General Questions

How Does it Work?
We apply electrodes to the scalp to listen in on brainwave activity. We process the signal by computer, and we extract information about certain key brainwave frequencies. (All brainwave frequencies are equal, but some are more equal than others…) We show the ebb and flow of this activity back to the person, who attempts to change the activity level. Some frequencies we wish to promote. Others we wish to diminish. We present this information to the person in the form of a video game. The person is effectively playing the video game with his or her brain. Eventually the brainwave activity is “shaped” toward more desirable, more regulated performance. The frequencies we target, and the specific locations on the scalp where we listen in on the brain, are specific to the conditions we are trying to address, and specific to the individual.
If neurofeedback is so effective, why don’t more people know about it?

It was first discovered in the 1960’s that people could control their brainwave patterns. Because the field was in its infancy, research was conducted at very few institutions. Results were published in highly specialized scientific journals with which health care providers were largely unfamiliar. For these reasons, the possibilities of this powerful tool have not become well known among physicians or the general public. This is now changing. Advances in computer technology have enabled neurofeedback to emerge from the laboratory to become a useful clinical tool in the offices of mental health providers.

What is neurofeedback? What is biofeedback?

NEUROFEEDBACK is a specialized form of BIOFEEDBACK.

NEUROFEEDBACK is a painless, non-invasive technique used to train the brain to improve its functioning. An individual receives instantaneous information (feedback) about whether the brain is moving towards or away from optimal function. It may be thought of as a kind of exercise for the brain: a retraining of the way the brain organizes itself.

When the brain is out of balance, people can experience a wide range of problems that affect learning, mood, sleep, concentration, and behavior. Neurofeedback training brings these problems gradually under control.

BIOFEEDBACK is a non-invasive technique by which people learn to use signals from their own bodies to improve their health. Various instruments (from sophisticated machines to simple hand-held thermometers) are used to provide information to individuals on the state of bodily processes about which they are normally unaware. They are then trained to adjust these states to ease a wide range of symptoms.

During a training session, measurements of a relevant physiological process (for instance, skin temperature, muscle tightness, or brainwave pattern) are continuously made. At the same time information (that is, feedback) is given to the individual about whether the measurements indicate optimal functioning, or are in a range that is indicative of symptoms they wish to relieve. The individual receives this feedback in the form of a musical tone, a computer graphic, or the continued playing of a movie.

Are personalities changed by the training?

Neurofeedback training does not change underlying personality. It may be seen, however, that when some adverse behavior problems are remediated, the intrinsic innate personality will be more in evidence. For example, in the beginning it may be difficult to dissociate irritability, hot-headedness, or cruelty from a child’s personality. After that behavior disappears, it is easy to understand that it was never a part of the child’s intrinsic personality.

Is there a minimum age required for training?

We have had success working with children as young as four years old and adults as old as 78. There is no upper age limitation for neurofeedback treatment.

Are there side effects associated with neurofeedback training?

For most conditions, there are no adverse side effects due to the training when conducted by a competent professional. If an occasional negative reaction to training does occur it tends to wear off quickly, or it can be trained away by the clinician, or both. Interestingly, our clients often note positive side effects. Someone undergoing training to treat migraines, for example, may report improved sleep, concentration, or mood.

How long do results last?

In most instances, once the brain has learned how to perform at its optimum level it retains this functioning. Think about learning to ride a bicycle. Remember how difficult that was? Did you fall? And then, after a while, you didn’t even have to think about balancing anymore? At a subconscious level, your brain was sending messages to your muscles to do what they needed to do to keep you upright. Even if you haven’t ridden a bicycle in years, if you were to get on one today your brain would quickly remember what it is supposed to do to help you remain balanced.

This is what happens through neurofeedback training. We train your brain to work in a way that will help keep you “balanced.” You will not need to concentrate consciously on what you need to do to “stay relaxed” (for example). Your brain will simply function the way it needs to, in order for you to be comfortable.

There are a few instances when we have observed that several “booster” sessions might be needed:

  • If the client has been involved in a long-term traumatic situation (for example, an abusive relationship or a family member suffering from a prolonged and difficult illness).
  • If the client has undergone long-term medical help (such as chemotherapy).
  • If the client has experienced a head trauma after training is completed (such as an automobile or skiing accident involving brain trauma).
  • If the client’s main presenting problem is depression. Often people who receive neurofeedback for depression will benefit from one to three booster sessions a few times per year.
  • If the client is still growing. Young children will often have to return for booster sessions as their brain and body develop.
Why does neurofeedback work?

The brain is amazingly adaptable. It is capable of making adjustments to improve its own performance if given cues about what to change. When the brain is regulating itself well and is alert and attentive, brainwaves (EEG) show particular patterns. We challenge the brain to maintain this “high-performance” alert and active state. Gradually, after 20 or more training sessions, the brain learns to stay at this high-performance state for longer periods of time and to retain these new skills.

How long do neurofeedback sessions take?

Each session takes between 45 and 60 minutes. The actual training period lasts a maximum of 30 minutes. Additional time is needed beforehand for sensor placement and adjustment. We also speak with our clients briefly before and after each training session to monitor how things are progressing. We reserve 60 minutes for each client to ensure that no one is rushed and that there will be time to discuss the results you are experiencing.

How frequent should the training sessions be?

When starting neurofeedback training, it is optimal that sessions be regular and frequent at two or three (or more) sessions per week. It is possible to do more than one sessions in a day or to have sessions on two or three consecutive days. As learning begins to consolidate, the pace can be reduced. If it is not possible to accommodate two or three sessions per week neurofeedback will still be just as beneficial, though it may be a longer period of time before lasting improvement is achieved.

How will I know when to reduce or stop my medication?

Neurofeedback is not “anti-medication.” We see the two methodologies working together, not against each other. Medication helps support brain function while the brain is learning what it needs to adjust. We tell clients to stay in close contact with their physicians and watch for symptoms of overmedication.

When working with hyperactive children, for example, a parent might report after the tenth session that their child is having trouble sleeping and is irritable (symptoms of stimulant side effects). We would suggest that the child’s doctor be consulted about reducing the child’s medication to see if the problems are remediated. In most cases, this proves to be the solution. As the brain becomes more efficient, it needs less pharmacological help to work optimally.

Do I have to stop taking my medication while doing neurofeedback training?

There may be a time when we might suggest—with your physician’s approval—that you temporarily not take some types of medication. This generally occurs before we administer an attention/cognition test (so we can get a baseline score) or before a brain map is done. We never suggest that a person stop any medication taken for physical conditions such as heart problems, seizure disorders, or blood pressure. Any changes in your medical regime must be made under your medical doctor’s supervision.

Will I be able to stop taking my medications?

Initially, neurofeedback usually supports medication dosages and clients tend to feel better while on their current doses. As training progresses and brain function improves, some clients may actually begin to experience symptoms of overmedication. At this point the client is referred to their physician, who would oversee any medication changes. Many of our clients have reported either that they no longer need their medications or that they are able to reduce the amounts needed after completion of neurofeedback training. However, if the goal is to stop taking medications, you should plan on a larger number of neurofeedback sessions.

What else can I do to support the neurofeedback brain training, to make it work better, or make it more likely to be effective?

The single most important factor is observing very carefully after each session to see what changes there may be and reporting those to us consistently after very session using our between-session reports.  Other than that, the general factors that have been associated with brain health are helpful. Get enough sleep. Eat a balanced diet with whole rather than highly processed foods. Make sure you get enough Omega 3 fatty acids, through your diet or with supplements. Get regular aerobic exercise.  Avoid excessive screen time and engage in a wide variety of activities that stimulate.

Do you have to be able to intentionally apply the strategies you learn in neurofeedback to have the benefits in daily life?

No. Neurofeedback is a way to retrain the brain to function better. It is not a matter of learning strategies to consciously apply, and then using those strategies in everyday life. What is important is that when it is effective, it results in brain change. And it is that changed brain that goes about the business of helping you adapt successfully in life.
You can think of it as like working out in a gym. You get stronger, more flexible, more fit. But you don’t have to think what you were thinking when you worked out in the gym in order to be strong, flexible, and fit during your daily life. Your retrained body takes care of that naturally, as does your retrained brain.

Does the person who is training have to know or understand how neurofeedback works? Does the trainee have to want to change his/her brain?

No. Studies have shown that neurofeedback can alter brain function in cats, rats, and monkeys. What is most important is that a reward or signal is given when the desired brain response is shown. The cats, rats, and monkeys were not trying to change their brains. They just liked it when they got rewards. However, we always want the person who is training to understand as best he/she can and to want to reach the goals or outcomes for training that have been established. The whole process makes much more sense if you understand that you can do better in life if you improve the brain function in the part of the brain involved in those functions. For example, “I want to be able to pay better attention when I play baseball. The front part of my brain helps me pay attention. So I want to make that part of my brain stronger so my attention is better.”

Will the benefits from neurofeedback last?

There have been multiple follow-up studies to answer this question. Follow-up research has been done on neurofeedback for ADHD, autism spectrum disorders, and PTSD. The period of follow-up has ranged from six months to three years. All of them show that the gains from neurofeedback last over the period of follow-up. Several studies showed continued improvement after the training ended. However, much more follow-up research needs to be done, and over longer periods of time.
Please remember though that these results are averages. If on average the gains last, still there may be individuals within the group whose gains do not last. In practice, we have found that for some individuals, the benefits from neurofeedback have lasted. Others need occasional booster sessions, say three or four times a year. Some though have required ongoing training at home to maintain their improvement. This is usually with more severe and more chronic problems.

What Does Brain-training Help

IQ Improvements?

Studies have shown that I.Q. scores generally raise 10 to 20 points after training. This is not because neurofeedback makes people smarter; it simply helps their brains become more efficient and flexible.

Cognitive Disabilities

We have had success working with clients with brain injuries and those suffering from many types of disabilities. Neurofeedback helps the brain become more efficient so that it works at its best capacity, whatever that capacity might be. If someone’s brain has been injured by a stroke or through surgery, the brain learns to “reroute” signals to create new neuronal pathways.

Neurofeedback works with learning disabilities as well. Brain regions and networks involved with learning (such as word recognition, reading comprehension, expressive language, etc.) can be strengthened, thus improving performance.

Alzheimer’s & Dementia

When neurofeedback is used for those suffering from Alzheimer’s or dementia, it is called “brain brightening.” Neurofeedback cannot improve the physical degeneration of the brain. What it can do is help the brain access areas of itself that have not yet been affected by the condition, which can slow symptom progression and thereby improve quality of life.

Anxiety And Panic Attacks

The most common use of biofeedback over the past twenty years has been in relaxation and stress management. This training is useful principally with various anxiety states which can be worsened by stressful situations. Anxiety states include such reactions as panic attacks and phobias at one extreme, and such problems as performance anxiety and stage fright on the other. When the person is challenged to perform in some way, the brain reacts by overly heightened vigilance that actually undermines ability to function well. This problem can compound itself, as the person becomes anxious, observes himself or herself becoming anxious, and becomes even more anxious. At a time of future challenges, the anxiety response can be more readily kindled because of the memory of earlier failure to perform.

We see anxiety as one manifestation of diminished self-regulation by the brain. The condition is often quite obvious in the EEG. The condition is highly responsive to brainwave training. By challenging the brain to regulate itself better, it subsequently also functions better under life’s normal (and unusual) challenges. Once the brain has been trained to self-regulate the mechanism by which it gears up for the challenges it faces (the regulation of physiological arousal), then the brain is no longer as vulnerable to the downward spiral of anxiety.

During EEG training for anxiety, the person is shown information derived from his or her EEG in real time, and is asked to bring certain aspects of it under control. This training repeatedly challenges the brain to improve its own internal regulatory processes. The training is not intimidating in itself because we adjust the level of difficulty to the situation.

As with other learning, the process is largely accomplished at a subconscious level. After all, we don’t generally have any awareness of the mechanisms by which the brain regulates its own activities. However, there may very well be some conscious awareness of changes taking place as the training proceeds. For example, the trainee will usually observe times when the EEG reflects existing anxiety states. The trainee then brings his skills to bear to bring these states under control. As mastery improves, the person gains confidence in his ability to control and regulate these states. The improved level of confidence further supports the process, and allows the person to work at a higher level of difficulty.

We find that most persons who undertake the training gain significantly in their ability to control anxiety and panic states, to the point that these no longer interfere with the conduct of their life. The learning that takes place leaves the brain in a better condition to operate calmly and stably. After completion of the training, which may take approximately twenty sessions (possibly more in severe cases), no continuing willful effort is required to control anxiety or panic. On the other hand, the training will also have given the person skills that can be consciously employed to aid in shifting to a more relaxed and appropriate high-performance state, if that should be necessary. Since the technique is based on learning, it is unlikely to require followup sessions after completion of the initial training sequence.

Learning Disabilities

EEG Biofeedback (also known as neurofeedback) is gradually becoming known and recognized for its utility in remediating Attention Deficit Disorder. Less well known is its emerging application to specific learning disabilities. This is surprising for several reasons. First of all, more children are affected by specific learning disabilities than are diagnosed with ADHD, so EEG biofeedback could potentially have a much larger impact there. Secondly, there is no claim that stimulant or anti-depressant medication is terribly helpful with learning disabilities, so that EEG biofeedback does not challenge and compete with an already accepted treatment. Thirdly, there is no claim that specific learning disabilities are “medical conditions.” To be sure, they certainly have a physiological foundation. However, they cannot be addressed by the usual remedies in the arsenal of the medical practitioner. Hence treatment with EEG training for learning disabilities does not get caught up in the third-party payer maelstrom or in the diagnostic ambiguity of whether something does or does not “qualify” as a bona fide learning disability. Finally, it is surprising because there is probably as much early research backing EEG biofeedback for learning disabilities as there is for Attention Deficit Disorder. The latter application has been criticized for a lack of robust research under controlled conditions. Ironically, part of the reason is that the early research was not exclusively focused on attention problems, but rather on learning disabilities as well.

Perhaps for this reason, much of the early work with EEG biofeedback in connection with attention and learning problems emphasized assessment of academic skills rather than behavioral measures. These had the advantage of being very objective, but at the same time they did not meet the expectations of researchers who had a focus on ADHD. These researchers have ever since called attention to a dearth of behavioral data, despite their notorious subjectivity.

The first significant study of both attention and learning problems using EEG biofeedback was performed by Joel and Judith Lubar (Lubar, 1984). The study reported on six children who had undergone the training. The motivation was that seizure disorders, ADHD, and specific learning disabilities were often characterized by elevated low-frequency (less than 10Hz) activity in the EEG (Lubar et al, 1985). Such elevated activity could be seen as disruptive to the ongoing mental activities, possibly either causing or exacerbating learning disorders. It had already been shown to be possible to control seizure susceptibility and hyperactivity with EEG training that attempted to “train down” the low frequency activity at the same time that certain higher-frequency activity is promoted (12-18 Hz) (Sterman, 1978). Could the same training impinge on learning disorders as well? The results of this initial study were highly promising in this regard, although they were compromised by the fact that five of the children were receiving other special academic support as well during the period of the study.

