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Electroencephalogram Neurofeedback: Application in ADHD and Epilepsy

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Electroencephalogram Neurofeedback: Application in ADHD and Epilepsy

Abstract

The use of electroencephalogram neurofeedback has been studied in a number of psychiatric disorders, especially for the treatment of attention-deficit/hyperactivity disorder (ADHD). However, many clinicians are not aware of this treatment and the level of evidence supporting its use. In this article, we review the evidence for the efficacy of neurofeedback in several psychiatric disorders and also discuss the specific neurofeedback protocols that have been found effective in the treatment of ADHD, such as slow cortical potential, theta/beta ratio, and sensorimotor rhythm neurofeedback.
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CME Article
Electroencephalogram Neurofeedback:
Application in ADHD and Epilepsy
ABSTRACT
The use of electroencephalogram
neurofeedback has been studied in a
number of psychiatric disorders, espe-
cially for the treatment of attention-
decit/hyperactivity disorder (ADHD).
However, many clinicians are not aware
of this treatment and the level of evi-
dence supporting its use. In this article,
we review the evidence for the ecacy
of neurofeedback in several psychiat-
ric disorders and also discuss the spe-
cic neurofeedback protocols that have
been found eective in the treatment
of ADHD, such as slow cortical poten-
tial, theta/beta ratio, and sensorimotor
rhythm neurofeedback. [Psychiatr Ann.
2016;46(10):594-600.]
Neurofeedback is a behavioral
therapy technique used to teach
or improve self-regulation of
brain activity. It is a variant of elec-
troencephalogram (EEG) biofeedback,
which aims to help the patient acquire
self-regulation over certain brain activ-
ity patterns based on operant condition-
ing principles.1,2 The EEG shows elec-
trical activity of the cerebral cortex and
reflects the summation of synchronized
excitatory and inhibitory postsynaptic
potentials of apical cortical pyramidal
cells. The roots of neurofeedback can
be traced back to the early 1930s, when
the first observations were made that
the EEG alpha-blocking response could
be classically conditioned.3,4 EEG was
more systematically investigated and
its efficacy confirmed in the 1940s.5,6
These early studies clearly demonstrat-
ed that conditioning principles can be
applied to EEG parameters such as the
alpha-blocking response.
The first successful application of
EEG conditioning with clinical ef-
fects, namely anticonvulsant effects,
was reported in 1968 by Wyrwicka and
Kerstin Mayer, PhD, is the Head, Education EMEA (Europe, Middle East, and Africa),
neuroCare Group; and a Postdoctoral Researcher, Institute for Medical Psychology and Behav-
ioral Neurobiology, University of Tübingen. Martijn Arns, PhD, is the Chief Scientific Officer, neu-
roCare Group; a Researcher, Department of Experimental Psychology, Utrecht University; and
the Director, Research Institute Brainclinics.
Address correspondence to Kerstin Mayer, PhD, neuroCare Group, Rindermarkt 7, 80331 Mu-
nich, Germany; email: kerstin.mayer@neurocaregroup.com.
Grant: M. A. has received research support from the National Institutes of Mental Health ICAN
(International Collaborative ADHD Neurofeedback) study.
Disclosure: Kerstin Mayer is a stock shareholder with the neuroCare Group. Martijn Arns is a
stock shareholder with the neuroCare Group.
doi: 10.3928/00485713-20160906-01
Kerstin Mayer, PhD; and Martijn Arns, PhD
© Shutterstock
Copyrighted material. Not for distribution.
PSYCHIATRIC ANNALS • Vol. 46, No. 10, 2016 595
CME Article
Sterman.7 This work involved the train-
ing of the sensorimotor rhythm (SMR)
in cats. This EEG rhythm was previous-
ly associated with stereotyped postures
characterized by a complete cessation
of spontaneous activity and immobile
behavior in the cat.7 Furthermore, train-
ing of this EEG rhythm during wakeful-
ness resulted in increased sleep spindle
density during sleep (an EEG rhythm
with the same frequency and topograph-
ical distribution as SMR) and improved
sleep quality in cats,8 a finding that was
also replicated in humans.9,10 In a ser-
endipitous finding, the anticonvulsant
effects of operant conditioning of this
SMR rhythm in cats exposed to the
convulsant drug monomethylhydrazine
were demonstrated,11 followed by rep-
lications of these effects in humans.12
These initial findings resulted in what
we currently know as “frequency band
neurofeedback.” About the same time,
the first report of voluntary control
over a slow brain potential called the
contingent negative variation or “bere-
itschaftspotential” (readiness potential,
due to the property of this potential to
emerge when preparing for action, such
as when waiting at a traffic light) was
reported,13 which laid the foundation of
another well-known neurofeedback ap-
proach—slow cortical potential (SCP)
neurofeedback.
Frequency band neurofeedback tar-
gets abnormal activity in frequency
bands, such as high or low power in a
specific frequency band or in a ratio
of two frequency bands. For attention-
deficit hyperactivity disorder (ADHD),
this might be a high theta/beta ratio or
high theta power and/or low beta power
in children,14 and similar patterns in
adults.15-17 The goal of frequency band
neurofeedback is to activate a specific
brain network, which is achieved by
changing the amplitude of a specific
frequency band. To do so, a therapist
either selects the target frequency band
according to the individual quantita-
tive EEG or employs standard proto-
cols. For ADHD, a standard protocol
might be the up-training of the SMR
(12-15 Hz) or a down-training of the
theta/beta ratio (4-7 Hz/13-21 Hz),2 and
for epilepsy this might be an SMR up-
training with concurrent theta down-
training.12 Standard protocols are based
on group-average findings that might
not hold for the individual patient;
therefore, some level of personalization
of neurofeedback could enhance treat-
ment outcome.18,19
SCP neurofeedback is focused on
learned self-regulation of cortical acti-
vation and inhibition. These threshold-
regulation mechanisms are slow electri-
cal shifts in brain activity. They change
periodically from being electrically
positive to electrically negative and are
described as a phasic tuning mecha-
nism in the regulation of attention.20
They are generated cortically and sub-
cortically, involving brain stem reticu-
lar mechanisms, the thalamus, and the
basal ganglia. The main factor contrib-
uting to SCP is synaptic activities at
apical dendrites in superficial layers of
the cortex. Negativation (ie, the signal
becoming electrically negative) repre-
sents activation, increasing the firing
probabilities of the underlying corti-
cal areas, and is caused by long-lasting
depolarization of superficial layer api-
cal dendrites. Positivation represents
an inhibition and a decrease in firing
probabilities. SCPs are related to cog-
nitive performance and motor actions.
