1-16.
[5] Xiang MQ, Hou XH, et al., Psychol Sport Exerc. 2018;36:114-122.
[6] Onagawa R, Muraoka Y, et al., Neuroimage. 2023;270:120000.
[7] Yuan H, Liu T, et al., Neuroimage. 2010;49:2596-2606.
[8] Ministry of Health, Labour and Welfare. Kenkō Dukuri no tameno Suimin Shishin 2014 [Sleep Guidelines for Good
Health 2014], Retrieved January 9, 2023; from https://www.mhlw.go.jp/file/06-Seisakujouhou-10900000-Kenkoukyoku/0000047221.pdf[9] Schabus M, Griessenberger H, et al., Brain. 2017;140:1041–1052.
[10] Takeuchi H, Bandes I, et al., OSF. Retrieved April 15, 2023; from https://osf.io/8s6mf[11] Binsch O, Wilschut ES, et al., Appl Psychophysiol Biofeedback. 2018;43(1):37-47.
[12] Posner MI, Rothbart MK, et al., Curr Opin Behav Sci. 2015;4:1-5.
[13] Albert J, Sánchez-Carmona AJ, et al., Curr Dev Disord Rep. 2017;4(3):86-93.
[14] Egner T & Gruzelier JH, Neuroreport. 2001;12(18):4155-4159.
[15] Egner T & Gruzelier JH, Clin Neurophysiol. 2004;115:131-139.
[16] Gonçalves ÓF, Carvalho S, et al., Appl Psychophysiol Biofeedback. 2018;43:143-151.
[17] Enriquez-Geppert S, Huster RJ, et al., Front Behav Neurosci. 2014;8:420.
[18] Kimura I, Noyama H, et al., bioRxiv. 2023;533384.
[19] Strijkstra AM, Beersma D, et al., Neurosci Lett. 2003;340(1):17-20.
[20] Chang YC & Huang SL, Int J Psychophysiol. 2012;86(1):39-47.
[21] Putilov AA & Donskaya OG, Clin Exp Pharmacol Physiol. 2014;41(12):956-964.
[22] Li G, Huang S, et al., BMC Neurosci. 2020;21:20.
[23] Tran Y, Craig A, et al., Psychophysiology. 2020;57(5):e13554.
[24] Sugimoto K, Kurashiki H, et al., OSF. Retrieved April 15, 2023; from https://osf.io/37dpy/[25] Dustman RE, LaMarche JA, et al., Neurobiol Aging. 1985;6:193-198.
[26] Carrier J, Land S, et al., Psychophysiology. 2001;38:232-242.
[27] Lardon MT & Polich J, Biol Psychol. 1996;44(1):19-30.
[28] Sorger B, Scharnowski F, et al., Neuroimage. 2019;186:256-265.
[29] Ministry of Health, Labour and Welfare, POST-APPROVAL SAFETY DATA MANAGEMENT: DEFINITIONS AND STANDARDS FOR EXPEDITED REPORTING. Retrieved July 21, 2023; from https://www.pmda.go.jp/files/000156499.pdf[30] Nihon Rinshō Shinkei Seirigaku Kai Nō Shigeki Hō ni Kansuru Shōiinkai, Rinshō Shinkeiseirigaku. 2019;47(2):126-130.
[31] Nihon Rinshō Shinkei Seirigaku Kai Nō Shigeki Hō ni Kansuru Shōiinkai, Rinshō Shinkeiseirigaku. 2021);49(2):109-113.
[32] Antal A, Alekseichuk I, et al., Clin Neurophysiol. 2017;128(9):1774-1809.
[33] Kamioka H, Origasa H et al., Jpn Pharmacol Ther, 2018;46(11),1785-1796.
[34] Brouwer M, Kho M et al., J. Clin. Epidemiol., 2010;63(12), 1308-1311.
[35] Minds Guidelines Library. Retrieved January 9, 2023; from https://minds.jcqhc.or.jp/docs/various/manual_2020/ver3_0/pdf/all_manual_2020ver3_0.pdf

