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Neurofeedback as ADHD therapy

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Neurofeedback as ADHD therapy

Neurofeedback is a scientifically recognized treatment technique that provides immediate feedback to the patient as he or she attempts to change the electrical activity of the brain as measured by electrodes.

ADHD is one of the main areas of application of neurofeedback,1 along with tic disorders, migraines, tinnitus, depression, and autism.2

Neurofeedback appears to improve ADHD symptoms about as effectively as cognitive behavioral therapy ( Effectiveness of different forms of treatment for ADHD) and seems to lead to lasting effects as well (see below). Because of the lasting effects, one can speak of a healing effect through neurofeedback. However, this healing effect is very rarely complete because of the limited symptom improvement and because not all affected persons respond equally. Neurofeedback is usually only useful as a complementary therapy to medication.

Neurofeedback works by improving the self-controllability of one’s brain activities (see below)
In treatment, the patient learns to influence his brain frequencies as they are measured and made visible to him as immediate feedback (e.g., colors; bar graphs; airplane flying higher or lower; movie running or stopping depending on readings achieved).

Neurologically, neurofeedback uses a variety of measures.

  1. EEG frequency bands EEG frequencies are controlled by the thalamus, whose function shows significant abnormalities in ADHD.3
  2. SCP - slow cortical potentials SCP training of slow cortical potentials targets phasic aspects of cortical excitability. Patients train potential shifts in a positive direction (“positivization”; decrease in excitability) or negative direction (“negativization”; increase in excitability).4
  3. QEEG - Quantitative EEG - EEG with spatial assignment to specific brain areas5

In practice, frequency bands without spatial allocation or SCP are mostly used, since the measurement of brain activity in specific brain areas is technically very complex.
For general EEG frequency band training, a 1-channel EEG measuring device is sufficient. For a spatial resolution of brain activities to individual brain areas, a large number of EEG channels (usually 19) is required. The corresponding devices are considerably more expensive, the operation more complex.
qEEG are studied as biomarkers for the diagnosis of various mental disorders.6

1. Neurofeedback frequency band training

1.1. Brain frequencies and their function

The brain communicates by means of groups of nerve cells that transmit and pause in a synchronized rhythm. The different frequencies of the rhythms correlate with specific states of consciousness and can be measured in EEG frequency bands.

1.1.1. The EEG brain frequencies

1.1.1.1. Delta
  • Delta - 0.4 to 3/3.5 Hz - calm, dreamless deep sleep, trance, unconsciousness; in infancy and toddlerhood also during wakefulness
1.1.1.2. Theta
  • Theta - 4 to 6.5/7 Hz - doziness and light sleep, waking dreams, hypnosis.
    Strong occurrence in infancy and toddlerhood, becomes weaker with age / increasing brain maturation (frequencies increase).

But if now

  • Theta is higher in young children and of course decreases with age and
  • there is delayed brain maturation in ADHD (and to the same extent as is typical in giftedness - both groups catch up in brain maturation by about age 12), it is not surprising to a certain extent that children under age 12 with ADHD show increased theta activity compared to non-affected (and non-gifted) individuals.

One could formulate that theta-beta training accelerates brain maturation in younger children.

Theta occurs in various forms:

  • Cortical theta rhythm7
    For infants and toddlers even when awake
    in adolescents and adults: in drowsiness, in the transition from wakefulness to sleep, during sleep, otherwise in brain pathologies
  • Hippocampal theta rhythm / frontal-midline theta7
    Decrease near the apex of the head (Cz)
    Is associated with
    • The anterior cingulate cortex (correlating with simultaneously increased glucose metabolism)
    • Theta rhythm in hippocampus, parahippocampal cortex, anterior cingulate cortex, mammillary bodies of hypothalamus, medial dorsal nucleus of thalamus
    • Papez circuit, which probably serves less for emotion control and has more memory relevance.
  • Dysfunctional front-midline-theta (FMT) in the range 5.5-8 Hz8
    See more at ADHD subtypes according to EEG
1.1.1.3. Alpha
  • Alpha - 7/8 to 12/13 Hz - alert relaxation, inward attention, closed eyes. Healthy physiological basic rhythm of the resting brain. Strongest expression moves from the center of the head (in children) towards the back of the head (puberty). Occurs mainly with closed eyes and is replaced by beta waves when opening the eyes or thinking (such as mental arithmetic with closed eyes).
    Distinct alpha waves increase creativity and reduce the risk of depression.9
  • Alpha (and beta) serve (at least for visual stimuli) for top-down information transfer from more developed to less developed brain areas.10
  • Methylphenidate and amphetamine drugs increase the power of alpha in the EEG (in rats), whereas atomoxetine and guanfacine do not.11
1.1.1.4. SMR / Low Beta
  • SMR (Low Beta) - 12 to 15 Hz - calm concentration, relaxed/undirected outward attention.
    SMR is also described as alpha from 9 to 13 Hz, derived via C3 and C4.12
    Migraine often has the picture of a low SMR and an excessive beta, often a rather high theta occurs in addition.
    Migraine: Up-training SMR is a typical and helpful migraine treatment.
    Many general practitioners prescribe NFB for migraine. If that doesn’t help, beta blockers (which don’t block beta waves in the brain, but beta receptors in the heart) are often the only option, but this should be the last choice.
1.1.1.5. Beta
  • Beta - 15 to 21 Hz - active attention
    Overactivation in the beta area is often said to be accompanied by underactivation in other brain areas in ADHD, mostly in the frontostriatal loop.13 This might correspond to the mechanism that an overactivated PFC (high dopamine level) deactivates the striatum (low dopamine level).
    Inattention correlates with low beta (12 - 30 Hz) and low gamma (30 - 50 Hz) values.14 We assume that the ADHD-I-typical inattention due to boredom is meant here, which has its cause in an underactivated PFC, not the ADHD-HI-typical inattention due to distractibility, which has its cause in an overactivated PFC.
    In many adults with sleep disorders, beta is elevated at rest, increasing instead of decreasing when trying to relax; also common in depression.