A positive shift reflects consumption of
resources and disfacilitation of excita-
tion thresholds. A negative shift reflects
provision of resources and facilitates
attention as well as initiation of goal-
directed behavior that can be observed
in enhanced reaction time, stimulus
detection, and short-term memory dur-
ing the negative shift phase.21 In SCP
neurofeedback, both conditions are
trained (activation/negativation and de-
activation/positivation). Self-regulation
of SCPs is important in disorders with
impaired excitation thresholds, such as
epilepsy or ADHD.
Both types of neurofeedback (ie, fre-
quency band neurofeedback and SCP
neurofeedback) were originally em-
ployed in the treatment of epilepsy,22
but are now also used in the treatment
of ADHD. Both ADHD and epilepsy
are characterized by difficulties in
regulation of cortical excitation thresh-
olds. A meta-analysis of the efficacy of
frequency (especially SMR) and SCP
feedback treatment in ADHD reported
clinical effects with a large effect size
(ES) on inattention and impulsivity and
a medium ES on hyperactivity.23
Neurofeedback has been used for
several disorders such as ADHD, epi-
lepsy, migraine, depression, autism,
tinnitus, anxiety, and others, but the
only evidence-based applications for
this technique are for ADHD and epi-
lepsy. Neurofeedback might be benefi-
cial for other disorders, but the body of
research is too small to make any valid
claims.
ADHD
Several years after Sterman and Fri-
ar’s24 initial demonstration of the anti-
convulsant effects of SMR neurofeed-
back, Lubar and Shouse25 described the
application of this same SMR neuro-
feedback in a child with hyperkinetic
disorder. Employing an A-B-A design,
they reported improvements in hyperac-
tivity and distractibility when SMR was
up-trained and found that symptoms
worsened when reversal training was
used.25 A few years later, these find-
The goal of frequency band
neurofeedback is to activate a
specific brain network.
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596 Copyright © SLACK Incorporated
CME Article
ings were subsequently replicated in a
larger study.26 These reports can now
be considered the first demonstrations
of clinical effects after neurofeedback
in what we today refer to as ADHD.
The first two randomized controlled
trials (RCTs) compared neurofeed-
back to a waiting-list control group
and found improvements in attention
and hyperactivity.27,28 More recently,
four RCTs have been published either
using a cognitive training-based29-31
or an electromyogram (EMG)-based
biofeedback training32 as a control
condition. These control conditions
were aimed at controlling for nonspe-
cific effects of neurofeedback, such as
the time of computer interaction and
amount of client-therapist interaction.
Another RCT compared SCP with the-
ta/beta ratio neurofeedback, and found
similar effects for both treatments on
ADHD symptoms.33
In all of the RCT studies except
that by Holtmann et al.,30 neurofeed-
back training effects were greater than
the control condition with respect to
ADHD symptoms (typically a medium
ES) according to parent and teacher
ratings. In three of these RCTs, follow
up was performed and the clinical ef-
fects were maintained at the 6-month34
and 2-year follow-up visits.35
Two of
these RCTs were multicenter studies
with large sample sizes (n = 10236 and
n = 10437).
In the past few years, several re-
views38-46 and meta-analyses18,23,47 on
ADHD investigated the effectiveness
of nonpharmacologic treatments, es-
pecially neurofeedback, for ADHD. In
general, all reviews and meta-analyses
found positive effects of neurofeedback
for ADHD as rated by parents. They
agreed that neurofeedback is as effec-
tive or more effective than waiting-list
groups, computerized cognitive train-
ing, and EMG feedback. The largest ef-
fect sizes were found for improvements
in symptoms of inattention (>0.8) and
impulsivity (>0.6), with smaller effect
sizes for hyperactivity (>0.3).23 Two
RCTs found that neurofeedback was
not inferior to treatment with psycho-
stimulants.48,49 Some investigations
concluded that neurofeedback is an
“efficacious and specific” treatment
for ADHD,23,38 and some still see a
need for methodologically improved
studies.44,47 Additionally, some clinical
trials are in the process of publication
and preliminary results are promising
regarding quality of study design as
well as clinical outcome.50,51
In addition to behavioral and clini-
cal improvements, other improve-
ments have also been reported, in-
cluding faster reaction times, smaller
reaction time variability, and reduced
error rates.52-54 Improvements in brain
activity have also been reported, such
as improved contingent-negative
variation and event-related potentials
(brain activity patterns that reflect
preparation and attention) in chil-
dren18,30,52,55,56 and adults,57 as well
as improvement in EEG frequency
bands.32,58 One study investigated the
effects of neurofeedback on sleep in
children and adults with ADHD and
found improved sleep-onset latency
and sleep quality after SMR neurofeed-
back that also mediated the clinical
effects of inattention.59 Furthermore,
functional magnetic resonance imag-
ing studies were able to demonstrate
structural changes after neurofeedback
in healthy participants60 and in patients
with ADHD.61 These findings provide
further support for understanding the
underlying mechanism of neurofeed-
back and its efficacy. The underlying
mechanisms of action have also been
investigated in theoretical articles2,62
and via studies that apply neurofeed-
back to healthy participants to inves-
tigate the effect on neurophysiologic
mechanisms and changes.63,64 Details
of these studies are not described here,
but these studies show that research
interest is ongoing as neurofeedback
yields such positive and promising re-
sults.