32People involved in the evidence book development
Evidence Evaluation Committee
Kaoru Amano: Professor. Grad Sch of Info Sci and Tech, The University of Tokyo. (RQ9)
Nobuhiro Hagura: Principal Investigator. Cent for Info and Neural Networks (CiNet), Advanced ICT Res Inst, National Institute ofInformation and Communications Technology (NICT). (RQ1)
Koichi Hosomi: Specially Appointed Associate Professor. Grad Sch of Med, Osaka University.
Aya Ihara: Principal Investigator. CiNet, Advanced ICT Res Inst, NICT.
Jun-ichiro Kawahara: Professor. Grad Sch of Humanities and Human Sci, Hokkaido University. (RQ3)
Akifumi Kishi: Project Lecturer. Grad Sch of Med, The University of Tokyo. (RQ2)
Maro Machizawa: Specially Appointed Associate Professor. Cent for Brain, Mind and KANSEI Sci Res, Hiroshima University.
Rieko Osu: Professor. Faculty of Human Sciences, Waseda University. (RQ3)
Mitsuaki Takemi: Project Assistant Professor. Grad Sch of Sci and Tech, Keio University. (Chairman of the Evidence Evaluation Committee, RQ1 and RQ9)
Masako Tamaki: Riken Hakubi Team Leader. Cognitive Somnology RIKEN Hakubi Res Team, RIKEN Center for Brain Science. (RQ2)
Takufumi Yanagisawa: Professor. Inst for Advanced Co-Creation Studies, Osaka University.
Natsue Yoshimura: Professor. Sch of Computing, Tokyo Institute of Technology.
Systematic Review Team
Isabel Bandes: PhD student. Dept of Info and Commun Eng, Tokyo Institute of Technology. (RQ2)
Seitaro Iwama: Assistant Professor. Fac of Sci and Tech, Keio University. (Appendix 1 and 2)
Naotsugu Kaneko: Assistant Professor. Grad Sch of Arts and Sci, The University of Tokyo. (Appendix 1)
Ikko Kimura: Special Postdoctoral Researcher. Lab for Brain Connectomics Imaging, RIKEN BDR. (RQ3 and Appendix 3)
Hideaki Kurashiki: Master student (Graduated in March 2023). Grad Sch of Sci and Tech, Keio University. (RQ9)
Yoshihito Muraoka: Master student (graduated in March 2023). Grad Sch of Sci and Tech, Keio University. (RQ1)
Hiroki Noyama: PhD student. Grad Sch of Eng, The University of Tokyo. (RQ3)
Ryoji Onagawa: JSPS Research Fellow (PD). Fac of Sci and Eng, Waseda Univ. (Leader of the Systematic Review Team, RQ1 and RQ3)
Atsushi Sasaki: JSPS Research Fellow (PD). Grad Sch of Eng Sci, Osaka University. (Appendix 2)
Kairi Sugimoto: PhD student. Faculty of Sci and Eng, Waseda University. (RQ9)
Hiroki Takeuchi: Project Researcher. Grad Sch of Education, The University of Tokyo. (RQ2)
Yuting Xu: PhD student. Grad Sch of Info Sci and Tech, The University of Tokyo. (RQ9)
Evidence Book External Review Board
Takeo Nakayama: Professor. Grad Sch of Med, Kyoto University.
Yu Nishitsutsumi: Researcher. CiNet, Advanced ICT Res Inst, NICT.
Noriko Osumi: (1) Professor. Grad Sch of Med, Tohoku University. (2) Vice-president. Tohoku University.
Takayoshi Sugawara: (1) Attorney at Law. Sedgefield Kobayashi and Partners. (2) Professor. Keio University Law School.
Yoshikazu Ugawa: Emeritus Professor. Fukushima Medical University.
Fumihiro Uno: President and CEO. Dobunshoin, Inc.
Systematic Review External Review Board
Masahiro Iguchi: Assistant Professor. Dept of Neurology, Fukushima Medical University.
Masahito Mihara: Professor. Dept of Neurology, Kawasaki Medical School.
Secretariat
Tomoya Nakanishi: Consultant. Neuro Innovation Unit, NTT Data Institute of Management Consulting, Inc.
Shiho Tenmoto: Director. Knowledge Mobility based System Institute.
Seiko Fujiwara: Part-time Clerk. Keio University.
Yumiko Kakubari: ARAYA Inc.
Ayumi Kusano: ARAYA Inc.
Editing
Ririko Sano (Illustration & Design), Kairi Sugimoto (Editing), Hiroki Takeuchi (Editing), Tatsuro Fujimaki (Editing),
Jacob Faller (English proofreading), Isabel Bandes (English proofreading)33

Acknowledgements
We would like to thank the following individuals for their advice and guidance in the development of thisevidence book.
Dr. Yoshihito Goto and Dr. Yuko Masuzawa: for their lecture on systematic reviews and guideline development.
Dr. Keigo Komamura, Dr. Yoshinori Oshima, Dr. Takeyuki Matsuo, Dr. Masahiko Sudo, and Dr. Masatoshi Kokubo: fortheir efforts in refining the text from a legal perspective.

Contact for the Neurotech Evidence Book
Neurotech Guidebook Development Committee Secretariat
E-mail: info_guideline@brains.link

34

List of Financial COI
Evidence Evaluation Committee*Affiliations, positions, grades, qualifications, etc. are as of April 1, 2023, and COI details, in principle, are based on declarations as of February 1, 2023.

