Publications

In major depressive disorder (MDD), elevated theta current density in the rostral anterior cingulate (rACC), as estimated by source localization of scalp-recorded electroencenphalogram (EEG), has been associated with response to antidepressant treatments, whereas elevated frontal theta has been linked to non-response. This study used source localization to attempt to integrate these apparently opposite results and test, whether antidepressant response is associated with elevated rACC theta and non-response with elevated frontal theta and whether theta activity is a differential predictor of response to different types of commonly used antidepressants. In the international Study to Predict Optimized Treatment in Depression (iSPOT-D), a multi-center, international, randomized, prospective practical trial, 1008 MDD participants were randomized to escitalopram, sertraline or venlafaxine-XR. The study also recruited 336 healthy controls. Treatment response and remission were established after eight weeks using the 17-item Hamilton Rating Scale for Depression (HRSD17). The resting-state EEG was assessed at baseline with eyes closed and source localization (eLORETA) was employed to extract theta from the rACC and frontal cortex. Patients with MDD had elevated theta in both frontal cortex and rACC, with small effect sizes. High frontal and rACC theta were associated with treatment non-response, but not with non-remission, and this effect was most pronounced in a subgroup with previous treatment failures. Low theta in frontal cortex and rACC are found in responders to antidepressant treatments with a small effect size. Future studies should investigate in more detail the role of previous treatment (failure) in the association between theta and treatment outcome.

Personalized medicine in psychiatry is in need of biomarkers that resemble central nervous system function at the level of neuronal activity. Electroencephalography (EEG) during sleep or resting-state conditions and event-related potentials (ERPs) have not only been used to discriminate patients from healthy subjects, but also for the prediction of treatment outcome in various psychiatric diseases, yielding information about tailored therapy approaches for an individual. This review focuses on baseline EEG markers for two psychiatric conditions, namely major depressive disorder and attention deficit hyperactivity disorder. It covers potential biomarkers from EEG sleep research and vigilance regulation, paroxysmal EEG patterns and epileptiform discharges, quantitative EEG features within the EEG main frequency bands, connectivity markers and ERP components that might help to identify favourable treatment outcome. Further, the various markers are discussed in the context of their potential clinical value and as research domain criteria, before giving an outline for future studies that are needed to pave the way to an electrophysiological biomarker-based personalized medicine.

In 2009 the United States National Institute of Mental Health (NIMH) introduced the Research Domain Criteria (RDoC) project, which intends to explicate fundamental bio-behavioral dimensions that cut across heterogeneous disorder categories in psychiatry. One major research domain is defined by arousal and regulatory systems. In this study we aimed to investigate the relation between arousal systems (EEG-beta phenotypes also referred to as spindling excessive beta (SEB), beta spindles or sub-vigil beta) and the behavioral dimensions: insomnia, impulsivity/hyperactivity and attention. This analysis is conducted within a large and heterogeneous outpatient psychiatric population, in order to verify if EEG-beta phenotypes are an objective neurophysiological marker for psychopathological properties shared across psychiatric disorders. SEBs had an occurrence between 0–10.8% with a maximum occurrence at frontal and central locations, with similar topography for the heterogeneous sample as well as a more homogenous ADHD subgroup. Patients with frontal SEBs only, had significantly higher impulsivity/hyperactivity (specifically on impulse control items) and insomnia complaints with medium effect sizes. Item level and mediation analysis revealed that sleep maintenance problems explained both frontal SEB EEG patterns (in line with SEB as a sub-vigil or hypoarousal EEG pattern) as well as the impulse control problems. These data thus suggest that frontal SEB might be regarded as a state marker caused by sleep maintenance problems, with concurrent impulse control problems. However, future longitudinal studies should investigate this state-trait issue further and replicate these findings Also studies manipulating SEB by for example neurofeedback and measuring consequent changes in sleep and impulse control could shed further light on this issue.