However, some of the studies and
the reviews and even the meta-anal-
yses themselves have been criticized
for methodologic failures and short-
comings. Shortcomings in the design
and procedure of neurofeedback stud-
ies are the main problems in proving
its effectiveness. Aside from the fact
that the gold standard of placebo-
controlled, randomized, double-blind
studies cannot be easily achieved in
neurofeedback therapy,2 there are
methodologic failures in some of the
studies conducted. Studies that did
not find clinically significant effects
of neurofeedback all had several fea-
tures in common, such as the use of
unconventional neurofeedback pro-
tocols and feedback locations,65-71
substantial deviations from the pre-
registered clinical trials register (such
as only including 60%70,72 to 34%68
of the pre-registered sample size) and
the use of suboptimal methodology
to optimize learning (eg, game-like
implementations2). Note that in regard
to learning principles, if a feedback
animation is too exciting and thrilling,
it might create a stimulus-reinforcer
association instead of a response-
reinforcer association, which means
that the participants will associate the
reinforcement with the stimulus rather
than the desired brain activity.73 Fur-
thermore, motivation and reinforce-
ment need to be given by the therapist,
Some clinical trials are in
the process of publication
and preliminary results are
promising.
Copyrighted material. Not for distribution.
PSYCHIATRIC ANNALS • Vol. 46, No. 10, 2016 597
CME Article
which makes double-blind, placebo-
controlled studies especially hard to
implement.
The problems mentioned regard-
ing the studies with no clinical ef-
fects were further highlighted in
a recent meta-analysis that found
overall effects of neurofeedback in
ADHD when inspecting parent rat-
ings, but not significant effects for
teacher ratings.74 However, when lim-
iting to neurofeedback studies that
used “standard” protocols, there were
significant clinical benefits for both
parent-rated and teacher-rated symp-
toms.74 Currently, some large multi-
center, controlled studies are being
conducted75 or in the process of being
published.50
From recent conferences it can be
concluded that (at least in the com-
pleted study50) a large sample size
and well-designed control conditions
yield promising results supporting
the efficaciousness of neurofeedback.
Taken together, neurofeedback can be
deemed a viable treatment option for
ADHD that is efficacious and specific.
EPILEPSY
Epilepsy is not an official psychi-
atric disorder but has the second-best
evidence in neurofeedback research
and is therefore described here.
Early studies employing SMR neu-
rofeedback, such as those by Sterman
et al.,76 Lubar and Bahler,77 and later
studies employing SCP neurofeedback
from the 1990s22,78,79 and early 2000s80
all showed promising anticonvulsant
effects in epilepsy. The mechanisms
of action are thought to be related to
the ability to regulate brain excita-
tion thresholds and therefore prevent
over-excitation and a subsequent sei-
zure. Studies from two independent
research groups examined this and
delivered promising clinical results
(for review and meta-analysis see Tan
et al.12). SMR and SCP neurofeed-
back protocols proved to be the most
effective in the treatment of epilepsy
with focal seizures. However, in the
2000s, this research interest decreased
dramatically, with only three results
in the literature search for the past 7
years (one review,81 one meta-analy-
sis,12 and one follow-up study82). The
meta-analysis by Tan et al.12 and the
review by Nagai81 concluded that neu-
rofeedback was found to produce a sig-
nificant reduction in seizure frequency.
The recent follow-up study was able to
demonstrate that clinical effects were
maintained even 10 years after treat-
ment,82 as seizure frequency was still
reduced and the ability to regulate
brain activity was still present. Given
that the patient group consisted mostly
of treatment-resistant patients, these
results are encouraging and clinically
meaningful.
OTHERS DISORDERS
Several studies83,84
have also re-
ported on the effect of neurofeedback
in other disorders, but only a few con-
trolled and randomized studies83,84
have been conducted for other indica-
tions. Therefore, although some indica-
tions appear promising, more research
is needed to reach solid conclusions for
the efficacy of neurofeedback in disor-
ders other than ADHD and epilepsy.
LONGTERM EFFECTS AND
CURRENT POSITION OF
NEUROFEEDBACK
Currently, the gold standard of treat-
ment for ADHD is psychostimulant
medication, including methylphenidate
and various amphetamine formulations
with large effect sizes on the group lev-
el in the acute treatment of ADHD.85
However, the clinical efficacy of psy-
chostimulant medication decreases
over time, as demonstrated in various
large-scale studies,86,87 possibly related
to an up-regulation of dopamine trans-
porter availability after sustained treat-
ment.88 Therefore, the need for more
effective and longer-lasting treatments
in ADHD is widely accepted. Because
neurofeedback is based on operant
conditioning principles, once the regu-
lation of the brain is learned and the
treatment was effective, these effects
are thought to be permanent. Interest-
ingly, some subsequent studies have all
shown that clinical benefits were main-
tained or even further improved at the
6 month follow-up34,37,53 and even after
2 years.35 Interestingly, patients were
still able to regulate their brain activ-
ity in the desired direction at these fol-
low-up moments.35,53 The same is true
for patients with epilepsy in a 10-year
follow-up study.82 Additionally, neuro-
feedback does not have any severe side
effects.67,68
NEUROFEEDBACK IS NOT “MAGIC
IN A BOX”
Neurofeedback is part of behavioral
psychotherapy and should be applied
according to those standards. A posi-
tive neurofeedback treatment should
be based on individual brain activity,
learning principles, a good patient-
therapist relationship, motivational
components, and possibly accom-
panying traditional psychotherapy.
Neurofeedback should be accompa-
nied by additional behavioral therapy
components implied in the sessions.
Most SCP neurofeedback studies with
children always implement a token
system and transfer to daily-life situ-
ations. The study by Drechsler et al.54
used extended support from the par-
ents for the daily transfer; all other
studies53 kept the parents rather unin-
volved. The transfer into daily life can
range from handing out transfer cards
and the instruction to practice regu-
lation at home, to sitting down and
guiding the children into an activated
state during their homework or other
tasks. This component seems to be an
important tool for application of the
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598 Copyright © SLACK Incorporated
CME Article
learned self-regulation into daily life,
be it monitored by parents or by the
children on their own.