In one reported case of childhood trauma, the sufferer’s monsters were kept in check by avoiding sleep; there was an extremely low theta, and a generally elevated beta, which increased further when relaxation was attempted.15

Migraine has similar picture (of an excessive beta), often additionally quite high theta and low SMR.

The beta rising in ADHD during relaxation is, in our view, a conclusive reason why meditation is so aversive for ADHD sufferers. It also explains the circling of thoughts when going to sleep (together with the fact that thinking releases dopamine - thinking can be an addiction to satisfy the need for dopamine). Both lead to a self-reinforcing cycle and ultimately to permanent exhaustion and even inability to recover.

  • Beta (and alpha) serve (at least for visual stimuli) for top-down information transfer from more developed to less developed brain areas.10
1.1.1.6. High Beta
  • High Beta - 21 to 35/38 Hz - hectic, stress, anxiety, overactivation.
    If too high: mind spinning, can’t get head still
1.1.1.7. Gamma
  • Gamma - 35/38 to 45/70 Hz - tense attention, strong concentration and information processing
  • Gamma (around 60 Hz) is used (at least for visual stimuli) for bottom-up information transfer from lower developed to higher developed brain areas.10

Higher scores on the Childhood Trauma Questionairy correlate (in addition to higher ADHD symptoms) with

  • Higher QEEG values in the areas16
    • Delta
    • Beta1
    • Beta2
    • Beta3
    • Gamma
  • Significantly reduced power values in the range17
    • Low alpha
  • Inattention correlates with
    • Low beta (12 - 30 Hz) values14
    • Low gamma values (30 - 50 Hz)14
    • Increased high-beta17
      • Which was unexpected for the authors
    • Low low alpha17
      • Which was unexpected for the authors

Inattention in high beta is likely to correspond to ADHD-HI-typical distractibility due to an overactivated PFC.

1.1.2. EEG brain frequencies according to further criteria

  • Rolandic waves18
    depending on age in the range 14 to 30 Hz. They are recorded (at rest with eyes closed or open) at C3, Cz, C4 above the (namesake) Rolando furrow (sulcus centralis).
    They differ1920 in
    • (rolandic) μ-rhythms or murmurs
      The name comes from the fact that its shape resembles a μ.
      The origin of μ-rhythms is the primary somatsensory cortex.18
    • Rolandic beta waves
      The origin of rolandic beta waves is the motor cortex.18

1.1.3. Changes in EEG brain frequencies with age

In all people, the power (current intensity) of the EEG changes with age, especially from childhood to adolescence. With age, the slow frequencies (delta and theta) decrease, while the fast frequencies (alpha and beta) become stronger. Total power (the sum of all individual frequency power values) decreases with age.2122 Age-related changes do occur in ADHD sufferers as well as in non-affected individuals, but to different degrees. In ADHD, the EEG approaches more closely that of non-affected persons with age, whereas it remains almost constant in ADHD-I affected persons.2324

Insofar as studies speak of “slowed brain activity,” the increase in power of slow brain frequencies (delta/theta) is meant.

1.1.4. QEEG and drug response

One study observed that in different attentional and affective disorders (here: ADHD, depression, bipolar according to DSM-III-R), neurometric features predicted medication response:25

  • frontal alpha excess responded 87% to antidepressants
  • frontal theta excess responded 100% to stimulants
  • frontal alpha excess with hypercoherence responded 85% to anticonvulsants/lithium
  • frontal theta excess with hypercoherence responded 80% to anticonvulsants

One study of ADHD found a good response at26
(too small numbers of subjects in the groups are noted)

ADHD-HI ADHD-I
frontal alpha excess (100% AMP (n = 3)) (66.7% AMP (n = 3))
92.3% MPH (50.0% MPH (n = 8))
frontal theta excess 76.9% AMP 41.2% AMP
73.9 % MPH 20.0 % MPH
frontal beta excess (100% AMP (n = 3)) (50% AMP (n = 2))
(66.7% MPH (n = 3)) (75% MPH (n = 4))

1.2. Brain wave investigation methods

  • EEG
  • Independent Component Analysis (ICA)
  • Low Resolution Electromagnetic Tomography (LORETA)

1.3. Basics of frequency band training

By targeted training of the affected brain frequencies (frequencies with too low intensity are trained up, frequencies with too high intensity are trained down), the symptoms correlating with the respective frequencies can be influenced. Not all affected persons respond in the same way. In 50% of ADHD sufferers, the symptoms can be reduced by at least 25%. 20 to 40 training sessions are required. The effect of neurofeedback was unchanged 6 months after the end of therapy.27

Procedure of the therapy session:
The patient’s EEG frequencies are measured by means of electrodes and visualized on the therapist’s PC.
The software now offers the patient stimuli (graphics, games, movies, etc.) that he can control by means of the EEG frequency to be trained. For example, the patient is supposed to control an airplane by changing the flight altitude based on the measured value of the brain frequency to be trained.

A real therapy case:

An ADHD-HI patient (with hyperactivity) had an SMR (EEG frequencies between 12 and 15 Hz) of 1.6 mV of Cz at the start of therapy. The typical value in non-affected persons is between 2.8 and 3.2. The patient was shown a film that continued to run whenever the SMR value measured simultaneously in the patient exceeded the threshold value set by the therapist. If the SMR value fell below the threshold, the film stopped.
Although the patient could not say exactly what he did to increase the amplitude of his SMR, he managed (within about 10 minutes) to go from 40% to 80% success (proportion of time in which the threshold is exceeded). On this, the threshold was increased slightly. If the success dropped to 30%, the threshold was decreased somewhat so as not to frustrate the patient too quickly (especially in ADHD-HI).
After 30 training sessions, the patient exercised at a threshold of 2.5 and achieved 50% to 60%
Transformational passes (attempts by the patient to increase SMR without feedback from a film) coped with 2.0 to 2.5.
Subjectively, the patient felt he was somewhat less sensitive to stress and had significantly fewer affect breakthroughs.
The patient wanted to continue training until the training showed no more improvement. After 60 training sessions, the value remained constant at 2.6. A further increase was not achieved even with further training.