Details of Self-reported Financial COI
1. . Employment as an

2. Profit on equity

3. Patent royalty

officer/director/adviser in aName

Affiliation

Occupation

Qualifications and Expertise

Specialty

Academic societies in hold positions, etc.

4. Daily allowance

5. Manuscript fees

6. Research funding, grants, etc.

(Remunerations, lecture fee, etc.)

7. Scholarship (Incentive)

8.

Donations, etc.

company/organization/institution receipt of gifts, etc.)

Endowed courses oﬀered by a 9. Others (travel expenses,

company or any for-profit
organization directly related to
the research and amount of
remuneration

Councilors,The Japan Neuroscience Society.
Working Group 4 member, Industry-Academia
Mitsuaki Takemi

Graduate School of Science and Technology, Keio University

Project Assistant Professor

Ph.D.

Neuroscience, Motor system

Collaboration Advisory Committee, Union of Brain
Science Associations in Japan.

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Program committee member, The JapaneseSociety for Motor Control (2023).

Committee Members, Industry-Academia
Kaoru Amano

Graduate School of Information Science and Technology, The Universityof Tokyo

Professor

Ph.D.

Non-invasive brain function measurement,
non-invasive brain stimulation

Partnership Committee, The Japan Neuroscience
Society.
Caretaker, Vision Society of Japan.
Director, Japanese Neural Network Society.
Evaluation panel member, The Strategic

Center for Information and Neural Networks (CiNet), Advanced ICT
Aya Ihara

Research Institute, National Institute of Information andSenior Researcher

Ph.D.

Communications Technology (NICT)

Cognitive Neuroscience, Brain functions

International Brain Science Research Promotion

involved in language

Program, Japan Agency for Medical Research andDevelopment.
Committee, Technical Committee on
Neurocomputing (NC), Institute of Electronics,

Rieko Osu

Faculty of Human Sciences, Waseda University

Professor

Ph.D.

Cognitive neuroscience

Information and Communication Engineers(Through March 2022).
Director, The Japanese Society for Motor Control.

1. NTT DATA INSTITUTE OF

Executive Director and Vice President, The

MANAGEMENT CONSULTING,
Inc., Applicable to: individual,

Japanese Psychological Association.
Jun-ichiro Kawahara

Graduate School of Humanities and Human Sciences, Hokkaido
University

Professor

Ph.D.

Cognitive Psychology

Managing Director, The Japanese Society for
Cognitive Psychology.

Period: September 2019 to
N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

present.
2. Universal Communication

Chairman of the Editorial Board, The Japanese

Design Association, Applicable to:

Psychological Association.

individual, Period: April 2019 topresent.
1. Toppan Inc., Applicable to:individual, Period: October 2019

Akifumi Kishi

Graduate School of Medicine, The University of Tokyo

Project Lecturer

Ph.D.

Educational Physiology

Councilor, Japanese Society for Chronobiology.

N/A

N/A

N/A

N/A

N/A

N/A

to present.
2. JMDC Inc., Applicable to:

N/A

N/A

individual, Period: July 2020 topresent.

Committee, Future Vision Board, The Japanese
Masako Tamaki

RIKEN Center for Brain Science (CBS), RIKEN Hakubi Team Leader
Cognitive Somnology RIKEN Hakubi Research TeamRIKEN Hakubi Team Leader

Ph.D.

Sleep Reserch, Cognitive Neuroscience

Society of Sleep Research.
Committee, Ethics Board, The Japanese Society of

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Sleep Research.

Research Institute, National Institute of Information and

NTT DATA INSTITUTE OF

Program committee member, The JapaneseCenter for Information and Neural Networks (CiNet), Advanced ICT
Nobuhiro Hagura

Senior Researcher

Ph.D.

Cognitive Neuroscience

Communications Technology (NICT)

Society for Motor Control (2021 to 2022).
Board Member, The Japanese Society for Motor

MANAGEMENT CONSULTING,
Inc., Applicable to: individual,
Period: September 2019 toControl (2023).

present.

Councilor, Japan Neuromodulation Society.
Delegate, Japanese Association for Study of Pain.
Koichi Hosomi

Graduate School of Medicine, Osaka University

Specially Appointed Associate
Professor

Functional Neurosurgery

Member of Academic Committee, Japan Society

Teijin Pharma Limited, Applicable

DAIICHI SANKYO COMPANY,International Relations Committee Member andM.D., Ph.D.

N/A

N/A

N/A

N/A

N/A

for Stereotactic and Functional Neurosurgery.