SELFDIRECTED EEG
NEUROFEEDBACK USING
WEARABLE DEVICES
During the past few years, there has
been development of “home training
devices” or “self-directed neurofeed-
back” for several reasons, such as the
many sessions that are required, travel
time, the availability of the therapist,
and reduction of costs. To this date,
there are no systematic studies that we
are aware of on the effect of neurofeed-
back home-training for psychiatric dis-
orders. Such unsupervised “home train-
ing” also implicates that the feedback
process that is currently performed
by a trained clinician can be fully and
effectively automated. As indicated
above, some of the double-blind stud-
ies (implicating that all parties, in-
cluding the therapist, were blinded)
necessitated automated feedback pro-
cedures; however, all such studies have
been found ineffective,66,89,90 making
it difficult to expect that such an auto-
mated approach is feasible at this mo-
ment. This will require more research
and validation. Therefore, in the near
future, it will be more likely that such
home-training approaches will consist
of “supervised home training” in which
the therapist can access the feedback
tools remotely and apply the neuro-
feedback remotely, sometimes termed
“tele-neurofeedback.”
In addition to the development of
home training, there has also been
large growth in “neuro-devices” claim-
ing to provide all kinds of sophis-
ticated feedback, supposedly based
on brain activity. In our view, these
devices cannot be recommended for
the following reasons: (1) the sig-
nal quality is low, (2) they are not
medically certified, (3) the electro-
physiologic foundations are unclear,
(4) the application is unsupervised, and
(5) they do not have any published data
to support their efficacy. At this stage,
the only possible home-training op-
tion is tele-neurofeedback with direct
supervision by the therapist via remote
access to computers and devices. Pre-
vious caregiver and neurofeedback
training by the therapist is advised.
CONCLUSION
Overall, it can be concluded that
psychiatrists can recommend neuro-
feedback to patients with ADHD as an
effective treatment when standard pro-
tocols, such as SMR, SCP, and theta/
beta neurofeedback, are used. Howev-
er, one should remain cautious regard-
ing the use of neurofeedback for other
indications due to a lack of sufficient
evidence. Even if some neurofeed-
back providers sell their product with
different claims, therapists should be
aware of the evidence base and look
critically at the quality of the product
as well as its claim. Neurofeedback is
an excellent tool for training certain
brain networks and therefore improv-
ing behavior, but the therapist is still
an indispensable component in the
treatment.
REFERENCES
1. Sherlin L, Arns M, Lubar J, et al. Neurofeed-
back and basic learning theory: implica-
tions for research and practice. J Neurother.
2011;15(4):292-304.
2. Arns M, Heinrich H, Strehl U. Evaluation
of neurofeedback in ADHD: the long and
winding road. Biol Psychol. 2014;95:108-
115.
3. Durup G, Fessard AI. L’électrencéphalogramme
de l’homme. Observations psycho-phys-
iologiques relatives à l’action des stimuli
visuels et auditifs. L’année Psychologique.
1935;36(1):1-32.
4. Loomis AL, Harvey EN, Hobart G. Potential
rhythms of the cerebral cortex during sleep.
Science. 1935;81(2111):597-598.
5. Jasper H, Shagass C. Conditioning the oc-
cipital alpha rhythm in man. J Exp Psychol.
1941;28(5):373-387.
6. Knott JR, Henry CE. The conditioning of
the blocking of the alpha rhythm of the hu-
man electroencephalogram. J Exp Psychol.
1941;28(2):134-144.
7. Wyrwicka W, Sterman MB. Instrumental
conditioning of sensorimotor cortex EEG
spindles in the waking cat. Physiol Behav.
1968;3(5):703-707.
8. Sterman MB, Howe RC, Macdonald LR.
Facilitation of spindle-burst sleep by condi-
tioning of electroencephalographic activity
while awake. Science. 1970;167(921):1146-
1148.
9. Hoedlmoser K, Pecherstorfer T, Gruber G, et
al. Instrumental conditioning of human sen-
sorimotor rhythm (12-15 Hz) and its impact
on sleep as well as declarative learning.
Sleep. 2008;31(10):1401-1408.
10. Schabus M, Heib DP, Lechinger J, et al.
Enhancing sleep quality and memory in
insomnia using instrumental sensorimo-
tor rhythm conditioning. Biol Psychol.
2014;95:126-134.
11. Sterman B, Lopresti RW, Fairchild MD.
Electroencephalographic and behavioral
studies of monomethylhydrazine toxicity in
the cat. J Neurother. 2010;14(4):293-300.
12. Tan G, Thornby J, Hammond DC, et al.
Meta-analysis of EEG biofeedback in
treating epilepsy. Clin EEG Neurosci.
2009;40(3):173-179.
13. McAdam DW, Irwin DA, Rebert CS, Knott
JR. Conative control of the contingent neg-
ative variation. Electroencephalogr Clin
Neurophysiol. 1966;21(2):194-195.
14. Barry RJ, Clarke AR, Johnstone SJ. A re-
view of electrophysiology in attention-defi-
cit/hyperactivity disorder: I. Qualitative and
quantitative electroencephalography. Clin
Neurophysiol. 2003;114(2):171-183.
15. Bresnahan SM, Anderson JW, Barry RJ.
Age-related changes in quantitative EEG
in attention-deficit/hyperactivity disorder.
Biol Psychiatry. 1999;46(12):1690-1697.
16. Bresnahan SM, Barry RJ. Specificity of
quantitative EEG analysis in adults with at-
tention deficit hyperactivity disorder. Psy-
chiatry Res. 2002;112(2):133-144.
17. Clarke AR, Barry RJ, Heaven PC, McCarthy
R, Selikowitz M, Byrne MK. EEG in adults
with attention-deficit/hyperactivity disor-
der. Int J Psychophysiol. 2008;70(3):176-
183.