Neurofeedback enables the targeted training of individual brain areas.

So far, neurofeedback is not generally reimbursed by insurance companies. However, prescribed occupational therapy is reimbursable. Occupational therapists who also offer neurofeedback are authorized to use neurofeedback as a form of occupational therapy.

An in-depth presentation of neurofeedback training for home use at Youtube by Dr. Kowalski, who (together with Ute Strehl) does research on neurofeedback at the University of Tübingen, using software he developed for home use: Kowalski at Youtube on Neurofeedback.
According to this opinion, neurofeedback can be trained at home, but it is absolutely necessary to be accompanied/guided by a neurofeedback therapist in private practice. If the wrong frequencies are trained in the wrong direction, the training could be harmful. Whether the devices and software are now sufficiently functional for home use cannot be judged at present.

2. Different EEG shapes in subtypes of ADHD

The different subtypes of ADHD have specific different EEG patterns. This means that in ADHD - depending on the specific subtype - different brain frequencies are more active or inactive than in non-affected individuals.

There are more subtypes classifiable according to EEG than classical subtypes have been distinguished according to behavior.

See more at ADHD subtypes according to EEG in the article The subtypes of ADHD: ADHD-HI, ADHD-I, SCT, and others.

3. Connectivity of brain regions in ADHD

See Brain networks and connectivity in ADHD In the chapter Neurological aspects.

4. Training models

4.1. Frequency band training

4.1.1. SMR training (increase of low beta, 12 - 15 Hz)

SMR training is a typical neurofeedback protocol for ADHD with the goal of increasing brain activity in the SMR band.2829
The SMR plays an important role in motor excitability.29
Amplification of the sensorimotor rhythm (12-15 Hz) over the motor cortex is thought to reduce hyperactivity by inhibiting the thalamo-cortical loop.30
SMR training reduces impulsivity and affect breakthroughs and promotes calm general attention. Serene attention is different from concentration (focused attention).

In a study of SMR frequency band training, 86 children between the ages of 9 and 14 with ADHD were assessed with Go/NoGo tasks. Each training session included:

  • Improvement of power ratio from 15-18 Hz in relation to the rest of the EEG (20 minutes), measurement on C3/Fz
  • Improvement of power ratio from 12-15 Hz in relation to the rest of the EEG (7 - 10 minutes), measurement on C4/Pz

After 15 to 22 neurofeedback sessions, those children who performed well in the training sessions showed gains in P 300 (Positive Component within 180-420 ms latency) over frontal-central brain areas in the Go/NoGo tasks. No gain was seen in the children who performed worse in the training sessions.31
Accordingly, activation of frontal-central brain regions appears to be amenable to beta training.

4.1.2. Theta-Beta or Theta-Alpha Ratio Training

  • Theta down and (if necessary simultaneously) beta up or
  • Theta down and alpha up (at the same time, if necessary)

The goal is to increase theta activity while decreasing beta activity.32

The two training methods, Theta-Beta and Theta-Alpha, differed little in their results. Both protocols alleviated symptoms of ADHD in general (p <0.001), symptoms of hyperactivity (p <0.001), inattention (p <0.001), and omission errors (p <0.001), but not oppositional and impulsive symptoms. Up-training alpha was reported to be more effective with respect to omission errors.33

A study comparing theta-beta training with the mechanisms of action of MPH concluded that theta-beta training primarily improves inhibition and impulse control rather than attention, but uses different mechanisms of action for this than methylphenidate.34 The theta/beta ratio at rest appears to mediate the relationship between motor competence and inhibition in children with ADHD.35
One study found differential effects of theta-beta frequency band training on different subtypes (ADHD-I and ADHD-C).36

A very small pilot study found that alpha/theta training produced improvements in attention even in students without ADHD.37

4.1.3. Individual beta rhythms

An experimental neurofeedback method used individual beta rhythms.38

4.2. Training of the self-regulation ability of the EEG

This approach turns away from normalization of EEG frequencies (comparison according to QEEG databases) because studies in groups could not find consistent characteristic EEG frequency patterns in children with ADHD.32
Therefore, some neurofeedback protocols work with alternating training phases to increase and decrease target values, which is also the usual approach to SCP regulation.

4.3. QEEG Neurofeedback Training (z-score training)

The Z-Score training is based on a database with examination results of about 600 healthy children and adults. The training aims to change one’s own brain frequency activities in the direction of these normal values.32

Also with the Z-score training, the effectiveness could possibly be achieved by training the self-control ability of the EEG. The fact that normal values of healthy people are used as target parameters does not change this.

One study reported that 70% of adults and 52% of children with ADHD improved so much after 30 training sessions of a combination of Z-score neurofeedback and HRV biofeedback training that they were no longer diagnosed in the clinical range of the ASEBA afterward, but in the normal range. If the diagnosis was previously in the borderline range of the ASEBA, 80% of the adults and 63% of the children reached the normal range. 4 of 9 adults and 10 of the 44 children who had previously used ADHD medications discontinued ADHD medications after treatment. No adult (of 30) and 1 child (of 55) who had not used ADHD medications before treatment used ADHD medications for the first time after treatment.39
If these results can be repeated, this would be - with all scientific restraint - a sensation. Therefore, the results should be viewed with appropriate attention and caution.

4.4. HeartMath - Training

On another arguably trademarked training model (which, scientifically speaking, always raises some suspicion), a study on the provider’s website reports positive results with ADHD that are said to be based on coherence improvements in brain communication.40

4.5. Training of slow cortical potentials (SCP)

SCP (Slow Cortical Potentials) are very slow frequencies of less than 0.1 Hz, which are outside the measurement range of a usual EEG.
SCP are responses of the brain to internal or external stimuli. SCP are understood as a measure of the excitability of the cerebral cortex.

Training to control slow cortical potentials can support providing improved information processing according to the situation.
The effectiveness of SCP training for ADHD has been proven many times.41

SCP had a slightly better effect on children’s ADHD symptoms than theta/beta frequency band training in one study.42 However, a combination of both methods is likely to be useful.
It would also be conceivable to train self-regulation of interhemispheric frontal asymmetry by SCP feedback. This has already been demonstrated in healthy subjects.43 Here, the synchronization of the left and right hemispheres of the brain is specifically trained. This is particularly helpful in depression, since depression and chronic frustration are often accompanied by a particularly strong asynchrony of the brain hemispheres.