LIMITED, Applicable to:individual, Period: from April 2019

to: individual, Period: from before
N/A

January 2019 to March 2021.

N/A*Not an endowed chair, but a joint

to December 2020.

research chair.

Member of Subcommittee on brain stimulation,
Japanese Society of Clinical Neurophysiology.

Center for Brain, Mind and KANSEI Sciences Research, Hiroshima
Maro Machizawa

University
Xiberlinc Inc. (April 1, 2022 to present)

Specially Appointed Associate
Professor

CAINZ Digital Innovation

Ph.D.

Cognitive Neurology

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Foundation, Period: from April

N/A

N/A

2020 to March 2021.

CEO

Councilor, Japanese Association for the Study of
Takufumi Yanagisawa

Institute for Advanced Co-Creation Studies, Osaka University

Professor

M.D., Ph.D.

Neuroscience, Neurosurgery, Epilepsy, Clinical Pain.
Neurophysiology

Councilor, The Japanese Society of Aromatherapy

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

(Through FY2021).

Natsue Yoshimura

School of Computing, Tokyo Institute of Technology

Professor

Ph.D.

Brain Information Decoding, Brain MachineInterfaces

Delegate, Japanese Neural Network Society.
Board Member, The Japanese Society for Motor
Control (2023).

*Affiliations, positions, grades, qualifications, etc. are as of April 1, 2023, and COI details, in principle, are based on declarations as of February 1, 2023.

Systematic Review Team

Details of Self-reported Financial COI
1. . Employment as an

2. Profit on equity

3. Patent royalty

officer/director/adviser in aName

Affiliation

Occupation

Qualifications and Expertise

Specialty

Academic societies in hold positions, etc.

4. Daily allowance

5. Manuscript fees

6. Research funding, grants, etc.

(Remunerations, lecture fee, etc.)

7. Scholarship (Incentive)

8.

Donations, etc.

company/organization/institution receipt of gifts, etc.)

Endowed courses oﬀered by a 9. Others (travel expenses,

company or any for-profit
organization directly related to
the research and amount of
remuneration

Ryoji Onagawa

Isabel Bandes

Faculty of Science and Engineering, Waseda University

Department of Information and Communications Engineering, Tokyo
Institute of Technology

Research Fellow (PD), Japan Society

Ph.D.

for the Promotion of Science

Second-year doctoral student-

Motor Control, Decision-making

Brain decoding associated with movement andthe design of online brain computer interface

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Seitaro Iwama

Faculty of Science and Technology, Keio University

Assistant Professor

Ph.D.

Neuroscience

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Naotsugu Kaneko

Graduate School of Arts and Sciences, The University of Tokyo

Assistant Professor

Ph.D.

Neurophysiology

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

M.D., Ph.D.

Neuroscience, Neurology

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

-

Cognitive Neuroscience

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

-

Brain-machine Interface

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Ph.D.

Neurophysiology

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Cognitive psychology

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Ikko Kimura

XU Yuting

Hideaki Kurashiki

Atsushi Sasaki

Laboratory for Brain Connectomics Imaging, RIKEN

Graduate School of Information Science and Technology, The Universityof Tokyo

Graduate School of Science and Technology, Keio University

Graduate School of Engineering Science, Osaka University

Special Postdoctoral Researcher(SPDR)First-year doctoral student

Completed master's degree (March2023)
Research Fellow (PD), Japan Society
for the Promotion of Science

Third-year doctoral student
Kairi Sugimoto

Faculty of Science and Engineering, Waseda University

Research Fellow (DC1), Japan Society Type 1 High school teaching license

Waseda University Honjo Senior High Schoolfor the Promotion of Sciencefor Informatics

Part-time lecturer

Hiroki Takeuchi

Graduate School of Education, The University of Tokyo

Project Researcher-

Educational physiology

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Hiroki Noyama

Graduate School of engineering, The University of Tokyo

Third-year doctoral student-

Neuroengineering

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

-

Neuroscience

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Yoshihito Muraoka

Graduate School of Science and Technology, Keio University

Completed master's degree (March2023)

Evidence Book External Review Board*Affiliations, positions, grades, qualifications, etc. are as of April 1, 2023, and COI details, in principle, are based on declarations as of February 1, 2023.

Details of Self-reported Financial COI
1. . Employment as an

2. Profit on equity

3. Patent royalty

officer/director/adviser in aName

Affiliation

Occupation

Qualifications and Expertise

Specialty

Academic societies in hold positions, etc.

4. Daily allowance

5. Manuscript fees

6. Research funding, grants, etc.

(Remunerations, lecture fee, etc.)