Moreover, the Lubars were not alone. Tansey and Bruner published a single case study of a child with both attention and learning problems in the same timeframe (Tansey, 1983). In this case, both conventional biofeedback and EEG biofeedback were used, so the interpretation of the results remained ambiguous. Tansey published a study of four children in 1985 in which the focus was learning disorders rather than attentional deficits, and this was the first of many studies in which improvements in IQ score were documented for EEG training. In a follow-up study using 24 subjects with learning disorders (Tansey 1990), an average improvement in Wechsler full-scale IQ score of 19 points was demonstrated, which was quite impressive. The improvements in performance IQ (deemed to reflect more right hemisphere function) was +19 points, and the improvement in verbal IQ (deemed to reflect left hemisphere function) was +16 points. Of the 24 children in the study, 11 had been diagnosed as neurologically impaired, 11 were judged perceptually impaired, and only two were diagnosed with ADD.

Our own clinical study for replication purposes took place in 1990-1991, and also emphasized academic skills assessments over behavioral measures (Othmer, 1991). In a study of 15 subjects, an average WISC-R improvement of 23 points was found (with independent testing). The improvement ranged from 7 points to 35. Thus every study participant improved his IQ score, and most did so significantly. Academic skills were also assessed with the Wide Range Achievement Test (WRAT), and on this test there was more of a divergence in outcomes than was the case for the IQ test. Only ten of the 15 children were evaluated with the WRAT. In the reading test, only one child scored below grade level at the outset. That child improved more than three grade levels with the training, and reached age-appropriate norms. Five other children significantly advanced their reading performance above grade level, in rank order by +5.6 years, + 4.5 years, +4.2 years, +3.5 years, and +2 years. Since only one child was reading below grade level initially, not much can be discerned from this about reading disabilities. On the other hand, the striking gains experienced by some children does indicate that the training had an effect on some of the mechanisms underpinning the reading process. It may be argued that the training moved them closer to their native reading ability.

By contrast, in the arithmetic test of the WRAT, nine of the ten children scored in deficit at the outset. After training, five had shown significant improvement: +7.6 years, +2.7 years, +2.3 years, +2 years, and +1.6 years. Two more treaded water, with gains of one year (whereas the test-retest interval in the study was nine months). One child tested the same on the retest, and two, sad to say, actually scored worse (although one of these remained way above grade level, and could be considered a case of regression to the mean). It is noteworthy that in some children major improvements were observed, whereas in others there was negligible change. This discrepancy could even be seen within the same child. For example, the child whose deficit in math performance worsened actually soared in terms of reading!

It is tempting to suggest that the training protocol employed in this study fortuitously happened to be what certain children needed in order to break the relevant bottleneck in reading or arithmetic ability. These tasks, it is now known from imaging studies, require certain cortical regions to activate in a timely manner and to communicate with one another for overall task completion. A training protocol that uses a single electrode placement on the scalp may not reasonably be expected to address all possible shortcomings in terms of local activation and intra-cortical communication involved in such complex processes as reading and arithmetic computation.

And then there is dysgraphia. No one fails out of school because of an inability to draw, so this particular disability does not get much attention, except perhaps from those who do assessments on children. The inability to draw reflects more on right hemisphere skills, and on inter-hemispheric communication. Whereas this disability may be harmless in itself, it can be an indicator for other deficiencies in right hemisphere skills that could indeed be important. To assess drawing skills, children are asked to draw their family during the intake interview. We have seen many children improve with the training from the point at which they are drawing stick figures to where they acquire full-bodied relatives-all within the span of a few weeks, with some twenty to forty training sessions.

It is the lack of systematic, predictable success with learning disorders-more than perhaps any other reason-that has kept the professional community of EEG biofeedback practitioners from promoting this application more overtly. However, the very striking results that can be achieved with many children also place an obligation on us to make this information available. As long as the potential trainee is aware of the finite likelihood of success, he should certainly have the opportunity to train. Clinicians have an understandable reluctance to promote a technique where the outcome may be so highly variable, in addition to being unpredictable, particularly in a field that is still trying to gain recognition by the mainstream educational and medical communities.

For the future, things look very bright indeed. The new imaging studies give us indications for what protocols to try in order to improve the likelihood of success. For example, Shaywitz et al (1998) recently published a study on PET scans in dyslexic subjects. Regions of heightened oxygen uptake may reflect areas where reading is being bottlenecked in such subjects. It is relatively straight-forward to try a variety of training schemes involving the identified sites. The combination of functional imaging and EEG biofeedback may yield near-term breakthroughs in the remediation of various specific learning disabilities that have been relatively intractable to date.

References

Lubar, J.O., and Lubar, J.F. (1984).
Electroencephalographic biofeedback of SMR and beta for treatment of attention deficit disorders in a clinical setting.
Biofeedback and Self-Regulation, 9 (1), 1-23.

Lubar, J.O., Bianchini, K., Calhoun, W., Lambert, E., Brody, Z. and Shabsin, H. (1985)
Spectral analysis of EEG differences between children with and without learning disabilities.
Journal of Learning Disabilities, 18, 403-408.

Othmer, S., Othmer, S.F., and Marks, C. (1991).
EEG biofeedback training for attention deficit disorder, specific learning disabilities, and associated conduct problems.
Web-published, www.eegspectrum.com. Available as a Monograph from EEG Spectrum, Encino, CA.

Shaywitz SE, Shaywitz BA, Pugh KR, Fulbright RK, Constable RT, Mencl WE, Shankweiler DP, Liberman AM, Skudlarski P, Fletcher JM, Katz L, Marchione KE, Lacadie C, Gatenby C, Gore JC (1998)
Functional disruption in the organization of the brain for reading in dyslexia.
Proc Natl Acad Sci U S A 95(5), 2636-2641

Sterman, M.B. and MacDonald, L.R. (1978)
Effects of central cortical EEG feedback training on incidence of poorly controlled seizures.
Epilepsia, 19(3), 207-222.

Tansey, M., and Bruner, R. (1983)
EMG and EEG biofeedback training in the treatment of a 10 year old hyperactive boy with a developmental reading disorder.
Biofeedback and Self-Regulation, 4, 299-311.

Tansey, M. (1990)
Righting the rhythms of reason: EEG biofeedback training as a therapeutic modality in a clinical office setting.
Medical Psychotherapy, 3, 57-68.

Migraine

EEG Biofeedback Training for Tension Headaches and Migraines

Over the last five years of clinical work in EEG biofeedback training, it has become apparent that the technique can be extremely helpful in the remediation of headache syndromes. This includes both conventional headaches often referred to as “tension” headaches, and also migraine headaches. With respect to migraine headaches, two types are identified for EEG training purposes: 1) precipitated by PMS or food allergies; and 2) precipitated by stress.

Although the EEG biofeedback training is not necessarily, or even ordinarily, done during the symptomatic phase, the training can have an immediate effect on headaches. Thus it is often our experience that a person with a conventional headache may have it eliminated, or significantly reduced in severity, within a half hour session. To a lesser degree, this is also true of migraine headaches, for which we have experienced roughly 50% incidence of reduced severity within a 30-minute training session.

EEG training can therefore induce a change in physiological state which causes the headache to “melt away”. This immediate benefit may be appreciated, and may be taken as an indication that the training is effective. However, the objective is to train the brain so that it has a higher threshold for headache onset in general. That is, the training is aimed at improved self-regulation, so that the brain is much less vulnerable subsequently to the factors which may have triggered headaches previously. This is a learning process, which requires a certain number of training sessions. With a successful outcome, however, the trainee may experience an essentially headache-free existence. Many graduates have reported being free of migraine headaches for several years after undertaking the EEG training.

There are causes of headaches which we do not expect to impact with this training. For example, “sinus headaches”, in which congestion may be the precipitate cause of the headache, no remedy is to be found or expected in EEG biofeedback. One must deal with the underlying cause instead. However, many headaches can be thought of as stress-related, particularly if we take the word “stress” in its inclusive sense, namely that the brain is in a less than optimal state because of “stressors” in the person’s life. In these instances, teaching the brain to self-regulate better affords it a higher stress tolerance.

With conventional headaches, a complete training regimen may require only about ten training sessions. For migraine headaches, the training regimen may be somewhat longer. In all cases, testing with the T.O.V.A. is helpful in order to assess the person’s attentional skills. Attention is one of the most fundamental of brain processes. Assessing how the person pays attention has been found to be also a good indicator of status of brain self-regulation, as well as of the appropriate EEG training protocol to effect remediation. The success rate for headaches has been extremely high. More than 80% of persons who complete the training regimen report remediation of headache syndromes.

Autoimmune Dysfunctions

There is much empirical evidence that EEG biofeedback training can help remediate the symptoms of autoimmune disease such as diabetes, rheumatoid arthritis, or lupus. In diseases such as this, the immune system is at war with the normally functioning body, in that it has failed to discriminate properly what is self from what is not-self. There is no suggestion that the biofeedback training in any sense reverses the course of the disease process. However, it is quite generally observed that persons afflicted with these conditions may be relieved of much of their pain; they may be more robust and energetic with the training; and they may not be as heavily impacted by flare-ups of the condition.

If the training is going to be helpful, this will usually be noticed by the individual during the first six to ten sessions, and the judgment can then be made as to whether it is worthwhile to continue the training. It is often helpful to employ the T.O.V.A. test as a measure of mastery of attentional variables, and it can be used as a measure of progress in the training.

In the case of Type I diabetes, a condition in which the body has lost its ability to fabricate insulin by virtue of autoimmune disease, EEG biofeedback training can provide a greater tolerance to variations in glucose level. Subjects report being more energetic and robust. They also report reduced pain associated with peripheral neuropathy, which is observable in advanced stages of the condition. In the case of Type II diabetes, which is more of a problem in glucose regulation, the necessity of providing supplemental insulin may be entirely avoided; insulin requirements may significantly reduce; and the person may feel the benefit of improved self-regulation in terms of higher energy level, better sleep, focused attention, and reduced mood volatility.

In the case of rheumatoid arthritis, persons undergoing the training may have pain relieved sufficiently that they no longer require pain medication. There may be a second mechanism of action for the training in this case, namely on the pain threshold directly. When pain persists at a certain location, the normal body response is to heighten sensitivity to that pain, i.e. a lowering of the pain threshold locally. The training may restore a normal pain threshold and disrupt the chronic pain mechanism. We assume a direct influence on the pain mechanism because of the rapidity with which EEG biofeedback can be effective. We are aware of no alternative mechanism which could respond so rapidly.

In the case of lupus, we have empirically observed benefit of the training in terms of the severity of flare-ups of the condition. The training appears to confer a prophylactic benefit, and is therefore conducted irrespective of whether the patient is symptomatic. Additionally, however, the training can confer benefits during the acute episodes as well.

Finally, we observe that women with breast implants often manifest symptoms which resemble those of the autoimmune diseases

PMS

Pre-Menstrual Syndrome, or PMS, exhibits symptoms which are highly variable among individuals. It can best be regarded as a condition of disregulation for which cyclic hormonal variations provide the stressor. EEG biofeedback has been surprisingly effective in stabilizing individuals through these hormonal cycles. To date, these findings are strictly clinical. That is, no controlled research has yet been published. In fact, EEG Spectrum is currently conducting a multi-site study of PMS with EEG biofeedback. Preliminary results being achieved in the context of this study are quite striking. The study is on-going, and interested clients are encouraged to apply for participation in the study.

PMS symptoms include a variety of physical and emotional symptoms associated with a specific phase of the menstrual cycle. Emotional symptoms include irritability, mood swings, anxiety, and depression. Also reported is less interest in the usual activities, fatigue, trouble concentrating, change in sleep or appetite, and various physical symptoms, including pain and migraines. These symptoms must be correlated with the premenstrual phase only and must be sufficient to result in serious impairment of relationships or interference with activities in order to be regarded as clinically significant.

Many of the PMS symptoms are characteristic of depression as well, and indeed PMS may be seen as a depressive syndrome. Antidepressant and antianxiety medications often provide relief from some emotional PMS symptoms. Medical management must be maintained continuously, and generally involves some undesirable side effects. The lack of successful medical management again augurs well for a biofeedback intervention. The fundamental issue is “disregulation”, for which the remedy is “reregulation”, rather than the more unilateral intervention implied by anti-depressants or anti-anxiety medications.

Intervention with EEG biofeedback has been found clinically to be very helpful to individuals suffering from both physical and emotional PMS symptoms. Most of these individuals were referred for specific symptoms which troubled them, rather than for “PMS”. However, these symptoms were related to the menstrual cycle in the classical temporal PMS pattern. Regardless of whether a person was referred for PMS or for specific symptoms, the training of the person revolved to a large degree around the constellation of symptoms associated with PMS.

EEG training for PMS typically requires 20-30 sessions. Our ongoing clinical research program stipulates 24. For those who complete the program of 24 sessions, favorable outcome is achieved by about 90% of women, by the criterion of effective remediation of symptoms (i.e., residual symptoms no longer inhibit activities or impinge adversely on relationships). The benefits are found to be retained for many months to years.

The symptom relief experienced by those who successfully complete the program includes all of the emotional symptoms associated with PMS, and the physical symptoms, including migraines. Some reach the point where they are essentially symptom-free, and do not experience the usual prior notice of the onset of menses. Favorable experience has also been observed with dysmenorrhea, and with such symptoms as excessive bleeding. The data on such phenomena are isolated and anecdotal.

Chronic Pain

EEG biofeedback has been shown to be very helpful with chronic pain. Since these results may be somewhat unexpected, they present perhaps the best challenge to our understanding of the mechanisms of EEG biofeedback. When we regard pain sensors alongside other sensory systems, such as vision and hearing, we observe a unique distinguishing characteristic. In the general case, when human sensory systems are presented with a constant stimulus there is a gradual decrease in response to that stimulus. The only known exception to this general rule is the body’s pain response to persistent challenge. In this case, the response is to gradually *increase* sensitivity to the stimulus, i.e. a lowering of the local pain threshold. Thus pain can survive even when the original provocation is removed, resulting in chronic pain. A self-sustaining interaction takes place between the cortex and the apparent source of the pain, perpetuating the sensation of pain. This explanation by no means denies the reality of the pain experience.
It simply defines it in terms of a self-reinforcing, self-sustaining activity involving the brain as well as the “periphery”. That is, the brain defines what is to be perceived as painful.