4.6. Infra Low Frequency Training - ILF

The training of ILF was developed by Othmer and is therefore sometimes called the Othmer method. It is also a very low frequency training. The technique, derivations and feedback are designed differently.

ILF training does not aim to increase or decrease frequencies at will, but to mirror / visualize specific parameters of low brain frequencies in such a way that it can be learned about to self-regulate the excitation level of the central nervous system (CNS).

4.7. LORETA Neurofeedback

LORETA (Low Resolution Brain Electromagnetic Tomography) is a three-dimensional low resolution electromagnetic brain imaging technique. Using LORETA, specific brain networks in deeper brain structures are trained by three-dimensional viewing.

4.8. EEG-BCI Training

One study reports a form of training in which subjects learn to suppress or enhance specific EEG waves not based on preset defaults, but with an EEG pattern individualized by the system that represents optimal attention based on training activities.44
A 24-session treatment produced a 3.2-point improvement in ADHD Rating Scale inattention.

5. Effectiveness neurofeedback

5.1. Mechanism of action

The basic effectiveness of neurofeedback is widely accepted scientifically.45

We assume that the effectiveness of neurofeedback lies in learning to control one’s own brain activity. One’s own brain activity is always unconsciously controlled: if one goes to sleep, one calms down, before an important task one concentrates. This is nothing else than a self-made regulation (among others) of certain brain frequencies. People in whom certain brain frequencies react abnormally or who have poor self-regulation can learn to improve it through a targeted reinforcement of successful self-regulation.

5.2. Treatment effectiveness

The level of effectiveness (effect size) can reach that of medication.464748
An elaborate study compared neurofeedback with stimulant treatment and found equally strong improvements in both groups.49
One study found significant improvements in children treated with 40 neurofeedback sessions with theta-beta training compared with traditionally treated children in the following areas50

  • Continued attention
  • Verbal working memory
  • Response inhibition / Impulse inhibition
  • Behavioral problems
  • Academic achievement.

A comparative study between neurofeedback (theta/beta training) and EMG biofeedback (30 sessions each) showed a reduction of theta/beta quotients in both groups over the course of treatment. However, attention performance, intelligence level, and behavior improved only in the neurofeedback group, and significantly there. In the EMG biofeedback group, on the other hand, there was only an indication of an increase in the work rate in a writing attention test, which was not confirmed in further testing.51
A double-blind study at considerable expense comparing (blind) neurofeedback with sham neurofeedback and alongside (not blind) with Cognitive Behavioral Therapy concluded that neurofeedback can reduce ADHD symptoms as effectively as Cognitive Behavioral Therapy - however, sham neurofeedback was equally effective.52

However, the test design suffers from the fact that the sham neurofeedback group received only 15 sham treatments and 15 regular neurofeedback treatments, while the neurofeedback group received 30 regular neurofeedback treatments. Thus, this is not a true neurofeedback versus sham neurofeedback comparison test.
In addition, it was not apparent from the available abstracts whether the sham feedback was true neurofeedback toward arbitrary target values or whether the feedback was completely decoupled from outcomes.

Provided that the sham feedback represented a true neurofeedback feedback in which only the target values were random or led to a reinforcement away from normal values or meaningful target values, the result that sham neurofeedback (training in arbitrary value changes) is as effective as neurofeedback training toward normalization of brain frequencies could be, could be justified by the fact that sham neurofeedback with random target values also leads to self-control of brain activity, i.e., that any form of brain training (neurofeedback, after all, trains control over brain waves) is as effective as cognitive behavioral therapy. This would require a closer look at the nature of the sham training.

There are other reports of very significant symptom reductions with neurofeedback. However, neurofeedback is not considered to be effective in all sufferers (responder rate 25 to 50%) and may not completely eliminate symptoms even in those who do. For responders, a symptom reduction of 50% is considered a success.

According to a metastudy, several factors improve the effectiveness of neurofeedback therapy:53

  • More intensive treatment (more treatments)
    • But not the duration of treatment (time over which the applications are spread)
  • Use of high quality EEG devices

One study has defined markers that can be used to better predict which ADHD sufferers will respond to neurofeedback and which will not.54

Irrespective of this, parents report a higher improvement compared to teachers. This is reminiscent of the differences in the evaluation of diets, where there is a suspicion that the high cost of the treatment promotes the attitude that this high cost must also result in a high success (bias).53

In another comparison of stimulants and neurofeedback, the drug-treated group performed significantly better, whereas little effect was demonstrated for neurofeedback in 30 treatments.55 Similarly, a comparative study between 25 sessions of SCP or Z-score within 5 weeks with usual care and working memory training found no significant benefits for neurofeedback.56 Several metastudies found no efficacy of neurofeedback compared with placebo or even reduced efficacy of neurofeedback in placebo-controlled trials.575859
How this can be reconciled with the multiple studies of existing efficacy in some sufferers is an open question.

A review came to the following conclusion:60

  • 2 Meta-analyses confirmed significant efficacy of standard neurofeedback protocols for parent- and teacher-rated symptoms, with a medium effect size and sustained effects at 6-12 months.
  • 4 multicenter RCT’s showed significant superiority over semi-active control groups, with intermediate effect sizes at the end of treatment or follow-up and remission rates of 32-47%.
  • Open studies confirmed the effectiveness of neurofeedback
  • No evidence of publication bias was found
  • No significant neurofeedback-specific side effects were reported.