7. Scholarship (Incentive)

8. Endowed courses offered by a

Donations, etc.

company/organization/institution receipt of gifts, etc.)

9. Others (travel expenses,

company or any for-profit
organization directly related to
the research and amount of
remuneration

Auditor, The Japanese Society of Neurology.
President, Asian Oceanian chapter of IFCN.
1.

Member, Executive Committee of IFCN.
M.D., Ph.D., Board Certified
Yoshikazu Ugawa

Fukushima Medical University

Emeritus Professor

Member of the Japanese Society ofInternal Medicine, Neurologist,

Neurology, Clinical Neurophysiology

Clinical neurophysiology's Doctor

Association of Radio

Industries and Businesses,

Chair, Brain Stimulation Special Interest Group of
IFCN.

N/A

Chair, Movement Disorder in Asia Study Group of

N/A

N/A

to: individual, Period: from April

1.

Applicable to: individual, Period:

CHUGAI-IGAKUSHA, Applicable
N/A

2019 to March 2022.

International Parkinson and Movement Disorders
Society (MDS) .

2.

Takeda General Hospital,

Applicable to: individual, Period:

from April 2019 to March 2023.

N/A

Tokyo Metropolitan Institutefrom April 2020 to March 2024.
2.

Aidu Chuo Hospital,of Medical Science, Applicable to:

Applicable to: individual, Period:

individual, Period: from April 2019from April 2019 to March 2022.

N/A

to March 2023.

Delegate, The Japanese Society of Neurology toWorld Federation of Neurology.

Publisher, Natural Medicine database Japan.
Fumihiro Uno

Dobunshoin, Inc.

Chief Executive Officer (CEO)-Financial Management

Executive Secretary, Japanese Association of

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Nutritional Science Education.

Councilor, The Japanese Society of
Neuropsychopharmacology.
Councilor, Union of Brain Science Associations inJapan.
Director (Through December 2022),Councilor
Tohoku University.
Noriko Osumi

Tohoku University Library.

Director.

Tohoku University Graduate School of Medicine.

Professor.

Center for Neuroscience.

(From January 2023), The Japan Neuroscience

Vice President.
Ph.D., DDS

Molecular Biology, Developmental Biology,
Neuroembryology, Science Communication

Chair.

Society.
Councilor, The Japanese Society for
Neurochemistry.
Delegate, The Japan Society of Developmental
Origins of Health and Disease.
Director, BRAINTECH CONSORTIUM.
Director, The Naito Foundation.
Councilor, Astellas Foundation for Research on
Metabolic Disorders.

Director, The Air Law Institute of Japan.
National Governance PT Member, KEIZAIDOYUKAI<Japan Association of Corporate
Executives>.
Civil law, commercial and corporate law,
Takayoshi Sugawara

Sedgefield Kobayashi and Partners.
Faculty of Law, Keio University.

Attorney at Law.
Professor.

Attoney at Law

Trustee, The Tokyo Bar Association Scholarship

1. Keio University, Applicable to:Foundation.

individual, Period: from April 2019

Information Law, Aviation and Space Law, and Director, Corporate Law Section, Legal Research

to March 2022.
2. ANA Strategic Research

Economic Law,

Department, Tokyo Bar Association.

Risk Management

Member, International Transaction Law

individual, Period: from April 2019

Department, Legal Research Division, Tokyo Bar

to March 2021.

Institute Co.,Ltd., Applicable to:

Association.
Academic member, Specialist Committee on
Economic Law and Regulations, The Japan
Chamber of Commerce and Industry.

1. Janssen Pharmaceutical K.K.,

Vice President, Japan Association of Health

Takeo Nakayama

Graduate School of Medicine and Faculty of Medicine, Kyoto University

Professor

1. Hanshin Dispensing Holdings

Applicable to: individual, Period:

M.D., Ph.D.

Communication.

Public Health and Social Medicine

Vice President, Japanese Society for Clinical

Certified Specialist, Japanese

Public Health, Epidemiology, Health

Knowledge.

Society of Public Health

Informatics, Health Communication, etc.

Vice President, The Japanese Association of

Certified Senior Epidemiologist,

Smoking Control Science.

Japan Epidemiological Association

Vice President, Japanese Society of HealthLtd., Applicable to: individual,

from April 2018 to March 2019.

Period: from April 2019 to March

2. Mitsubishi Tanabe Pharma
N/A

N/A

N/A

Corporation, Applicable to:individual, Period: from April 2020

KONICA MINOLTA, INC.,
N/A

from April 2019 to March 2022.

to March 2021.

Science for Children.

Applicable to: individual, Period:2022.
2. Nakagawa Pharmacy Co., Ltd.,
Applicable to: individual, Period:
from April 2019 to March 2022.