A striking correlation has been observed between the occurrence of chronic pain and a history of abuse or trauma in childhood. One study found that such abuse was present in as many as 85% of cases of chronic pain. Clearly, then, more than a “purely” physiologically-based phenomenon is at issue. Why, then, should a technique which appeals strictly to the underlying physiology be effective? We conjecture that there is a mutual relationship between the phenomenon of chronic pain and a state of depression. The physiological state of depression (to which the person may be susceptible due to the prior abuse) may bring in train disregulation of the pain threshold; or the causal chain may go the other way: the persistence of chronic pain may bring about a chronic state of depression, to which the person is particularly vulnerable. In any case, we observe symptoms characteristic of underarousal. The EEG training is presumptively effective in remediating the chronic underarousal condition, effecting a normalization of mood and of the pain threshold. Effectively, then, the brain has simply recalibrated the pain threshold. It no longer interprets the incoming stimuli as being sufficient to constitute “pain”.

This view may, however, be an oversimplification. Frequently, persons undergoing the EEG training for chronic pain will, after a few sessions, experience vivid recollections of long-suppressed traumatic memories. This occurs with such regularity that we always encourage persons undergoing the EEG training for chronic pain to undergo concurrent therapy as well, in order to deal with what comes up. In the larger view, then, the remediation we effect may involve dealing comprehensively with the larger, underlying issues which manifest in chronic pain and in depression.

Undoubtedly both mechanisms play a role during the full course of EEG training. In case there is any doubt, however, about the specific role and benefit of EEG training in remediation of chronic pain, it should be said that the two mechanisms operate on very different time scales. Reports of alleviation of pain can occur even within the first session; further progress can be charted from one session to the next. The surfacing of suppressed memories may not take place until sessions 6-15, and the therapeutic benefit of adjunctive therapies not until after that. Hence, there is clearly a role implied for the EEG training.

It is noteworthy that the field of pain management has seen the first truly comprehensive, multi-disciplinary approach emerge, one in which biofeedback plays an indispensable role. Up to the present time, the predominant use of biofeedback has tended to be relaxation training. The implications of our work with EEG training to remediate chronic pain are that emphasis should perhaps be placed more on the achievement of regulation and control, rather than relaxation.

Chronic Fatigue Syndrome

Over the past four years, we have observed considerable clinical evidence for the effectiveness of EEG biofeedback training as an adjunct modality for remediating the symptoms of Chronic Fatigue Syndrome (CFS), or Chronic Fatigue Immune Deficiency Syndrome (CFIDS). The training appears to help symptoms of depression, cognitive deficits, memory and concentration problems, sleep disturbances, and chronic pain such as headaches. It also increases energy level. When it is used with persons who are not entirely disabled by the condition, it has allowed some of them to return to full-time productive activity within a matter of weeks. In more severe cases, the impact of the training is generally felt to be helpful, but full remediation has not been demonstrated in such cases.

The mechanism of action appears to be that the EEG training impacts on the regulation of arousal, and it increases the brain’s regulation of its own functions. It does this by monitoring brainwave activity, and restoring it, by operant conditioning, to more normal ranges. The process is largely unconscious. The biofeedback modality simply makes available the necessary information upon which the brain then acts. No claim is made that the training directly addresses the fundamental cause of Chronic Fatigue Syndrome. However, by increasing the ability of the brain to self-regulate, we may be increasing the ability of the person to manage challenges, including this condition.

Persons suffering from Chronic Fatigue Syndrome may wish to evaluate the effectiveness of the training for themselves by undertaking it for an initial sequence of ten half-hour sessions. If the training is likely to be effective, they should see early signs of that within ten sessions: an increase in energy level, and perhaps favorable changes in sleep patterns or reduction in pain. A judgment can then be made as to whether it is worthwhile to continue the training. The first ten sessions should be conducted in close succession, at a minimum of three sessions per week. Daily sessions would be preferable. Under these circumstances, the gains from each training session are more cumulative, and also the changes induced by the training can be more readily distinguished from those ascribable to other factors.

Completion of the training may take some months, at a rate of one to three training sessions per week. Cumulatively some forty or more training sessions may be required. The training is monitored continuously, and if expected gains are not observed, then termination of the training should be considered. The clinical experience on which the above is based now extends to more than fifty cases.

Sleep Disorders

“There ain’t no way to find out why a snorer can’t hear himself snore.”
– Mark Twain, Tom Sawyer Abroad

Clinical evidence now exists for the remediation of a variety of sleep disorders with EEG biofeedback training, including those sleep problems which may be ascribable to neurological immaturity of childhood, or correlated with attentional problems: bedwetting, sleep walking and talking, night terrors, anxiety-related difficulties falling asleep, and insomnia. Among adult sleep disorders, promising evidence exists for remediation of insomnia and sleep apnea.

Many of the conditions helped with EEG biofeedback are correlated with disorders of sleep. This includes epilepsy, anxiety and depression, closed head injury, hyperactivity and attention deficit disorder, chronic pain, and Tourette Syndrome. Even when poor sleep is not the cause for referral for biofeedback, it is often mentioned as a problem during the intake interview. The first reported signs of change upon initiating EEG training often relate to the quality of sleep. We believe that the principal mechanism of efficacy of EEG training is that it normalizes self-regulation of physiological arousal, and the beneficial effects of the training on sleep can be explained in the same manner. When self-regulation is deficient, this should be apparent when arousal level is least tightly regulated, i.e. during sleep in general, and during transitions between sleep stages in particular. Nothing so cogently demonstrates that EEG biofeedback confers a new competence to the brain–as opposed to a consciously applied tool to the patient–than its efficacy in remediating disorders of sleep.

Bedwetting is among the most common symptoms seen in our clinical population, which consists largely of persons with attentional deficits (bedwetting is seen in 30% of institutionalized children; i.e. there is a high correlation with minor neurological deficits). In more than 90% of children under twelve with this condition, remediation is expected within the first twenty sessions of training. In older children and in adults, the problem is more resistant to remediation. It may take more training sessions than in younger children. We have seen much lower incidence of sleep walking, sleep talking, and night terrors. However, remediation is also observed for these conditions. Excessive fears about falling asleep, or about sleeping in one’s own bed, usually remediate very quickly with the onset of training.

There is an intimate connection of insomnia with disorders of arousal such as anxiety and depression. The success of EEG training in effecting improved self-regulation of arousal should, therefore, be expected to result in improved regulation of sleep in these cases, and that is what we observe.

Sleep apnea is generally thought to consist of a central, neurological component, and a somatic, obstructive component, the latter due to the fact that the condition closely correlates with obesity. Obstructive sleep apnea has historically been treated surgically, with rather poor outcomes, so that surgery is now gradually being abandoned in favor of a breathing aid device which provides continuous positive airway pressure (CPAP). EEG training has been successful in fully remediating apnea episodes in adult males, even in the absence of any other behavioral changes such as weight loss. The condition is seen as arising from cortical underarousal. Only a few cases have been studied.

Minor Traumatic Brain Injury/Stroke

The long-term consequences of Minor Traumatic Brain Injury (MTBI) have recently become more widely acknowledged. Persons suffering loss of function due to minor head injuries were usually given CAT scans and MRI scans, which might not reveal any organic injury. As a result, victims were often not taken seriously, and accused of fabricating their symptoms and malingering. More recently, tests of brain function have demonstrated a basis for the symptoms which are described. Such tests include PET scans, topographic brain mapping of EEG activity, and evoked response measurements. These functional tests reveal changes in cortical activation, anomalous EEG activity traceable to head injury, and slowed response.

The symptoms which accompany minor head injury include principally loss of energy; headaches and chronic pain; dizziness and vertigo; memory impairment; difficulty concentrating; anxiety, depression, and mood swings; sleep disturbances; irritability; visual perception problems and dyslexia; and even apparent personality changes. Seizures may also be observed, or seizure-like activity such as auras. If persons exhibited certain weaknesses before the accident, such as attention deficit disorder, migraine headaches, or sleep difficulties, then such symptoms might be considerably exacerbated by the head injury. The apparent severity of the injury, including the length of period of unconsciousness (if any), has little to do with the severity of subsequent symptoms. New symptoms may arise months or even years after the head injury.

We know of no published literature on the use of EEG biofeedback for head injury. We are aware only of clinical work in this field in a number of settings. Over the past six years, we have obtained considerable clinical evidence for the effectiveness of EEG biofeedback training as an adjunct modality for remediating the symptoms of minor closed head injury. By September of 1992, we had accumulated a clinical history of EEG training for 88 cases of (mostly minor) traumatic brain injury. The training appears to be effective even years post-injury, when spontaneous remediation is no longer expected. The training can impact favorably on all of the symptoms listed above.

By means of EEG training, we have been able to restore to productive life a number of individuals who had been totally disabled for a number of years due to head injury. The training is not always that effective. However, essentially everyone who undertakes the training for head injury derives significant benefit. The training needs to be undertaken for a minimum of ten training sessions in order to be able to make a meaningful assessment of whether the training is worthwhile. Completion of training may take anywhere from 25 to more than 100 sessions. Of course, anyone continuing for 100 sessions would only be motivated to do so if there were continuing benefit. The gains made in the training appear to hold for the long term. That is, once the brain is taught again how to regulate itself, it does not relinquish that capability.

When clients are seen within the first six months after head injury, there is a concern about new symptoms continuing to emerge post-injury. Clients must be aware that this may happen despite the biofeedback training, since the latter takes effect gradually. If this understanding exists, and the client is willing to proceed, there may be additional benefit if the training is undertaken soon after injury.

Depression

The most prominent use of biofeedback in the United States is for anxiety disorders and stress management. For these conditions, relaxation training and peripheral biofeedback modalities are very helpful. Unfortunately, these techniques do not generally address the far more common depressive conditions, such as primary unipolar depression, reactive depression, seasonal affective disorder, bipolar disorder, and PMS. Often, anxiety is seen in the context of depression, in which case the conventional relaxation techniques only address the anxiety condition, and may not remediate the underlying depression. The latter requires training to a more highly activated state.

EEG biofeedback offers a new modality for addressing depressive conditions as well as anxiety. This appears to be the case because EEG training impacts on the basic mechanism by which the brain controls physiological arousal. In this manner, normal regulation of arousal may be restored, which means that sleep may normalize in the depressed person, and normal range of affect may return. Other benefits of the training may accrue as well. If the person is experiencing chronic pain, which may be either a cause of depression, or its effect, such pain may remediate as well.

The training appears to be effective regardless of the pathway by which the person has become depressed, whether this results from a genetic pre-disposition, early childhood trauma, or a subsequent traumatic (physical or emotional) experience, or simply a physiological change of unknown causation. As the training proceeds, the client may find that anti-depressant or stimulant medication will no longer be needed. Hence, the person should be under continuing medical care for his condition, so that the medication dose may be monitored. It is generally observed that the requirement for anti-depressant medication will be reduced or eliminated entirely as the training proceeds.

It is true of all remedies for depression that they are accompanied commonly by the recall of prior traumatic memories, which may have been totally suppressed over the years. It is therefore important that counselling be available in the event of such traumatic recall, and for other profound emotional changes which can be elicited by the training.

The training has also been found to be helpful in cases of depression caused by specific traumatic events, such as rape, and by other insults to the brain such as chemotherapy, or general anesthesia in the elderly. EEG biofeedback training is also indicated for those clients who do not respond favorably to medical management, and for those who are counselled to avoid certain medications by their doctor. This category includes in particular pregnant women.

There is evidence that once a person experiences a depressive episode, subsequent episodes are more likely. Hence, training the brain to remediate depression may have the beneficial effect of tending to make subsequent recurrences less likely. The training also appears to be effective for a variety of conditions which are seen concomitantly with depression, such as alcohol dependence and violent behavior.

Tourette Syndrome

Perhaps the best description of Tourette syndrome is by a person who has it, Adam Ward Seligman: “Tourette syndrome is considered a very common genetic behavioral disorder characterized by a lack of inhibition. The inhibition may be around movement, resulting in tics or twitches. It may be a problem inhibiting speech or sound, resulting in vocalizations. It may be a breakdown in thought or action resulting in obsessive compulsive disorder. It may be a breakdown in controlling one’s concentration, resulting in attention deficit disorder. It may even be a problem controlling emotion.” (Adam Seligman, Don’t Think About Monkeys).

By definition, Tourette syndrome is a matter of motor and vocal tics. The diagnostic criteria are such that only severe cases meet them; hence the public perception that the condition is rare and severe. In fact, the symptoms are more varied, and they range broadly in severity. Looked at in this more inclusive sense, the condition is quite common. Whereas the original choice of diagnostic criteria was entirely arbitrary, the emerging, more comprehensive view of Tourette syndrome comes from a better understanding of the underlying genetics. Parents who hear “Tourette syndrome” mentioned in connection with their child need not immediately draw the worst inferences.

Over the past two years, we have observed considerable clinical evidence for the effectiveness of EEG biofeedback training as an adjunct modality for remediating the symptoms of Tourette syndrome. Rather than focusing on the condition as a whole, it is preferable to focus on the individual classes of symptoms. For example, a number of symptoms are highly correlated with Tourette Syndrome. These include attention deficits, anxiety and depression, oppositional-defiant behavior, conduct disorder, obessive- compulsive behavior, episodic dyscontrol, hypersexuality and addictive behavior. We appear to impact many of these symptoms irrespective of whether they are associated with Tourette Syndrome. This includes particularly the attention deficits, anxiety and depression. The training can also be helpful for oppositional- defiant behavior, for conduct disorder, and for obsessive- compulsive behavior. Little data exists to date with respect to addictive behavior or sexual behavior as it is affected by EEG training of Tourette subjects. With regard to tics, our experience to date is that if the tic behavior is of recent onset there is a higher probability of achieving full remediation. This is also true of tics induced by medication, such as that prescribed for hyperactivity and attention deficits (such as Ritalin (R), dexedrine, and Cylert (R) [pemoline]). In adults with decades of history with tics, full remediation is much less likely.

Because of the multiplicity of symptoms, it is often difficult to establish one EEG training protocol which addresses all of them. For example, a protocol selected to deal with attention deficits may not be appropriate for obsessive-compulsive behavior. Under these circumstances, the most significant and troublesome symptoms need to be addressed first in training, leaving minor ones until later. The situation is similar to that which prevails in the medical management of this condition, where a number of medications may be required to address all of the symptoms.

Whereas in general it is our experience that the effect of the training is cumulative and permanent, it has been observed that some Touretters may backslide somewhat between training sessions. In such cases, the training may have to be more frequent, particularly in the early going (perhaps three times per week), and the client may benefit from occasional booster sessions even after the bulk of the training is completed. In the extreme case, children may even benefit from a continuation of EEG training sessions on a regular schedule. Such continuing training appears to be necessary in only a small fraction of cases.

Most of the clients referred for Tourette syndrome are under pharmacological management for the condition. As the training proceeds, downward adjustment of the medication(s) is usually necessary, so the person should be in the care of a supportive physician.