It is essential to improve antidepressant treatment of major depressive disorder (MDD) and one way this could be achieved is by reducing the number of treatment steps by employing biomarkers that can predict treatment outcome. This study investigated differences between MDD patients and healthy controls in the P3 and N1 component from the event-related potential (ERP) generated in a standard two-tone oddball paradigm. Furthermore, the P3 and N1 are investigated as predictors for treatment outcome to three different antidepressants. In the international Study to Predict Optimized Treatment in Depression (iSPOT-D)--a multi-center, international, randomized, prospective practical trial--1008 MDD participants were randomized to escitalopram, sertraline or venlafaxine-XR. The study also recruited 336 healthy controls. Treatment response and remission were established after eight weeks using the 17-item Hamilton Rating Scale for Depression. P3 and N1 latencies and amplitudes were analyzed using a peak-picking approach and further replicated by using exact low resolution tomography (eLORETA). A reduced P3 was found in MDD patients compared to controls by a peak-picking analysis. This was validated in a temporal global field power analysis. Source density analysis revealed that the difference in cortical activity originated from the posterior cingulate and parahippocampal gyrus. Male non-responders to venlafaxine-XR had significantly smaller N1 amplitudes than responders. This was demonstrated by both analytical methods. Male non-responders to venlafaxine-XR had less activity originating from the left insular cortex. The observed results are discussed from a neural network viewpoint.

This study could not confirm the association between the Catechol-O-Methyltransferase Val158Met polymorphism (COMT) and electroencephalographic (EEG) alpha peak frequency (APF) in two independent cohorts of 187 (96 depressed and 91 healthy participants) and 413 healthy participants. If COMT and APF play a role in depression or antidepressant treatment response, they do not have a shared pathway. We emphasize the importance of publishing null-findings for obtaining more accurate overall estimates of genetic effects.

Prediction studies in subjects at Clinical High Risk (CHR) for psychosis are hampered by a high proportion of uncertain outcomes. We therefore investigated whether quantitative EEG (QEEG) parameters can contribute to an improved identification of CHR subjects with a later conversion to psychosis.

In the present study the frontal and parietal P300, elicited in an auditory oddball paradigm were investigated in a large sample of healthy participants (N = 1572), aged 6-87. According to the concepts of the compensation-related utilization of neural circuits hypothesis (CRUNCH) it was hypothesized that the developmental trajectories of the frontal P300 would reach a maximum in amplitude at an older age than the amplitude of the parietal P300 amplitude. In addition, the amplitude of the frontal P300 was expected to increase with aging in adulthood in contrast to a decline in amplitude of the parietal P300 amplitude. Using curve-fitting methods, a comparison was made between the developmental trajectories of the amplitudes of the frontal and parietal P300. It was found that the developmental trajectories of frontal and parietal P300 amplitudes differed significantly across the lifespan. During adulthood, the amplitude of the parietal P300 declines with age, whereas both the frontal P300 amplitude and behavioral performance remain unaffected. A lifespan trajectory of combined frontal and parietal P300 amplitudes was found to closely resemble the lifespan trajectory of behavioral performance. Our results can be understood within the concepts of CRUNCH. That is, to compensate for declining neural resources, older participants recruit additional neural resources of prefrontal origin and consequently preserve a stable behavioral performance. Though, a direct relation between amplitude of the frontal P300 and compensatory mechanisms cannot yet be claimed.

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.

Among the clinical applications of neurofeedback, most research has been conducted in ADHD. As an introduction a short overview of the general history of neurofeedback will be given, while the main part of the paper deals with a review of the current state of neurofeedback in ADHD. A meta-analysis on neurofeedback from 2009 found large effect sizes for inattention and impulsivity and medium effects sizes for hyperactivity. Since 2009 several new studies, including 4 placebo-controlled studies, have been published. These latest studies are reviewed and discussed in more detail. The review focuses on studies employing (1) semi-active, (2) active, and (3) placebo-control groups. The assessment of specificity of neurofeedback treatment in ADHD is discussed and it is concluded that standard protocols such as theta/beta, SMR and slow cortical potentials neurofeedback are well investigated and have demonstrated specificity. The paper ends with an outlook on future questions and tasks. It is concluded that future controlled clinical trials should, in a next step, focus on such known protocols, and be designed along the lines of learning theory.