3. Eli Lilly Japan K.K., Applicable

3. YUYAMA Co., Ltd, Applicable

to: individual, Period: from April

to: individual, Period: from April

2020 to March 2021.

2019 to March 2022.

Center for Information and Neural Networks (CiNet), Advanced ICT
Yu Nishitsutsumi

Research Institute, National Institute of Information andCommunications Technology (NICT)

Researcher

Ph.D.

Philosophy of Mind, Neuroethics

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Systematic Review External Review Board*Affiliations, positions, grades, qualifications, etc. are as of April 1, 2023, and COI details, in principle, are based on declarations as of February 1, 2023.

Details of Self-reported Financial COI
1. . Employment as an

2. Profit on equity

3. Patent royalty

officer/director/adviser in aName

Affiliation

Occupation

Qualifications and Expertise

Specialty

Academic societies in hold positions, etc.

4. Daily allowance

5. Manuscript fees

6. Research funding, grants, etc.

(Remunerations, lecture fee, etc.)

7. Scholarship (Incentive)

8.

Donations, etc.

company/organization/institution receipt of gifts, etc.)

Endowed courses oﬀered by a 9. Others (travel expenses,

company or any for-profit
organization directly related to
the research and amount of
remuneration

Masahiro Iguchi

Department of Neurology, Fukushima Medical University

Masahito Mihara

Department of Neurology, Kawasaki Medical School

Associate Professor

M.D., Ph.D.

Clinical Neurology

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Professor

M.D., Ph.D.

Clinical Neurology, Neurorehabilitation

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

4. Daily allowance

5. Manuscript fees

*Affiliations, positions, grades, qualifications, etc. are as of April 1, 2023, and COI details, in principle, are based on declarations as of February 1, 2023.

Secretariat

Details of Self-reported Financial COI
1. . Employment as an

2. Profit on equity

3. Patent royalty

officer/director/adviser in aName

Affiliation

Occupation

Qualifications and Expertise

Specialty

Academic societies in hold positions, etc.

6. Research funding, grants, etc.

(Remunerations, lecture fee, etc.)

7. Scholarship (Incentive)

8.

Donations, etc.

company/organization/institution receipt of gifts, etc.)

Endowed courses oﬀered by a 9. Others (travel expenses,

company or any for-profit
organization directly related to
the research and amount of
remuneration

Yumiko Kakubari

ARAYA Inc.

-

-

ー

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Ayumi Kusano

ARAYA Inc.

-

Ph.D.

Molecular genetics

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Shiho Tenmoto

Knowledge Mobility based System Institute

Director-

Science Communication

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Seiko Fujiawara

Keio University

Part-time Clerk

-

ー

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Consultant

Ph.D., Physical Therapist

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Tomoya Nakanishi

Neuro Innovation Unit, NTT Data Institute of Management Consulting,Inc.

Rehabilitation Science, Sports Science
Neurophysiology, Neuroscience2023/8/19[RQ1] List of Academic COI
Details of Self-reported Academic COI

Name

Affiliation

Occupation

Function

1. I have cited my academic papers 2. I am a family or relative of

3. I have a close mentor-pupil

4. Endowed courses related to BMI 5. Not applicable to the items

in systematic reviews of the social

relationship or direct employment

are offered by a company or a for-another committee member.

questions. However, systematic

relationship with another committee profit corporate organization orreview articles summarizing themember.

In particular：

above, but there are events in whicha conflict of interest is assumed.

group in the department, division,

findings of this RQ are excluded.

etc. at the university, national
research institute, or other research
institution to which I belong, or at
the same company.

Mitsuaki Takemi

Graduate School of Science and Technology, Keio University

Project Assistant Professor

Member of Guidebook Development Committee,

N/A

N/A

Member of Evidence Evaluation Committee

N/A

N/A

Systematic Review Member

N/A

N/A

Systematic Review Member

N/A

N/A

Chairman of Evidence Evaluation Committee

Applicable person: Junichi Ushiba

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Relationship: My employer

Center for Information and Neural Networks (CiNet), Advanced

Nobuhiro Hagura

ICT Research Institute, National Institute of Information andSenior Researcher

Communications Technology (NICT)

Ryoji Onagawa

Faculty of Science and Engineering, Waseda University

Yoshihito Muraoka Graduate School of Science and Technology, Keio University

Research Fellow (PD), Japan Society
for the Promotion of Science

Completed master's degree (March
2023)

Applicable person: Junichi Ushiba
Relationship: My supervisor[RQ2] List of Academic COI
Details of Self-reported Academic COI

Name

Affiliation

Occupation

Function

1. I have cited my academic papers 2. I am a family or relative of

3. I have a close mentor-pupil

4. Endowed courses related to BMI 5. Not applicable to the items

in systematic reviews of the social

relationship or direct employment

are offered by a company or a for-another committee member.

questions. However, systematic

relationship with another committee profit corporate organization orreview articles summarizing themember.

