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ATTENTION & SLEEP
Keywords:
neurofeedback, attention, sleep,
insomnia, ADHD, E-NFT
The effects of neurofeedback on attention and sleep in
individuals with and without ADHD or insomnia: a
literature review
Annel Koomen
1
, Daniel Keeser
2
, Sonja Verhagen
3
1 University of Amsterdam, Amsterdam
2 Ludwig Maximilian University, Munich
3 Hersencentrum Mental Health Institute, Amsterdam
*Correspondence: annel_koomen_@hotmail.com
DOI: 10.31739/ANAMH.2021.1.30
ABSTRACT
Electroencephalography-Neurofeedbacktraining (E-NFT) is a method
to support subjects in learning to self-regulate their own brain activity.
Besides that E-NFT may improve cognitive functions in healthy
people, it may improve symptoms in different disorders, such as
Attention Deficit and Hyperactivity Disorder (ADHD) and insomnia.
The evidence of E-NFT for the treatment of attention problems in
ADHD is still under debate, just as the suggested efficacy of E-NFT
for reducing sleep problems in individuals suffering from insomnia
and for improving attention and sleep in the general population.
Therefore, this review examines the efficacy of E-NFT on attention
and sleep in patients and healthy individuals. The reviewed literature
provides evidence that standard E-NFT protocols may have a positive
long-lasting effect on the inattention and hyperactivity/impulsivity
symptoms in children with ADHD. In healthy children and young
adults, E-NFT has been found to improve different aspects of
attention and to reduce impulsivity. In addition, positive effects of E-
NFT have been documented on sleep onset latency and on tiredness
in healthy individuals. Sleep improvements have also been found in
insomnia patients after standard E-NFT, although these subjective
sleep improvements may likely depend on unspecific E-NFT effects.
E-NFT, ATTENTION & SLEEP
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INTRODUCTION
Electroencephalography Neurofeedbacktraining (E-
NFT), also known as electroencephalography (EEG)
biofeedback, is a method wherein subjects learn to self-
regulate their own brain activity [1]. During E-NFT, the
subject’s brain waves are continuously measured with
EEG and instant positive or negative feedback in the
form of audio and/or video based on this activity is
provided to the subject [2]. E-NFT is not only used to
improve functions in healthy persons [3-7], but also to
treat different disorders, such as attention deficit
hyperactivity disorder (ADHD) and insomnia [8].
Children with ADHD have several inattentive and/or
hyperactivity/impulsivity (HI) symptoms, while
insomnia is characterized by difficulties with initiating
and maintaining sleep and by early-morning awakenings
[9]. In addition, both disorders are accompanied with
impairments in daily life functioning [9]
The E-NFT protocols used for the treatment of ADHD
and/or insomnia include amongst others theta/beta ratio
(TBR), slow cortical potential (SCP) and sensorimotor
rhythm (SMR) E-NFT [10]. These E-NFT protocols
are well-studied in children with ADHD and therefore
considered to be standard E-NFT protocols [11]. TBR
E-NFT is aimed to decrease the TBR; thus to increase
the power of beta waves over theta waves [10], which is
found to be decreased in children and adolescents with
ADHD [12, 13]. Notably, beta waves are found when a
person is alert, and theta waves when a person is sleepy
[8]. Furthermore, SCP E-NFT is used to improve the
direction of SCPs [8], which are associated with
increased attention [14, 15]. It has been shown that 36
sessions of combined TBR and SCP E-NFT in children
with ADHD decreased inattentive, HI and total ADHD
symptoms when compared to children with ADHD
after computerized attention skills training sessions [16].
Furthermore, children with ADHD showed significant
improvements in inattentive symptoms after receiving
30 sessions of SCP E-NFT as compared to the children
with ADHD that had underwent group sessions [17].
The overall ADHD symptoms were also improved
after 25 SCP neurofeedback sessions in children with
ADHD as compared to children with ADHD that were
on a waiting list (Heinrich et al., 2004). Improved
scores on a sustained attention task after 20 sessions
beta power enhancing E-NFT (short: beta E-NFT) was
found in healthy subjects as well, but only when the beta
waves were changed after E-NFT [18].
Another E-NFT protocol that is aimed to enhance the
SMR power across sensorimotor areas called SMR E-
NFT [8]. The sensorimotor area is a cortical area that
integrates sensory and motor information [19].
Improved inattention and impulsivity symptoms were
found in children with ADHD after 36 sessions of SMR
as well as TBR E-NFT [20]. SMR E-NFT in the
treatment of children with ADHD started because of its
beneficial effect on motor inhibition [21, 22]. In
addition, in a young epileptic patient sleep onset latency
was reduced after 12 sessions of SMR E-NFT [23].
Many years later, the effects of E-NFT were studied in
people with psychophysiological insomnia, which is a
type of insomnia caused by psychological and
physiological factors such as tension [24]. No sleep
improvements were found after sessions of SMR E-
NFT, electromyographic (EMG) biofeedback or
combined EMG biofeedback and theta power
enhancing E-NFT (short: theta E-NFT) as compared to
no feedback [25]. EMG biofeedback is, in contrast to E-
NFT, not based on the subject’s brain waves but on
their muscular tension, with the aim to reduce this
tension. The amount of SMR enhanced during SMR E-
NFT, however, correlated positively with sleep
improvements in this study. Also, baseline tension was
correlated negatively with sleep improvements for the
SMR E-NFT group, and positively with sleep
improvements for the EMG biofeedback group. In a
follow-up study people with psychophysiological
insomnia showed increased total time of sleep per night
and reduced sleep onset latency after six sessions of
EMG biofeedback and 26 sessions of either theta or
SMR E-NFT [26]. The number of awakenings were
decreased after theta E-NFT as well. As in line with the
previous study, baseline tension of the insomnia
patients correlated positively with sleep improvements
after theta E-NFT, and negatively with the sleep
improvements after SMR E-NFT. Because in the early
80’s the number of sessions needed to increase desired
EEG power was high and E-NFT equipment was
expensive, studies examining E-NFT effects were no
longer performed [26]. Due to technological
advantages, studies using E-NFT interventions were
continued decennia later [27]. One such technological
advantage is the introduction of E-NFT based on Z-
scores, which is the deviation of the subjects EEG
measured at multiple sites as compared to a normative
EEG database of healthy people [28]. Case studies in
people with various disorders such as autism spectrum
disorder indicated improved sleep pattern after Z-score
based E-NFT [28]. However, recent studies should be
evaluated to more substantially clarify the efficacy of E-
NFT for improving sleep and decreasing sleep
problems.
The efficacy of E-NFT in ADHD has been investigated
in a meta-analysis with controlled studies investigating E-
NFT and its effect in children with ADHD [29]. In this
study, large effect sizes were found for impulsivity and
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inattention and a medium effect size for hyperactivity,
therefore stating E-NFT as an efficacious and specific
treatment for ADHD. However, a lot of these
controlled studies showed important methodological
problems [30], such as the lack of a specific control
group [31, 32] or missing the randomization of group
assignment [20, 31]. The evidence of E-NFT for the
treatment of ADHD was therefore recently considered
insufficient [33]. A general effect of E-NFT on
attention, in healthy people as well, is also not
substantialized.