Traumatic Brain Injury

The long-term consequences of Minor Traumatic Brain Injury (MTBI) have recently become more widely acknowledged. Persons suffering loss of function due to minor head injuries were usually given CAT scans and MRI scans, which might not reveal any organic injury. As a result, victims were often not taken seriously, and accused of fabricating their symptoms and malingering. More recently, tests of brain function have demonstrated a basis for the symptoms which are described. Such tests include PET scans, topographic brain mapping of EEG activity, and evoked response measurements. These functional tests reveal changes in cortical activation, anomalous EEG activity traceable to head injury, and slowed response.

The symptoms which accompany minor head injury include principally loss of energy; headaches and chronic pain; dizziness and vertigo; memory impairment; difficulty concentrating; anxiety, depression, and mood swings; sleep disturbances; irritability; visual perception problems and dyslexia; and even apparent personality changes. Seizures may also be observed, or seizure-like activity such as auras. If persons exhibited certain weaknesses before the accident, such as attention deficit disorder, migraine headaches, or sleep difficulties, then such symptoms might be considerably exacerbated by the head injury. The apparent severity of the injury, including the length of period of unconsciousness (if any), has little to do with the severity of subsequent symptoms. New symptoms may arise months or even years after the head injury.

We know of no published literature on the use of EEG biofeedback for head injury. We are aware only of clinical work in this field in a number of settings. Over the past six years, we have obtained considerable clinical evidence for the effectiveness of EEG biofeedback training as an adjunct modality for remediating the symptoms of minor closed head injury. By September of 1992, we had accumulated a clinical history of EEG training for 88 cases of (mostly minor) traumatic brain injury. The training appears to be effective even years post-injury, when spontaneous remediation is no longer expected. The training can impact favorably on all of the symptoms listed above.

By means of EEG training, we have been able to restore to productive life a number of individuals who had been totally disabled for a number of years due to head injury. The training is not always that effective. However, essentially everyone who undertakes the training for head injury derives significant benefit. The training needs to be undertaken for a minimum of ten training sessions in order to be able to make a meaningful assessment of whether the training is worthwhile. Completion of training may take anywhere from 25 to more than 100 sessions. Of course, anyone continuing for 100 sessions would only be motivated to do so if there were continuing benefit. The gains made in the training appear to hold for the long term. That is, once the brain is taught again how to regulate itself, it does not relinquish that capability.

When clients are seen within the first six months after head injury, there is a concern about new symptoms continuing to emerge post-injury. Clients must be aware that this may happen despite the biofeedback training, since the latter takes effect gradually. If this understanding exists, and the client is willing to proceed, there may be additional benefit if the training is undertaken soon after injury.

Learning Disabilities

EEG Biofeedback (also known as neurofeedback) is gradually becoming known and recognized for its utility in remediating Attention Deficit Disorder. Less well known is its emerging application to specific learning disabilities. This is surprising for several reasons. First of all, more children are affected by specific learning disabilities than are diagnosed with ADHD, so EEG biofeedback could potentially have a much larger impact there. Secondly, there is no claim that stimulant or anti-depressant medication is terribly helpful with learning disabilities, so that EEG biofeedback does not challenge and compete with an already accepted treatment. Thirdly, there is no claim that specific learning disabilities are “medical conditions.” To be sure, they certainly have a physiological foundation. However, they cannot be addressed by the usual remedies in the arsenal of the medical practitioner. Hence treatment with EEG training for learning disabilities does not get caught up in the third-party payer maelstrom or in the diagnostic ambiguity of whether something does or does not “qualify” as a bona fide learning disability. Finally, it is surprising because there is probably as much early research backing EEG biofeedback for learning disabilities as there is for Attention Deficit Disorder. The latter application has been criticized for a lack of robust research under controlled conditions. Ironically, part of the reason is that the early research was not exclusively focused on attention problems, but rather on learning disabilities as well.

Perhaps for this reason, much of the early work with EEG biofeedback in connection with attention and learning problems emphasized assessment of academic skills rather than behavioral measures. These had the advantage of being very objective, but at the same time they did not meet the expectations of researchers who had a focus on ADHD. These researchers have ever since called attention to a dearth of behavioral data, despite their notorious subjectivity.

The first significant study of both attention and learning problems using EEG biofeedback was performed by Joel and Judith Lubar (Lubar, 1984). The study reported on six children who had undergone the training. The motivation was that seizure disorders, ADHD, and specific learning disabilities were often characterized by elevated low-frequency (less than 10Hz) activity in the EEG (Lubar et al, 1985). Such elevated activity could be seen as disruptive to the ongoing mental activities, possibly either causing or exacerbating learning disorders. It had already been shown to be possible to control seizure susceptibility and hyperactivity with EEG training that attempted to “train down” the low frequency activity at the same time that certain higher-frequency activity is promoted (12-18 Hz) (Sterman, 1978). Could the same training impinge on learning disorders as well? The results of this initial study were highly promising in this regard, although they were compromised by the fact that five of the children were receiving other special academic support as well during the period of the study.

Moreover, the Lubars were not alone. Tansey and Bruner published a single case study of a child with both attention and learning problems in the same timeframe (Tansey, 1983). In this case, both conventional biofeedback and EEG biofeedback were used, so the interpretation of the results remained ambiguous. Tansey published a study of four children in 1985 in which the focus was learning disorders rather than attentional deficits, and this was the first of many studies in which improvements in IQ score were documented for EEG training. In a follow-up study using 24 subjects with learning disorders (Tansey 1990), an average improvement in Wechsler full-scale IQ score of 19 points was demonstrated, which was quite impressive. The improvements in performance IQ (deemed to reflect more right hemisphere function) was +19 points, and the improvement in verbal IQ (deemed to reflect left hemisphere function) was +16 points. Of the 24 children in the study, 11 had been diagnosed as neurologically impaired, 11 were judged perceptually impaired, and only two were diagnosed with ADD.

Our own clinical study for replication purposes took place in 1990-1991, and also emphasized academic skills assessments over behavioral measures (Othmer, 1991). In a study of 15 subjects, an average WISC-R improvement of 23 points was found (with independent testing). The improvement ranged from 7 points to 35. Thus every study participant improved his IQ score, and most did so significantly. Academic skills were also assessed with the Wide Range Achievement Test (WRAT), and on this test there was more of a divergence in outcomes than was the case for the IQ test. Only ten of the 15 children were evaluated with the WRAT. In the reading test, only one child scored below grade level at the outset. That child improved more than three grade levels with the training, and reached age-appropriate norms. Five other children significantly advanced their reading performance above grade level, in rank order by +5.6 years, + 4.5 years, +4.2 years, +3.5 years, and +2 years. Since only one child was reading below grade level initially, not much can be discerned from this about reading disabilities. On the other hand, the striking gains experienced by some children does indicate that the training had an effect on some of the mechanisms underpinning the reading process. It may be argued that the training moved them closer to their native reading ability.

By contrast, in the arithmetic test of the WRAT, nine of the ten children scored in deficit at the outset. After training, five had shown significant improvement: +7.6 years, +2.7 years, +2.3 years, +2 years, and +1.6 years. Two more treaded water, with gains of one year (whereas the test-retest interval in the study was nine months). One child tested the same on the retest, and two, sad to say, actually scored worse (although one of these remained way above grade level, and could be considered a case of regression to the mean). It is noteworthy that in some children major improvements were observed, whereas in others there was negligible change. This discrepancy could even be seen within the same child. For example, the child whose deficit in math performance worsened actually soared in terms of reading!

It is tempting to suggest that the training protocol employed in this study fortuitously happened to be what certain children needed in order to break the relevant bottleneck in reading or arithmetic ability. These tasks, it is now known from imaging studies, require certain cortical regions to activate in a timely manner and to communicate with one another for overall task completion. A training protocol that uses a single electrode placement on the scalp may not reasonably be expected to address all possible shortcomings in terms of local activation and intra-cortical communication involved in such complex processes as reading and arithmetic computation.

And then there is dysgraphia. No one fails out of school because of an inability to draw, so this particular disability does not get much attention, except perhaps from those who do assessments on children. The inability to draw reflects more on right hemisphere skills, and on inter-hemispheric communication. Whereas this disability may be harmless in itself, it can be an indicator for other deficiencies in right hemisphere skills that could indeed be important. To assess drawing skills, children are asked to draw their family during the intake interview. We have seen many children improve with the training from the point at which they are drawing stick figures to where they acquire full-bodied relatives-all within the span of a few weeks, with some twenty to forty training sessions.

It is the lack of systematic, predictable success with learning disorders-more than perhaps any other reason-that has kept the professional community of EEG biofeedback practitioners from promoting this application more overtly. However, the very striking results that can be achieved with many children also place an obligation on us to make this information available. As long as the potential trainee is aware of the finite likelihood of success, he should certainly have the opportunity to train. Clinicians have an understandable reluctance to promote a technique where the outcome may be so highly variable, in addition to being unpredictable, particularly in a field that is still trying to gain recognition by the mainstream educational and medical communities.

For the future, things look very bright indeed. The new imaging studies give us indications for what protocols to try in order to improve the likelihood of success. For example, Shaywitz et al (1998) recently published a study on PET scans in dyslexic subjects. Regions of heightened oxygen uptake may reflect areas where reading is being bottlenecked in such subjects. It is relatively straight-forward to try a variety of training schemes involving the identified sites. The combination of functional imaging and EEG biofeedback may yield near-term breakthroughs in the remediation of various specific learning disabilities that have been relatively intractable to date.

References

Lubar, J.O., and Lubar, J.F. (1984).
Electroencephalographic biofeedback of SMR and beta for treatment of attention deficit disorders in a clinical setting.
Biofeedback and Self-Regulation, 9 (1), 1-23.

Lubar, J.O., Bianchini, K., Calhoun, W., Lambert, E., Brody, Z. and Shabsin, H. (1985)
Spectral analysis of EEG differences between children with and without learning disabilities.
Journal of Learning Disabilities, 18, 403-408.

Othmer, S., Othmer, S.F., and Marks, C. (1991).
EEG biofeedback training for attention deficit disorder, specific learning disabilities, and associated conduct problems.
Web-published, www.eegspectrum.com. Available as a Monograph from EEG Spectrum, Encino, CA.

Shaywitz SE, Shaywitz BA, Pugh KR, Fulbright RK, Constable RT, Mencl WE, Shankweiler DP, Liberman AM, Skudlarski P, Fletcher JM, Katz L, Marchione KE, Lacadie C, Gatenby C, Gore JC (1998)
Functional disruption in the organization of the brain for reading in dyslexia.
Proc Natl Acad Sci U S A 95(5), 2636-2641

Sterman, M.B. and MacDonald, L.R. (1978)
Effects of central cortical EEG feedback training on incidence of poorly controlled seizures.
Epilepsia, 19(3), 207-222.

Tansey, M., and Bruner, R. (1983)
EMG and EEG biofeedback training in the treatment of a 10 year old hyperactive boy with a developmental reading disorder.
Biofeedback and Self-Regulation, 4, 299-311.

Tansey, M. (1990)
Righting the rhythms of reason: EEG biofeedback training as a therapeutic modality in a clinical office setting.
Medical Psychotherapy, 3, 57-68.

ADHD

Automated Neurofeedback Brain-training as a Primary ADHD Intervention

Abstract:  Neurofeedback brain-training has a significant presence in the literature for its efficacy in alleviating the symptoms and behavioral manifestations of ADHD, with no enduring negative side-effects.  It is considered a behavioral intervention in that it teaches the brain to better manage its own brain-wave activity, leading to reduction of 80-85% of symptoms in the first 30-40 training sessions.  Brain-training has shown efficacy in treating autism spectrum disorder, anxiety, depression, learning disabilities, and many more brain-imbalances that prevent children from full academic and social capacity.  Barriers to broad-based implementation in both clinical and subclinical settings include cost of equipment, lengthy, in-depth training requirements, and a lack of clear guidance in developing and implementing brain-training protocols specific to each individual’s brain-phenotype.  Automated Psychophysiological assessment and EEG Biofeedback training systems demonstrate equal efficacy as clinician-guided EEG Systems.  We propose that Automated EEG Biofeedback systems have evolved to differentiate and train a multiplicity of brain-phenotypes related to symptoms of ADHD and other childhood developmental disorders.  Further, these systems decrease the cost of brain-training significantly, reduce the training requirements for brain-trainers, and significantly increase the effectiveness of all other behavioral and academic school/district level interventions.  We propose that automated brain-training can be implemented at a school/district level, by a licensed school social worker, counselor, nurse or other person qualified by their understanding of behavioral training.

Introduction:

Attention Deficit/Hyperactivity Disorder (ADHD is a chronic syndrome whose symptoms affect approximately 11% of American school-aged children, and nearly 20% of adolescent boys.  The most common symptoms of ADHD include inattention, distractedness, disorganization, impulsiveness and hyperactivity.  There has been a substantial increase in the diagnosis of ADHD, 42% between 2003 and 2012 (Visser, Zablotsky, Hlbrook, Danielson, & Bitsko (2015), with many experts believing that ADHD is over-diagnosed.  Accurate diagnosis is further challenged by medical symptoms have the capacity to mimic ADHD symptoms.  These conditions include vision and hearing challenges, sleep disturbances, substance abuse, mood disorders, learning disorders, sensory-processing disorders, seizure disorders, obsessive-compulsiveness, Asperger’s syndrome, fetal alcohol syndrome, and Fragile X syndrome.

Neuro imaging and EEG Brain-mapping research over the past three-decades has produced an Arousal Model of mental health that identifies eleven universal brain-phenotypes involved in nearly all mental health disorders.  These brain-phenotypes, subtypes of mental health disorders describe symptom and behavioral manifestations of regional brain overarousal, underarousal, or instability.  (Gunkleman & Cripe, 2008; Amen, 2015).  The most current Brain-phenotype model for ADHD arises out of Amen’s extensive and broad-ranged neuroimaging studies that describe implicated brain-region arousal levels.   Amen’s (2015) phenotype model identifies seven brain-phenotypes, with their symptom/behavioral manifestations, and implicated brain-region related to ADHD. The extensive body of neuroimaging studies is revelatory for understanding the underlying neurological imbalances involved in ADHD, for predicting medication efficacy and especially for understanding the importance of neurofeedback as a primary intervention for ADHD.

Our purpose in this article is to provide an overview of the Arousal model that has evolved in neuroscience based on our understanding of brain-phenotypes to provide the context for which automated neurofeedback systems can be applied.  Next, we will describe evolvement of automated NFB assessment and interventions, potential side effects, and contraindications.  I will review the research support for brain-training in various addiction and mental health populations.  Finally, strategies for integrating automated brain-training systems in clinical and subclinical settings is explored.