In particular：

above, but there are events in whicha conflict of interest is assumed.

group in the department, division,

findings of this RQ are excluded.

etc. at the university, national
research institute, or other research
institution to which I belong, or at
the same company.

Akifumi Kishi

Graduate School of Medicine, The University of Tokyo

Project Lecturer

Member of Evidence Evaluation Committee

N/A

N/A

N/A

N/A

N/A

N/A

RIKEN Hakubi Team Leader

Member of Evidence Evaluation Committee

N/A

N/A

N/A

N/A

N/A

N/A

Project Researcher

Systematic Review Member

N/A

N/A

N/A

N/A

N/A

N/A

Second-year doctoral student

Systematic Review Member

N/A

N/A

N/A

N/A

N/A

N/A

RIKEN Center for Brain Science (CBS), RIKEN Hakubi Team

Masako Tamaki

LeaderCognitive Somnology RIKEN Hakubi Research Team

Hiroki Takeuchi

Isabel Bandes

Graduate School of Education, The University of Tokyo

Department of Information and Communications Engineering,Tokyo Institute of Technology

[RQ3] List of Academic COI
Details of Self-reported Academic COI

Name

Affiliation

Occupation

Function

1. I have cited my academic papers 2. I am a family or relative of

3. I have a close mentor-pupil

4. Endowed courses related to BMI 5. Not applicable to the items

in systematic reviews of the social

relationship or direct employment

are offered by a company or a for-another committee member.

questions. However, systematic

relationship with another committee profit corporate organization orreview articles summarizing themember.

In particular：

above, but there are events in whicha conflict of interest is assumed.

group in the department, division,

findings of this RQ are excluded.

etc. at the university, national
research institute, or other research
institution to which I belong, or at
the same company.

Rieko Osu

Faculty of Human Sciences, Waseda University

Jun-ichiro

Graduate School of Humanities and Human Sciences, Hokkaido

Kawahara

University

Ryoji Onagawa

Faculty of Science and Engineering, Waseda University

Ikko Kimura

Laboratory for Brain Connectomics Imaging, RIKEN

Hiroki Noyama

Graduate School of engineering, The University of Tokyo

Professor

Member of Evidence Evaluation Committee

N/A

N/A

N/A

N/A

N/A

N/A

Professor

Systematic Review Member

N/A

N/A

N/A

N/A

N/A

N/A

Systematic Review Member

N/A

N/A

N/A

N/A

N/A

N/A

Systematic Review Member

N/A

N/A

N/A

N/A

N/A

Systematic Review Member

N/A

N/A

N/A

N/A

N/A

Research Fellow (PD), Japan Society
for the Promotion of Science

Special Postdoctoral Researcher(SPDR)

Third-year doctoral student

Applicable person: Kaoru Amano
Relationship: My supervisor

N/A[RQ9] List of Academic COI
Details of Self-reported Academic COI

Name

Affiliation

Occupation

Function

1. I have cited my academic papers 2. I am a family or relative of

3. I have a close mentor-pupil

4. Endowed courses related to BMI 5. Not applicable to the items

in systematic reviews of the social

relationship or direct employment

are offered by a company or a for-another committee member.

questions. However, systematic

relationship with another committee profit corporate organization orreview articles summarizing themember.

In particular：

above, but there are events in whicha conflict of interest is assumed.

group in the department, division,

findings of this RQ are excluded.

etc. at the university, national
research institute, or other research
institution to which I belong, or at
the same company.

Kaoru Amano

Graduate School of Information Science and Technology, The
University of Tokyo

Mitsuaki Takemi

Graduate School of Science and Technology, Keio University

Hideaki Kurashiki

Graduate School of Science and Technology, Keio University

Professor

Project Assistant Professor

Completed master's degree (March
2023)

Member of Evidence Evaluation Committee

Member of Guidebook Development Committee,
Chairman of Evidence Evaluation Committee

Systematic Review Member

N/A

N/A

N/A

N/A

N/A

N/A

Applicable person: Ikko Kimura, XU Yuting
Relationship: My students

Applicable person: Junichi Ushiba
Relationship: My employer

Applicable person: Junichi Ushiba
Relationship: My supervisor

Although I haven't published a paper yet, I
N/A

am currently researching on the relationshipN/Abetween brain waves and relaxation.

N/A

N/A

N/A

I previously conducted the studies using the
N/Aindicators possibly treated in the RQ and am

N/Agoing to published them as a paper.