In summary, the clinical efficacy of E-NFT in the
treatment of ADHD and insomnia is not robust and
undebatable. This is also the case for the effects of E-
NFT on attention and sleep in healthy subjects.
Therefore, the aim of this literature review is to further
examine the efficacy of EEG-NFT on attention and
sleep in individuals with ADHD or sleeping problems
and in healthy individuals. First, the E-NFT effects on
ADHD symptoms in children are discussed. Second,
the E-NFT effects on attention in healthy children and
young adults are examined. Third, the E-NFT effects
on sleep in insomnia patients are discussed. Lastly, the
E-NFT effects on sleep in healthy individuals are
reviewed.
Neurofeedback effects on ADHD symptoms in
children: results from meta-analyses of randomized
controlled trials
In this section, the E-NFT effects on ADHD symptoms
in children with ADHD are discussed based on the
results of meta-analyses of randomized controlled trials
(RCTs). In these RCTs, the ADHD symptoms and
subscales of inattention and HI are measured before
and after the experimental E-NFT or control condition.
With respect to the control condition studies with
medication interventions as a control condition are
excluded. The change in symptoms after relative to
before E-NFT is used to calculate the E-NFT effects. In
the case of children as participants, symptoms are rated
by someone other than the subject itself, most often the
children’s parents and/or teachers [34]. In the meta-
analyses, a distinction between probably blinded (PB)
and probably unblinded (PU) raters are made. PB
raters, often the participant’s teachers [10], are likely
unaware of the participant’s condition because they are
not that much invested in the E-NFT, or are unaware of
the participant’s condition when it concerns a placebo-
controlled RCT [35]. In contrast, PU raters are
normally the participant’s parents [10]. They are closest
to the therapeutic setting and therefore often aware of
the participant’s condition [35]. The E-NFT effects in
children with ADHD on ADHD symptoms, based on
PU and PB raters, of all meta-analyses are summarized
in Table 1.
In 2016, a meta-analysis of 13 RCTs was performed by
Cortese et al. in children with ADHD that received E-
NFT as experimental condition. A small-to-moderate
but significant improvement on inattention, HI, and
total ADHD symptoms after E-NFT was found as
compared to the control condition when the scores of
the PU raters were used. When considering the PB
assessments, all improvements were no longer
significant. An additional analysis of RCTs that met the
standard E-NFT protocol criteria set up by Arns et al.
[36] (n=7), also found a significant decrease in
inattention, HI, and total ADHD symptoms rated by
PU assessors. The inattentive and total ADHD
symptoms were found to be decreased as well by the
RCTs with both standard E-NFT protocols and PB
assessments (n=3), while the hyperactivity symptoms
were not changed. These improvements were also
found, notably with larger effect sizes, after replicating
and updating this meta-analysis by including recent
RCTs (n=3) [37].
These results are in line with the findings of a recent
meta-analysis of RCTs using a standard protocol E-
NFT for the experimental condition in children with
ADHD [38]. When the RCTs using PU assessments
were analyzed (n=11), a decrease in inattentive and HI
symptoms was found after E-NFT as compared to the
control condition. When the RCTs with PB
assessments were used (n=9), a significant decrease of
inattentive symptoms, but no significant difference in
HI symptoms was found. The total ADHD symptoms
were not investigated in this study.
In the above cited meta-analysis of [39], a separate
analysis was performed in studies using active and
placebo control groups. In addition, studies with control
conditions resembling treatment as usual and waiting list
periods were excluded. The remaining RCTs had
control conditions including cognitive training, EMG
biofeedback and placebo-controlled E-NFT. With
respect to PU assessments, E-NFT was found to
improve the HI symptoms in the children with ADHD,
with a small effect size, but the inattention and total
ADHD symptoms were not different. Moreover, the
inattention, HI, and total ADHD symptoms were not
different when only the PB assessments were used.
Another meta-analysis showed different results when
using 5 RCTs with the same control conditions as
described in the meta-analysis above [40]. When
considering the PU assessments, improvements were
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found on inattention, HI, and total ADHD symptoms
after E-NFT as compared to the control condition.
When considering the PB assessments, the inattention
symptoms, but not HI and total ADHD symptoms,
were found to improve. This is in contrast with the
findings of Cortese et al. [39], who only found an
improvement in HI symptoms for the PU
measurements. This finding can be explained by the
exclusion of nonstandard E-NFT procedures and
measures of only PU measurements by Micoulaud-
Franchi et al. [40], which was not the case in the study
of Cortese et al. [39]. In addition, larger effect sizes for
all outcomes and smaller effect sizes for the PU
outcomes were found in the study of Micoulaud-
Franchi et al. [40] as compared to Cortese et al. [39].
Furthermore, the results of Micoulaud-Franchi et al.
[40] are in line with the results of Riesco-Matías et al.
[38], who also found significant improvements in
ADHD symptoms for the PU measurements, and in
inattentive scores for the PB measurements.
A quite recent meta-analysis included 10 RCTs that also
examined long-term effects of E-NFT on the ADHD
symptoms in children with ADHD [41]. The PU
measurements were used as the outcomes. A significant
improvement was found for both inattention and HI
symptoms after the neurofeedback sessions, as well as
after 2 to 12 months following the E-NFT, as compared
to the control conditions. Interestingly, the effect sizes
were increased at follow-up as compared to post E-NFT
for both subscales. When the E-NFT group was
analyzed apart from the control group, a medium effect
size of E-NFT was found after treatment, and a large
effect size of E-NFT at follow-up was found for
inattention symptoms. For HI symptoms, medium
effect sizes were found after E-NFT and at follow-up.
The results were the same when only standard E-NFTs
were considered.
A meta-analysis of studies on E-NFT efficacy in
children with ADHD, examined the experimental and
clinical factors influencing this efficacy [37]. For this
purpose, also non-controlled and non-randomized
studies were included. A total of 33 studies were
analyzed. The E-NFT effect on ADHD
symptomatology was found to be most dependent of
the amount of blindness of the raters, the total
treatment length and EEG quality. In addition, E-NFT
efficacy was higher when the EEG quality was higher,
and when the total treatment length was shorter. The
assessment of a PB rater did reduce the efficacy.
Importantly, they found that this reduced efficacy was
probably due to the notion that blinded raters scored
the ADHD symptoms significantly lower before E-
NFTs at baseline, instead of significantly higher after E-
NFT, as compared to PU raters. Also the influence of
amongst others ADHD severity at baseline, control
group presence and the type of reward in the E-NFT
protocol on the E-NFT efficacy in children with
ADHD could not be examined because of too many
missing and too heterogenous data points. The type of
E-NFT protocol used, TBR E-NFT, SMR E-NFT or
SCP E-NFT, did not seem to differentiate the E-NFT
outcome in children with ADHD.
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Table 1. Results of the meta-analyses of RCTs on the effect of E-NFT in children with ADHD on ADHD symptoms
based on PU and PB raters.