ADHD/ADD Diagnosis:

Diagnosis of ADHD is typically conducted by licensed physicians, psychiatrists, social workers, and other appropriately trained and licensed mental health providers, using diagnostic indicators provided by the American Psychiatric Association (APA) in the Diagnostic and Statistical Manual, Fifth edition (DSM-5; APA, 2013), or the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10).  Diagnostic features of both systems are restricted to the areas of Inattention, Hyperactivity/Impulsivity, or both.  Challenges in arriving at an accurate diagnosis may include the presence of other medical symptoms that mimic ADHD symptoms (McReynolds, Villalpando, & Britt, 2018), which include vision and hearing difficulties, sleep disturbances, mood disorders, learning disabilities, sensory-processing disorders, giftedness, seizure disorders, obsessive-compulsive disorders, Tourette’s and Asperger’s syndrome, schizophrenia, fetal alcohol syndrome, and Fragile X syndrome (Saul, 2014).

Neuroimaging and EEG research provides many new clues to the underlying etiology of ADHD and the frequently occurring symptoms related to other brain-wave imbalances, including those listed above.  In fact, it is only through seeing and hearing brain activity that a comprehensive Arousal model has developed that provides a framework for both diagnosing and treating the broad range of ADHD symptoms.  Brain imagining techniques have developed at a significantly rapid pace over the past 3 decades, leading to a much more comprehensive understanding of the effects of regional brain arousal levels:  under-aroused, overaroused, instable, on mental health symptoms.  Researchers have now identified Eleven universal brain-phenotypes that describe out-of-balance arousal levels implicated in nearly all mental health disorders.  Seven individual brain-phenotypes have been identified related to ADHD specifically (Table 1), with seven phenotypes identified for Anxiety/Depression, six phenotypes for Addiction, and six phenotypes for Eating Disorders.  There is considerable overlap between the ADHD phenotypes, and phenotypes related to other mental health disorders.  Identifying the individual brain-phenotype involved in ADHD, and other disorders, is a critical first step in diagnosis, and is necessary for predicting medication efficacy (Amen, Hanks, & Prunella, 2008).

 

 

Type Symptoms Involved br
1.  Classic ADD Inattentive, distracted, disorganized, impulsive, hyperactive Low Pre-Frontal Cortex (PFC) and cerebellum
2.  Inattentive ADD Inattentive, distracted, disorganized, not very impulsive or hyperactive Low PFC and cerebellum
3.  Over focused ADD Inattentive plus over focused, worrying, oppositional, holds grudges Low PFC and increased Anterior Cingular Gyrus (ACG)
4.  Temporal Lobe ADD Temper problems, mood instability, irritability, memory problems, learning disabilities Abnormal Temporal Lobe (TL)
5.  Limbic ADD Inattentive plus chronic low-level sadness Low PFC plus high limbic activity
6.  Ring of Fire ADD Inattentive plus hyperactive, impulsive, mood instability, sensitive to noise and touch Excessive brain activity
7.  Anxious ADD Inattentive plus anxious, tense, nervous, predicts the worst, self-medicates to calm Low PFC and high basal ganglia

 

Until recently, assessing brain-phenotypes for ADHD and other mental health disorders required extensive clinical training and experience.  Accurate assessment has traditionally relied on quantitative Electroencephalograph (qEEG) evaluation.   qEEG systems listen to the various components of brain-wave activity.  The most comprehensive qEEG systems analyze data obtained from 19-channels on the scalp where brain-wave signals are known to rise sufficiently to be heard by sensors placed on those locations.  The signals are amplified, and the data is compared against norms of normal brain activity.  The data produces graphics that can identify over 5,100 components of brain activity including arousal levels, connectivity, coherence, and brain-injury.  Unfortunately, recording and interpreting the qEEG requires complex interpretations of baseline Electroencephalograph (EEG), participants’ presenting symptoms, between-session changes in symptoms, and within session reward criteria. Complex neurofeedback systems, and the necessary skills and knowledge to effectively operate them are typically well beyond operational capacity of most mental health providers, let alone school behavioral interventionists.

A second form of assessing brain-phenotypes, psycho-physiological assessment, demonstrates equal efficacy in reducing ADHD symptoms (Keith, Theodore, Rapgay, Schwartz, & Ross, 2015) and other brain-phenotype imbalances (Scott, 2018).  Psycho-physiological assessments more coherently identify both ADHD and other co-occuring mental health symptoms then the DSM-V and ICD-10 include, thereby providing a broader understanding of the underlying brain-arousal levels and their implications for both assessment and treatment.  Rather than identifying single features of a specific diagnostic category, psychophysiological assessments provide a more comprehensive perspective on all the mental health issues that may impede learning, social engagement, and academic achievement in school-aged children.  Technological development within the neurofeedback field now provides guided semi-automatic psychophysiological assessment and training hardware/software with demonstrated equal efficacy when compared with more complex clinical guided neurofeedback (Keith et al., 2015).  Automated assessment and brain-training hardware/software provides practical, safe, and effective brain training tools that can be readily implemented a broad range of sub-clinical school settings.

Treatment for ADHD:

Treatments for ADHD are designed to reduce the behavioral symptoms of ADHD and generally fall under two categories: psychopharmacological, and behavioral.  Many children respond well to behavioral interventions coupled with medications (Fabiano et al, 2009), though others do not (Sonuga-Barke, et al, 2013).  Behavioral interventions have been associated with several positive outcomes including increased parent empowerment and reducing conduct problems of children diagnosed with ADHD (Daley et al, 2014), though improvements in academic performance and social skills have not been substantiated in reviews of behavioral interventions (McReynolds et al., 2018).

Medication treatment approaches raise multiple concerns regarding both the side effects of typical prescription regimens including possible bone-loss, gastrointestinal problems (Ellis, 2016), sleep problems, decreased appetite (Brazier, 2015), and height suppression (Poulton et al, 2013).  Further, medications do not have enduring effects (Swanson et al, 2017).  Though medications are being prescribed at younger ages then previously (DSM-5; APA), the use of stimulant medications without matching to brain-phenotype is too simplistic of an approach to treat the complex brain-imbalances underlying an individuals unregulated emotional, behavioral, cognitive, social, and academic difficulties (Dunlop & Newman, 2016).  Further, continued benefits from medications require continuous use, with increasing dosages over time to account for tolerance to both pharmacological effect and increases in side effects (Pigott, Bodenhamer-Davis, Davis & Harbin, 2013; Pigott & Cannon, 2014)

Neurofeedback Brain-Training (NFBT) is a form of evidence-based behavioral therapy that uses a computer-human interface to receive, interpret, and provide feedback of brain electrical energy to the trainee. This form of operant conditioning facilitates the brain’s neuro-plasticity, its ability to rapidly change and reorganize neural pathways in response to brain-training.  NFBT has been broadly recognized as effective in alleviating ADHD symptoms, reaching a “Level 5 Research Outcome, signifying the highest level of clinical research and statistical significance when compared to medication and placebo treatments (Arns et al, 2009, AACAP, 2011).

Arousal models traditionally used in assessing ADHD largely focused on the Beta/Theta ratio, and/or Sensory Motor Rhythm (SMR), primarily in the pre-frontal cortex.  Though the standardized protocols that have developed have demonstrated efficacy and endurance in neurofeedback studies, inconsistencies in protocol application are the source of methodological criticisms (Pigott & Cannon, 2014).  As previously discussed, methodological evaluation of brain-phenotypes has been largely restricted to clinician administered qEEG analysis, with most training conducted with standardized ADHD protocols.

More recent developments in phenotype models demonstrate regional arousal levels that include the previously identified phenotypes, and add several phenotypes that more distinctly address other implicated brain-regions (Amen, 2015).  As previously discussed, assessing the multiplicity of brain-phenotypes is beyond the scope and practice of most clinicians, even many experienced neurofeedback therapists.  Designing and implementing treatment protocols that address the multiplicity of symptoms is also beyond the experience scope of all but the most experienced neurofeedback therapists.  Further, clinician guided NFBT requires ongoing evaluation of in-session, and between-session changes that typically identify over zealous brain-training.  Nearly all previous positive studies demonstrating NFBT’s efficacy in alleviating ADD/ADHD symptomology and improving long-lasting EEG patterns have relied on complex neurofeedback systems requiring extensive training and experience, with accumulated understanding of neurophysiology.  The complexity of systems, skills, and knowledge required for its clinical and sub-clinical applications has limited more broad spread application of this behavioral training method.

Pioneer neurofeedback researcher and therapist Bill Scott recognized the multiplicity of brain-phenotype symptoms early in NFBT’s history.  In addition to creating the only 3-dimensional visual feedback instrument, a fractal image of the brain’s total EEG, Scott developed NFBT’s first, and as far as we know, only automated brain-training system, BrainPaint.   The BrainPaint system is a widely used, automated phenotype-based assessment and training human-computer interface.  Its design includes a 90-question psycho-physiological assessment with strong correlations to Amen’s 7-brain phenotypes for ADD/ADHD. Additionally, the automated assessment includes symptom assessment for each of the phenotypes associated with anxiety, depression, addictions, and eating disorders.  Once the trainer completes the automated assessment, the automated system produces recommended training protocol  suggestions that have demonstrated efficacy in others with related brain-phenotypes.

Scott’s automated NFBT system converges the long history of neurofeedback’s demonstrated efficacy in symptom relief in a broad range of mental-health disorders with the emerging understanding of brain-phenotypes.   Though BrainPaint has been widely used in research and clinical settings with great efficacy, little literature yet exists on its unique ability to assess and train to specific brain-phenotype arousal levels.   Developments in automated NFBT systems provide an advantage in that they directly assist neurofeedback practitioners in assessing and training Arousal levels in those regions identified by the trainee’s individual brain phenotype.

Scott’s development and continued enhancements to his BrainPaint platform provide the ability to more easily identify individual arousal levels from reported symptoms and behavioral manifestations.  The computerized evaluation, incorporated into the BrainPaint software includes the 90-question Symptoms Checklist 90 – Revised  that can be completed by the trainer and trainee in approximately 30-minutes.  With children, the trainer and trainee’s parents complete the evaluation, with the child present.  Once the evaluation questions are answered, the system produces brain-training protocol suggestions specific to each individual’s phenotype, and brain-training can commence immediately.  We propose that a trained school/district level behavioral interventionist can easily implement the BrainPaint evaluation in a sub-clinical setting.  This model was tested in the Juneau School district in a 2 year grant aimed at reducing suicides in the school in 2010.  The school eliminated suicides for the entire duration of their use of BrainPaint.

BrainPaint’s automated production of individualized training protocol sugestions eliminates the skills/knowledge requirements of most NFBT systems.  Nearly all childhood brain-phenotypes are trained at two sites along the Sensory Motor Strip with the Brainpaint system, with demonstrated equal efficacy to more complex 19-site NFBT training (Keith et al, 2015).  This feature enables much easier technical administration of brain-training, reducing much of the complexity of NFBT to pasting sensors to the trainee’s scalp and ears, and coaching them to train their brains.

Scott also had the foresight to include several behavioral and psychiatric evaluation tools within the Brainpaint platform that have great utility in demonstrating, to the client, and in supporting research, positive gains of neurofeedback.  These tools are also helpful in determining appropriate training termination points, in that they will identify when a client plateau’s in their training.  The BrainPaint system includes a Continuous Performance Test (CPT) that reliably assesses attention, focus, and impulse control.  BrainPaint’s CPT can be used pre-during-and post training.  For evaluation and research, we recommend the CPT every 5-10 sessions.  BrainPaint also includes an automated in-session and between-session evaluation, helpful in identifying overzealous or underzealous training protocols, able to make immediate changes to training intensities, on-the-fly. Session-by-session tools to evaluate significant negative effects of neurofeedback which, when appropriate, offer the opportunity to further enhance the training protocol, reducing any identified negative effects.  Finally, all clinical and non-clinical trainers will appreciate the semi-automatic production of treatment goals.  Scott has developed and included a list of several hundred phenotype related behavioral goals that can be used as is, or adapted on-the-fly for each client.  Goal setting assists the neurofeedback process by providing specific behavioral measurements that the client can report improvements/declines in their next session.  As progress towards each goal moves towards attainment, trainer and trainee can identify further goals that might be achieved through additional training, or move towards termination of the current cycle of NFBT.

Scott’s BrainPaint system is likely one of the more widely used neurofeedback systems, and as previously discussed, is the only automated NFBT system with demonstrated efficacy in both research and clinical settings.  Though little research has been conducted in the broader scope of brain-phenotype directed training, Keith et al (2015) demonstrated that this system was equally effective in both assessing and training in a population of addicted individuals with co-occurring ADHD symptoms.

We have used BrainPaint in clinical and non-clinical settings to assess and train over 200 individuals, from nearly all of the eleven known brain-phenotypes.  ADHD symptoms are the predominant issues in our child and adolescent clients, while anxiety, depression, and addiction predominate our adult clients.  Our clients typically experience the reduction in symptomology in the first few sessions, congruent with Scott’s reporting, with 80-85% symptom reduction occurring between sessions 20-40.  Congruent with McReynolds et al (2017) reporting, our clients report that symptom reduction continues past termination of NFBT, which leads us to believe that near-complete symptom reduction is possible for nearly all mental health disorders when phenotype based NFBT is administered.

Sub-clinical application of Neurofeedback

Currently, there is no licensing requirement to perform neurofeedback, and is regulated under the scope-of-practice of state-licensing boards.  As a behavioral intervention, it can be learned and implemented by a broad scope of current school/district level behavioral interventionists.  There is a national certification board that reviews applicant’s experience and education.  Certification is available at two levels, technician, and therapist, requires 36-hours of CEU’s in specific areas of knowledge pertinent to the field, and clinical supervision (BCIA.org).   BrainPaint provides a ready-to use and implement system on a leased basis, providing great flexibility for the development and maintenance of a cost-effective behavioral intervention program.  Trainers are provided a System and Operations manual that can typically be completed in 10-hours or less, and BrainPaint conducts a weekly support webinar attended by BrainPaint trainers worldwide.

Conclusion:  We propose that Automated Neurofeedback Brain-training systems have evolved both towards practical application and demonstrated efficacy and safety to further explore their use as a primary behavioral intervention in sub-clinical settings, specifically school/district level brain-training labs.  The BrainPaint automated system reduces training requirements, purchase of complex NFBT assessment and training systems, and provides a ready-to-use NFBT system with wide applicability in clinical and subclinical settings.  Its system includes tools that can, and should be used in evaluating a phenotype approach to NFBT, and can be implemented easily, affordably, and safely.

