Is EEG-biofeedback an effective treatment in autism spectrum disorders? A randomized controlled trial

Neurofeedback Recuperates Cognitive Functions in Children with Autism Spectrum Disorders (ASD)

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interaction, verbal and nonverbal communication, and behaviors or interests. Besides behavioral, psychopharmacological and biomedical interventions there is increasing evidence of non-invasive treatments like neurofeedback (NFB) that can improve brain activity. In this study, we have investigated whether NFB can improve cognitive functions in children with ASD. Thirty-five children with ASD (7-17 years) were selected by purposive sampling. The subjects underwent 30 sessions of NFB training for 20 min over 10 weeks' period. Psychometric tests i.e. Childhood Autism Rating Scale (CARS), IQ scoring and Reward sensitivity tests were administered at baseline. Pre and post NFB intervention assessment of executive functions, working memory and processing speed were done by NIH Toolbox Cognition Batteries. Friedman test revealed that children showed a statistically significant improvement in the NIH Tool Box cognitive assessments, including the Flankers Inhibitory Control and Attention Test (Pre-test = 3.63, Post-test = 5.22; p = 0.00), the Dimensional Change Card Sorting Test (Pre-test = 2.88, Post-test = 3.26; p = 0.00), the Pattern Comparison Processing Speed Test (Pre-test = 6.00, Post-test = 11:00; p = 0.00) and the List Sorting Working Memory Test (Pre-test = 4.00, Post-test = 6:00; p = 0.00), and displayed a trend of improvement at 2-month follow-up (Flankers Inhibitory Control and Attention Test (Post-test = 5.11 ± 2.79, Follow-Up = 5.31 ± 2.67; p = 0.21), the Dimensional Change Card Sorting Test (Post-test = 3.32 ± 2.37, Follow-Up = 3.67 ± 2.35; p = 0.054), the Pattern Comparison Processing Speed Test (Post-test = 13.69 ± 9.53, Follow-Up = 14.42 ± 10.23 p = 0.079) and the List Sorting Working Memory Test (Post-test = 6.17 ± 4.41, Follow-Up = 5.94 ± 4.03; p = 0.334). Our findings suggest NFB intervention for 10 weeks produce improvement in executive functions (Inhibitory Control and Attention and Cognitive Flexibility), Processing Speed and Working Memory in ASD Children.

Multimodal and hemispheric graph-theoretical brain network predictors of learning efficacy for frontal alpha asymmetry neurofeedback

EEG neurofeedback using frontal alpha asymmetry (FAA) has been widely used for emotion regulation, but its effectiveness is controversial. Studies indicated that individual differences in neurofeedback training can be traced to neuroanatomical and neurofunctional features. However, they only focused on regional brain structure or function and overlooked possible neural correlates of the brain network. Besides, no neuroimaging predictors for FAA neurofeedback protocol have been reported so far. We designed a single-blind pseudo-controlled FAA neurofeedback experiment and collected multimodal neuroimaging data from healthy participants before training. We assessed the learning performance for evoked EEG modulations during training (L1) and at rest (L2), and investigated performance-related predictors based on a combined analysis of multimodal brain networks and graph-theoretical features. The main findings of this study are described below. First, both real and sham groups could increase their FAA during training, but only the real group showed a significant increase in FAA at rest. Second, the predictors during training blocks and at rests were different: L1 was correlated with the graph-theoretical metrics (clustering coefficient and local efficiency) of the right hemispheric gray matter and functional networks, while L2 was correlated with the graph-theoretical metrics (local and global efficiency) of the whole-brain and left the hemispheric functional network. Therefore, the individual differences in FAA neurofeedback learning could be explained by individual variations in structural/functional architecture, and the correlated graph-theoretical metrics of learning performance indices showed different laterality of hemispheric networks. These results provided insight into the neural correlates of inter-individual differences in neurofeedback learning.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-09939-x.

EEG Biofeedback Decreases Theta and Beta Power While Increasing Alpha Power in Insomniacs: An Open-Label Study