In this review article an overview of the history and current status of neurofeedback for the treatment of ADHD and insomnia is provided. Recent insights suggest a central role of circadian phase delay, resulting in sleep onset insomnia (SOI) in a sub-group of ADHD patients. Chronobiological treatments, such as melatonin and early morning bright light, affect the suprachiasmatic nucleus. This nucleus has been shown to project to the noradrenergic locus coeruleus (LC) thereby explaining the vigilance stabilizing effects of such treatments in ADHD. It is hypothesized that both Sensori-Motor Rhythm (SMR) and Slow-Cortical Potential (SCP) neurofeedback impact on the sleep spindle circuitry resulting in increased sleep spindle density, normalization of SOI and thereby affect the noradrenergic LC, resulting in vigilance stabilization. After SOI is normalized, improvements on ADHD symptoms will occur with a delayed onset of effect. Therefore, clinical trials investigating new treatments in ADHD should include assessments at follow-up as their primary endpoint rather than assessments at outtake. Furthermore, an implication requiring further study is that neurofeedback could be stopped when SOI is normalized, which might result in fewer sessions.

Several linear electroencephalographic (EEG) measures at baseline have been demonstrated to be associated with treatment outcome after antidepressant treatment. In this study we investigated the added value of non-linear EEG metrics in the alpha band in predicting treatment outcome to repetitive transcranial magnetic stimulation (rTMS).

As numbers of published articles rise, the scholarly review system must adapt to avoid unmanageable burdens and slipping standards, says Martijn Arns.

The P300 component of the event-related potential is a large positive waveform that can be extracted from the ongoing electroencephalogram using a two-stimuli oddball paradigm, and has been associated with cognitive information processing (e.g. memory, attention, executive function). This paper reviews the development of the auditory P300 across the lifespan.

This chapter summarises recent developments on personalised medicine in psychiatry with a focus on ADHD and depression and their associated biomarkers and phenotypes. Several neurophysiological subtypes in ADHD and depression and their relation to treatment outcome are reviewed. The first important subgroup consists of the 'impaired vigilance' subgroup with often-reported excess frontal theta or alpha activity. This EEG subtype explains ADHD symptoms well based on the EEG Vigilance model, and these ADHD patients responds well to stimulant medication. In depression this subtype might be unresponsive to antidepressant treatments, and some studies suggest these depressive patients might respond better to stimulant medication. Further research should investigate whether sleep problems underlie this impaired vigilance subgroup, thereby perhaps providing a route to more specific treatments for this subgroup. Finally, a slow individual alpha peak frequency is an endophenotype associated with treatment resistance in ADHD and depression. Future studies should incorporate this endophenotype in clinical trials to investigate further the efficacy of new treatments in this substantial subgroup of patients.

Personalized medicine aims to provide the right treatment for the right person at the right time, as opposed to the currently employed ‘one-size-fits-all ' approach. This development relies on identification of ADHD subgroups using biomarkers. One important ADHD subgroup is characterised by impaired vigilance regulation, as quantified by the EEG and this sub-group responds well to stimulant medication and neurofeedback. Recent insights suggest a clear association between reduced sleep duration and ADHD complaints in this sub-group of ADHD patients. A recently published model explains how different treatments e.g. chronobiological treatments and neurofeedback impact on this neural circuitry and mediate ADHD symptom improvement.

Objective: Many EEG studies have reported that ADHD is characterized by elevated Theta/Beta ratio (TBR). In this study we conducted a meta-analysis on the TBR in ADHD. Method: TBR data during Eyes Open from location Cz were analyzed from children/adolescents 6-18 years of age with and without ADHD. Results: Nine studies were identified with a total of 1253 children/adolescents with and 517 without ADHD. The grand-mean effect size (ES) for the 6-13 year-olds was 0.75 and for the 6-18 year-olds was 0.62. However the test for heterogeneity remained significant; therefore these ESs are misleading and considered an overestimation. Post-hoc analysis found a decreasing difference in TBR across years, explained by an increasing TBR for the non-ADHD groups. Conclusion: Excessive TBR cannot be considered a reliable diagnostic measure of ADHD, however a substantial sub-group of ADHD patients do deviate on this measure and TBR has prognostic value in this sub-group, warranting its use as a prognostic measure rather than a diagnostic measure.