Meta-analysis
Studies analyzed
PU rater based effects after E-NFT
(number studies analyzed)
PB rater based effects
after E-NFT (number of
studies analyzed)
Cortese et al.
(2016 [39])
All RCTs
Inattention symptoms improved (n=11)
HI symptoms improved (n=10)
Total ADHD symptoms improved (n=13)
Inattention symptoms
unchanged (n=7)
HI symptoms unchanged
(n=7)
Total ADHD symptoms
unchanged (n=8)
Standard E-NFT
protocol RCTs
Inattention symptoms improved (n=5)
HI symptoms improved (n=5)
Total ADHD symptoms improved (n=7)
Inattention symptoms
improved (n=3)
HI symptoms unchanged
(n=3)
Total ADHD symptoms
improved (n=3)
RCTs with active
and placebo
control groups
Inattention symptoms unchanged (n=6)
HI symptoms improved (n=6)
Total ADHD symptoms unchanged (n=7)
Inattention symptoms
unchanged (n=5)
HI symptoms unchanged
(n=5)
Total ADHD symptoms
unchanged (n=6)
Bussalb et al.
(2019 [37])
All RCTs
Inattention symptoms improved (n=13)
HI symptoms improved (n=12)
Total ADHD symptoms improved (n=16)
Inattention symptoms
unchanged (n=8)
HI symptoms unchanged
(n=8)
Total ADHD symptoms
unchanged (n=9)
Standard E-NFT
protocol RCTs
Inattention symptoms improved (n=6)
HI symptoms improved (n=6)
Total ADHD symptoms improved (n=9)
Inattention symptoms
improved (n=4)
HI symptoms unaffected
(n=4)
Total ADHD symptoms
improved (n=4)
Riesco-Matías et
al. (2019 [38])
Standard E-NFT
protocol RCTs
Inattention symptoms improved (n=11)
HI symptoms improved (n=11)
Inattention symptoms
improved (n=9)
HI symptoms unchanged
(n=9)
Micoulaud-
Franchi et al.
(2014 [40])
Standard E-NFT
protocol RCTs
with active and
placebo control
groups
Inattention symptoms improved (n=5)
HI symptoms improved (n=5)
Total ADHD symptoms improved (n=5)
Inattention symptoms
improved (n=5)
HI symptoms unchanged
(n=5)
Total ADHD symptoms
unchanged (n=5)
van Doren et al.
(2019 [41])
RCTs with two to
12 months follow-
up data
Inattention symptoms improved (n=10)
HI symptoms improved (n=10)
After E-NFT, as well as follow-up
Note: ADHD = attention deficit hyperactivity disorder, HI = hyperactivity/impulsivity, E-NFT = EEG
neurofeedbacktraining, PB = probably blinded, PU = probably unblinded, RCT = randomized controlled trial
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The finding that the type of E-NFT protocol had no
significant effect on the ADHD symptoms in children
with ADHD was also in line with two other studies that
compared E-NFT protocols. In the first study, children
with ADHD were randomly assigned to a group
receiving 30 sessions TBR E-NFT (n=19) or 30 sessions
SCP E-NFT (n=19) [42]. In another study, 37 ADHD
patients were assigned to a group receiving TBR E-NFT
(n=10) or SMR E-NFT (n=27), for on average 29 and
31 sessions respectively [11]. In both studies significant
improvements were found in inattention and HI
symptoms over the course of the sessions. This effect
was not significantly different between the E-NFT
protocol, so not significant different between the TBR
as compared to the SCP protocol and between the
TBR as compared to the SMR protocol. This was true
for both the PB and PU measures.
Neurofeedback effects on attention in healthy children
and young adults
In this section, the E-NFT effects on attention and
impulsivity are reviewed in children and young adults
without ADHD. Different aspects of attention are
measured in the studies, which are sustained attention,
selective attention and attention control. Sustained
attention is the capacity to maintain focus and alertness
over time [43]. The focus on a specific target for
enhanced processing is called selective attention [43].
Lastly, attention control is the ability to regulate
responses, especially in conflict situations [44]. It must
be noted that sustained attention, selective attention and
attentional control overlap and often more attentional
processes are needed in attentional tasks.
An RCT in children without attentional problems could
not find an effect of TBR E-NFT on sustained and
selective attention [45]. The d2 test was used to
measure selective and sustained attention in 47 children
of 8 and 9 years. The children were randomly assigned
to an TBR E-NFT (n=24) and control group that did
not receive E-NFT (n=23). The d2 test was performed
before and after one week, wherein the TBR E-NFT
group received 10 sessions of TBR E-NFT. Children
with scores on the d2 test indicative for ADHD were
excluded from the study. After this week, a significant
improvement in processing speed, accuracy of
processing and total effectiveness on the test was found,
but this was found in both the TBR E-NFT and control
condition and appeared not to be different between the
groups, although effect sizes in the experimental group
were larger than in the control group.
When different attention tasks were used, a positive
effect of TBR E-NFT on selective attention was found
in healthy children [46]. Twenty-nine children of 10-13
years old were divided in a TBR E-NFT group (n=12)
and sham E-NFT group (n=15), wherein EEG was
measured but no feedback was provided. Selective
attention was measured before and after ten to 15
neurofeedback sessions in two weeks. TBR was
significantly decreased within the neurofeedback
sessions in the TBR E-NFT and not sham E-NFT
group. Furthermore, different aspects of selective
attention which were working efficiency measured with
Schulte’s tables and productivity of attention measured
with Bourdon’s correcture test was improved in the
experimental group only.
In healthy young adults, there seems to be a positive
effect on sustained attention after SMR and TBR E-
NFT, reflected by better performance after SMR E-
NFT and faster responses after TBR E-NFT [47]. In
this RCT, 25 students of 21 ± 2.24 (SD) year without
mental or neurological illness not using medication
were randomly assigned to a SMR E-NFT (n=9), beta
E-NFT (n=8) and behavioral training control group
(n=8). Additionally, theta and high beta power were
reduced during SMR and beta E-NFT as well. Notably,
CONCLUSION I
The meta-analyses provide evidence that
E-NFT treatment has a positive effect on
inattention and HI symptoms in children
with ADHD. This effect seems to last
over a longer period of time, with even a
better improvement for the inattention
symptoms after the ending of the E-NFT
treatment. This effect is more robust
when standard E-NFT protocols are used,
while the type of standard E-NFT
protocol seems not to differently affect
the outcomes. The improvement in
inattentive symptoms are found when the
PB as well as the PU measures are used.
The HI symptoms are found to be
improved when the PU measures are
used but not the PB. However, it is
thought that this difference is caused by an
underestimation of these symptoms by
PB raters. In addition, PB raters rate
these symptoms already low before the E-
NFT treatment, as compared to the more
proximal PU raters, therefore making
improvement less possible. As a
consequence, it is thought that E-NFT
treatment has a positive effect on both the
HI and inattention symptoms.
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theta waves are associated with being sleepy and high
beta waves with being hyperalert and anxious [8].