Third-year doctoral student

Kairi Sugimoto

Faculty of Science and Engineering, Waseda University

Research Fellow (DC1), Japan Society

Waseda University Honjo Senior High Schoolfor the Promotion of Science

Systematic Review Member

N/A

N/A

Systematic Review Member

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Part-time lecturer

XU Yuting

Graduate School of Information Science and Technology, The
University of Tokyo

First-year doctoral student

Applicable person: Kaoru Amano
Relationship: My supervisor

[Appendix] List of Academic COI
Details of Self-reported Academic COI

Name

Affiliation

Occupation

Function

1. I have cited my academic papers 2. I am a family or relative of

3. I have a close mentor-pupil

4. Endowed courses related to BMI 5. Not applicable to the items

in systematic reviews of the social

relationship or direct employment

are offered by a company or a for-another committee member.

questions. However, systematic

relationship with another committee profit corporate organization orreview articles summarizing themember.

In particular：

above, but there are events in whicha conflict of interest is assumed.

group in the department, division,

findings of this RQ are excluded.

etc. at the university, national
research institute, or other research
institution to which I belong, or at
the same company.

Seitaro Iwama

Faculty of Science and Technology, Keio University

Assistant Professor

Systematic Review Member

N/A

N/A

Naotsugu Kaneko

Graduate School of Arts and Sciences, The University of Tokyo

Assistant Professor

Systematic Review Member

N/A

N/A

Ikko Kimura

Laboratory for Brain Connectomics Imaging, RIKEN

Systematic Review Member

N/A

N/A

Atsushi Sasaki

Graduate School of Engineering Science, Osaka University

Systematic Review Member

N/A

N/A

Special Postdoctoral Researcher(SPDR)

Research Fellow (PD), Japan Society
for the Promotion of Science

Applicable person: Junichi Ushiba
Relationship: My supervisor

N/A

Applicable person: Kaoru Amano
Relationship: My supervisor

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

[Evidence Book External Review Board] List of Academic COI
Details of Self-reported Academic COI
1. I am a family or relative of

2. I have a close mentor-pupil

3. Endowed courses related to BMI 4. Not applicable to the items

another committee member.

relationship or direct employment

are offered by a company or a for-relationship with another committee profit corporate organization ormember.
Name

Affiliation

Occupation

In particular：

above, but there are events in whicha conflict of interest is assumed.

group in the department, division,

Function

etc. at the university, national
research institute, or other research
institution to which I belong, or at
the same company.

Yoshikazu Ugawa

Fukushima Medical University

Emeritus Professor

Evidence Book External Review Board

N/A

N/A

N/A

N/A

N/A

Fumihiro Uno

Dobunshoin, Inc.

Chief Executive Officer (CEO)Evidence Book External Review Board

N/A

N/A

N/A

N/A

N/A

Tohoku University

Vice President

Tohoku University Library

Director

Tohoku University Graduate School of Medicine

Professor

Evidence Book External Review Board

N/A

N/A

N/A

N/A

N/A

Center for Neuroscience

Chair

Takayoshi

Sedgefield Kobayashi and Partners

Attorney at Law

Sugawara

Faculty of Law, Keio University

Professor

Evidence Book External Review Board

N/A

N/A

N/A

N/A

N/A

Professor

Evidence Book External Review Board

N/A

N/A

N/A

N/A

N/A

Researcher

Evidence Book External Review Board

N/A

N/A

N/A

N/A

N/A

Noriko Osumi

Takeo Nakayama

Graduate School of Medicine and Faculty of Medicine, Kyoto
University

Center for Information and Neural Networks (CiNet), Advanced

Yu Nishitsutsumi

ICT Research Institute, National Institute of Information andCommunications Technology (NICT)

[Systematic Review External Review Board] List of Academic COI
Details of Self-reported Academic COI
1. I am a family or relative of

2. I have a close mentor-pupil

3. Endowed courses related to BMI 4. Not applicable to the items

another committee member.

relationship or direct employment

are offered by a company or a for-relationship with another committee profit corporate organization ormember.
Name

Affiliation

Occupation

In particular：

above, but there are events in whicha conflict of interest is assumed.

group in the department, division,

Function

etc. at the university, national
research institute, or other research
institution to which I belong, or at
the same company.

Masahiro Iguchi

Department of Neurology, Fukushima Medical University

Associate Professor

Systematic Review External Review Board

N/A

N/A

N/A

N/A

N/A

Masahito Mihara

Department of Neurology, Kawasaki Medical School

Associate Professor

Systematic Review External Review Board

N/A

N/A

N/A

N/A

N/A