Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Neurofeedback is attracting renewed interest as a method to self-regulate one’s own brain activity to directly alter the underlying neural mechanisms of cognition and behaviour. It promises new avenues as a method for cognitive enhancement in healthy subjects, but also as a therapeutic tool. In the current article, we present a review tutorial discussing key aspects relevant to the development of EEG neurofeedback studies. In addition, the putative mechanisms underlying neurofeedback learning are considered. We highlight both aspects relevant for the practical application of neurofeedback as well as rather theoretical considerations related to the development of new generation protocols. Important characteristics regarding the set-up of a neurofeedback protocol are outlined in a step-by-step way. All these practical and theoretical considerations are illustrated based on a protocol and results of a frontal-midline theta up-regulation training for the improvement of executive functions. Not least, assessment criteria for the validation of neurofeedback studies as well as general guidelines for the evaluation of training efficacy are discussed.

Purpose of Review Current traditional treatments for ADHD present serious limitations in terms of long-term maintenance of symptom remission and side effects. Here, we provide an overview of the rationale and scientific evidence of the efficacy of neurofeedback in regulating the brain functions in ADHD. We also review the institutional and professional regulation of clinical neurofeedback implementations. Recent Findings Based on meta-analyses and (large multicenter) randomized controlled trials, three standard neurofeedback training protocols, namely theta/beta (TBR), sensori-motor rhythm (SMR), and slow cortical potential (SCP), turn out to be efficacious and specific. However, the practical implementation of neurofeedback as a clinical treatment is currently not regulated. Summary We conclude that neurofeedback based on standard protocols in ADHD should be considered as a viable treatment alternative and suggest that further research is needed to understand how specific neurofeedback protocols work. Eventually, we emphasize the need for standard neurofeedback training for practitioners and binding standards for use in clinical practice.

Purpose: Recent reviews have proposed that scientifically validated standard EEG neurofeedback (NF) protocols are an efficacious and specific treatment for attention-deficit hyperactivity disorder (ADHD). Here, we review the current evidence for the treatment efficacy and clinical effectiveness of NF in ADHD to investigate whether NF treatment personalization (standard protocols matched to the electrophysiological features of ADHD) and combination with other interventions (psychosocial, sleep hygiene and nutritional advice) might yield superior long-term treatment outcomes relative to non-personalized NF and medication monotreatments. Methods: The electronic databases PubMed and PsycINFO were systematically searched using our key terms. Of the 38 resulting studies, 11 randomized controlled trials (RCTs) and open-label studies were eligible for inclusion. Studies were analyzed for effect sizes and remission rates at the end of treatment and at follow-up. The effects of personalized and multimodal NF treatments were compared to non-personalized NF monotreatments and with two benchmark medication studies. Results: The analysis of RCTs indicated that the long-term effects of personalized NF interventions were superior to non-personalized NF and comparable to those of medication alone or in combination with behavioral intervention. The analysis of open-label trials further indicates that the interaction of NF with parental interventions, sleep and nutritional advice might yield superior clinical effectiveness relative to NF and medication monotreatments. Conclusion: Personalized and multimodal NF interventions seem to yield superior treatment efficacy relative to NF alone and superior clinical effectiveness relative to medication. We propose that treatment outcomes may be further enhanced by adjusting NF non-specific factors (eg, reinforcement contingencies) to specific ADHD characteristics (eg, reward sensitivity). Future NF research should focus on the systematic evaluation of the treatment outcomes of personalized and multimodal treatments.

Age-related neurocognitive effects have been observed at different levels ranging from reduced amplitudes of even-related potentials and brain oscillations, to topography changes of brain activity. However, their association remains incompletely understood. We investigated time-frequency and time-course effects in functional networks underlying the P300 and their involvement in reactive control. Electroencephalographic (EEG) data of three different age groups (30 young: 18–26 years, 30 mid-aged: 49–58 years, 30 elderly: 65–75 years) was measured while they performed a cued colour/thickness switching task. Neural data was analysed concerning the targets. To consider restart, mixing, and switching processes, the targets´ position after a cue (first or third target) as well as their context in the single-task (distractor cue) or the mixed-task block (switch- or repeat cue) was analysed. P300 EEG data was decomposed by means of group-independent component and time-frequency analyses focusing on theta and beta oscillations. RTs generally slowed down with age (main effect group), and effects were specifically strong in targets after a switching cue (larger Cohens d). Peaking at around 300 ms, we detected five functionally independent networks reflecting the multicomponent process underlying task-switching. These networks differed in terms of their topography (parietal and frontal), their involvement in task processes (switch-specific, mixing-, restart-, and single-task processes) and in terms of frequency effects. All were affected by age, as indicated by amplitude changes of the target-P300 and power reductions most consistently shown in beta oscillations. Most extensive age-related changes were observed in one parietal network sensitive to mixing and restart processes. Changes included a topography shift, P300 and beta amplitudes, and were ongoing in the elderly group.