18. Arns M, Drinkenburg W, Kenemans JL.
The effects of QEEG-informed neuro-
feedback in ADHD: an open-label pilot
study. Appl Psychophysiol Biofeedback.
2012;37(3):171-180.
19. Monastra VJ, Monastra DM, George S. The
effects of stimulant therapy, EEG biofeed-
back, and parenting style on the primary
symptoms of attention-deficit/hyperactivity
disorder. Appl Psychophysiol Biofeedback.
2002;27(4):231-249.
20. Rockstroh B, Elbert T, Birbaumer N, Lu-
tzenberger W. Biofeedback-produced
hemispheric asymmetry of slow cortical
potentials and its behavioural effects. Int J
Copyrighted material. Not for distribution.
PSYCHIATRIC ANNALS • Vol. 46, No. 10, 2016 599
CME Article
Psychophysiol. 1990;9(2):151-165.
21. Birbaumer N, Elbert T, Canavan AG, Rock-
stroh B. Slow potentials of the cerebral cortex
and behavior. Physiologic Rev. 1990;70(1):1-
41.
22. Rockstroh B, Elbert T, Birbaumer N, et al.
Cortical self-regulation in patients with epi-
lepsies. Epilepsy Res. 1993;14(1):63-72.
23. Arns M, de Ridder S, Strehl U, Breteler M,
Coenen A. Efficacy of neurofeedback treat-
ment in ADHD: the effects on inattention,
impulsivity and hyperactivity: a meta-analy-
sis. Clin EEG Neurosci. 2009;40(3):180-189.
24. Sterman MB, Friar L. Suppression of sei-
zures in an epileptic following sensorimotor
EEG feedback training. Electroencephalogr
Clin Neurophysiol. 1972;33(1):89-95.
25. Lubar JF, Shouse MN. EEG and behavioral
changes in a hyperkinetic child concurrent
with training of the sensorimotor rhythm
(SMR): a preliminary report. Biofeedback
Self Regul. 1976;1(3):293-306.
26. Shouse MN, Lubar JF. Operant conditioning
of EEG rhythms and ritalin in the treatment
of hyperkinesis. Biofeedback Self Regul.
1979;4(4):299-312.
27. Lévesque J, Beauregard M, Mensour B. Ef-
fect of neurofeedback training on the neural
substrates of selective attention in children
with attention-deficit/hyperactivity disorder:
a functional magnetic resonance imaging
study. Neurosci Lett. 2006;394(3):216-221.
28. Linden M, Habib T, Radojevic V. A con-
trolled study of the effects of EEG biofeed-
back on cognition and behavior of children
with attention deficit disorder and learn-
ing disabilities. Biofeedback Self Regul.
1996;21(1):35-49.
29. Gevensleben H, Holl B, Albrecht B, et
al. Is neurofeedback an efficacious treat-
ment for ADHD? A randomised controlled
clinical trial. J Child Psychol Psychiatry.
2009;50(7):780-789.
30. Holtmann M, Grasmann D, Cionek-Szpak
E, et al. Spezifische wirksamkeit von neuro-
feedback auf die impulsivität bei ADHS.
Kindheit und Entwicklung. 2009;18(2):95-
204.
31. Steiner NJ, Sheldrick RC, Gotthelf D, Per-
rin EC. Computer-based attention training in
the schools for children with attention deficit/
hyperactivity disorder: a preliminary trial.
Clin Pediatr (Phila). 2011;50(7):615-622.
32. Bakhshayesh AR, Hänsch S, Wyschkon
A, Rezai MJ, Esser G. Neurofeedback in
ADHD: a single-blind randomized con-
trolled trial. Eur Child Adolesc Psychiatry.
2011;20(9):481-491.
33. Leins U, Goth G, Hinterberger T, Klinger
C, Rumpf N, Strehl U. Neurofeedback for
children with ADHD: a comparison of SCP
and theta/beta protocols. Appl Psychophysiol
Biofeedback. 2007;32(2):73-88.
34. Gevensleben H, Holl B, Albrecht B, et al.
Neurofeedback training in children with
ADHD: 6-month follow-up of a randomised
controlled trial. Eur Child Adolesc Psychia-
try. 2010;19(9):715-724.
35. Gani C, Birbaumer N, Strehl U. Long term
effects after feedback of slow cortical po-
tentials and of theta-beta-amplitudes in
children with attentiondeficit/hyperactiv-
ity disorder (ADHD). Int J Bioelectromagn.
2008;10(4):209-232.
36. Gevensleben H, Holl B, Albrecht B, et
al. Is neurofeedback an efficacious treat-
ment for ADHD? A randomised controlled
clinical trial. J Child Psychol Psychiatry.
2009;50(7):780-789.
37. Steiner NJ, Frenette EC, Rene KM, Bren-
nan RT, Perrin EC. In-school neurofeedback
training for adhd: sustained improvements
from a randomized control trial. Pediatrics.
2014;133(3):483-492.
38. Gevensleben H, Rothenberger A, Moll GH,
Heinrich H. Neurofeedback in children with
ADHD: validation and challenges. Expert
Rev Neurother. 2012;12(4):447-460.
39. Gevensleben H, Kleemeyer M, Rothen-
berger LG, et al. Neurofeedback in ADHD:
further pieces of the puzzle. Brain Topogr.
2014;27(1):20-32.
40. Moriyama TS, Polanczyk G, Caye A, Ban-
aschewski T, Brandeis D, Rohde LA. Evi-
dence-based information on the clinical use
of neurofeedback for ADHD. Neurothera-
peutics. 2012;9(3):588-598.
41. Mayer K, Wyckoff SN, Strehl U. One size fits
all? Slow cortical potentials neurofeedback:
a review. J Atten Disord. 2013;17(5):393-
409.
42. Gruzelier JH. EEG-neurofeedback for opti-
mising performance. I: a review of cognitive
and affective outcome in healthy participants.
Neurosci Biobehav Rev. 2014;44:124-141.