Objective: Additional treatments with persisting benefit are needed for ADHD. Because ADHD often shows excessive theta electroencephalogram (EEG) power, low beta, and excessive theta-beta ratio (TBR), a promising treatment is neurofeedback (NF) downtraining TBR. Although several nonblind randomized clinical trials (RCTs) show a medium-large benefit for NF, a well-blinded, sham-controlled RCT is needed to differentiate specific from nonspecific effects. Method: Experts in NF, ADHD, clinical trials, and statistics collaborated to design a double-blind multisite RCT. Results/Conclusion: At four sites, 180 children aged 7 to 10 years with rigorously diagnosed ADHD and TBR ≥ 5 will be randomized to active TBR-NF versus sham NF of equal duration, intensity, and appearance. Sham, utilizing prerecorded EEGs with participant artifacts superimposed, will keep participants and staff blind. Treatment fidelity will be trained/monitored by acknowledged NF leaders. Multidomain assessments before, during, and after treatment (follow-up to 2 years) will also include tests of blinding and sham inertness.

Electroencephalography (EEG) may be a promising source of physiological biomarkers accompanying chronic pain. Several studies in patients with chronic neuropathic pain have reported alterations in central pain processing, manifested as slowed EEG rhythmicity and increased EEG power in the brain's resting state. We aimed to investigate novel potential markers of chronic pain in the resting state EEG of patients with chronic pancreatitis.

The amplitude and latency of the P300 may be associated by variations in dopaminergic genes. The current study was conducted to determine whether functional variants of the catechol-O-methyltransferase (COMT) and dopamine beta-hydroxylase (DBH) gene were associated with P300 amplitude and latency in an auditory oddball task.

Major depressive disorder has a large impact on patients and society and is projected to be the second greatest global burden of disease by 2020. The brain-derived neurotrophic factor (BDNF) gene is considered to be one of the important factors in the etiology of major depressive disorder. In a recent study, alpha power was found to mediate between BDNF Met and subclinical depressed mood. The current study looked at a population of patients with major depressive disorder (N = 107) to examine the association between the BDNF Val66Met polymorphism, resting state EEG alpha power, and depression severity. For this purpose, repeated-measures analysis of variance, partial correlation, and multiple linear models were used. Results indicated a negative association between parietal-occipital alpha power in the eyes open resting state and depression severity. In addition, Met/Met patients showed lower global absolute alpha power in the eyes closed condition compared with Val-carriers. These findings are in accordance with the previously uncovered pathway between BDNF Val66Met, resting state EEG alpha power, and depression severity. Additional research is needed for the clarification of this tentative pathway and its implication in personalized treatment of major depressive disorder.

Major depressive disorder (MDD) has high population prevalence and is associated with substantial impact on quality of life, not least due to an unsatisfactory time span of sometimes several weeks from initiation of treatment to clinical response. Therefore extensive research focused on the identification of cost-effective and widely available electroencephalogram (EEG)-based biomarkers that not only allow distinguishing between patients and healthy controls but also have predictive value for treatment response for a variety of treatments. In this comprehensive overview on EEG research on MDD, biomarkers that are either assessed at baseline or during the early course of treatment and are helpful in discriminating patients from healthy controls and assist in predicting treatment outcome are reviewed, covering recent decades up to now. Reviewed markers include quantitative EEG (QEEG) measures, connectivity measures, EEG vigilance-based measures, sleep-EEG-related measures and event-related potentials (ERPs). Further, the value and limitations of these different markers are discussed. Finally, the need for integrated models of brain function and the necessity for standardized procedures in EEG biomarker research are highlighted to enhance future research in this field.

Attention-deficit/hyperactivity disorder (ADHD) is the most common psychiatric disorder of childhood, with average worldwide prevalence of 5.3%, varying by region.