Sustained attention was measured with a continuous
performance task (CPT) and divided attention task
before and after ten sessions in ten weeks. While
baseline measures on the tasks were not different
between the groups before E-NFT, significant faster
reaction times on the CPT were found after beta E-
NFT as compared to the control group. Furthermore,
results on the divided attention task showed that
omission errors were reduced and hit to false rate ratios
were increased after SMR neurofeedback sessions as
compared to the control group.
Another study also found a decreased number of
omission errors and increased hit rates on a CPT in
young adults in the SMR E-NFT group only [48]. Thus,
this also suggests a positive effect of SMR E-NFT on
sustained attention and better performance. In this
single-blind RCT, 29 students of 20-28 year were
randomly assigned to one of three groups which
received SMR E-NFT (n=10) while inhibiting theta and
beta power, theta E-NFT in sensorimotor areas (n=9)
while inhibiting power of alpha and delta power, and a
Non-NFT control group (n=10). Notably, alpha waves
are associated with being relaxed, and delta waves with
being unaware [8]. Sustained attention was measured
with a CPT before and after 8 neurofeedback sessions
in 4 weeks. No differences on the task were found after
theta E-NFT. In addition, theta was not significantly
increased within the sessions of theta E-NFT, while
SMR was significantly increased within the sessions of
SMR E-NFT.
In a double-blind RCT using Z-based E-NFT instead of
standard E-NFT protocols, no effect of E-NFT on
sustained attention and impulsivity was found in young
adults (Logemann et al., 2010). Twenty-seven healthy
students that scored relatively high on impulsivity and
inattention questionnaires were randomly assigned to
individualized protocols based on Z-scores (n=14) and
sham E-NFT group (n=13). The sham E-NFT group
received E-NFT based on a simulated EEG signal. No
significant differences were found after 16
neurofeedback sessions in eight weeks on the reaction
time on a CPT measuring sustained attention. This was
also the case for the reaction time and false-alarm rate
on CPTs related to impulsivity.
In a single-blind RCT, school children aged 11 years
were randomly assigned to 10 sessions of SMR E-NFT
(n=9), 10 sessions of theta alpha ratio (TAR) E-NFT
(n=10) or to a non-treatment control group (n=11) [49].
During TAR, an increase in power of theta waves over
alpha waves and thus an increase in TAR is aimed [50].
Alpha waves are associated with being relaxed and with
being alert, and theta waves with being sleepy [8]. For
SMR E-NFT, it was also aimed to reduce theta and high
beta power. Within the sessions, significant excess SMR
over high beta power in the SMR E-NFT group and
increased TAR in the TAR E-NFT group was found.
Across neurofeedback sessions, no significant
differences in EEG power was found. Commission
errors in a CPT, reflecting impulsivity, was significantly
reduced after TAR as compared to the control group.
No differences were found on the CPT after SMR E-
NFT. This was in line with the results of Egner &
Gruzelier [47], who used the same task and also did not
find significant differences after SMR. Thus, TAR E-
NFT seems to have a positive effect on impulsivity in
children.
A positive effect of theta E-NFT in frontomedial brain
areas on attention control was found in heathy young
adults [51]. In this single-blind RCT, healthy young
adults of 21-25 year old who were free from
neurological, psychological and mood disorders were
randomly assigned to a theta E-NFT condition (n=8)
and sham E-NFT control condition (n=8). Sham E-
NFT was aimed to enhance random bins in frequencies
ranging from alpha to high beta waves. An attention
network task was performed before and after 12
neurofeedback sessions in four weeks. Theta power, as
well as executive attention or attention control, was
enhanced after the 12 theta neurofeedback sessions as
compared to the 12 sham neurofeedback sessions.
CONCLUSION II
The majority of findings provide evidence
of positive effects of standard E-NFT
protocols on attention and impulsivity in
children and young adults without
ADHD. In addition, sustained and
selective attention might be improved by
TBR E-NFT in these children and young
adults. SMR E-NFT seems to have a
positive effect on sustained attention in
these young adults. More specifically,
better performance after SMR E-NFT
and faster responses after TBR E-NFT
were found. Impulsivity might be
improved by TAR E-NFT in children,
and attention control after theta E-NFT in
young adults.
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Neurofeedback effects on sleep in insomnia patients
In this section, studies examining the E-NFT effects on
sleep in insomnia patients are discussed, with a focus on
SMR E-NFT. As can be seen in the preceding sections
as well, SMR E-NFT is often accompanied with the
reduction of high beta and theta power at these areas as
well. In addition, high beta waves are associated with
hyperalertness and anxiety [8, 52]. Theta waves are
associated with being sleepy, and only delta waves are
lower in frequency, which are associated with being
unaware and asleep [8]. Furthermore, to measure sleep
polysomnography (PSG) during sleep or questionnaires
are used in these studies. These measurements are
done before and after the experimental or control
condition. Also, sleep diaries that are kept by the
subjects throughout the experiment are used to
calculate specific sleep parameters. The change in these
sleep variables in insomnia patients after as compared
to before E-NFTs are discussed below. The results of
the studies in this section are summarized in Table 2.
In a single-blind RCT, 17 insomnia patients were
randomly assigned to SMR E-NFT (n=9) and EMG
biofeedback control group (n=8) [2]. Medication-free
patients with primary insomnia symptoms, assessed with
questionnaires and a semi-structured psychiatric
interview, for a minimum of three times a week for at
least six months were included. Besides increasing SMR
power, E-NFT was administered to reduce theta and
high beta power in sensorimotor areas. Twenty E-NFT
or EMG biofeedback sessions were performed at home
with a portable device. As a consequence, potential
biases of informed clinicians during E-NFT were
excluded as well, which is also the case for double-blind
studies. Sleep was measured objectively using PSG and
subjectively using sleep diaries. Insomnia patients
without objective sleep problems were excluded from
the study. The baseline somatic arousal and baseline
tension level was not higher in the insomnia patients of
each group as compared to a group of 12 healthy
individuals. In the E-NFT relative to the control group,
an increase in objective total sleep time was observed, as
well as an improvement in subjective sleep variables,
which were the total sleep time, wake after sleep onset
and sleep onset latency. In both the E-NFT and
biofeedback group, the sessions shortened the objective
wake after sleep onset and sleep onset latency and
increased the total rapid eye movement (REM) sleep
and subjective sleep efficiency. There was no
association between the baseline EMG tension level
and sleep outcome after each feedback session found in
the insomnia patients. This suggests that E-NFT aimed
to enhance SMR and to reduce theta and high beta
power in sensorimotor areas and EMG biofeedback
both have a positive effect on the objective sleep onset
latency, wake after sleep onset, amount of REM sleep
and subjective sleep efficiency in insomnia patients.
Furthermore, objective and subjective total sleep time
and subjective sleep onset latency and wake after sleep
onset was found only after SMR E-NFT.