43. Hodgson K, Hutchinson AD, Denson L.
Nonpharmacological treatments for ADHD:
a meta-analytic review. J Atten Disord.
2014;18(4):275-282.
44. Holtmann M, Sonuga-Barke E, Cortese S,
Brandeis D. Neurofeedback for ADHD: a
review of current evidence. Child Adolesc
Psychiatr Clin N Am. 2014;23(4):789-806.
45. Windthorst P, Veit R, Enck P, Smolka R,
Zipfel S, Teufel M. Biofeedback and neu-
rofeedback: applications in psychosomatic
medicine and psychotherapy. Psychother
Psychosom Med Psychol. 2015;65(3-4):146-
158.
46. Zuberer A, Brandeis D, Drechsler R. Are
treatment effects of neurofeedback training
in children with ADHD related to the suc-
cessful regulation of brain activity? A review
on the learning of regulation of brain activity
and a contribution to the discussion on speci-
ficity. Front Hum Neurosci. 2015;9:135.
47. Sonuga-Barke EJ, Brandeis D, Cortese S,
et al.; European ADHD Guidelines Group.
Nonpharmacological interventions for
ADHD: systematic review and meta-analyses
of randomized controlled trials of dietary and
psychological treatments. Am J Psychiatry.
2013;170(3):275-289.
48. Duric NS, Assmus J, Gundersen DI, Elgen
IB. Neurofeedback for the treatment of chil-
dren and adolescents with ADHD: a random-
ized and controlled clinical trial using paren-
tal reports. BMC Psychiatry. 2012;12(1):107.
49. Meisel V, Servera M, Garcia-Banda G, Cardo
E, Moreno I. Neurofeedback and standard
pharmacological intervention in ADHD: a
randomized controlled trial with six-month
follow-up. Biol Psychol. 2013;94(1):12-21.
50. Holtmann M, Pniewski B, Wachtlin D, Wörz
S, Strehl U. Neurofeedback in children
with attention-deficit/hyperactivity disorder
(ADHD)--a controlled multicenter study of
a non-pharmacological treatment approach.
BMC Pediatr. 2014;14:202.
51. Mayer K, Blume F, Wyckoff SN, Brokmeier
LL, Strehl U. Neurofeedback of slow corti-
cal potentials as a treatment for adults with
attention deficit-/hyperactivity disorder. Clin
Neurophysiol. 2016;127(2):1374-1386.
52. Heinrich H, Gevensleben H, Freisleder FJ,
Moll GH, Rothenberger A. Training of slow
cortical potentials in attention-deficit/hyper-
activity disorder: evidence for positive be-
havioral and neurophysiological effects. Biol
Psychiatry. 2004;55(7):772-775.
53. Strehl U, Leins U, Goth G, Klinger C, Hin-
terberger T, Birbaumer N. Self-regulation of
slow cortical potentials: a new treatment for
children with attention-deficit/hyperactiv-
ity disorder. Pediatrics. 2006;118(5):e1530-
1540.
54. Drechsler R, Straub M, Doehnert M, Hein-
rich H, Steinhausen HC, Brandeis D. Con-
trolled evaluation of a neurofeedback train-
ing of slow cortical potentials in children
with Attention Deficit/Hyperactivity Disor-
der (ADHD). Behav Brain Funct. 2007;3:35.
55. Kropotov JD, Grin-Yatsenko VA, Ponomarev
VA, Chutko LS, Yakovenko EA, Nikish-
ena IS. ERPs correlates of EEG relative beta
training in ADHD children. Int J Psycho-
physiol. 2005;55(1):23-34.
56. Wangler S, Gevensleben H, Albrecht B, et al.
Neurofeedback in children with ADHD: spe-
cific event-related potential findings of a ran-
domized controlled trial. Clin Neurophysiol.
2011;122(5):942-950.
57. Mayer K, Blume F, Wyckoff SN, Brokmeier
LL, Strehl U. Neurofeedback of slow corti-
cal potentials as a treatment for adults with
Attention-Deficit/Hyperactivity Disorder.
Clin Neurophysiol. 2016;127(2):1374-1386.
58. Gevensleben H, Holl B, Albrecht B, et al.
Distinct EEG effects related to neurofeed-
back training in children with ADHD: a ran-
domized controlled trial. Int J Psychophysiol.
2009;74(2):149-157.
59. Arns M, Feddema I, Kenemans JL. Differen-
tial effects of theta/beta and SMR neurofeed-
back in ADHD on sleep onset latency. Front
Copyrighted material. Not for distribution.
600 Copyright © SLACK Incorporated
CME Article
Hum Neurosci. 2014;8:1019.
60. Ghaziri J, Tucholka A, Larue V, et al. Neu-
rofeedback training induces changes in
white and gray matter. Clin EEG Neurosci.
2013;44(4):265-272.
61. Beauregard M, Lévesque J. Functional mag-
netic resonance imaging investigation of the
effects of neurofeedback training on the neu-
ral bases of selective attention and response
inhibition in children with attention-deficit/
hyperactivity disorder. Appl Psychophysiol
Biofeedback. 2006;31(1):3-20.
62. Ros T, J Baars B, Lanius RA, Vuilleumier
P. Tuning pathological brain oscillations
with neurofeedback: a systems neurosci-
ence framework. Front Hum Neurosci.
2014;8:1008.
63. Gevensleben H, Moll GH, Rothenberger A,
Heinrich H. Neurofeedback in attention-def-
icit/hyperactivity disorder - different models,
different ways of application. Front Hum
Neurosci. 2014;8:846.
64. Studer P, Kratz O, Gevensleben H, et al. Slow
cortical potential and theta/beta neurofeed-
back training in adults: effects on attentional
processes and motor system excitability.
Front Hum Neurosci. 2014;8:555.
65. Ogrim G, Hestad KA, Kropotov J, et al.
Predicting the clinical outcome of stimulant
medication in pediatric attention-deficit/
hyperactivity disorder: data from quantitative
electroencephalography, event-related poten-
tials, and a go/no-go test. Neuropsychiatr Dis
Treat. 2014;10:231-242.