One metastudy found no improvement in executive function in ADHD with neurofeedback.61
A double-blind, randomized controlled trial found efficacy for ADHD on aggression and impulsivity after only 12 one-hour sessions over 6 weeks62
A study of adults with ADHD reports improvements in attention and unclear outcomes related to hyperactivity.63 Neurofeedback combined with cognitive computer games (CCGs) can improve time perception, attention, and working memory in children with ADHD.64
A metastudy of 14 studies of EEG neurofeedback with n = 429 subjects with ADHD found:65

  • significant improvement of attention performance
  • significant EEG-NF-associated positive effect on sustained attention
  • limited improvement of selective attention
  • limited improvement of working memory
  • Beta enhancement protocol worked better than protocols to decrease theta/beta ratio or SCP modulation
  • three sessions per week showed the best effect with EEG-NF
  • Efficacy of surface EEG-NF was significantly lower
  • Improvement in attentional performance persisted unchanged 6-12 months after EEG-NF intervention (3 studies)

In conclusion, standard neurofeedback protocols were considered a well-established treatment for ADHD with moderate to large effect sizes.

5.3. Duration of effectiveness of neurofeedback

Studies suggest that the positive effects from neurofeedback treatment are long-lasting. A meta-study of 165 studies found a long-lasting significant improvement of ADHD symptoms through neurofeedback.66
An elaborate study comparing neurofeedback with stimulant treatment found persistent symptom improvements after discontinuation of stimulants and cessation of neurofeedback training only in the neurofeedback group, which was consistent with persistent changes in EEG in these participants.67
In another study, the effect of neurofeedback was also unchanged 6 months after the end of therapy.27

One study found one year after beta/theta training, the significant improvement in working memory achieved by training continued completely.68 A randomized double-blind placebo-controlled trial of theta/beta training found slight benefits for the treatment group after 25 months, particularly a relatively lower need for medication.69
After 40 neurofeedback sessions with theta-beta training in the areas of50

  • Continued attention
  • Verbal working memory
  • Response inhibition / Impulse inhibition
  • Behavioral problems
  • Academic achievement.

improvements were still present 6 months after the end of treatment.

5.4. Combination neurofeedback and medication

A combination of neurofeedback and methylphenidate was found to be more effective than neurofeedback alone.7071

6. More about Neurofeedback

According to this view, research on ADHD suffers fundamentally from the fact that many studies distinguish their subjects only according to ADHD/non-affected. Since the subtypes of ADHD-HI and ADHD-I differ besides their stress response phenotype (= ADHD symptomatology) especially with respect to different amplitude strengths of brain frequencies, a more precise separation in investigations would be helpful.

Neurofeedback frequency band training is usually only carried out with 1- or 2-channel systems.72 This means that measurements of the brain frequencies occurring there are taken at 1 to 2 points on the skull. Medically approved 1 to 2-channel devices cost from € 3,500.
With only a few EEG channels, it is not possible to spatially localize the measured brain frequencies to specific brain areas. Since in ADHD very specific brain areas show very specific changes in brain frequencies, a spatial allocation would be desirable for some therapies. A frequency band training with 1 or 2 leads hopes quasi “blindly” that the values measured at these 1 to 2 locations “somehow” originate from the affected brain areas. For this purpose, empirical values are used, at which point of the skull the activity of the relevant brain areas is most likely to be measurable. This does not ensure a reliable assignment. However, for some brain frequencies (such as SMR = low beta), a single-channel derivation (for SMR at Cz = center of the skull) has already proven to be quite reliable and practical.
It remains to be hoped that as neurological research continues to develop, multi-channel EEG measurement devices will be used much more frequently and thus become less expensive. It remains to be seen whether the recommended 100 recording channels2 are actually required in therapy for an exact spatial allocation of the measured brain frequencies to individual brain areas, or whether the 19-channel devices described by other researchers as sufficiently reliable (which cost around €20,000 as of 2017) are sufficient for reliable diagnostics and therapy.


  1. Enriquez-Geppert, Smit, Pimenta, Arns (2019): Neurofeedback as a Treatment Intervention in ADHD: Current Evidence and Practice. Curr Psychiatry Rep. 2019 May 28;21(6):46. doi: 10.1007/s11920-019-1021-4.

  2. Strehl (Herausgeber) (2013): Neurofeedback, Kohlhammer

  3. Bailey, Joyce (2015): The role of the thalamus in ADHD symptomatology and treatment. Appl Neuropsychol Child. 2015;4(2):89-96. doi: 10.1080/21622965.2015.1005475.

  4. Gevensleben, Moll, Heinrich (2010): Neurofeedback-Training bei Kindern mit Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung (ADHS); Effekte auf Verhaltens- und neurophysiologischer Ebene; Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie, 38 (6), 2010, 409–420

  5. Kropotov (2008): Quantitative EEG, Event-Related Potentials and Neurotherapy

  6. McVoy, Lytle, Fulchiero, Aebi, Adeleye, Sajatovic (2019): A systematic review of quantitative EEG as a possible biomarker in child psychiatric disorders. Psychiatry Res. 2019 Sep;279:331-344. doi: 10.1016/j.psychres.2019.07.004. REVIEW

  7. Müller, Candrian, Kropotov (2011): ADHS – Neurofeedback in der Praxis, Springer, S. 156

  8. Müller, Candrian, Kropotov (2011): ADHS – Neurofeedback in der Praxis, Springer, S. 157

  9. Bergland (2015): Alpha Brain Waves Boost Creativity and Reduce Depression; Increasing alpha brain waves can stimulate creativity and minimize depression; Psychologytoday

  10. Michalareas, Vezoli, van Pelt, Schoffelen, Kennedy, Fries (2015): Alpha-Beta and Gamma Rhythms Subserve Feedback and Feedforward Influences among Human Visual Cortical Areas; Neuron, Volume 89, Issue 2, 384 – 397, DOI: https://doi.org/10.1016/j.neuron.2015.12.018

  11. Takahashi, Ohmiya, Honda, Ni (2018): The KCNH3 inhibitor ASP2905 shows potential in the treatment of attention deficit/hyperactivity disorder. PLoS One. 2018 Nov 21;13(11):e0207750. doi: 10.1371/journal.pone.0207750. eCollection 2018.