An improvement in subjective total sleep time,
insomnia severity and sleep quality was observed in
insomnia patients after Z-score based E-NFT protocols
[27]. In this single-blind pilot-study, eight medication-
free patients with a Diagnostic and Statistical Manual of
Mental Disorders (DSM) IV primary insomnia
diagnosis and poor subjective sleep quality based on a
questionnaire were randomly assigned to an
individualized E-NFT protocol (n=5) or SMR E-NFT
protocol that was also aimed to reduce theta and high
beta power at sensorimotor areas (n=3). Z-scores were
used to continuously provide feedback and to
normalize amplitude and connectivity at variables at
multiple sites for the individualized E-NFT protocol
and at sensorimotor areas for the SMR E-NFT
protocol. Besides sleep variables measured with sleep
diaries, questionnaires were administered as well. Based
on the data of these questionnaires, the sleep quality,
sleep efficiency, insomnia severity and quality of life was
improved after E-NFT as well. All these improvements
were found when using the data of both conditions, and
thus independent of E-NFT protocol. After E-NFT, the
beta and delta waves were significantly normalized, and
a trend towards normalized high beta waves was also
found. It must be noted, however, that in this study a
small sample and no control group was present.
A subsequent RCT in 40 insomnia patients was
therefore performed, using the same Z-based SMR E-
NFT protocol as Hammer et al. [27] as experimental E-
NFT condition [53]. Patients that met the DSM-5
criteria for insomnia disorder, had poor subjective sleep
quality and did not take medication for their sleep
complaints were included. These participants were
randomly assigned to a group receiving 20 sessions of
SMR E-NFT (n=10), nine sessions of cognitive
behavioral therapy (CBT) (n=10) or no treatment as a
control group (n=20). In this study, significant enhanced
SMR and reduced high beta power in sensorimotor
areas was found within the neurofeedback sessions
across the sessions. Sleep quality and insomnia severity
was measured with questionnaires before and after
finishing the treatments in three months. Both SMR E-
NFT and CBT improved the subjective sleep quality, as
compared to the control condition. This improvement
related to the control group was significantly higher for
the SMR E-NFT group as compared to the CBT group.
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Furthermore, a significant reduction in insomnia
severity was found after E-NFT as compared to the
CBT and control condition. Thus, SMR E-NFT has a
positive effect on insomnia severity and sleep quality in
insomnia patients, and was even more effective than
common treatments for insomnia. The control group in
this study, however, did not receive any treatment and
thus did not control for any unspecific effects such as
the participant’s expectation.
Another single-blind RCT used sham E-NFT as a
placebo-controlled condition in insomnia patients [54].
During sham E-NFT, five random frequency bands in
the beta range except for SMR frequencies were used as
rewarded frequency bands. The authors found that
successful SMR but also unwanted high beta E-NFT in
sensorimotor areas improved the objective amount of
awakenings and slow wave sleep (SWS) and possibly
the subjective sleep quality in insomnia patients. In
addition, 24 participants with primary insomnia
received ten SMR neurofeedback sessions as well as
five sham neurofeedback sessions in a counterbalanced
manner. The research diagnostic criteria for primary
insomnia [55], with insomnia symptoms occurring at
least three times a week, and the DSM-III-R criteria for
sleep disorders was used to determine primary
insomnia. Poor subjective sleep quality based on sleep
diaries and abstinence of medication throughout the
experiment was also needed. Sleep was measured using
PSG, sleep diaries and questionnaires. In the
sensorimotor areas, SMR power was significantly
enhanced after SMR E-NFT as compared to sham E-
NFT, as well as high beta power. After the SMR E-NFT
as compared to sham neurofeedback sessions,
improvements in PSG measurements were found.
These improvements were a reduction of number of
awakenings and an increase of SWS. No significant
difference in other PSG measures were found such as
the total sleep time, waking after sleep onset, sleep
onset latency, sleep efficiency, time in bed and amount
of sleep stages other than SWS. These were also not
found for sleep measured based on the sleep diaries of
the subjects, including the total sleep time, sleep onset
latency and sleep efficiency. Furthermore, the physical
quality of life, assessing domains such as energy and
fatigue, and sleep quality, both measured with
questionnaires, was significantly improved after E-NFT.
However, for the physical quality of life this effect was
found for both SMR and sham E-NFT, while it was not
studied whether improvement in subjective sleep quality
was also independent of E-NFT protocol. Furthermore,
more social support was experienced by the subjects
when they were in the experimental as compared to the
control condition
The previous study was therefore replicated in 25
medication-free patients that met the research criteria
for primary insomnia [55], but included some changes
to eliminate unspecific effects such as social support
[56]. First of all, clinicians were not informed of the
condition of the subjects, making it a double-blind
RCT. Also, 12 sessions of SMR E-NFT as well as sham
E-NFT were used to increase the specificity of the
control group. Furthermore, insomnia patients without
objective sleep problems were excluded. No sleep
improvements were found after the SMR as compared
to sham neurofeedback sessions. Only a significant
improvement after both SMR and sham E-NFT was
found on sleep quality and physical quality of life,
irrespective of type of E-NFT, which is in line with the
results of Schabus et al. [54]. No difference after E-
NFT was found for other sleep parameters measured
with PSG and questionnaires. Also no relationship
between more relaxed and less tense insomnia patients
and better objective sleep quality after specifically SMR
E-NFT was found. Lastly, SMR power was enhanced
within the neurofeedback sessions across all 12
sessions, but was not higher after E-NFT as compared
to before E-NFT as in contrast to Schabus et al. [54].
Absence of increased SMR power after SMR E-NFT
was also found in healthy young adults that received the
same E-NFT protocol, and is therefore probably not
due to learning impairments that can be found in
insomnia patients because of their disease. These
results suggest that improved subjective sleep quality
and physical quality of life in insomnia patients is rather
due to unspecific E-NFT effects such as social support,
motivation and expectation, because they are not
related to the trained frequency after E-NFT.
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Table 2. Results of the studies on the effect of SMR E-NFT in insomnia patients on different sleep variables.
Study
Experimen
tal group
(amount
sessions)
Contr
ol
group
(amo
unt
sessi
ons)
Sleep variable (measurement
method) /
if available: EEG data
Result
Cortoos
et al.
(2010
[2])
SMR E-
NFT,
inhibiting
theta and
high beta
(20)
EMG
biofe
edbac
k (20)
Total sleep time (PSG+S)
Sleep onset latency (S)
Wake after sleep onset (S)
Higher improvement after sessions for
experimental as compared to control group
Sleep onset latency (PSG)
Wake after sleep onset (PSG)
REM sleep (PSG)
Sleep efficiency (S)
Improved after sessions, for both the
experimental and control group
Hammer
et al.
(2011
[27])
SMR E-
NFT,
inhibiting
theta and
high beta,
Z-score
based (13)
Indivi
dualiz
ed Z-
based
E-NFT
(13)
Beta and delta power
Reduced after E-NFT sessions in
experimental group
Total sleep time (S)
Sleep quality (Q)
Sleep efficiency (Q)
Insomnia severity (Q)
Quality of life (Q)
Improved after E-NFT sessions, for both
groups combined
Wake after sleep onset (S)
No significant change after E-NFT sessions in
both groups
Basiri et
al. (2017
[53])
SMR E-
NFT,
inhibiting
theta and
high beta,
Z-score
based (20)
No
treat
ment
&
CBT
(9)
Insomnia severity (Q)
Improved after E-NFT sessions, as compared
to control and CBT group
Sleep quality (Q)
Improved after E-NFT and CBT sessions, as
compared to control group, with higher
improvement for E-NFT group as compared
to CBT group
Schabus
et al.