66. Lansbergen MM, van Dongen-Boomsma
M, Buitelaar JK, Slaats-Willemse D. ADHD
and EEG-neurofeedback: a double-blind ran-
domized placebo-controlled feasibility study.
J Neural Transm. 2011;118(2):275-284.
67. Arnold LE, Lofthouse N, Hersch S, et al.
EEG neurofeedback for ADHD: double-
blind sham-controlled randomized pilot fea-
sibility trial. J Atten Disord. 2013;17(5):410-
419.
68. van Dongen-Boomsma M, Vollebregt MA,
Slaats-Willemse D, Buitelaar JK. A ran-
domized placebo-controlled trial of electro-
encephalographic (EEG) neurofeedback in
children with attention-deficit/hyperactivity
disorder. J Clin Psychiatry. 2013;74(8):821-
827.
69. Vollebregt MA, van Dongen-Boomsma
M, Buitelaar JK, Slaats-Willemse D. Does
EEG-neurofeedback improve neurocognitive
functioning in children with attention-deficit/
hyperactivity disorder? A systematic review
and a double-blind placebo-controlled study.
J Child Psychol Psychiatry. 2014;55(5):460-
472.
70. Bink M, van Nieuwenhuizen C, Popma A,
Bongers IL, van Boxtel GJ. Behavioral ef-
fects of neurofeedback in adolescents with
ADHD: a randomized controlled trial. Eur
Child Adolesc Psychiatry. 2015;24(9):1035-
1048.
71. Maurizio S, Liechti MD, Heinrich H, et al.
Comparing tomographic EEG neurofeed-
back and EMG biofeedback in children with
attention-deficit/hyperactivity disorder. Biol
Psychol. 2014;95:31-44.
72. Janssen TW, Bink M, Geladé K, van Mourik
R, Maras A, Oosterlaan J. A randomized
controlled trial investigating the effects of
neurofeedback, methylphenidate, and physi-
cal activity on event-related potentials in
children with attention-deficit/hyperactivity
disorder. J Child Adolesc Psychopharmacol.
2016;26(4):344-353.
73. Sherlin L, Arns M, Lubar J, et al. Neuro-
feedback and basic learning theory: implica-
tions for research and practice. J Neurother.
2011;15(4):292-304.
74. Cortese S, Ferrin M, Brandeis D, et al. Neu-
rofeedback for attention-deficit/hyperactivity
disorder: meta-analysis of clinical and neu-
ropsychological outcomes from randomized
controlled trials. J Am Acad Child Adolesc
Psychiatry. 2016;55(6):444-455.
75. Arnold G, Arns M, Conners K, et al.; the
Collaborative Neurofeedback Group. A pro-
posed multisite double-blind randomized
clinical trial of neurofeedback for ADHD:
need, rationale, and strategy. J Atten Disord.
2013;17(5):420-436.
76. Sterman MB, Macdonald LR, Stone
RK. Biofeedback training of the sensorimo-
tor electroencephalogram rhythm in man: ef-
fects on epilepsy. Epilepsia. 1974;15(3):395-
416.
77. Lubar JF, Bahler WW. Behavioral man-
agement of epileptic seizures following
EEG biofeedback training of the senso-
rimotor rhythm. Biofeedback Self Regul.
1976;1(1):77-104.
78. Kotchoubey B, Schneider D, Schleichert
H, et al. Self-regulation of slow cortical
potentials in epilepsy: a retrial with analy-
sis of influencing factors. Epilepsy Res.
1996;25(3):269-276.
79. Kotchoubey B, Strehl U, Holzapfel S, et al.
Control of cortical excitability in epilepsy.
Adv Neurol. 1999;81:281-290.
80. Kotchoubey B, Strehl U, Uhlmann C, et al.
Modification of slow cortical potentials in
patients with refractory epilepsy: a controlled
outcome study. Epilepsia. 2001;42(3):406-
416.
81. Nagai Y. Biofeedback treatment for epi-
lepsy. [Article in Japanese]. Nihon Rinsho.
2014;72(5):887-893.
82. Strehl U, Birkle SM, Wörz S, Kotchoubey
B. Sustained reduction of seizures in patients
with intractable epilepsy after self-regulation
training of slow cortical potentials - 10 years
after. Front Hum Neurosci. 2014;8:604.
83. Koprivova J, Congedo M, Raszka M, Prasko
J, Brunovsky M, Horacek J. Prediction of
treatment response and the effect of inde-
pendent component neurofeedback in ob-
sessive-compulsive disorder: a randomized,
sham-controlled, double-blind study. Neuro-
psychobiology. 2013;67(4):210-223.
84. Choi SW, Chi SE, Chung SY, Kim JW, Ahn
CY, Kim HT. Is alpha wave neurofeedback
effective with randomized clinical trials in
depression? A pilot study. Neuropsychobiol-
ogy. 2011;63(1):43-51.
85. Faraone SV, Buitelaar J. Comparing the effi-
cacy of stimulants for ADHD in children and
adolescents using meta-analysis. Eur Child
Adolesc Psychiatry. 2010;19(4):353-364.
86. Molina BS, Hinshaw SP, Swanson JM, et
al.; MTA Cooperative Group. The MTA at
8 years: prospective follow-up of children
treated for combined-type ADHD in a multi-
site study. J Am Acad Child Adolesc Psychia-
try. 2009;48(5):484-500.
87. Riddle MA, Yershova K, Lazzaretto D, et al.
The Preschool Attention-Deficit/Hyperactiv-
ity Disorder Treatment Study (PATS) 6-year
follow-up. J Am Acad Child Adolesc Psychi-
atry. 2013;52(3):264-278.e2.
88. Wang GJ, Boraud T, Volkow ND, et al. Long-
term stimulant treatment affects brain dopa-
mine transporter level in patients with atten-
tion deficit hyperactive disorder. PLoS ONE.
2013;8(5):e63023.