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Gunkelman, J., & Cripe, C. (2008).  Clinical Outcomes in Addiction:  A Neurofeedback Case Series.  Biofeedback 36(3), 152-156

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Addictions

Automated Neurofeedback Brain-training as a Primary Addiction Intervention

Abstract:  Neurofeedback brain-training has a significant presence in the literature for its efficacy in alleviating the symptoms and behavioral manifestations that significantly challenge recovery from addictive disorders, with no enduring negative side-effects.  It is considered a behavioral intervention in that it teaches the brain to better manage its own brain-wave activity, leading to reduction of 80-85% of symptoms in the first 30-40 training sessions.  Brain-training has shown efficacy in alleviating symptoms of ADHD, depression, PTSD, insomnia and many other neurological conditions that co-occur with addicted populations.  Barriers to broad-based implementation clinical and subclinical settings include cost of equipment, lengthy, in-depth training requirements, and a lack of clear guidance in developing and implementing brain-training protocols specific to each individual’s brain-phenotype.  Automated Psychophysiological assessment and EEG Biofeedback training systems demonstrate equal efficacy as clinician-guided EEG Systems.  We propose that Automated EEG Biofeedback systems have evolved to differentiate and train a multiplicity of brain-phenotypes related to symptoms of addictive disorders as well as many other co-occurring psychophysiological symptoms. These systems decrease the cost of brain-training significantly, reduce the training and experience requirements for brain-trainers, and will increase recovery potential in nearly all addiction treatment models.  The aim of this report is to illuminate the broad understandings of automated neurofeedback brain-training as an essential primary intervention in addictions treatment.

Introduction:

Addictive disorders are marked by cognitive, behavioral, and physiological impairments with an accompanied dysregulation in brain circuitry that may continue well beyond initial abstinence into the months and years of early recovery.  Neuro-dysregulation models are the target of all psychopharmacological research and interventions.  Despite increased focus on producing more effective psychopharmacological interventions, treatment of addictive disorders has remained challenging both at the research and clinical level.   Traditional treatment models combining bio-psycho-social-spiritual rehabilitation yield poor results, with 65-70% of those completing treatment relapsing within the first 12-months after treatment (McKay, Atterman, Rutherford, Cacciola, &McLellan,1999).  One of the most challenging aspects in the addiction recovery field is the presence and treatment of the symptoms of other disorders that co-occur with addictive disorders such as ADHD, Anxiety, Depression, Insomnia, and PTSD.

Neuro-imaging and quantitative Electroencephalograph (qEEG) Brain-mapping research over the past three-decades has produced identifiable patterns of electrical-brain waves, brain-phenotypes, that differentiate those with addictive disorders from normal controls.  Analysis of hundred’s of thousands of qEEG’s and neuro-imaging results have produced an Arousal Model of mental health that identifies eleven universal brain-phenotypes involved in nearly all mental health disorders.  These brain-phenotypes, subtypes of mental health disorders describe symptom and behavioral manifestations of regional brain over-arousal, under-arousal, or instability.  (Gunklelman & Cripe, 2008; Amen, 2015).  The most current Brain-phenotype model for addictions arises out of Amen’s extensive and broad-ranged neuroimaging studies that describe implicated brain-region arousal levels.   Amen’s (2015) phenotype model identifies six brain-phenotypes, with their symptom/behavioral manifestations, and implicated brain-region related to addictive disorders. He also describes six similar phenotypes related to eating disorders.  The extensive body of neuroimaging studies is revelatory for understanding the underlying neurological imbalances involved in addictive disorders, for predicting medication efficacy and especially for understanding the importance of neurofeedback as a primary intervention for addictive disorders.

Our purpose in this section is to provide an overview of the Arousal model that has evolved in neuroscience based on our understanding of brain-phenotypes to provide the context for which automated neurofeedback systems can be applied.  Next, we will describe evolvement of automated NFB assessment and interventions, potential side effects, and contraindications.  I will review the research support for brain-training in various addiction and mental health populations.  Finally, strategies for integrating automated brain-training systems in clinical and subclinical settings is explored.

Addiction Diagnosis:

Diagnosis of addictive disorders is typically conducted by licensed physicians, psychiatrists, social workers, and other appropriately trained and licensed mental health providers, typically with a bio-psycho-social-spiritual framework of assessment and treatment.  Assessor’s are guided by diagnostic indicators provided by the American Psychiatric Association (APA) in the Diagnostic and Statistical Manual, Fifth edition (DSM-5; APA, 2013), or the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10).  Diagnostic features of both systems rely on assessment of tolerance, withdrawal, and behavioral manifestations of an unhealthy relationship with the substance of choice.  A significant proportion of addiction treatment populations also demonstrate co-occurring symptoms that are better described by other DSM-V diagnoses like ADHD, anxiety, depression, obsessive compulsive disorders, and insomnia, to name a few (McReynolds, Villalpando, & Britt, 2018, Volkow & Li, 2005).

Neuroimaging and qEEG studies provide evidence identifying the underlying etiology of addictive disorders, as well as frequently occurring symptoms related to other mental health disorders, including those listed above.  In fact, it is only through seeing and hearing brain activity that a comprehensive arousal model has developed that provides a framework for both diagnosing and treating the broad range of addictive symptoms.  Neuro imaging and EEG Brain-mapping research over the past three-decades has produced advances in the arousal model of mental health that identifies eleven universal brain-phenotypes involved in nearly all mental health disorders.  These brain-phenotypes, subtypes of mental health disorders describe symptom and behavioral manifestations of regional brain over-arousal, under-arousal, or instability.  (Gunkleman & Cripe, 2008; Amen, 2015).    Amen (2015) identifies six individual brain-phenotypes related to addictive disorders specifically (Table 1).  Six corresponding phenotypes have been identified related to eating disorders.  Further, seven phenotypes have been identified for ADHD, and seven phenotypes identified for Anxiety/Depression.  There is considerable overlap between the addiction phenotypes, and phenotypes related to other mental health disorders.  Identifying the individual brain-phenotype involved in addictive and other disorders, is a critical first step in predicting appropriate therapeutic interventions necessary for individualizing addiction recovery at the neurological level (Amen, Hanks, & Prunella, 2008).

Addiction Phenotypes

Type Symptoms Brain Region Involved
Compulsive Addicts Over focused, worrying, trouble letting go of hurts Increased Anterior Cingulate Gyrus (ACG)
Impulsive Addicts Inattentive, impulsive, easily distracted Low Prefrontal Cortex (PFC)
Impulsive/ Compulsive Addicts Combination of types 1 and 2 High ACG plus low PFC
Sad or Emotional Addicts Sad or depressed mood, winter blues, carbohydrate cravings, loss of interest, sleeps a lot, low energy, self medicates to improve mood High limbic activity, low PFC
Anxious Addicts Anxious, tense, nervous, predicts the worst, self-medicates to calm High basal ganglia
Temporal Lobe Addicts Temper problems, mood instability, memory problems, learning disabilities Abnormal Temporal Lobe activity

 

Until recently, assessing brain-phenotypes for addictive and other mental health disorders required extensive clinical training and experience.  Accurate assessment has traditionally relied on quantitative Electroencephalograph (qEEG) evaluation.   qEEG systems listen to the various components of brain-wave activity.  The most comprehensive qEEG systems analyze data is obtained from 19-channels on the scalp concurrently, where brain-wave signals are known to rise sufficiently to be heard by sensors placed on those locations.  The signals are amplified, and the data is compared against measures of normal brain activity.  The data produces graphics that can identify over 5,100 components of brain activity including arousal levels, connectivity, coherence, and brain-injury.  Unfortunately, recording and interpreting the qEEG requires complex interpretations of baseline (qEEG), participants’ presenting symptoms, between-session changes in symptoms, and within session reward criteria. Complex neurofeedback systems, and the necessary skills and knowledge to effectively operate them are typically well beyond operational capacity of most mental health providers, let alone as a primary addictions intervention.

A second form of assessing brain-phenotypes, psycho-physiological assessment, demonstrates equal efficacy in improving addiction recovery as well as decreasing ADHD symptoms (Keith, Rapgay, Theodore, Schwartz, & Ross, 2015) and other brain-phenotype imbalances (Ros, Baars, Lanius & Vuilleurnier, 2014; Ros et al, 2016).  Psycho-physiological assessments more coherently identify both addictive and other co-occurring mental health symptoms then the DSM-V and ICD-10 include, thereby providing a broader understanding of the underlying brain-arousal levels and their implications for both assessment and treatment.  Rather than identifying single features of a specific diagnostic category, psychophysiological assessments provide a more comprehensive perspective on all the mental health issues that may impede addictions recovery.  Technological development within the neurofeedback field now provides guided semi-automatic psychophysiological assessment and training hardware/software with demonstrated equal efficacy when compared with more complex clinical guided neurofeedback (Keith et al., 2015).  Automated assessment and brain-training hardware/software provides practical, safe, and effective brain training tools that can be readily implemented a broad range of clinical and sub-clinical addiction recovery settings.

Limbic-System Hijacking

In addictions, as well as PTSD, there is an unhealthy relationship between Alpha in our prefrontal cortex, and Theta in the Limbic System.  Changes in the ratio of these brain waves are triggered by sensory memory inputs.  Sensory memory systems record input throughout our life, some pleasant, some unpleasant.  In times of trauma, some of those sensory memories can become linked to the limbic system memory, which is a much more biological memory.  In addictions, the limbic system memory remembers how good it felt, how much relief was provided.  In the case of PTSD, the limbic system, remembers how bad it felt.  When triggered, the limbic system memory activates the autonomic fight-or-flight response, showing up in brain waves as an escalation of Theta, the rhythm that largely drives the limbic system.  Needing more energy to maintain this state of alert, the brain shifts (steals) energy from elsewhere.  In the case of both addictions and PTSD, the brain steals energy from the pre-frontal cortex rhythm Alpha.  One can imagine, that without sufficient Alpha prefrontally, that portion of the brain doesn’t have sufficient energy to do it’s job sufficiently.  Some of the most important prefrontal left functions are cognition, impulse control, emotional regulation, and decision making.  Prefrontal right functions include empathy, compassion, self-care.

This makes a lot of sense physiologically.  The thalamus, the brains gatekeeper of sensory information, is very close to the limbic system, and very distant, relatively, to the prefrontal cortex.  The limbic system gets the information first, and results in what has been called “limbic system hijacking.”  When we monitor this brain process with electroencephalograph (EEG) we see Theta taking control of the brain, draining energy from Alpha in the prefrontal cortex.  Literally, the part of the brain we need for good recovery does not have the energy it needs to do its job.  From the neurofeedback perspective, limbic system hijacking represents dysregulation of the brain-reward circuitry, and provides the basis for development of brain-training protocols specific to correcting this dysregulation, Alpha/Theta training.

Treatment for Addictions:

Substance abuse is an ongoing societal and treatment problem.  While significant national resources have been committed to study and treat addictive disorders, there has been little significant improvement in treatment success rates.  In the current treatment paradigm, over 70% of individuals relapse back into substance abuse within weeks or months of completion of addiction treatment (Mclellan, Lewis, Brien, & Kleber, 2000).  Only 9.1% of those who have reported a lifetime history of a significant substance abuse disorder report having resolved it, either through spontaneous remission, through 12-step attendance, or through formalized substance abuse treatment (Kelly, Bergman, Hoeppner, & Vilsaint; Mclellan et al, 2000).

Neurofeedback Brain-Training (NFBT) is a form of evidence-based behavioral therapy that uses a computer-human interface to receive, interpret, and provide feedback of brain electrical energy to the trainee. This form of operant conditioning facilitates the brain’s neuro-plasticity, its ability to rapidly change and reorganize neural pathways in response to brain-training.  NFBT has been broadly recognized as effective in alleviating brain imbalances implicit in a broad range of mental health disorders, including addiction recovery.  NFBT is safe, with the only reported common side effects of mild headaches and/or slight disorientation.  Approximately 75-80% of brain-trainees successfully learn how to train their brain-waves, typically eliminating 80-85% of symptoms related to their brain phenotype (Shepard, 2008, Brainpaint, ).

In addition to the arousal dysregulations identified in Amen’s (2015) models related to ADHD, depression, and anxiety, addictive disorders exhibit a significant dysregulation between Theta, which drives the limbic system, and Alpha, which drives the pre-frontal cortex.  Earliest positive results of neurofeedback in addiction studies focused on training the relationship between alpha and theta and led to wider-spread us of an eyes-closed alpha/theta training (Sokhadze, 2008).  Peniston and Kulkosky (1989) conducted the first randomized and controlled study of alcoholics treated with alpha-theta brain training.   What we now call the Peniston protocol demonstrated significant improvements in reduction of depression, increase in treatment retention, stabilization of the stress indexing beta-endorphins, more sustained relapse prevention, improvements in psychological adjustment measures (Peniston & Kulkosky, 1989, 1990).  Significantly, the experimental group exhibited 80% sobriety rate at the 1-year follow up.  These results have been replicated in multiple studies (Sokhadze, 2008).

Bill Scott, an earlier neurofeedback pioneer, furthered development of the Peniston protocol.  His early work recognized that training phenotype dysregulations associated with ADHD, depression, and anxiety concurrently with alpha-theta training would enhancing overall training efficacy in addicted populations.  Scott’s (Scott, Kaiser, Othmer, & Sideroff, 2005) study confirmed his hypothesis, demonstrating a 44% increase in program retention, 67% decrease in against-medical-advice departures, and 77% success rate 18-months post-study.  His application of beta/theta and sensory motor training protocols in addition to alpha-theta training are now known as the Scott-Kaiser modification to the Peniston Protocol (Sokhadze et al, 2008).  Scott et al’s (2005) application of the protocol of the application named after him has been replicated 7-times (DeBeus, Prinzel, Ryder-Cook & Allen, 2001; Burkett, Cummins, Dickson, &Skolnick, 2005; Narimani & Rajabi, 2011; Dehghani-Arani, Rostami, & Nadali, 2013; Keith et al, 2015; Rostami & Dehghani-Arani, 2015; Hashemian, 2015).

More recent developments in phenotype models demonstrate regional arousal levels that include the previously identified addiction phenotypes, and add several phenotypes that more distinctly address other implicated brain-regions (Amen, 2015).  As previously discussed, assessing the multiplicity of brain-phenotypes is beyond the scope and practice of most clinicians, even many experienced neurofeedback therapists.  Designing and implementing treatment protocols that address the multiplicity of symptoms is also beyond the experience scope of all but the most experienced neurofeedback therapists.  Further, clinician guided NFBT requires ongoing evaluation of in-session, and between-session changes that typically identify overzealous brain-training.  Nearly all previous positive studies demonstrating NFBT’s efficacy in supporting addiction recovery and improving long-lasting EEG patterns have relied on complex neurofeedback systems requiring extensive training and experience, with accumulated understanding of neurophysiology.  The complexity of systems, skills, and knowledge required for its clinical and sub-clinical applications has limited more broad spread application of this behavioral training method.