(2014
[54])
SMR E-NFT
(10)
Sham
E-NFT
(5)
SMR and high beta power
Enhanced after E-NFT sessions in
experimental group
Number awakenings (PSG)
SWS duration (PSG)
Higher improvement after E-NFT sessions
for experimental as compared to control
condition
Sleep quality (Q)
Physical quality of life (Q)
Improved after E-NFT sessions, for both the
experimental as control condition
Total sleep time (PSG+S)
Sleep onset latency (PSG+S)
Wake after sleep onset (PSG)
Sleep efficiency (PSG+S)
Time in bed (PSG)
Duration sleep stages other than
SWS (PSG)
No significant change after E-NFT sessions in
both groups
Schabus
et al.
(2017
[56])
SMR E-NFT
(12)
Sham
E-NFT
(12)
EEG frequency bins, including
SMR power
No significant change after E-NFT sessions in
both groups
Sleep quality (Q)
Physical quality of life (Q)
Improved after E-NFT sessions, for both the
experimental as control condition
See variables of Schabus et al.
(2014)
No significant change after E-NFT sessions in
both groups
Note: CBT = cognitive behavioral therapy, EEG = electroencephalography, EMG = electromyography, E-NFT =
EEG neurofeedbacktraining, PSG = polysomnography, Q = questionnaire, S = sleep diary, SMR = sensorimotor
rhythm
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Neurofeedback effects on sleep in healthy individuals
In this paragraph, the E-NFT effects on sleep in healthy
individuals ae reviewed. First, tiredness during E-NFT
and then the effect of sleep after E-NFT are discussed.
Furthermore, the above discussed SMR E-NFT
technique as well as TAR E-NFT are emphasized. It
should be again noted that theta waves are present when
someone is sleepy, and alpha when someone is relaxed
and alert [8]. While SMR E-NFT is characterized by
visual or audiovisual feedback, in the studies below
TAR E-NFT was provided by audio feedback only, and
an eyes-closed state was required by the participants.
During E-NFT, tiredness was found to be increased
after SMR and TBR E-NFT in healthy individuals [50].
Ten neurofeedback sessions were performed by 22
healthy students free of mental or neurological illness
who did not take medication. In each session, SMR and
beta E-NFT was given to the subjects in a
counterbalanced order. High beta as well as theta power
were reduced. Tiredness and tension were measured
with questionnaires before and after each protocol.
Tiredness was increased after the E-NFT protocols,
independent of the type of protocol. Tension was not
changed after SMR or beta E-NFT.
Besides tiredness, also tension was found to be
increased during E-NFT in healthy individuals after
TAR or sham E-NFT, irrespective of type of E-NFT
[57]. In this RCT, 18 healthy students were randomly
assigned to an experimental (n=9) and sham E-NFT
group (n=9). Five neurofeedback sessions were
performed in total, and tiredness and tension was
measured before and after each session. The
experimental E-NFT consisted of TAR E-NFT, while
the feedback of a random session was played during
sham E-NFT. While a significant increase was found
within the sessions for the TAR as compared to the
sham E-NFT group, no significant differences were
found across sessions for both groups. Tiredness was
increased and tension decreased after each E-NFT
session, which was not dependent on experimental or
sham E-NFT.
A positive effect of TAR E-NFT on sleep time and
sleep architecture during the E-NFT was found in
healthy individuals [58]. Forty mentally and somatically
healthy young subjects were divided into a group
receiving TAR E-NFT (n=20) or sham E-NFT (n=20).
Sham E-NFT consisted of feedback of random training
units from previous sessions. Ten neurofeedback
sessions were completed by the subjects instructions to
not fall asleep during the training were given. Objective
sleep was measured during these sessions using PSG
data. The TAR was significantly higher for both groups
within the sessions, while changes in TAR across
sessions were not noted. In total, 38 participants fell
asleep at least once during the neurofeedback sessions.
On average, all participants were asleep at one third of
the neurofeedback sessions. While both groups showed
the same amount of subjective sleepiness before the
training, more stage 1 non-REM sleep and less time
awake was observed during TAR E-NFT as compared
to sham E-NFT.
Also, a positive effect of TAR across TAR
neurofeedback sessions on sleep onset latency was
found in healthy individuals [59]. Thirty-five young
healthy participants that did not use medication listened
to relaxation music while TAR E-NFT was provided in
the experimental condition or no feedback was given as
a control condition. After eight sessions, TAR
enhancement was found in the TAR group as
CONCLUSION III
The above reviewed literature indicate
objective improvements in total sleep
time, sleep onset latency, amount of
awakening and SWS in insomnia patients
after SMR E-NFT, and subjective
improvements in insomnia severity, sleep
efficiency, sleep quality and quality of life.
Improvements of subjective sleep quality
and physical quality of life in insomnia
patients are probably rather due to
unspecific E-NFT effects and not to the
specific trained frequencies. In contrast,
objective sleep improvements in the
amount of awakening and SWS are found
after successful enhancement of SMR
after SMR E-NFT. Other improvements
might not become significant because
high beta was not reduced during SMR E-
NFT, which is normally seen, and this
resulted in elevated high beta power. In
addition, other waves such as high beta
and delta might also be of importance for
SMR E-NFT efficacy on sleep in
insomnia patients. In most studies,
unfortunately, the change in EEG after as
compared to before treatment was not
measured or noted. The improved
objective sleep improvements, however,
might also be related to unspecific effects
such as social support.
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compared to control group. In addition, successful
TAR enhancement was associated with the transition
from awake to sleep states, which was verified with
measures of thumb and index finger pressure. Based on
these results, it was concluded that the sleep onset
latency based on the TAR was significantly reduced
after TAR E-NFT as compared to the control group.
No effects after E-NFTs were found in healthy
individuals wherein SMR was not successfully trained
[60]. In this study, sleep was examined in 11 students
free of mental or physical illnesses, mood disorders and
sleep disturbances, that received sigma E-NFT and
sham E-NFT in a counterbalanced design. During
sigma E-NFT, the SMR was trained, as well as the
upper alpha wave frequency band, which is related to
optimizing cognitive performance [8]. During sham E-
NFT, random feedback was given. Before and after
four training blocks of E-NFT, sleep architecture was
measured, which depicts the amount of time spend in
each sleep stage, with PSG. Furthermore, subjective
sleep such as the total sleep time and wake after sleep
onset was measured with sleep diaries. No significant
changes were found on objective and subjective sleep
after sigma or sham E-NFT. In addition, the four 10
min blocks of E-NFT failed to significantly enhance
SMR or other frequency bands.
