Neurofeedback for ADHD: A Review of Current Evidence

Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly heterogeneous diagnostic category, encompassing several endophenotypes and comorbidities, including sleep problems. However, no predictor of clinical long-term trajectories or comorbidity has yet been established. Sleep EEG has been proposed as a potential tool for evaluating the synaptic strength during development, as well as the cortical thickness, which is presumed to be altered in ADHD. We investigated whether the slope of the Slow Waves (SWs), a microstructural parameter of the sleep EEG, was a potential predictive parameter for psychiatric comorbidities and neuropsychological dimensions in ADHD.

70 children (58 m; 8.76 ± 2.77 y) with ADHD who underwent psychiatric and neurologic evaluations and a standard EEG recording during naps were investigated. After sleep EEG analysis, we grouped the extracted SWs in bins of equal amplitude and then measured the associations, through generalized linear regression, between their maximum downward slopes (MDS) and the individual scores obtained from clinical rating scales.

The presence of Multiple Anxiety Disorders was positively associated with MDS of medium amplitude SWs in temporo-posterior left areas. The Child Behavior Checklist scores showed negative associations in the same areas for small SWs. The presence of autistic traits was positively associated with MDS of high amplitude SWs in bilateral anterior and temporal left areas. The WISC-IV Processing Speed Index showed negative associations with MDS of small-to-medium SWs in anterior and temporal right areas, while positive associations in posterior and temporal left areas.

Consistency of association clusters' localization on the scalp suggests that variations in the local MDS, revealing alterations of local synaptic strength and/or in daytime use of certain cortical circuits, could underlie specific neurodevelopmental trajectories resulting in different ADHD clinical phenotypes.

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common pediatric epilepsy comorbidities. Treating ADHD in the context of epilepsy can be overwhelming for parents and clinicians. Current frontline treatment for ADHD is stimulant medication. However, some parents of pediatric patients with epilepsy have concerns about adding additional medication to their child’s epilepsy regimen and/or about adverse effects of stimulant medication. Non-medication ADHD treatments including psychosocial interventions and ketogenic diet have also shown success in improving ADHD symptoms. Our focused review provides an easy-to-use guide for clinicians on ADHD interventions and combinations of interventions for pediatric patients with epilepsy and ADHD. Our guide includes information from 8 electronic databases for peer-reviewed, English language studies of psychosocial treatments for youth with epilepsy and ADHD. One hundred eight studies were selected based on inclusion criteria (21 systematic reviews, 12 meta-analyses, 8 literature reviews, 6 population surveys, 31 clinical trials, 20 cross-sectional studies, and 10 retrospective reviews). Results indicated that stimulant medication is a frontline treatment for ADHD symptoms in youth with epilepsy, with important caveats and alternatives.

According to the BIOS theory, attention deficit hyperactivity disorder (ADHD) is a disorder that transfers the power of the high-frequency bands to the low-frequency bands by changing the electrical actions generated by the brain's opposite structures. Nevertheless, studies on this disorder have often focused on the EEG walks (voltage levels) and provided no information about the status of the brain's opposites, which generate the EEG actions (voltage changes in time). In this study, we accordingly investigated the status of partial opposites in the trigonometric plots obtained from the EEG signals of children with and without ADHD, which have been recorded under the resting eyes-open and eyes-closed conditions. In other words, we first extracted a set of features from the status of partial opposites activated in the trigonometric space and the status of transitions in this plot. Then, we evaluated these features to separate children with and without ADHD by using the t-test analysis and the SVM classifiers. Generally, the outcomes of this analysis in addition to improving the separability of the ADHD children with a figure of merit (FOM) of about 72.4% detected that ADHD changes the EEG actions, so that the larger EEG actions usually occur more than the smaller EEG actions. Therefore, it seems that the proposed technique can significantly improve clinical protocols, especially in applications such as diagnostic tools, neurofeedback, and game therapy.

The present chapter describes the main features of biosensors and biofeedback, with particular attention to their definitions, main properties, classifications and a general overview of their implementation within several contexts.

Subsequently, their application within the field of clinical psychology will be critically discussed, in light of recent research evidence. This examination will follow a developmental rationale, beginning with conditions affecting early ages and adolescence, proceeding to adulthood and senescence. Recommendations for future researches will be pointed out, tracing the path for the next steps for the advancement in clinical applications of biofeedback and biosensors.

Current treatment practices for comorbid conditions of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) remain limited. This study examined the feasibility of an EEG brain-computer interface (BCI) programme for children with ASD and co-occurring ADHD.

Twenty children were randomised to the intervention or waitlist-control group. Intervention consisted of thrice-weekly sessions of BCI-based training over 8 weeks. Both groups were followed up 4 weeks later. The BCI-based programme comprised of a series of attention and gaze-modulated games aimed to train social cognitive skills.

All participants completed at least 20 training sessions and none dropped out of the study. No severe adverse events were reported. Side effects included mild headaches, fatigue, irritability and self-injurious behaviours. All were addressed within the same session. Feedback from therapists indicated that participants’ interest and motivation could be sustained with appropriate supports. Change scores indicated greater improvement in the intervention group compared to the waitlist-control on ADHD symptoms as measured on the ADHD rating scale; no significant differences were observed on social deficits on the Social Responsiveness Scale (SRS). Pooled data suggests that pre-post improvements could be maintained.

Findings indicate the BCI-based program is tolerable for most participants. Positive effects were also reported for ADHD symptoms. A future large clinical trial will incorporate appropriate controls to ascertain the efficacy of our training programme.

Altered functional networks in attention deficit/hyperactivity disorder (ADHD) have been frequently reported, but effective connectivity has hardly been studied. Especially the differences of effective connectivity in children with ADHD after receiving neurofeedback (NF) training have been merely reported. Therefore, this study aimed to explore the effective networks of ADHD and the positive influence of NF on the effective networks. Electroencephalogram (EEG) data were recorded from 22 children with ADHD (including data from children pretraining and posttraining) and 15 age-matched healthy controls during an eyes-closed resting state. Phase transfer entropy (PTE) was used to construct the effective connectivity. The topological properties of networks and flow gain were measured separately in four bands (delta, theta, alpha, and beta). Results revealed the following: pretraining children with ADHD manifested a higher clustering coefficient and lower characteristic path length in the delta band than healthy controls; weakened anterior-to-posterior flow gain in the delta band, strengthened posterior-to-anterior flow gain in the alpha band and strengthened anterior-to-posterior flow gain in the beta band were observed in pretraining children with ADHD; The topological properties and flow gain in posttraining children with ADHD were close to those of healthy controls. Moreover, parent’s SWAN presented significant improvements of ADHD symptoms after NF. Our findings revealed that the effective connectivity of ADHD was altered and that NF could improve the brain function of ADHD. The present study provided the first evidence that children with ADHD differed from healthy children in phase-based effective connectivity and that NF could reduce the differences.