Pioneer neurofeedback researcher and therapist Bill Scott recognized the multiplicity of brain-phenotype symptoms early in NFBT’s history.  In addition to creating the only 3-dimensional visual feedback instrument, a fractal image of the brain’s total EEG, Scott developed NFBT’s first, and as far as we know, only automated brain-training system, BrainPaint.   The BrainPaint system is a widely used, automated phenotype-based assessment and training human-computer interface.  Its design includes a 90-question psycho-physiological assessment with strong correlations to Amen’s 7-brain phenotypes for ADD/ADHD. Additionally, the automated assessment includes symptom assessment for each of the phenotypes associated with anxiety, depression, addictions, and eating disorders.  Once the trainer completes the automated assessment, the automated system produces recommended training protocol  suggestions that have demonstrated efficacy in others with related brain-phenotypes.

Scott’s automated NFBT system converges the long history of neurofeedback’s demonstrated efficacy in symptom relief in a broad range of mental-health disorders with the emerging understanding of brain-phenotypes.   Though BrainPaint has been widely used in research and clinical settings with great efficacy, little literature yet exists on its unique ability to assess and train to specific brain-phenotype arousal levels.   Developments in automated NFBT systems provide an advantage in that they directly assist neurofeedback practitioners in assessing and training Arousal levels in those regions identified by the trainee’s individual brain phenotype.

Scott’s development and continued enhancements to his BrainPaint platform provide the ability to more easily identify individual arousal levels from reported symptoms and behavioral manifestations.  The computerized evaluation, incorporated into the BrainPaint software includes the 90-question Symptoms Checklist 90 – Revised  that can be completed by the trainer and trainee in approximately 30-minutes.  With children, the trainer and trainee’s parents complete the evaluation, with the child present.  Once the evaluation questions are answered, the system produces brain-training protocol suggestions specific to each individual’s phenotype, and brain-training can commence immediately.  We propose that a trained school/district level behavioral interventionist can easily implement the BrainPaint evaluation in a sub-clinical setting.  This model was tested in the Juneau School district in a 2 year grant aimed at reducing suicides in the school in 2010.  The school eliminated suicides for the entire duration of their use of BrainPaint.

BrainPaint’s automated production of individualized training protocol suggestions eliminates the skills/knowledge requirements of most NFBT systems.  Nearly all childhood brain-phenotypes are trained at two sites along the Sensory Motor Strip with the Brainpaint system, with demonstrated equal efficacy to more complex 19-site NFBT training (Keith et al, 2015).  This feature enables much easier technical administration of brain-training, reducing much of the complexity of NFBT to pasting sensors to the trainee’s scalp and ears, and coaching them to train their brains.

Scott also had the foresight to include several behavioral and psychiatric evaluation tools within the Brainpaint platform that have great utility in demonstrating, to the client, and in supporting research, positive gains of neurofeedback.  These tools are also helpful in determining appropriate training termination points, in that they will identify when a client plateau’s in their training.  The BrainPaint system includes a Continuous Performance Test (CPT) that reliably assesses attention, focus, and impulse control.  BrainPaint’s CPT can be used pre-during-and post training.  For evaluation and research, we recommend the CPT every 5-10 sessions.  BrainPaint also includes an automated in-session and between-session evaluation, helpful in identifying overzealous or under zealous training protocols, able to make immediate changes to training intensities, on-the-fly. Session-by-session tools to evaluate significant negative effects of neurofeedback which, when appropriate, offer the opportunity to further enhance the training protocol, reducing any identified negative effects.  Finally, all clinical and non-clinical trainers will appreciate the semi-automatic production of treatment goals.  Scott has developed and included a list of several hundred phenotype related behavioral goals that can be used as is, or adapted on-the-fly for each client.  Goal setting assists the neurofeedback process by providing specific behavioral measurements that the client can report improvements/declines in their next session.  As progress towards each goal moves towards attainment, trainer and trainee can identify further goals that might be achieved through additional training, or move towards termination of the current cycle of NFBT.

Scott’s BrainPaint system is likely one of the more widely used neurofeedback systems, and as previously discussed, is the only automated NFBT system with demonstrated efficacy in both research and clinical settings.  Though little research has been conducted in the broader scope of brain-phenotype directed training, Keith et al (2015) demonstrated that this system was equally effective in both assessing and training in a population of addicted individuals with co-occurring ADHD symptoms.

We have used BrainPaint in clinical and non-clinical settings to assess and train over 200 individuals, from nearly all of the eleven known brain-phenotypes.  ADHD symptoms are the predominant issues in our child and adolescent clients, while anxiety, depression, and addiction predominate our adult clients.  Our clients typically experience the reduction in symptomology in the first few sessions, congruent with Scott’s reporting, with 80-85% symptom reduction occurring between sessions 20-40.  Congruent with McReynolds et al (2018) reporting, our clients report that symptom reduction continues past termination of NFBT, which leads us to believe that near-complete symptom reduction is possible for nearly all mental health disorders when phenotype based NFBT is administered.

Sub-clinical application of Neurofeedback

Currently, there is no licensing requirement to perform neurofeedback, and is regulated under the scope-of-practice of state-licensing boards.  As a behavioral intervention, it can be learned and implemented by a broad scope of current school/district level behavioral interventionists.  There is a national certification board that reviews applicant’s experience and education.  Certification is available at two levels, technician, and therapist, requires 36-hours of CEU’s in specific areas of knowledge pertinent to the field, and clinical supervision (BCIA.org).   BrainPaint provides a ready-to use and implement system on a leased basis, providing great flexibility for the development and maintenance of a cost-effective behavioral intervention program.  Trainers are provided a System and Operations manual that can typically be completed in 10-hours or less, and BrainPaint conducts a weekly support webinar attended by BrainPaint trainers worldwide.

Conclusion:  We propose that Automated Neurofeedback Brain-training systems have evolved both towards practical application and demonstrated efficacy and safety to further explore their use as a primary behavioral intervention in sub-clinical settings, specifically school/district level brain-training labs.  The BrainPaint automated system reduces training requirements, purchase of complex NFBT assessment and training systems, and provides a ready-to-use NFBT system with wide applicability in clinical and subclinical settings.  Its system includes tools that can, and should be used in evaluating a phenotype approach to NFBT, and can be implemented easily, affordably, and safely.

 

References

Amen, D.G. (2015).  Change Your Brain Change Your Life.  New York, NY.  Harmony Books

Amen, D. G., Hanks, C., Prunella, J. (2008). Predicting positive and negative treatment responses to stimulants with brain SPECT imaging.  Journal of Psychoactive Drugs, 40(2), Epub 2008/08/30. PubMed PMID: 18720661

Burkett V, Cummins J, Dickson R, Skolnick M (2005) An Open Clinical Trial Utilizing Real-Time EEG Operant Conditioning as an Adjunctive Therapy in the Treatment of Crack Cocaine Dependence. Journal of Neurotherapy, Vol. 9(2) 2005 by The Haworth Press, Inc.

DeBeus, R., Prinzel, H., Ryder-Cook, A., & Allen, L. (2001, October). QEEG-based versus research-based EEG biofeedback treatment with chemically dependent outpatients: Preliminary results. Paper presented at the 9th annual conference for the Society of Neuronal Regulation, Monterey, CA.

Dehghani-Arani, F., Rostami, R., & Nadali, H. (2013). Neurofeedback training for opiate addiction: Improvement of mental health and craving. Applied Psychophysiology and Biofeedbck:38(2),133–141.

Gunkelman, J., & Cripe, C. (2008).  Clinical Outcomes in Addiction:  A Neurofeedback Case Series.  Biofeedback 36(3), 152-156

Hashemian, P. (2015) The Effectiveness of Neurofeedback Therapy in Craving of Methamphetamine Use. Open Journal of Psychiatry:5, 177-179.

Keith, J.R., Rapgay, L., Theodore, D., Schwartz, J. M., & Ross, J. L., (2015).  An Assessment of an Automated EEG Biofeedback System for Attention Deficits in a Substance Use Disorders Residential Treatment Setting.  Psychology of Addictive Behaviors, 29(1), 17-25.

Kelly, J. F., Bergman, B, Hoeppner, B, Vilsaint, C, White, W. (2017).  Prevalence and pathways of recovery from drug and alcohol problems in the United States population:  Implications for practice, research, and policy.  Drug & Alcohol Dependence, 181, 162-169

McKay, J., Atterman, A., Rutherford, M., Cacciola, J., & McLellan, A. (1999). The relationship of alcohol use to cocaine relapse in cocaine dependent patients in an after-care study. Journal of Studies on Alcohol,60,176–180.

Mclellan, A. T., Lewis, D. C., Brien, C. P. O., & Kleber, H. D. (2000). Drug dependence, a chronic medical illness: Implications for treatment, insurance, and Outcomes Evaluation. JAMA, 284(13), 1689– 1695.

McReynolds, C. J., Villalpando, L. S., & Britt, C. E. (2018).  Using Neurofeedback to Improve ADHD Symptoms in School-Aged Children.  NeuroRegulation, 5(4), 109-128.  http://dx.doi.org/10.15540/nr.5.4.109

Narimani M, Rajabi, S (2011) Evaluation of Alpha/Theta Neurofeedback Composed with Scott and Kaiser Protocol as a Treatment for Substance Use Disorders, International Journal of Psychology, Vol. 5, No. 2, Summer & Fall 2011 PP. 93-114 PP. 146-160.

Peniston, E. G., & Kulkosky, P. J. (1990). Alcoholic personality and alphatheta brainwave training. Medical Psychotherapy, 2, 37–55.

Peniston, E. G., & Kulkosky, P. J. (1989). Alpha theta brainwave training and beta-endorphin levels in alcoholics. Clinical and experimental research, 13, 271-279.

Ros, T., J Baars, B., Lanius, R. A., & Vuilleumier, P. (2014). Tuning pathological brain oscillations with neurofeedback: a systems neuroscience framework. Frontiers in human neuroscience, 8, 1008.

Ros T., Frewen P., Théberge J., Michela A., Kluetsch R., Mueller A., et al. (2016). Neurofeedback tunes scale-free dynamics in spontaneous brain activity. Cereb. Cortex

Rostami R, Dehghani-Arani F. (2015). Neurofeedback Training as a New Method in Treatment of Crystal Methamphetamine Dependent Patients: A Preliminary Study. Appl Psychophysiol Biofeedback:2015 Apr 19.

Scott, W. C. (2018).  Brainpaint Training Manual

Scott, W. C., Kaiser, D., Othmer, S., & Sideroff, S. I. (2005). Effects of an EEG biofeedback protocol on a mixed substance abusing population. American Journal of Drug Alcohol Abuse, 31(3), 455–469.

Sokhadze, T. M., Cannon, R. L., Trudeau, D. L. (2008).  EEG Biofeedback as a Treatment for Substance Use Disorders:  Review, Rating of Efficacy, and Recommendations for Further Research.  Journal of Applied Psychophysiology and Biofeedback 33:1-28

Shepard, J. C. (2008).  Neurofeedback Training for Substance Use Disorders:  A Review of the Applicability in Treatment. Ideas and Research You Can Use:  VISTAS 2015.  68.  Retrieved from: https://www.counseling.org/docs/default-source/vistas/ article_68a05a22f16116603abcacff0000bee5e7.pdf?sfvrsn=3e4c422c_4

Post Traumatic Stress Syndrome

Automated Neurofeedback Brain-training as a Primary PTSD Intervention
Donald Posson, Ph.D., LADC, BCN