Results of a single-blind RCT indicated a positive effect
of successfully trained SMR after SMR E-NFT on sleep
onset latency in healthy individuals [61]. Twenty-seven
young subjects free of mood disorders, intelligence or
learning problems and sleep disturbances were
randomly assigned to a group receiving ten sessions of
SMR E-NFT (n=16) or sham E-NFT (n=10). Sham E-
NFT consisted of random frequency bins trained in
each session. Objective sleep measures were performed
using polygraphic sleep recordings during a 90 min nap
before and after the ten neurofeedback sessions. In
contrast to Berner et al. [60], a significant SMR
enhancement and a shorter sleep onset latency was
found after the neurofeedback sessions in the SMR E-
NFT group only. Also, a trend of increased total sleep
time and more SWS was found after SMR and not after
sham E-NFT.
DISCUSSION
The aim of this literature review was to examine the
efficacy of EEG-NFT on attention and sleep in
individuals with ADHD or insomnia disorders as well
as in individuals without these problems . Meta-analyses
provide evidence that standard E-NFT protocols which
are TBR, SMR and SCP E-NFT, have a positive long-
lasting effect on the inattention and HI symptoms in
children with ADHD. In healthy children and young
adults, TBR seems to improve sustained and selective
attention, SMR sustained attention, TAR E-NFT
impulsivity and theta E-NFT attention control. There
also seems to be a positive effect of SMR and TAR E-
NFT on the objective and subjective sleep onset
latency, and an unspecific E-NFT effect on tiredness
and tension in healthy individuals. Objective and
subjective sleep improvements are found in insomnia
patients after SMR E-NFT as well, with it being argued
that the subjective sleep improvements likely depend on
unspecific E-NFT effects. Also, reduced high beta and
delta power after SMR E-NFT might be important for
SMR E-NFT efficacy in sleep.
Taken together, EEG E-NFT seems to have a positive
effect on attention and impulsivity in subjects with
ADHD and healthy young people. In addition, sleep
improvements in insomnia patients might rely on the E-
NFT protocol used, the amount of impaired sleep
CONCLUSION IV
Neurofeedback seems to increase tiredness
and decrease tension in healthy individuals
during the application of E-NFT. In the case
of eye-closed TAR neurofeedback sessions,
but possibly also in other experimental
neurofeedback sessions, this effect is rather
due to unspecific effects because it is also
found in the nonexperimental E-NFT
condition. In addition, successful training of
TAR across neurofeedback sessions
shortened the sleep onset latency and
seemed also to decrease awake times and to
increase the amount stage 1 non-REM sleep
observed during the training. A shortened
sleep onset latency is also observed after
SMR neurofeedback sessions, but only when
SMR is successfully trained across these
neurofeedback sessions. Training of TAR
and SMR across neurofeedback sessions
seems to be more successful when more
training sessions are applied.
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quality of the insomnia patient or be related to
unspecific E-NFT effects. Sleep improvements in
healthy people can also be found after E-NFT, and
direct unspecific E-NFT effects on tiredness.
For attention, standard E-NFT protocols seem to be
important for the efficacy in healthy young people and
children with ADHD. In healthy young people,
enhanced SMR and beta power through SMR and TBR
E-NFT have a positive effect on attention, while
enhanced theta power through TAR and theta E-NFT
have a positive effect on impulsivity and attention
control. In children with ADHD, a positive effect of
SMR, TBR and SCP E-NFT is found on both
inattention and HI symptoms, while it might be
expected that only attentional symptoms might be
reduced because of enhanced SMR and beta but not
necessary theta power. However, differential effects of
E-NFT in ADHD patients have been found as well.
First of all, the long-lasting effects of E-NFT after the
end of the treatment was higher for the inattention
symptoms. Also, only the effect on HI symptoms was
dependent on the amount of blinding in the studies. In
addition, efficacy of E-NFT to reduce HI symptoms
was no longer found when blinded raters were
considered. It is therefore possible that in children with
ADHD, E-NFT protocols aimed to enhance SMR and
beta power can improve the inattentive symptoms, and
those aimed to enhance theta power to improve HI
symptoms, as in line with the findings in healthy young
people. However, that HI is not always reduced based
on blinded raters can be accounted to an
underestimation of these symptoms by these raters.
Therefore, SMR and TBR E-NFT might reduce
inattention in healthy young people and both
inattention and HI in children with ADHD.
For sleep, standard and Z-score based SMR E-NFT
protocols were used. In healthy individuals, more
tiredness and less tension are found that are not
explained by the trained frequency but is rather due to
the E-NFT protocol wherein the subjects had to close
their eyes and were instructed to relax. Also in SMR
and TBR E-NFT that requires an active state, increased
tiredness was found after each E-NFT session.
Unspecific training effects in SMR and TBR E-NFT
would rather include concentration, motivation and
expectation. As there was no specific control group,
tiredness as a results of SMR and TBR E-NFT is not
necessarily indicated because of unspecific training
effects. However, also in insomnia patients, subjective
sleep improvements were assumed to be improved by
unspecific E-NFT effects of SMR E-NFT, because they
did not depend on the trained frequency during E-
NFT. This is not necessarily true for objective sleep,
which was increased after enhanced SMR and was
unaltered when SMR enhancement was not successful.
In addition, healthy individuals also showed a decreased
sleep onset latency after successful SMR enhancement
after SMR E-NFT. Thus, it is speculated that in both
healthy individuals and insomnia patients,
nonexperimental relaxation and possibly also activating
E-NFT procedures can have a positive effect on
tiredness and give rise to some subjective sleep
improvements. However, SMR enhancement after
SMR E-NFT can improve objective sleep in healthy
individuals and therefore improve the insomnia
symptomatology even more in patients, therefore
making it an efficacious treatment for insomnia.
The efficacy of standard E-NFT protocols for the
treatment of ADHD is in line with previous studies that
found improved inattention and HI symptoms in
children with ADHD after TBR and SCP E-NFT [16,
31, 32] and after SMR and TBR E-NFT [20]. These
positive effects on attention after TBR and SMR E-
NFT is also found in healthy young people [46-48].
Furthermore, faster reaction time on a sustained
attention task was found in healthy young adults after
TBR E-NFT as compared to the control group [47].
This is also in line with earlier research, that found
faster reaction times and better scores on a sustained
attention task after beta E-NFT [18]. One already
mentioned different effect between children with
ADHD and young people after E-NFT is that
concerning impulsivity. Lower impulsivity on a
sustained attention task was found after SMR and TBR
E-NFT in children with ADHD [20], but this was not
found in healthy young adults [47, 48]. This reduction
in impulsivity on the same task used by Fuchs et al. [20]
was found in school children without ADHD after
TAR E-NFT [49]. It is possible that different tasks must
be used in healthy individuals to find an effect on
impulsivity. Of course, it is also possible that only in
children with ADHD the standard protocols have an
effect on impulsivity besides attention as well. In healthy
individuals, reduced impulsive responses might then be
realized rather by TAR relaxation E-NFT [49].