  12. Müller, Candrian, Kropotov (2011): ADHS – Neurofeedback in der Praxis, Springer, Seite 26

  13. Müller, Candrian, Kropotov (2011): ADHS – Neurofeedback in der Praxis, Springer, S. 108

  14. Roh, Park, Shim, Lee (2016): EEG beta and low gamma power correlates with inattention in patients with major depressive disorder. J Affect Disord. 2016 Nov 1;204:124-30. doi: 10.1016/j.jad.2016.06.033. N = 73

  15. Persönliches Gespräch mit einer Neurofeedbacktrainerin 2017

  16. Lee, Park, Jin, Lee, Hahn (2017): Childhood Trauma Associated with Enhanced High Frequency Band Powers and Induced Subjective Inattention of Adults.; Front Behav Neurosci. 2017 Aug 15;11:148. doi: 10.3389/fnbeh.2017.00148. eCollection 2017. n =157

  17. Lee, Park, Jin, Lee, Hahn (2017): Childhood Trauma Associated with Enhanced High Frequency Band Powers and Induced Subjective Inattention of Adults.; Front Behav Neurosci. 2017 Aug 15;11:148. doi: 10.3389/fnbeh.2017.00148. eCollection 2017.n =157

  18. Müller, Candrian, Kropotov (2011): ADHS – Neurofeedback in der Praxis, Springer, S. 167

  19. Kühle, Dr. med Hans-Jürgen, Neurofeedbacktherapie bei ADHS, 2010 (PDF, Download August 2015), Seite 3

  20. Wikipedia: Elektroenzephalografie

  21. Clarke, Barry, McCarthy, Selikowitz (2001): Age and sex effects in the EEG: development of the normal child; Clin Neurophysiol 112(5): 806-814.

  22. Albrecht et al. 2010, zitiert nach Schmitt (2014): Veränderungen des QEEG bei Kindern mit einer ADHS nach Neurofeedback-Training der langsamen kortikalen Potentiale, Dissertation

  23. Clarke, Barry, McCarthy, Selikowitz (2001): Age and sex effects in the EEG: differences in two subtypes of attention-deficit/hyperactivity disorder; Clin Neurophysiol 112(5): 815-826

  24. Schmitt (2014): Veränderungen des QEEG bei Kindern mit einer ADHS nach Neurofeedback-Training der langsamen kortikalen Potentiale, Dissertation, Seite 17

  25. Suffin, Emory (1995): Neurometric subgroups in attentional and affective disorders and their association with pharmacotherapeutic outcome. Clin Electroencephalogr. 1995 Apr;26(2):76-83. doi: 10.1177/155005949502600204. PMID: 7781194.

  26. Chabot, Orgill, Crawford, Harris, Serfontein (1999): Behavioral and electrophysiologic predictors of treatment response to stimulants in children with attention disorders. J Child Neurol. 1999 Jun;14(6):343-51. doi: 10.1177/088307389901400601. PMID: 10385840.

  27. Strehl (Herausgeber) (2013): Neurofeedback

  28. Kropotov, Grin-Yatsenko, Ponomarev, Chutko, Yakovenko, Nikishena (2005): ERPs correlates of EEG relative beta training in ADHD children. International Journal of Psychophysiology, 2005 Jan;55(1):23-34

  29. Zuberer, Brandeis, Drechsler (2015): Are treatment effects of neurofeedback training in children with ADHD related to the successful regulation of brain activity? A review on the learning of regulation of brain activity and a contribution to the discussion on specificity. Front Hum Neurosci. 2015; 9: 135. doi: 10.3389/fnhum.2015.00135, mit weiteren Nachweisen – REVIEW

  30. Holtmann, Stadler, Leins, Strehl, Birbaumer, Poustka (2004): Neurofeedback in der Behandlung der Aufmerksamkeitsdefizit-Hyperaktivitätsstörung (ADHS) im Kindes- und Jugendalter; Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie (2004), 32, pp. 187-200. https://doi.org/10.1024/1422-4917.32.3.187, Seite 191

  31. Kropotov, Grin-Yatsenko, Ponomarev, Chutko, Yakovenko, Nikishena (2005): ERPs correlates of EEG relative beta training in ADHD children. International Journal of Psychophysiology, 2005 Jan;55(1):23-34, n = 86

  32. Zuberer, Brandeis, Drechsler (2015): Are treatment effects of neurofeedback training in children with ADHD related to the successful regulation of brain activity? A review on the learning of regulation of brain activity and a contribution to the discussion on specificity. Front Hum Neurosci. 2015; 9: 135. doi: 10.3389/fnhum.2015.00135 mit weiteren Nachweisen – REVIEW

  33. Mohagheghi, Amiri, Moghaddasi Bonab, Chalabianloo, Noorazar, Tabatabaei, Farhang (2017): A Randomized Trial of Comparing the Efficacy of Two Neurofeedback Protocols for Treatment of Clinical and Cognitive Symptoms of ADHD: Theta Suppression/Beta Enhancement and Theta Suppression/Alpha Enhancement. Biomed Res Int. 2017;2017:3513281. doi: 10.1155/2017/3513281, n = 60

  34. Bluschke, Friedrich, Schreiter, Roessner, Beste (2018): A comparative study on the neurophysiological mechanisms underlying effects of methylphenidate and neurofeedback on inhibitory control in attention deficit hyperactivity disorder. Neuroimage Clin. 2018 Oct 25;20:1191-1203. doi: 10.1016/j.nicl.2018.10.027.

  35. Lin, Huang, Tsai, Chueh, Hung, Chang, Hung (2021): Resting Theta/Beta Ratios Mediate the Relationship Between Motor Competence and Inhibition in Children With Attention Deficit/Hyperactivity Disorder. Front Psychol. 2021 Jun 3;12:649154. doi: 10.3389/fpsyg.2021.649154. PMID: 34149535; PMCID: PMC8211439.

  36. Bluschke, Schreiter, Friedrich, Adelhöfer, Roessner, Beste (2020): Neurofeedback trains a superordinate system relevant for seemingly opposing behavioral control deficits depending on ADHD subtype. Dev Sci. 2020 Feb 27:e12956. doi: 10.1111/desc.12956. PMID: 32107844.