89. Arnold VK, Feifel D, Earl CQ, Yang R, Adler
LA. A 9-week, randomized, double-blind,
placebo-controlled, parallel-group, dose-
finding study to evaluate the efficacy and
safety of modafinil as treatment for adults
with ADHD. J Atten Disord. 2014;18(2):133-
144.
90. DeBeus R, Kaiser D. Neurofeedback with
children with attention deficit hyperactivity
disorder: a randomized double-blind place-
bo-controlled study. In: Coben R, Evans J,
eds. Neurofeedback and Neuromodulation:
Techniques and Applications. San Diego,
CA: Elsevier; 2011:127-152.
Copyrighted material. Not for distribution.
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While issues of efficacy and specificity are crucial for the future of neurofeedback training, there may be alternative designs and control analyses to circumvent the methodological and ethical problems associated with double-blind placebo studies. Surprisingly, most NF studies do not report the most immediate result of their NF training, i.e., whether or not children with ADHD gain control over their brain activity during the training sessions. For the investigation of specificity, however, it seems essential to analyze the learning and adaptation processes that take place in the course of the training and to relate improvements in self-regulated brain activity across training sessions to behavioral, neuropsychological and electrophysiological outcomes. To this aim, a review of studies on neurofeedback training with ADHD patients which include the analysis of learning across training sessions or relate training performance to outcome is presented. Methods on how to evaluate and quantify learning of EEG regulation over time are discussed. "Non-learning" has been reported in a small number of ADHD-studies, but has not been a focus of general methodological discussion so far. For this reason, selected results from the brain-computer interface (BCI) research on the so-called "brain-computer illiteracy", the inability to gain control over one's brain activity, are also included. It is concluded that in the discussion on specificity, more attention should be devoted to the analysis of EEG regulation performance in the course of the training and its impact on clinical outcome. It is necessary to improve the knowledge on characteristic cross-session and within-session learning trajectories in ADHD and to provide the best conditions for learning.
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Neurofeedback has been proposed as a potentially effective intervention for reducing Attention Deficit Hyperactivity Disorder (ADHD) symptoms. However, it remains unclear whether neurofeedback is of additional value to treatment as usual (TAU) for adolescents with clinical ADHD symptoms. Using a multicenter parallel-randomized controlled trial design, adolescents with ADHD symptoms were randomized to receive either a combination of TAU and neurofeedback (NFB + TAU, n = 45) or TAU-only (n = 26). Randomization was computer generated and stratified for age group (ages 12 through 16, 16 through 20, 20 through 24). Neurofeedback treatment consisted of approximately 37 sessions of theta/sensorimotor rhythm (SMR)-training on the vertex (Cz). Primary behavioral outcome measures included the ADHD-rating scale, Youth Self Report, and Child Behavior Checklist all assessed pre- and post-intervention. Behavioral problems decreased equally for both groups with medium to large effect sizes, range of partial eta2 = 0.08-0.31, p < 0.05. Hence, the combination of NFB + TAU was not more effective than TAU-only on the behavioral outcome measures. In addition, reported adverse effects were similar for both groups. On behavioral outcome measures, the combination of neurofeedback and TAU was as effective as TAU-only for adolescents with ADHD symptoms. Considering the absence of additional behavioral effects in the current study, in combination with the limited knowledge of specific treatment effects, it is questionable whether theta/SMR neurofeedback for adolescents with ADHD and comorbid disorders in clinical practice should be used. Further research is warranted to investigate possible working mechanisms and (long-term) specific treatment effects of neurofeedback.
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Neurofeedback (NFB) is emerging as a promising technique that enables self regulation of ongoing brain oscillations. However, despite a rise in empirical evidence attesting to its clinical benefits, a solid theoretical basis is still lacking on the manner in which NFB is able to achieve these outcomes. The present work attempts to bring together various concepts from neurobiology, engineering, and dynamical systems so as to propose a contemporary theoretical framework for the mechanistic effects of NFB. The objective is to provide a firmly neurophysiological account of NFB, which goes beyond traditional behaviorist interpretations that attempt to explain psychological processes solely from a descriptive standpoint whilst treating the brain as a "black box". To this end, we interlink evidence from experimental findings that encompass a broad range of intrinsic brain phenomena: starting from "bottom-up" mechanisms of neural synchronization, followed by "top-down" regulation of internal brain states, moving to dynamical systems plus control-theoretic principles, and concluding with activity-dependent as well as homeostatic forms of brain plasticity. In support of our framework, we examine the effects of NFB in several brain disorders, including attention deficit hyperactivity (ADHD) and post traumatic stress disorder (PTSD)). In sum, it is argued that pathological oscillations emerge from an abnormal formation of brain-state attractor landscape(s). The central thesis put forward is that NFB tunes brain oscillations toward a homeostatic set-point which affords an optimal balance between network flexibility and stability (i.e., self organised criticality (SOC)).
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In children with attention-deficit/hyperactivity disorder (ADHD), different neurofeedback (NF) protocols have been applied, with the most prominent differentiation between EEG frequency-band (e.g., theta/beta) training and training of slow cortical potentials (SCPs). However, beyond distinctions between such basic NF variables, there are also competing assumptions about mechanisms of action (e.g., acquisition of regulation capability, generalization to daily life behavior). In the present article, we provide a framework for NF models and suppose two hypothetical models, which we call "conditioning-and-repairing model" and "skill-acquisition model," reflecting extreme poles within this framework. We argue that the underlying model has an impact not only on how NF is applied but also on the selection of evaluation strategies and suggest using evaluation strategies beyond beaten paths of pharmacological research. Reflecting available studies, we address to what extent different views are supported by empirical data. We hypothesize that different models may hold true depending on the processes and behaviors to be addressed by a certain NF protocol. For example, the skill-acquisition model is supported by recent findings as an adequate explanatory framework for the mechanisms of action of SCP training in ADHD. In conclusion, evaluation and interpretation of NF trials in ADHD should be based on the underlying model and the way training is applied, which, in turn, should be stated explicitly in study reports.
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