Major depressive disorder (MDD) has high population prevalence and is associated with substantial impact on quality of life, not least due to an unsatisfactory time span of sometimes several weeks from initiation of treatment to clinical response. Therefore extensive research focused on the identifi cation of cost-effective and widely available electroencephalogram (EEG)-based biomarkers that not only allow distinguishing between patients and healthy controls but also have predictive value for treatment response for a variety of treatments. In this comprehensive overview on EEG research on MDD, biomarkers that are either assessed at baseline or during the early course of treatment and are helpful in discriminating patients from healthy controls and assist in predicting treatment outcome are reviewed, covering recent decades up to now. Reviewed markers include quantitative EEG (QEEG) measures, connectivity measures, EEG vigilance-based measures, sleep-EEG-related measures and event-related potentials (ERPs). Further, the value and limitations of these different markers are discussed. Finally, the need for integrated models of brain function and the necessity for standardized procedures in EEG biomarker research are highlighted to enhance future research in this fi eld.

This review article summarizes some recent developments in psychiatry such as personalized medicine, employing biomarkers and endophenotypes, and developments collectively referred to as neuromodulation with a focus on ADHD. Several neurophysiological subtypes in ADHD and their relation to treatment outcome are reviewed. In older research the existence of an “abnormal EEG” or “paroxysmal EEG” was often reported, most likely explained by the high occurrence of this EEG subtype in autism, as the diagnosis of autism was not coined until 1980. This subgroup might respond best to anticonvulsant treatments, which requires more specific research. A second subgroup is a beta-excess or beta-spindling subgroup. This group responds well to stimulant medication, albeit several studies suggesting that neurophysiologically this might represent a different subgroup. The third subgroup consists of the “impaired vigilance” subgroup with the often-reported excess frontal theta or excess frontal alpha. This subgroup responds well to stimulant medication. Finally, it is proposed that a slow individual alpha peak frequency is an endophenotype related to treatment resistance in ADHD. Future studies should incorporate this endophenotype in clinical trials to further investigate new treatments for this substantial subgroup of patients, such as NIRS-biofeedback, transcranial Doppler sonography biofeedback, hyperbaric oxygen therapy, or medications such as nicotine and piracetam.

A case study on neurofeedback and cognitive behavior therapy (CBT) of an 11-year-old girl diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and oppositional defiant disorder (ODD) is presented. The quantitative electroencephalograms (QEEG) demonstrated a low-voltage electroencephalograms (EEG) with excess relative theta. After 31 sessions of theta/beta neurofeedback treatment, the client no longer met criteria for both ADHD and ODD. Her inattentive problems and hyperactive and impulsive behavior declined to normal levels, further evidenced by neuropsychological and event related potentials (ERP) improvements. Also oppositional and aggressive behavior improved dramatically. This case study demonstrates the possibility to treat clients with ADHD and comorbid disorders with combined neurofeedback and CBT. However, further controlled studies are required to replicate and extend these findings and investigate which effects are related to neurofeedback and which to CBT.

The application of rTMS in Depression has been very well investigated over the last few years. However, little is known about predictors of non-response associated with rTMS treatment.

This work presents the application of nonlinear dynamics measures to electroencephalograms (EEG) acquired from patients with Attention Deficit/Hyperactivity Disorder (ADHD) before and after a neurofeedback therapy, with the aim to assess the effects of the neurofeedback in a quantitative way. The database contains EEG registers of seven patients acquired in eyes-closed and eyes-opened conditions, in pre-and post-treatment phases. Five measures were applied: largest Lyapunov exponent, Lempel-Ziv complexity, Hurst exponent, and multiscale entropy on two different scales. The purpose is to test whether these measures are apt to detect and quantify differences from EEG registers between pre- and post-treatment. The results indicate that these measures could have a potential utility for detection of quantitative changes in specific EEG channels. In addition, the performance of some of these measures improved when the bandwidth was reduced to 3-30 Hz.

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 QEEG-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.