Abstract: Neurofeedback brain-training has a significant presence in the literature for its efficacy in
alleviating the symptoms and behavioral manifestations of PTSD, with no enduring negative side-effects.
It is considered a behavioral intervention in that it teaches the brain to better manage its own brainwave
activity, leading to reduction of 80-85% of symptoms in the first 30-40 training sessions. Braintraining
has shown efficacy in improving recovery from anxiety, depression, insomnia, addictions,
emotional and cognitive dysregulation, attention, impulse control and many more co-occurring
symptoms of PTSD. Barriers to broad-based implementation in both clinical and subclinical settings
include cost of equipment, lengthy, in-depth training requirements, and a lack of clear guidance in
developing and implementing brain-training protocols specific to each individual’s brain-phenotype.
Automated Psychophysiological assessment and EEG Biofeedback training systems demonstrate equal
efficacy as clinician-guided EEG Systems. We propose that Automated EEG Biofeedback systems have
evolved to differentiate and train a multiplicity of brain-phenotypes related to PTSD. Further, these
systems decrease the cost of brain-training significantly, reduce the training requirements for braintrainers,
and significantly increase the effectiveness of all other behavioral and pharmacological
interventions. We propose that automated brain-training can be more broadly implemented in clinical
and sub-clinical settings as a primary behavioral intervention for PTSD.
Introduction:
Post-traumatic stress disorder (PTSD) is a widespread debilitating disorder with substantial
negative affects in academic, employment, social, emotional, health dimensions, and quality of life
(Asnaani Reddy, & Shea, 2014; Irish et al., 2013; Pagotto, et al., 2015). From the neurological
perspective, PTSD is best described as a complex dysregulation of neurological function of intrinsic
connectivity networks (ICN). EEG activity in these networks become dysregulated as a result of trauma.
Whether or not PTSD is acute or chronic is dependent on the ability of these networks to return to a
more regulated state, spontaneously, or through treatment interventions. Psychopharmacological
therapies attempting to regulate these networks have failed to produce efficacious and enduring
outcomes, or significant reduction in diagnosis of those treatment of PTSD. Similarly, psycho-social
treatments currently used in treating PTSD only benefit about half of those treated, with most
continuing to have substantial residual symptoms negatively impacting their life (Gapen et al, 2016, van
der Kolk et al, 2016)
Neuro imaging and EEG Brain-mapping research over the past three-decades has produced
significant insight into ICN involvement in PTSD and other related and non-related mental health
disorders. The Arousal Model developed from these studies identify eleven universal brain-phenotypes
involved in nearly all mental health disorders. These brain-phenotypes, subtypes of mental health
disorders describe symptom and behavioral manifestations of regional brain over-arousal, underarousal,
or instability. (Gunkelman & Cripe, 2008; Amen, 2015). In PTSD, dysregulation of three intrinsic
connectivity networks are identified: The Central Executive Network (CEN), the Salience Network (SN),
and the Default Mode Network (DMN). The CEN, including the right inferior parietal lobule and the right
inferior frontal gyrus, is crucial to executive functioning and verbal learning. The Salience Network (SN)
consists of the dorsal anterior cingulate cortex and the frontoinsular cortex, directs behavior to the most
important stimuli. The Default Mode Network (DMN) consists of the anterior and posterior medial
cortices and lateral parietal lobes. The DMN affects autobiographical memory, referential processing,
and social cognition (Lanius, Frewen, Tursich, Jetly, & McKinnon, 2015).
The PTSD phenotype demonstrates a pattern of low arousal in the CEN, accompanied by higher
arousal in the DMN. Dysregulation of the SN maintains the condition of pre-frontal under-arousal and
limbic-system over-arousal in PTSD populations. The extensive body of neuroimaging studies is
revelatory for understanding the underlying neurological imbalances involved in PTSD, for predicting
medication efficacy and especially for understanding the importance of automated neurofeedback as a
primary intervention for PTSD.
Our purpose in this article is to provide an overview the literature on the effectiveness of
neurofeedback as a PTSD intervention, specifically by addressing intrinsic connectivity network
dysregulation. Next, we will describe evolvement of automated NFB assessment and interventions,
potential side effects, and contraindications. I will review the research support for brain-training in
various addiction and mental health populations. Finally, strategies for integrating automated braintraining
systems in clinical and subclinical settings is explored.
Neuroimaging and EEG research provides many new clues to the underlying etiology of PTSD
and the frequently co-occurring symptoms related to other brain-wave imbalances. In fact, it is only
through seeing and hearing brain activity that a comprehensive Arousal model has developed that
provides a framework for both diagnosing and treating the broad range of PTSD symptoms. Brain
imagining techniques have developed at a significantly rapid pace over the past 3 decades, leading to a
much more comprehensive understanding of the effects of regional brain arousal levels: under-aroused,
over-aroused, or unstable, on mental health symptoms. Researchers have now identified Eleven
universal brain-phenotypes that describe out-of-balance arousal levels implicated in nearly all mental
health disorders. Seven individual brain-phenotypes have been identified related to ADHD specifically,
with seven phenotypes identified for Anxiety/Depression, six phenotypes for Addiction, and six
phenotypes for Eating Disorders. There is considerable overlap between the PTSD symptoms and
phenotypes related to other mental health disorders. Identifying the individual brain-phenotype
involved in PTSD, and other disorders, is a critical first step in diagnosis, and is necessary for predicting
medication efficacy (Amen, Hanks, & Prunella, 2008).
Limbic-System Hijacking
In PTSD, as well as addictions, there is an unhealthy relationship between the brain-waves Alpha
in our prefrontal cortex, and Theta in the Limbic System. Changes in the ratio of these brain waves are
triggered by sensory memory inputs. Sensory memory systems record input throughout our life, some
pleasant, some unpleasant. In times of trauma, some of those sensory memories can become linked to
the limbic system memory, which is a much more biological memory. In addictions, the limbic system
memory remembers how good it felt, how much relief was provided. In the case of PTSD, the limbic
system, remembers how bad it felt. When triggered, the limbic system memory activates the autonomic
fight-or-flight response, showing up in brain waves as an escalation of Theta, the rhythm that largely
drives the limbic system. Needing more energy to maintain this state of alert, the brain shifts (steals)
energy from elsewhere. In the case of both addictions and PTSD, the brain steals energy from the prefrontal
cortex rhythm Alpha. One can imagine, that without enough Alpha pre-frontally, that portion of
the brain doesn’t have sufficient energy to do its job sufficiently. Some of the most important prefrontal
left functions are cognition, impulse control, emotional regulation, and decision making. Prefrontal right
functions include empathy, compassion, self-care.
This makes a lot of sense physiologically. The thalamus, the brains gatekeeper of sensory
information, is very close to the limbic system, and very distant, relatively, to the prefrontal cortex. The
limbic system gets the information first, and results in what has been called “limbic system hijacking.”
When we monitor this brain process with electroencephalograph (EEG) we see Theta taking control of
the brain, draining energy from Alpha in the prefrontal cortex. Literally, the part of the brain we need
for good recovery does not have the energy it needs to do its job. From the neurofeedback perspective,
limbic system hijacking represents dysregulation of the brain-reward circuitry and provides the basis for
development of brain-training protocols specific to correcting this dysregulation, Alpha/Theta training.
Until recently, assessing brain-phenotypes for PTSD and other mental health disorders required
extensive clinical training and experience. Accurate assessment has traditionally relied on quantitative
Electroencephalograph (qEEG) evaluation. qEEG systems listen to the various components of brainwave
activity. The most comprehensive qEEG systems analyze data obtained from 19-channels on the
scalp where brain-wave signals are known to rise sufficiently to be heard by sensors placed on those
locations. The signals are amplified, and the data is compared against norms of normal brain activity.
The data produces graphics that can identify over 5,100 components of brain activity including arousal
levels, connectivity, coherence, and brain-injury. Unfortunately, recording and interpreting the qEEG
requires complex interpretations of baseline Electroencephalograph (EEG), participants’ presenting
symptoms, between-session changes in symptoms, and within session reward criteria. Complex
neurofeedback systems, and the necessary skills and knowledge to effectively operate them are typically
well beyond operational capacity of most mental health providers, let those assisting PTSD survivor’s in
non-clinical environments.
A second form of assessing brain-phenotypes, psycho-physiological assessment, demonstrates
equal efficacy in reducing PTSD symptoms (Keith, Theodore, Rapgay, Schwartz, & Ross, 2015) and other
brain-phenotype imbalances (Scott, 2018). Psycho-physiological assessments more coherently identify
both PTSD and other co-occurring mental health symptoms then the DSM-V and ICD-10 include, thereby
providing a broader understanding of the underlying brain-arousal levels and their implications for both
assessment and treatment. Rather than identifying single features of a specific diagnostic category,
psychophysiological assessments provide a more comprehensive perspective on all the mental health
issues that may impede cognitive processing, social engagement, emotional stability, and quality of life
for those with PTSD symptoms. Technological development within the neurofeedback field now
provides guided semi-automatic psychophysiological assessment and training hardware/software with
demonstrated equal efficacy when compared with more complex clinical guided neurofeedback (Keith
et al., 2015). Automated assessment and brain-training hardware/software provides practical, safe, and
effective brain training tools that can be readily implemented a broad range of clinical and sub-clinical
settings.
Neurofeedback Brain-Training (NFBT) is a form of evidence-based behavioral therapy that uses a
computer-human interface to receive, interpret, and provide feedback of brain electrical energy to the
trainee. This form of operant conditioning facilitates the brain’s neuro-plasticity, its ability to rapidly
change and reorganize neural pathways in response to brain-training. NFBT has been broadly
recognized as effective in alleviating brain imbalances implicit in a broad range of mental health
disorders, including PTSD. NFBT is safe, with the only reported common side effects of mild headaches
and/or slight disorientation. Approximately 75-80% of brain-trainees successfully learn how to train
their brain-waves, typically eliminating 80-85% of symptoms related to their brain phenotype (Shepard,
2008, Valenzuela, 2016).
NFBT, in nearly every study, has been recommended as an excellent candidate as a PTSD
intervention. It is non-invasive, has few reported short-term side effects, and no reported enduring
side-effects. Unlike other PTSD therapeutic models, NFBT directly addresses and alleviates arousal
dysregulation by training the brain to better manage its own arousal states. NFBT has been
demonstrated to improve scores on the MMPI (Peniston and Kulkosky, 1991; Peniston, Marrinan,
Deming & Kulkosky, 1993), reduce anxiety levels (Nicholson et al, 2016), increase emotional regulation,
and decreases dissociative symptoms (Nicholson et al, 2017). Clinically significant reductions of PTSD
symptoms have been reported by Gerin, et al (2016) and van der Kolk et al. (2016) after NFBT.
Though nearly all reports of NFBT’s benefits in PTSD treatment yield positive outcomes, a
primary concern is the lack of cohesiveness in identifying, using, and researching the broad spectrum of
protocols utilized in NFBT (Panisch & Hai, 2018). As previously discussed, methodological evaluation of
brain-phenotypes has been largely restricted to clinician administered qEEG analysis, with most training
conducted with variations of Alpha/Theta training. More recent developments in phenotype models
demonstrate regional arousal levels implicated in PTSD (Amen, 2015). Assessing the multiplicity of
brain-phenotypes is beyond the scope and practice of most clinicians, even many experienced
neurofeedback therapists. Designing and implementing treatment protocols that address the
multiplicity of symptoms is also beyond the experience scope of all but the most experienced
neurofeedback therapists. Further, clinician guided NFBT requires ongoing evaluation of in-session, and
between-session changes that typically identify over zealous brain-training. Nearly all previous positive
studies demonstrating NFBT’s efficacy in alleviating PTSD symptomology and improving long-lasting EEG
patterns have relied on complex neurofeedback systems requiring extensive training and experience,
with accumulated understanding of neurophysiology. The complexity of systems, skills, and knowledge
required for its clinical and sub-clinical applications has limited more broad spread application of this
behavioral training method.
Pioneer neurofeedback researcher and therapist Bill Scott recognized the multiplicity of brainphenotype
symptoms early in NFBT’s history. In addition to creating the only 3-dimensional visual
feedback instrument, a fractal image of the brain’s total EEG, Scott developed NFBT’s first, and as far as
we know, only automated brain-training system, BrainPaint. The BrainPaint system is a widely used,
automated phenotype-based assessment and training human-computer interface. Its design includes a
90-question Symptom Checklist 90-R which can be used in assessment as well as research applications.
Additionally, the automated assessment includes symptom assessment for each of the phenotypes
associated with anxiety, depression, addictions, and eating disorders. Once the trainer completes the
automated assessment, the automated system produces recommended training protocol suggestions
that have demonstrated efficacy in others with related brain-phenotypes.
Scott’s automated NFBT system converges the long history of neurofeedback’s demonstrated
efficacy in symptom relief in a broad range of mental-health disorders with the emerging understanding
of brain-phenotypes. Though BrainPaint has been widely used in research and clinical settings with
great efficacy, little literature yet exists on its unique ability to assess and train to specific brainphenotype
arousal levels. Only one study has been conducted comparing clinician guided NFBT with
automated neurofeedback. Keith et al. (2015) demonstrated that automated systems have equal
efficacy in positive outcomes as clinician guided NFBT. Developments in automated NFBT systems
provide an advantage in that they directly assist neurofeedback practitioners in assessing and training
Arousal levels in those regions identified by the trainee’s individual brain phenotype.
Scott’s development and continued enhancements to his BrainPaint platform provide the ability
to more easily identify individual arousal levels from reported symptoms and behavioral manifestations.
The computerized evaluation, incorporated into the BrainPaint software to evaluate individualized
brain-arousal levels, can be completed by the trainer and trainee in approximately 30-minutes. With
children, the trainer and trainee’s parents complete the evaluation, with the child present. Once the
evaluation questions are answered, the system produces brain-training protocol suggestions specific to
each individual’s phenotype, and brain-training can commence immediately. We propose that a trained
behavioral interventionist can easily implement the BrainPaint evaluation in clinical and sub-clinical
settings. BrainPaint’s automated production of individualized training protocol suggestions eliminates
the skills/knowledge requirements of most NFBT systems. Automated NFBT systems typically reduce
the complexity of technical aspects of administering NFBT by using three-sites only for most training
protocols. Phenotypes identified by Amen (2015) for ADHD, anxiety, and depression are trained with
eyes-open training at two sites along the Sensory Motor Strip with the Brainpaint system, with
demonstrated equal efficacy to more complex 19-site NFBT training (Keith et al, 2015). Phenotypes
related to PTSD, addictions, and personality disorders are trained at one location at the back of the
scalp, where Alpha and Theta brain-waves can be identified and trained in eyes-closed modality. This
feature enables much easier technical administration of brain-training, reducing much of the complexity
of NFBT to pasting sensors to the trainee’s scalp and ears, and coaching them to train their brains.
Scott also had the foresight to include several behavioral and psychiatric evaluation tools within
the Brainpaint platform that have great utility in demonstrating, to the client, and in supporting
research, positive gains of neurofeedback. These tools are also helpful in determining appropriate
training termination points, in that they will identify when a client plateau’s in their training. The
BrainPaint system includes a Continuous Performance Test (CPT) that reliably assesses attention, focus,
and impulse control. BrainPaint’s CPT can be used pre-during-and post training. For evaluation and
research, we recommend the CPT every 5-10 sessions. BrainPaint also includes an automated in-session
and between-session evaluation, helpful in identifying overzealous or under zealous training protocols,
able to make immediate changes to training intensities, on-the-fly. Session-by-session tools to evaluate
significant negative effects of neurofeedback which, when appropriate, offer the opportunity to further
enhance the training protocol, reducing any identified negative effects. Finally, all clinical and nonclinical
trainers will appreciate the semi-automatic production of treatment goals. Scott has developed
and included a list of several hundred phenotype related behavioral goals that can be used as is or
adapted on-the-fly for each client. Goal setting assists the neurofeedback process by providing specific
behavioral measurements that the client can report improvements/declines in their next session. As
progress towards each goal moves towards attainment, trainer and trainee can identify further goals
that might be achieved through additional training or move towards termination of the current cycle of
NFBT.
Scott’s BrainPaint system is likely one of the more widely used neurofeedback systems, and as
previously discussed, is the only automated NFBT system with demonstrated efficacy in both research
and clinical settings. Though little research has been conducted in the broader scope of brainphenotype
directed training, Keith et al (2015) demonstrated that this system was equally effective in
both assessing and training in a population of addicted individuals with co-occurring ADHD symptoms.
We have used BrainPaint in clinical and non-clinical settings to assess and train over 200 individuals,
from nearly all the eleven known brain-phenotypes. PTSD symptoms are the predominant issues in our
veteran clients, while anxiety, depression, and addiction predominate our adult non-veteran clients.
Occasionally, we have trained PTSD symptoms out of our child and adolescent clients, though that
population primarily presents with ADHD.
Our clients typically experience the reduction in symptomology in the first few sessions,
congruent with Scott’s reporting, with 80-85% symptom reduction occurring between sessions 20-40.
Congruent with McReynolds et al (2017) reporting, our clients report that symptom reduction continues
past termination of NFBT, which leads us to believe that near-complete symptom reduction is possible
for nearly all mental health disorders when phenotype based NFBT is administered.
Sub-clinical application of Neurofeedback
Currently, there is no licensing requirement to perform neurofeedback, and is regulated under
the scope-of-practice of state-licensing boards. As a behavioral intervention, it can be learned and
implemented by a broad scope of current clinical and non-clinical level behavioral interventionists.
There is a national certification board that reviews applicant’s experience and education. Certification is
available at two levels, technician, and therapist, requires 36-hours of CEU’s in specific areas of
knowledge pertinent to the field, and clinical supervision (BCIA.org). BrainPaint provides a ready-to use
and implement system on a leased basis, providing great flexibility for the development and
maintenance of a cost-effective behavioral intervention program. Trainers are provided a System and
Operations manual that can typically be completed in 10-hours or less, and BrainPaint conducts a
weekly support webinar attended by BrainPaint trainers worldwide.
Conclusion: We propose that Automated Neurofeedback Brain-training systems have evolved both
towards practical application and demonstrated efficacy and safety to further explore their use as a
primary behavioral intervention in sub-clinical settings. The BrainPaint automated system reduces
training requirements, purchase of complex NFBT assessment and training systems, and provides a
ready-to-use NFBT system with wide applicability in clinical and subclinical settings. Its system includes
tools that can and should be used in evaluating a phenotype approach to NFBT, and can be
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