EEG – Lessons From A Half-Million Brains


Listen to the full podcast here Jay Gunkelman Podcast

This week we’re joined by QEEG Diplomate (yes, that’s a term!) and founder of Brain Science International Jay Gunkelman, to talk Electroencephalography.  After analyzing over a half-million EEG scans, Jay has a pretty robust set of human brain data at his disposal… And he uses that body of knowledge to guide the work of psychiatric and other health professionals who make proscriptive recommendations about patients’ brains.

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Differential effects of theta/beta and SMR neurofeedback in ADHD on sleep onset latency

Recent studies suggest a role for sleep and sleep problems in the etiology of attention deficit hyperactivity disorder (ADHD) and a recent model about the working mechanism of sensori-motor rhythm (SMR) neurofeedback, proposed that this intervention normalizes sleep and thus improves ADHD symptoms such as inattention and hyperactivity/impulsivity. In this study we compared adult ADHD patients (N = 19) to a control group (N = 28) and investigated if differences existed in sleep parameters such as Sleep Onset Latency (SOL), Sleep Duration (DUR) and overall reported sleep problems (PSQI) and if there is an association between sleep-parameters and ADHD symptoms. Secondly, in 37 ADHD patients we investigated the effects of SMR and Theta/Beta (TBR) neurofeedback on ADHD symptoms and sleep parameters and if these sleep parameters may mediate treatment outcome to SMR and TBR neurofeedback. In this study we found a clear continuous relationship between self-reported sleep problems (PSQI) and inattention in adults with- and without-ADHD. TBR neurofeedback resulted in a small reduction of SOL, this change in SOL did not correlate with the change in ADHD symptoms and the reduction in SOL only happened in the last half of treatment, suggesting this is an effect of symptom improvement not specifically related to TBR neurofeedback. SMR neurofeedback specifically reduced the SOL and PSQI score, and the change in SOL and change in PSQI correlated strongly with the change in inattention, and the reduction in SOL was achieved in the first half of treatment, suggesting the reduction in SOL mediated treatment response to SMR neurofeedback. Clinically, TBR and SMR neurofeedback had similar effects on symptom reduction in ADHD (inattention and hyperactivity/impulsivity). These results suggest differential effects and different working mechanisms for TBR and SMR neurofeedback in the treatment of ADHD.

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FDA Approval of EEG Aid for ADHD


There has been a lot of discussion since the FDA announced approving a new medical device just approved to assist in the diagnosis of ADHD in children and adolescents. “The device, the Neuropsychiatric EEG-Based Assessment Aid (NEBA) System, is based on electroencephalogram technology, which records different kinds of electrical impulses given off by neurons in the brain and the number of times the impulses are given off each second. The NEBA System is a 15- to 20-minute noninvasive test that calculates the ratio of two standard brain-wave frequencies, known as theta and beta waves; the ratio has been shown to be higher in children and adolescents with ADHD than in those without it, according to FDA” ( fda-approves-device-to-help-diagnose.html). However, the use of this technology to assist in the diagnosis of ADHD is not new.

David Rabiner, Ph.D. (Senior Research Scientist, Duke University) published a report (Attention Research Update April 2001) titled “New Support for the Use of qEEG scanning in Diagnosing ADHD” ( This report acknowledged utilizing the measure of the ratio of theta to beta waves in the prefrontal cortex as a marker for ADHD (ages 6-20). Therefore the technology is not new, and although the NEBA System is helping to bring scientific evidence into the realm of psychiatric diagnosis, there is more to it then has been discussed thus far.

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Technology Helps Explain Medication Failure

In almost every area of medicine, doctors can order tests to provide objective physical data to guide their medication selection. However, the practice of psychiatry is most often based on observation, self-report and psychological testing. It appears that we are better at measuring impairment than we are at identifying the source and prescribing an effective medication. Is there a way we can do better?

The director of the National Institute of Mental Health, Tomas Insel, suggests there are many medicines, but they are not working adequately. This is because the symptoms of mental illness are too illusive and are shared by many diagnoses. Insel (2012) says, “It’s much harder to fix something if you don’t know what is going wrong.” Medications are being prescribed to treat a set of symptoms suggestive of a specific disorder without any objective evidence of the cause. Additionally, the practice of polypharmacy has become way too common in children and adolescents.

Pharmaceutical industry advertising promotes adding a medication when the first medication fails to produce the desired results (i.e., adding Abilify to your antidepressant). The message is that when one medication fails, keep adding more in an effort to address the additional symptoms. Each additional medication increases the risk of side effects. It is not uncommon for children to come to us with several medications prescribed. Last month, for example, we saw a 9-year-old female with prescriptions for Olanzapine three times a day, Lithium Carbonate daily and Amphetamine Salts three times a day. Also, a 10-year-old male came to us on Focolin three times a day, Seroquel twice a day, Lexipro daily and Zyprexa daily. If there was a way to determine why a medication failed, would it not be prudent to investigate why? If current technology could help?