The aim of this study was to investigate if biomarkers in QEEG, genetic and neuropsychological measures are suitable for the prediction of antidepressant treatment outcome in depression. Twenty-five patients diagnosed with major depressive disorder were assessed twice, pretreatment and at 8-wk follow-up, on a variety of QEEG and neuropsychological tasks. Additionally, cheek swab samples were collected to assess genetic predictors of treatment outcome. The primary outcome measure was the absolute decrease on the HAM-D rating scale. Regression models were built in order to investigate which markers contribute most to the decrease in absolute HAM-D scores. Patients who had a better clinical outcome were characterized by a decrease in the amplitude of the Auditory Oddball N1 at baseline. The ‘Met/Met’ variant of the COMT gene was the best genetic predictor of treatment outcome. Impaired verbal memory performance was the best cognitive predictor. Raised frontal Theta power was the best EEG predictor of change in HAM-D scores. A tentative integrative model showed that a combination of N1 amplitude at Pz and verbal memory performance accounted for the largest part of the explained variance. These markers may serve as new biomarkers suitable for the prediction of antidepressant treatment outcome.

Chronic pain has been associated with impaired cognitive function. We examined cognitive performance in patients with severe chronic pancreatitis pain. We explored the following factors for their contribution to observed cognitive deficits: pain duration, comorbidity (depression, sleep disturbance), use of opioids, and premorbid alcohol abuse. The cognitive profiles of 16 patients with severe pain due to chronic pancreatitis were determined using an extensive neuropsychological test battery. Data from three cognitive domains (psychomotor performance, memory, executive functions) were compared to data from healthy controls matched for age, gender and education. Multivariate multilevel analysis of the data showed decreased test scores in patients with chronic pancreatitis pain in different cognitive domains. Psychomotor performance and executive functions showed the most prominent decline. Interestingly, pain duration appeared to be the strongest predictor for observed cognitive decline. Depressive symptoms, sleep disturbance, opioid use and history of alcohol abuse provided additional explanations for the observed cognitive decline in some of the tests, but to a lesser extent than pain duration. The negative effect of pain duration on cognitive performance is compatible with the theory of neurodegenerative properties of chronic pain. Therefore, early and effective therapeutic interventions might reduce or prevent decline in cognitive performance, thereby improving outcomes and quality of life in these patients.

Brain activity assessed by electroencephalography (EEG) has been demonstrated to respond to conditioning techniques. The concept of modulating this activity has been called EEG biofeedback, more recently neurofeedback, and is based on operant learning principles. Technological advancements have significantly enhanced the ease and affordability of recording and analyzing brain activity. Thus, properly trained practitioners can implement these conditioning strategies in their practice. Recent research indicating evidenced-based efficacy has made this technique a more viable option for clinical intervention. The objective of this article is to highlight the learning principles that have provided the fundamentals of this neuromodulatory approach. In addition, it is recommended that future applications in clinical work, research, and development adhere to these principles.

This chapter focuses on normative electroencephalography (EEG), or qEEG data that are compared to a control group or normative database. It also limits the application of qEEG to neuropsychiatric conditions and focuses on more strictly neurological applications that fall beyond the scope. Abnormal EEG findings consist of the so-called “paroxysmal” or “epileptiform discharges.” The estimated incidences of paroxysmal EEG in some attention deficit hyperactivity disorder (ADHD) groups were around 12–13% to approximately 30%, which are high as compared to 1–2% in normal populations. The exact implications of such EEG activity in subjects without overt signs of epilepsy are not very well understood and many neurologists will see no need to treat these subjects as epileptics. With the introduction of qEEG and computerized EEG analysis many more studies are carried out investigating the neurophysiology of ADHD.

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. Future research should elucidate the functional role of resting-state brain oscillations by investigating neurophysiological subgroups, which may have a clearer relation to cognitive functions than single frequency bands.

This position paper provides the current evidence supporting the use of neurofeedback in the treatment of ADHD and recommendations on the implementation of neurofeedback in clinical practice. The paper also provides basic information regarding the diagnosis and psychophysiological etiology of ADHD. The paper does not focus on a specific age range of a clinical population. Unless otherwise noted, we are referring to all subtypes of ADHD (inattentive, hyperactive only, and combined). Conclusions and recommendation are based on the most recent research; however, we also refer to relevant historical studies that support our position on neurofeedback. The readers are strongly advised to research behavioral diagnostic criteria and testing methods elsewhere. This paper is not intended as a comprehensive educational tool for diagnosis or treatment of ADHD. Our purpose is to demonstrate the rationale and to reference the necessary support for neurofeedback in order to be recognized as a legitimate, scientific, and evidence-based intervention for the treatment of ADHD.