Insomnia, often associated with anxiety and depression, is a prevalent sleep disorder. Biofeedback (BFB) treatment can help patients gain voluntary control over physiological events such as by utilizing electroencephalography (EEG) and electromyography (EMG) power. Previous studies have rarely predicted biofeedback efficacy by measuring the changes in relative EEG power; therefore, we investigated the clinical efficacy of biofeedback for insomnia and its potential neural mechanisms. We administered biofeedback to 82 patients with insomnia, of whom 68 completed 10 sessions and 14 completed 20 sessions. The average age of the participants was 49.38 ± 12.78 years, with 26 men and 56 women. Each biofeedback session consisted of 5 min of EMG and 30 min of EEG feedback, with 2 min of data recorded before and after the session. Sessions were conducted every other day, and four scale measures were taken before the first, fifth, and tenth sessions and after the twentieth session. After 20 sessions of biofeedback treatment, scores on the Pittsburgh Sleep Quality Index (PSQI) were significantly reduced compared with those before treatment (-5.5 ± 1.43,t = -3.85, p = 0.006), and scores on the Beck Depression Inventory (BDI-II) (-7.15 ± 2.43, t = -2.94, p = 0.012) and the State-Trait Anxiety Inventory (STAI) (STAI-S: -12.36 ± 3.40, t = -3.63, p = 0.003; and STAI-T: -9.86 ± 2.38, t = -4.41, p = 0.001) were significantly lower after treatment than before treatment. Beta and theta power were significantly reduced after treatment, compared with before treatment (F = 6.25, p = 0.014; and F = 11.91, p = 0.001). Alpha power was increased after treatment, compared with before treatment, but the difference was not prominently significant (p > 0.05). EMG activity was significantly decreased after treatment, compared with before treatment (F = 2.11, p = 0.015). Our findings suggest that BFB treatment based on alpha power and prefrontal EMG relieves insomnia as well as anxiety and depression and may be associated with increased alpha power, decreased beta and theta power, and decreased EMG power.

Successful alpha neurofeedback training enhances working memory updating and event-related potential activity

Neurofeedback (NF) is a promising method to self-regulate human brain activity for cognition enhancement. Due to the unclear results of alpha NF training on working memory updating as well as the impact of feedback modality on NF learning, this study aimed to understand further the underlying neural mechanism of alpha NF training effects on working memory updating, where the NF learning was also compared between visual and auditory feedback modalities. A total of 30 participants were assigned to Visual NF, Auditory NF, and Control groups. Working memory updating was evaluated by n-back (n =2,3) tasks before and after five alpha upregulation NF sessions. The result showed no significant difference in NF learning performance between the Visual and Auditory groups, indicating that the difference in feedback modality did not affect NF learning. In addition, compared to the control group, the participants who achieved successful NF learning showed a significant increase in n-back behavioral performance and P3a amplitude in 2-back and a significant decrease in P3a latency in 3-back. Our results in n-back further suggested that successful alpha NF training might improve updating performance in terms of the behavioral and related event-related potential (ERP) measures. These findings contribute to the understanding of the effect of alpha training on memory updating and the design of NF experimental protocol in terms of feedback modality selection.

Prediction of Behavioral Improvement Through Resting-State Electroencephalography and Clinical Severity in a Randomized Controlled Trial Testing Bumetanide in Autism Spectrum Disorder

BACKGROUND

Mechanism-based treatments such as bumetanide are being repurposed for autism spectrum disorder. We recently reported beneficial effects on repetitive behavioral symptoms that might be related to regulating excitation-inhibition (E/I) balance in the brain. Here, we tested the neurophysiological effects of bumetanide and the relationship to clinical outcome variability and investigated the potential for machine learning-based predictions of meaningful clinical improvement.

METHODS

Using modified linear mixed models applied to intention-to-treat population, we analyzed E/I-sensitive electroencephalography (EEG) measures before and after 91 days of treatment in the double-blind, randomized, placebo-controlled Bumetanide in Autism Medication and Biomarker study. Resting-state EEG of 82 subjects out of 92 participants (7-15 years) were available. Alpha frequency band absolute and relative power, central frequency, long-range temporal correlations, and functional E/I ratio treatment effects were related to the Repetitive Behavior Scale-Revised (RBS-R) and the Social Responsiveness Scale 2 as clinical outcomes.

RESULTS

We observed superior bumetanide effects on EEG, reflected in increased absolute and relative alpha power and functional E/I ratio and in decreased central frequency. Associations between EEG and clinical outcome change were restricted to subgroups with medium to high RBS-R improvement. Using machine learning, medium and high RBS-R improvement could be predicted by baseline RBS-R score and EEG measures with 80% and 92% accuracy, respectively.

CONCLUSIONS

Bumetanide exerts neurophysiological effects related to clinical changes in more responsive subsets, in whom prediction of improvement was feasible through EEG and clinical measures.

Brain-Computer Interface Training of mu EEG Rhythms in Intellectually Impaired Children with Autism: A Feasibility Case Series