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The Effects of QEEG-Informed Neurofeedback in ADHD: An Open-Label Pilot Study

Martijn Arns • Wilhelmus Drinkenburg • J. Leon Kenemans

Abstract In ADHD several EEG biomarkers have been described before, with relevance to treatment outcome to stimulant medication. This pilot-study aimed at personalizing neurofeedback treatment to these specific sub-groups to investigate if such an approach leads to improved clinical outcomes. Furthermore, pre- and post-treatment EEG and ERP changes were investigated in a sub-group to study the neurophysiological effects of neurofeedback. Twenty-one patients with ADHD were treated with EEG-informed neurofeedback and post-treatment effects on inattention (ATT), hyperactivity/impulsivity (HI) and comorbid depressive symptoms were investigated. There was a significant improvement for both ATT, HI and comorbid depressive complaints after QEEG-informed neurofeedback. The effect size for ATT was 1.78 and for HI was 1.22. Furthermore, anterior individual alpha peak frequency (iAPF) demonstrated a strong relation to improvement on comorbid depressive complaints. Pre- and post-treatment effects for the SMR neurofeedback sub-group exhibited increased N200 and P300 amplitudes and decreased SMR EEG power post-treatment.

This pilot study is the first study demonstrating that it is possible to select neurofeedback protocols based on individual EEG biomarkers and suggests this results in improved treatment outcome specifically for ATT, however these results should be replicated in further controlled studies. A slow anterior iAPF at baseline predicts poor treatment response on comorbid depressive complaints in line with studies in depression. The effects of SMR neurofeedback resulted in specific ERP and EEG changes.

Read the full text here The Effects of QEEG-Informed Neurofeedback in ADHD:
An Open-Label Pilot Study
– This article is published with open access at Applied Psychophysiology and Biofeedback. doi: 10.1007/s10484-012-9191-4

QEEG-guided Neurofeedback: New Brain-based Individualized Evaluation and Treatment for Autism

by James Neubrander, MD, Michael Linden, PHD, Jay Gunkelman, QEEGd, and Cynthia Kerson, PHD

QEEG-guided neurofeedback is based on normalizing dysregulated brain regions that relate to specific clinical presentation. With ASD, this means that the approach is specific to each individual’s QEEG subtype patterns and presentation. The goal of neurofeedback with ASD is to correct amplitude abnormalities and balance brain functioning, while coherence neurofeedback aims to improve the connectivity and plasticity between brain regions. This tailored approach has implications that should not be underestimated. . . . Clinicians, including the authors, have had amazing results with ASD, including significant speech and communication improvements, calmer and less aggressive behavior, increased attention, better eye contact, and improved socialization. Many of our patients have been able to reduce or eliminate their medications after completion of QEEG-guided neurofeedback.

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New Study Shows – The increase in theta/beta ratio on resting-state EEG in boys with attention-deficit/hyperactivity disorder is mediated by slow alpha peak frequency

References and further reading may be available for this article. To view references and further reading you must purchase this article.


Attention-deficit/hyperactivity disorder (ADHD) was found to be characterized by a deviant pattern of electrocortical activity during resting state, particularly increased theta and decreased beta activity.

The first objective of the present study is to confirm whether individuals with slow alpha peak frequency contribute to the finding of increased theta activity in ADHD. The second objective is to explore the relation between resting-state brain oscillations and specific cognitive functions. From 49 boys with ADHD and 49 healthy control boys, resting-state EEG during eyes open and eyes closed was recorded, and a variety of cognitive tasks were administered. Theta and beta power and theta/beta ratio were calculated using both fixed frequency bands and individualized frequency bands. As expected, theta/beta ratio, calculated using fixed frequency bands, was significantly higher in ADHD children than control children. However, this group effect was not significant when theta/beta ratio was assessed using individualized frequency bands. No consistent relation was found between resting-state brain oscillations and cognition. The present results suggest that previous findings of increased theta/beta ratio in ADHD may reflect individuals with slow alpha peak frequencies in addition to individuals with true increased theta activity. Therefore, the often reported theta/beta ratio in ADHD can be considered a non-specific measure combining several distinct neurophysiological subgroups such as frontal theta and slowed alpha peak frequencies.

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How EEG can Show an Epileptogenic Process

This is the first of a few posts with a variety of ways the EEG can show an epileptogenic process. The morphology of the underlying process are quite dramatically varied.

The two images below show the referential and sequential montage display of an active right temporal-parietal spike and slow wave focus, seen in a child clinically diagnosed with an attachment disorder. There was no history of convulsion, nor any suspicion of the actual underlying pathophysiological basis for the behavioral presentation.

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