The effects on sleep in healthy people were not
investigated in the previous century. In an epilepsy
patient, however, reduced sleep onset latency was found
after SMR E-NFT [23], but only when the SMR was
successfully enhanced. Improved sleep onset latency
after SMR E-NFT was also found in a RCT with
healthy individuals [61], but again this was not true
when the SMR was not successfully trained [60]. The
positive correlation of baseline tension of insomnia
patients with the sleep improvements after theta E-NFT
[26], can be explained by the observed effect of theta E-
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NFT in healthy individuals on reducing tension and
increasing tiredness after each E-NFT session [57],
increasing time asleep during the sessions [58] and
reducing sleep onset latency across the sessions [59].
The reduced sleep onset latency after theta E-NFT is
implied and not an objective measure [59]. In insomnia
patients, however, no change in sleep onset latency was
found after theta E-NFT, while it did improve the
number of awakenings [26]. After SMR E-NFT,
improvements were found in insomnia patients on total
sleep time [2, 27] and sleep onset latency [2] based on
sleep diaries. This was also found in the study of Hauri
et al. [26]. Objective sleep improvements on total sleep
time after SMR E-NFT were found in insomnia patients
as well for total sleep time [2] and the amount of SWS
and awakenings [54]. Another study did not find any
objective sleep improvements after SMR E-NFT [56].
No objective sleep improvements in insomnia patients
after SMR E-NFT was also found in the previous
studies [25, 26]. In addition, the negative correlation
between the baseline tension of the insomnia patients
and the sleep improvements that were found after SMR
E-NFT [25, 26], could not be found in later studies [2,
56]. One difference is that in the studies of Hauri [25]
and Hauri et al. [26], the subjects are
psychophysiological insomnia patients that experience
cognitive and physical arousal before sleep, such as
tension, while later studies were not specifically focused
on this subtype of insomnia. In addition, the baseline
tension levels of the insomnia patients were not
significantly higher than of healthy controls in the study
that did experience sleep improvements after SMR E-
NFT [2]. This is in line with the association between
less tense insomnia patients and better outcomes after
SMR E-NFT [25, 26]. Other studies did not measure or
note these baseline tension levels of the subjects. Also,
SMR and other EEG changes after SMR E-NFT were
not checked in the study of Hauri et al. [26], and it is
argued earlier in this discussion that EEG changes other
than SMR might be important for the SMR E-NFT
efficacy in insomnia patients.
Although the exact working mechanisms of E-NFT are
not yet clear, some suggestions are made based on this
review. Overall disturbances in TBR in children with
ADHD are normalized by TBR E-NFT [12, 13], and
provide an increased attentional over sleepy states [8].
Besides an increase in overall attention, it provides
improvement in selective attention, also in healthy
individuals. Selective attention is thought to be
important for inhibitory control which is related to
impulsivity [62], which might explain why reduced
impulsivity after TBR E-NFT is found in children
showing problems with impulsivity due to ADHD.
SMR E-NFT rather decreases motor hyperactivity and
impulsivity [21, 22]. Therefore, less motor information
has to be processed in sensorimotor areas, and more
information related to executive functions such as
attention is provided [63]. This may give rise to
improved sustained attention in children with ADHD,
but not in healthy children that do not exhibit this
hyperactivity. Increased motor inhibition after SMR E-
NFT is also beneficial for sleep in healthy individuals
and insomnia patients. SMR E-NFT also reduces high
beta, which is elevated in insomnia patients and is
associated with more negative perception of sleep
quality [64]. Excessive low frequency delta and theta
waves in insomnia patients might be related to being
exhausted by the disease [27], and reduced power might
improve mental or physical state as well. When
increased tension is found in the insomnia patients that
is related to negative thoughts about sleep [24], theta E-
NFT might be more appropriate. Theta E-NFT seems
to decrease tension, but may also provide a more rapid
transition into sleep, also in healthy individuals.
Decreased tension and a more relaxed state after theta
E-NFT might also increase the cognitive load in healthy
individuals that is needed for increased inhibitory
control.
Unfortunately, the amount of studies on E-NFT with a
good methodology, which are double-blind RCTs, are
also in recent years rather scarce. Moreover, only one
double-blind RCT has been performed on E-NFT
effects on sleep in insomnia patients. It becomes clear,
however, that especially in EEG E-NFT studies, a good
methodological design is harder to achieve and also
debatable. First, for a double-blind design a sham E-
NFT condition is needed. In this sham E-NFT
condition, the operant conditioning principle must still
be respected [36]. This means that random frequency
bins must be trained, without it providing significantly
enhanced EEG power in certain frequency waves.
Studies have shown, however, that this is possible. It is
also mentioned that it is better to not use sham E-NFT
as a control condition, because the so-called unspecific
E-NFT effects such as motivation and control beliefs
are characteristic for E-NFT and its efficacy [65]. It is a
scientific consensus, however, for a treatment to be
efficacious if it shows improved effects relative to a
sham condition. This seems to be the case for ADHD,
but unfortunately still today needs to be investigated for
insomnia. Also, sleep improvements after E-NFT in
patients other than with insomnia and attention
improvements after E-NFT in patients other than
ADHD must be investigated. In addition, after TBR E-
NFT improvements in sustained attention and response
inhibition were also found in children with autism
spectrum disorder [66], and improvements in sustained,
selective and inhibitory control in children with
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dyslexia [67]. In migraine patients, more than the half
of the patients showed improved sleep after Z-score
based E-NFT in patients with migraine [68].
Furthermore, after SMR and TBR E-NFT,
improvements in sleep quality were found in adults with
ADHD [11] and less sleep problems in children with
ADHD [69]. Although the study of van Dongen-
Boomsma et al. [69] was a double-blind RCT, the
applied experimental E-NFT protocol is criticized as it
probably prevented the desired frequency bands to be
learned by the participants [36]. The successful training
of the experimental waves after E-NFT is thought to be
important for its effect on sleep as well as attention in
healthy individuals as well as in ADHD and in
insomnia patients. The EEG changes after E-NFT are,
unfortunately, often not recorded. Future research
should also focus on the effects of E-NFT on attention
in patients other than those with ADHD, and the E-
NFT effects on sleep in insomnia patients as well as in
patients with other disorders. Furthermore, it should be
investigated why some people do and some people do
not successfully train specific brainwaves following E-
NFT, to increase the effects on behavior in healthy
people or to more successfully reduce symptoms in
patients.
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ABBREVIATIONS
ADHD = attention deficit hyperactivity disorder
Beta E-NFT = beta power enhancing E-NFT
CBT = cognitive behavioral therapy
CPT = continuous performance task
DSM = diagnostic and statistical manual of mental disorders
EEG = electroencephalography
EMG = electromyography
E-NFT = electroencephalography neurofeedbacktraining
HI = hyperactivity/impulsivity
NF = neurofeedback
PB = probably blinded
PSG = polysomnography
PU = probably unblinded
q = questionnaire
RCT = randomized controlled trial
REM = rapid eye movement
S = sleep diary
SCP = slow cortical potential
SMR = sensorimotor rhythm
SWS = slow wave sleep
TAR = theta/alpha ratio
TBR = theta/beta ratio
Theta E-NFT = theta power enhancing E-NFT