  37. Nan W, Wan M, Jiang Y, Shi X, Wan F, Cai D. (2022): Alpha/Theta Ratio Neurofeedback Training for Attention Enhancement in Normal Developing Children: A Brief Report. Appl Psychophysiol Biofeedback. 2022 Jun 13. doi: 10.1007/s10484-022-09550-6. PMID: 35691974. n = 8

  38. Hao Z, He C, Ziqian Y, Haotian L, Xiaoli L (2022): Neurofeedback training for children with ADHD using individual beta rhythm. Cogn Neurodyn. 2022 Dec;16(6):1323-1333. doi: 10.1007/s11571-022-09798-y. Epub 2022 Apr 1. PMID: 36408061; PMCID: PMC9666577.

  39. Groeneveld, Mennenga, Heidelberg, Martin, Tittle, Meeuwsen, Walker, White (2019): Z-Score Neurofeedback and Heart Rate Variability Training for Adults and Children with Symptoms of Attention-Deficit/Hyperactivity Disorder: A Retrospective Study. Appl Psychophysiol Biofeedback. 2019 May 22. doi: 10.1007/s10484-019-09439-x. n = 139. Volltextlink

  40. Lloyd, Brett, Wesnes (2010): Coherence Training In Children With Attention-Deficit Hyperactivity Disorder: Cognitive Functions and Behavioral Changes; ALTERNATIVE THERAPIES, jul/aug 2010, VOL. 16, NO. 4

  41. Müller, Candrian, Kropotov (2011): ADHS – Neurofeedback in der Praxis, Springer, Seite 26 mit Verweis auf Gevensleben et al 2009, und Strehl et al 2006

  42. Heinrich, Gevensleben, Becker, Rothenberger (2019): Effects of neurofeedback on the dysregulation profile in children with ADHD: SCP NF meets SDQ-DP – a retrospective analysis. Psychol Med. 2019 Jan 24:1-6. doi: 10.1017/S0033291718004130.

  43. Hardman, Gruzelier, Cheesman, Jones, Liddiard, Schleichert, Birbaumer, (1997). Frontal interhemispheric asymmetry: self regulation and individual differences in humans. Neuroscience Letters 221, 117–120, zitiert nach Holtmann, Stadler, Leins, Strehl, Birbaumer, Poustka (2004): Neurofeedback in der Behandlung der Aufmerksamkeitsdefizit-Hyperaktivitätsstörung (ADHS) im Kindes- und Jugendalter; Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie (2004), 32, pp. 187-200. https://doi.org/10.1024/1422-4917.32.3.187

  44. Lim, Poh, Fung, Guan, Bautista, Cheung, Zhang, Yeo, Krishnan, Lee (2019): A randomized controlled trial of a brain-computer interface based attention training program for ADHD. PLoS One. 2019 May 21;14(5):e0216225. doi: 10.1371/journal.pone.0216225. eCollection 2019.

  45. Sampedro Baena, Fuente, Martos-Cabrera, Gómez-Urquiza, Albendín-García, Romero-Bejar, Suleiman-Martos (2021): Effects of Neurofeedback in Children with Attention-Deficit/Hyperactivity Disorder: A Systematic Review. J Clin Med. 2021 Aug 25;10(17):3797. doi: 10.3390/jcm10173797. PMID: 34501246. REVIEW

  46. Holtmann, Stadler, Leins, Strehl, Birbaumer, Poustka (2004): Neurofeedback in der Behandlung der Aufmerksamkeitsdefizit-Hyperaktivitätsstörung (ADHS) im Kindes- und Jugendalter; Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie (2004), 32, pp. 187-200. https://doi.org/10.1024/1422-4917.32.3.187

  47. Fuchs, Birbaumer, Lutzenberger, Gruzelier, Kaiser (2003): Neurofeedback-Behandlung bei Aufmerksamkeitsdefizit-/ Hyperaktivitätsstörung bei Kindern: ein Vergleich mit Methylphenidat. In: Appl. Psychophysiol. Biofeedback, 2003 Mar; 28(1): 1-12; n = 34

  48. Lubar, Swartwood, Swartwood, Donnell (1995): Evaluation of the effectiveness of EEG neurofeedback training for ADHD in a clinical setting as measured by changes in T.O.V.A. scores, behavioral ratings, and WISC-R performance. Biofeedback and Self Regulation 20, 83–99

  49. Monastra, Monastra, George (2002): The effects of stimulant therapy, EEG biofeedback, and parenting style on the primary symptoms of attention-deficit/hyperactivity disorder. Applied Psychophysiology and Biofeedback 27, 231–249. n = 100

  50. Shereena, Gupta, Bennett, Sagar, Rajeswaran (2018): EEG Neurofeedback Training in Children With Attention Deficit/Hyperactivity Disorder: A Cognitive and Behavioral Outcome Study. Clin EEG Neurosci. 2018 Nov 20:1550059418813034. doi: 10.1177/1550059418813034.

  51. Bakhshayesh (2007): Die Wirksamkeit von Neurofeedback im Vergleich zum EMG-Biofeedback bei der Behandlung von ADHS-Kindern, Dissertation, n = 35

  52. Schönenberg, Wiedemann, Schneidt, Scheeff, Logemann, Keune, Hautzinger (2017): Neurofeedback, sham neurofeedback, and cognitive-behavioural group therapy in adults with attention-deficit hyperactivity disorder: a triple-blind, randomised, controlled trial; Lancet Psychiatry. 2017 Aug 9. pii: S2215-0366(17)30291-2. doi: 10.1016/S2215-0366(17)30291-2, n= 113

  53. Bussalb, Congedo, Barthélemy, Ojeda, Acquaviva, Delorme, Mayaud (2019): Clinical and Experimental Factors Influencing the Efficacy of Neurofeedback in ADHD: A Meta-Analysis. Front Psychiatry. 2019 Feb 18;10:35. doi: 10.3389/fpsyt.2019.00035. eCollection 2019.

  54. Shahmoradi, Liraki, Karami, Savareh, Nosratabadi (2019): Development of Decision Support System to Predict Neurofeedback Response in ADHD: an Artificial Neural Network Approach. Acta Inform Med. 2019 Sep;27(3):186-191. doi: 10.5455/aim.2019.27.186-191.