Prior studies show that neurofeedback training (NFT) of mu rhythms improves behavior and EEG mu rhythm suppression during action observation in children with autism spectrum disorder (ASD). However, intellectually impaired persons were excluded because of their behavioral challenges. We aimed to determine if intellectually impaired children with ASD, who were behaviorally prepared to take part in a mu-NFT study using conditioned auditory reinforcers, would show improvements in symptoms and mu suppression following mu-NFT. Seven children with ASD (ages 6-8; mean IQ 70.6 ± 7.5) successfully took part in mu-NFT. Four cases demonstrated positive learning trends (hit rates) during mu-NFT (learners), and three cases did not (non-learners). Artifact-creating behaviors were present during tests of mu suppression for all cases, but were more frequent in non-learners. Following NFT, learners showed behavioral improvements and were more likely to show evidence of a short-term increase in mu suppression relative to non-learners who showed little to no EEG or behavior improvements. Results support mu-NFT's application in some children who otherwise may not have been able to take part without enhanced behavioral preparations. Children who have more limitations in demonstrating learning during NFT, or in providing data with relatively low artifact during task-dependent EEG tests, may have less chance of benefiting from mu-NFT. Improving the identification of ideal mu-NFT candidates, mu-NFT learning rates, source analyses, EEG outcome task performance, population-specific artifact-rejection methods, and the theoretical bases of NFT protocols, could aid future BCI-based, neurorehabilitation efforts.

Heart Rate Variability Biofeedback to Treat Anxiety in Young People With Autism Spectrum Disorder: Findings From a Home-Based Pilot Study

Background

People with autism spectrum disorder (ASD) frequently experience high levels of anxiety. Despite this, many clinical settings do not provide specialist ASD mental health services, and demand for professional support frequently outstrips supply. Across many sectors of health, investigators have explored digital health solutions to mitigate demand and extend the reach of professional practice beyond traditional clinical settings.

Objective

This critical appraisal and pilot feasibility study examines heart rate variability (HRV) biofeedback as an approach to help young people with ASD to manage anxiety symptoms outside of formal settings. The aim is to explore the use of portable biofeedback devices to manage anxiety, while also highlighting the risks and benefits of this approach with this population.

Methods

We assessed the feasibility of using home-based HRV biofeedback for self-management of anxiety in young people with ASD. We adopted coproduction, involving people with ASD, to facilitate development of the study design. Next, a separate pilot with 20 participants with ASD (n=16, 80% male participants and n=4, 20% female participants, aged 13-24 years; IQ>70) assessed adoption and acceptability of HRV biofeedback devices for home use over a 12-week period. Data were collected from both carers and participants through questionnaires and interviews; participants also provided single-lead electrocardiogram recordings as well as daily reports through smartphone on adoption and use of their device.

Results

Pre-post participant questionnaires indicated a significant reduction in anxiety in children (t₆=2.55; P=.04; Cohen d=0.99) as well as adults (t₇=3.95; P=.006; Cohen d=0.54). Participant age was significantly negatively correlated with all HRV variables at baseline, namely high-frequency heart rate variability (HF-HRV: P=.02), the root mean square of successive differences in normal heartbeat contractions (RMSSD: P=.02) and the variability of normal-to-normal interbeat intervals (SDNN: P=.04). At follow-up, only SDNN was significantly negatively correlated with age (P=.05). Levels of ASD symptoms were positively correlated with heart rate both before (P=.04) and after the intervention (P=.01). The majority (311/474, 65.6%) of reports from participants indicated that the devices helped when used. Difficulties with the use of some devices and problems with home testing of HRV were noted. These initial findings are discussed within the context of the strengths and challenges of remotely delivering a biofeedback intervention for people with ASD.

Conclusions

HRV biofeedback devices have shown promise in this pilot study. There is now a need for larger evaluation of biofeedback to determine which delivery methods achieve the greatest effect for people with ASD.

Trial Registration

ClinicalTrials.gov NCT04955093; https://clinicaltrials.gov/ct2/show/NCT04955093

Genome-wide DNA methylation profiles of autism spectrum disorder

OBJECTIVES

We aimed to identify differentially methylated genes and related signaling pathways in autism spectrum disorder (ASD).

METHODS

First, the DNA methylation profile in the brain samples (GSE131706 and GSE80017) and peripheral blood samples (GSE109905) was downloaded from the Gene Expression Omnibus database (GEO) dataset, followed by identification of differentially methylated genes and functional analysis. Second, the GSE109905 data set was used to further validate the methylation state and test the ability to diagnose disease of identified differentially methylated genes. Third, expression measurement of selected differentially methylated genes was performed in whole blood from an independent sample. Finally, protein-protein interaction (PPI) network of core differentially methylated genes was constructed.

RESULTS

Totally, 74 differentially methylated genes were identified in ASD, including 38 hypermethylated genes and 36 hypomethylated genes. 15 differentially methylated genes were further identified after validation in the GSE109905 data set. Among these, major histocompatibility complex (HLA)-DQA1 was involved in the molecular function of myosin heavy chain class II receptor activity; HLA-DRB5 was involved in the signaling pathways of cell adhesion molecules, Epstein-Barr virus infection and antigen processing and presentation. In the PPI analysis, the interaction pairs of HLA-DQA1 and HLA-DRB5, FMN2 and ACTR3, and CALCOCO2 and BAZ2B were identified. Interestingly, FMN2, BAZ2B, HLA-DRB5, CALCOCO2 and DUSP22 had a potential diagnostic value for patients with ASD. The expression result of four differentially methylated genes (HLA-DRB5, NTM, IL16 and COL5A3) in the independent sample was consistent with the integrated analysis.

