Evidence-Based Information on the Clinical Use of Neurofeedback for ADHD [pdf]
Tais S. Moriyama, Guilherme Polanczyk, and Luis A. Rohde
www.ncbi.nlm.nih.gov/pmc/articles/PMC3441929/Neurofeedback (NF) is a training to enhance self-regulatory capacity over brain activity patterns and consequently over brain mental states. Recent findings suggest that NF is a promising alternative for the treatment of attention-deficit/hyperactivity disorder (ADHD). We comprehensively reviewed literature searching for studies on the effectiveness and specificity of NF for the treatment of ADHD. In addition, clinically informative evidence-based data are discussed. We found 3 systematic review on the use of NF for ADHD and 6 randomized controlled trials that have not been included in these reviews. Most nonrandomized controlled trials found positive results with medium-to-large effect sizes, but the evidence for effectiveness are less robust when only randomized controlled studies are considered. The direct comparison of NF and sham-NF in 3 published studies have found no group differences, nevertheless methodological caveats, such as the quality of the training protocol used, sample size, and sample selection may have contributed to the negative results. Further data on specificity comes from electrophysiological studies reporting that NF effectively changes brain activity patterns. No safety issues have emerged from clinical trials and NF seems to be well tolerated and accepted. Follow-up studies support long-term effects of NF. Currently there is no available data to guide clinicians on the predictors of response to NF and on optimal treatment protocol. In conclusion, NF is a valid option for the treatment for ADHD, but further evidence is required to guide its use.Efficacy of Neurofeedback Treatment in ADHD: The Effects on Inattention, Impulsivity and Hyperactivity: a Meta-Analysis [pdf]
by Arns M, de Ridder S, Strehl U, Breteler M and Coenen A
Journal of Clinical EEG & Neuroscience, July, 2009ABSTRACT
Since the first reports of neurofeedback treatment in Attention Deficit Hyperactivity Disorder (ADHD) in 1976, many studies have investigated the effects of neurofeedback on different symptoms of ADHD such as inattention, impulsivity and hyperactivity. This technique is also used by many practitioners, but the question as to the evidence-based level of this treatment is still unclear. In this study selected research on neurofeedback treatment for ADHD was collected and a meta-analysis was performed.

Both prospective controlled studies and studies employing a pre- and post-design found large effect sizes (ES) for neurofeedback on impulsivity and inattention and a medium ES for hyperactivity. Randomized studies demonstrated a lower ES for hyperactivity suggesting that hyperactivity is probably most sensitive to nonspecific treatment factors.

Due to the inclusion of some very recent and sound methodological studies in this meta-analysis, potential confounding factors such as small studies, lack of randomization in previous studies and a lack of adequate control groups have been addressed, and the clinical effects of neurofeedback in the treatment of ADHD can be regarded as clinically meaningful. Three randomized studies have employed a semi-active control group which can be regarded as a credible sham control providing an equal level of cognitive training and client-therapist interaction. Therefore, in line with the AAPB and ISNR guidelines for rating clinical efficacy, we conclude that neurofeedback treatment for ADHD can be considered “Efficacious and Specific” (Level 5) with a large ES for inattention and impulsivity and a medium ES for hyperactivity.

Place of EEG Biofeedback for ADHD [pdf]
by Hirshberg LM
Expert Review Neurotherapeutics, 7(4), 315-319

ABSTRACT
Although methodological weaknesses limited early research into electroencephalograpic (EEG) biofeedback (EBF) for treatment of attention-deficit/hyperacticity disorder (ADHD), recent stronger randomized controlled trials have provided substantial, but not yet conclusive, empirical support. Additional support is found in research on functional magnetic resonance imaging (fMRI) feedback and brain-computer interface (BCI) models which involve feedback-guided learning to achieve control over neural activation.