  55. Ogrim, Hestad (2013): Effects of neurofeedback versus stimulant medication in attention-deficit/hyperactivity disorder: a randomized pilot study. J Child Adolesc Psychopharmacol. 2013 Sep;23(7):448-57. doi: 10.1089/cap.2012.0090.

  56. Hasslinger, Bölte, Jonsson (2021): Slow Cortical Potential Versus Live Z-score Neurofeedback in Children and Adolescents with ADHD: A Multi-arm Pragmatic Randomized Controlled Trial with Active and Passive Comparators. Res Child Adolesc Psychopathol. 2021 Sep 3. doi: 10.1007/s10802-021-00858-1. PMID: 34478006. n = 202

  57. Holtmann, Sonuga-Barke, Cortese, Brandeis (2014): Neurofeedback for ADHD: a review of current evidence. Child Adolesc Psychiatr Clin N Am. 2014 Oct;23(4):789-806. doi: 10.1016/j.chc.2014.05.006. REVIEW

  58. Vollebregt, van Dongen-Boomsma, Buitelaar, Slaats-Willemse (2014): 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 May;55(5):460-72. doi: 10.1111/jcpp.12143. REVIEW

  59. Vollebregt, van Dongen-Boomsma, Slaats-Willemse, Buitelaar (2014): What future research should bring to help resolving the debate about the efficacy of EEG-neurofeedback in children with ADHD. Front Hum Neurosci. 2014 May 15;8:321. doi: 10.3389/fnhum.2014.00321

  60. Arns, Clark, Trullinger, deBeus, Mack, Aniftos (2020): Neurofeedback and Attention-Deficit/Hyperactivity-Disorder (ADHD) in Children: Rating the Evidence and Proposed Guidelines. Appl Psychophysiol Biofeedback. 2020 Jun;45(2):39-48. doi: 10.1007/s10484-020-09455-2. PMID: 32206963; PMCID: PMC7250955. REVIEW

  61. Louthrenoo, Boonchooduang, Likhitweerawong, Charoenkwan, Srisurapanont (2021): The Effects of Neurofeedback on Executive Functioning in Children With ADHD: A Meta-Analysis. J Atten Disord. 2021 Oct 26:10870547211045738. doi: 10.1177/10870547211045738. PMID: 34697957. METASTUDY

  62. Dashbozorgi, Ghaffari, Karamali Esmaili, Ashoori, Moradi, Sarvghadi (2021): Effect of Neurofeedback Training on Aggression and Impulsivity in Children With Attention-Deficit/Hyperactivity Disorder: A Double-Blinded Randomized Controlled Trial. Basic Clin Neurosci. 2021 Sep-Oct;12(5):693-702. doi: 10.32598/bcn.2021.2363.1. PMID: 35173923; PMCID: PMC8818111. n = 40

  63. Fan HY, Sun CK, Cheng YS, Chung W, Tzang RF, Chiu HJ, Ho CN, Hung KC (2022): A pilot meta-analysis on self-reported efficacy of neurofeedback for adolescents and adults with ADHD. Sci Rep. 2022 Jun 15;12(1):9958. doi: 10.1038/s41598-022-14220-y. PMID: 35705685.

  64. Moradi, Rajabi, Mansouri Nejad (2022): The effect of neurofeedback training combined with computer cognitive games on the time perception, attention, and working memory in children with ADHD. Appl Neuropsychol Child. 2022 Aug 24:1-13. doi: 10.1080/21622965.2022.2112679. PMID: 36002025.

  65. Chiu HJ, Sun CK, Fan HY, Tzang RF, Wang MY, Cheng YC, Cheng YS, Yeh PY, Chung W (2022): Surface electroencephalographic neurofeedback improves sustained attention in ADHD: a meta-analysis of randomized controlled trials. Child Adolesc Psychiatry Ment Health. 2022 Dec 19;16(1):104. doi: 10.1186/s13034-022-00543-1. PMID: 36536438; PMCID: PMC9764556.

  66. Moreno-García, Cano-Crespo, Rivera (2022): Results of Neurofeedback in Treatment of Children with ADHD: A Systematic Review of Randomized Controlled Trials. Appl Psychophysiol Biofeedback. 2022 May 25. doi: 10.1007/s10484-022-09547-1. PMID: 35612676. METASTUDY

  67. Monastra, Monastra, George (2002). The effects of stimulant therapy, EEG biofeedback, and parenting style on the primary symptoms of attention-deficit/hyperactivity disorder. Applied Psychophysiology and Biofeedback 27, 231–249. n = 100

  68. Dobrakowski, Łebecka (2019): Individualized Neurofeedback Training May Help Achieve Long-Term Improvement of Working Memory in Children With ADHD. Clin EEG Neurosci. 2019 Oct 3:1550059419879020. doi: 10.1177/1550059419879020.

  69. Neurofeedback Collaborative Group (2022): Neurofeedback for Attention-Deficit/Hyperactivity Disorder: 25-Month Follow-up of Double-Blind Randomized Controlled Trial. J Am Acad Child Adolesc Psychiatry. 2022 Dec 12:S0890-8567(22)01971-2. doi: 10.1016/j.jaac.2022.07.862. PMID: 36521694.

  70. Pakdaman, Irani, Tajikzadeh, Jabalkandi (2018): The efficacy of Ritalin in ADHD children under neurofeedback training. Neurol Sci. 2018 Sep 5. doi: 10.1007/s10072-018-3539-3.

  71. Lin FL, Sun CK, Cheng YS, Wang MY, Chung W, Tzang RF, Chiu HJ, Cheng YC, Tu KY (2022): Additive effects of EEG neurofeedback on medications for ADHD: a systematic review and meta-analysis. Sci Rep. 2022 Nov 27;12(1):20401. doi: 10.1038/s41598-022-23015-0. PMID: 36437272; PMCID: PMC9701807.

  72. Strehl (Herausgeber) (2013): Neurofeedback, Kohlhammer, Seite 62