CONCLUSIONS

Identified differentially methylated genes and enriched signaling pathway could be associated with ASD.

Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus

The widespread understanding that chronic tinnitus is a heterogeneous phenomenon with various neural oscillatory profiles has spurred investigations into individualized approaches in its treatment. Neurofeedback, as a non-invasive tool for altering neural activity, has become increasingly popular in the personalized treatment of a wide range of neuropsychological disorders. Despite the success of neurofeedback on the group level, the variability in the treatment efficacy on the individual level is high, and evidence from recent studies shows that only a small number of people can effectively modulate the desired aspects of neural activity. To reveal who may be more suitable, and hence benefit most from neurofeedback treatment, we classified individuals into unobserved subgroups with similar oscillatory trajectories during the treatment and investigated how subgroup membership was predicted by a series of characteristics. Growth mixture modeling was used to identify distinct latent subgroups with similar oscillatory trajectories among 50 individuals suffering from chronic subjective tinnitus (38 male, 12 female, mean age = 47.1 ± 12.84) across 15 neurofeedback training sessions. Further, the impact of characteristics and how they predicted the affiliation in the identified subgroups was evaluated by including measures of demographics, tinnitus-specific (Tinnitus Handicap Inventory) and depression variables, as well as subjective quality of life subscales (World Health Organization—Quality of Life Questionnaire), and health-related quality of life subscales (Short Form-36) in a logistic regression analysis. A latent class model could be fitted to the longitudinal data with a high probability of correctly classifying distinct oscillatory patterns into 3 different groups: non-responder (80%), responder (16%), and decliner (4%). Further, our results show that the health-related wellbeing subscale of the Short Form-36 questionnaire was differentially associated with the groups. However, due to the small sample size in the Responder group, we are not able to provide sufficient evidence for a distinct responder profile. Nevertheless, the identification of oscillatory change-rate differences across distinct groups of individuals provides the groundwork from which to tease apart the complex and heterogeneous oscillatory processes underlying tinnitus and the attempts to modify these through neurofeedback. While more research is needed, our results and the analytical approach presented may bring clarity to contradictory past findings in the field of tinnitus research, and eventually influence clinical practice.

Effects of an intensive slow cortical potentials neurofeedback training in female and male adolescents with autism spectrum disorder : Are there sex differences?

Background

This study aims to compare the effects of neurofeedback training on male and female adolescents with autism spectrum disorder (ASD). Furthermore, it examines sex differences regarding improvements in co-occurring psychopathological symptoms, cognitive flexibility and emotion recognition abilities. The study might provide first hints whether there is an influence of sex on treatment outcomes.

Methods

Six female and six male adolescents with ASD were matched according to age, IQ and symptom severity. All participants received 24 sessions of electroencephalography-based neurofeedback training. Before and after the intervention, psychological data for measuring co-occurring psychopathological symptoms as well as behavioral data for measuring cognitive flexibility and emotion recognition abilities were recorded.

Results

Caregivers rated statistically significant higher psychopathological problems in female than in male adolescents with ASD at baseline. Apart from that, no statistically significant sex-related differences were revealed in this sample; however, male adolescents tended to report greater improvements of externalizing, internalizing and total symptoms, whereas females experienced smaller improvements of externalizing and total problems, but no improvements of internalizing problems. Regarding caregivers’ assessments, more improvement of total problems was reported for females. For males, only improvements of internalizing and total problems were described.

Conclusion

This study reveals preliminary results that sex-related differences might play a role when evaluating treatment outcomes after neurofeedback training regarding comorbid psychopathological symptoms. Adolescents’ self-report and parental assessments, especially concerning psychopathological symptoms, should be combined and considered in future studies to help prevent sex bias in adolescents with ASD.

Validation of eyes-closed resting alpha amplitude predicting neurofeedback learning of upregulation alpha activity

Neurofeedback training (NFT) enables users to learn self-control of EEG activity of interest and then to create many benefits on cognitive function. A considerable number of nonresponders who fail to achieve successful NFT have often been reported in the within-session prediction. This study aimed to investigate successful EEG NFT of upregulation alpha activity in terms of trainability, independence, and between-session predictability validation. Forty-six participants completed 12 training sessions. Spectrotemporal analysis revealed the upregulation success on brain activity of 8-12 Hz exclusively to demonstrate trainability and independence of alpha NFT. Three learning indices of between-session changes exhibited significant correlations with eyes-closed resting state (ECRS) alpha amplitude before the training exclusively. Through a stepwise linear discriminant analysis, the prediction model of ECRS's alpha frequency band amplitude exhibited the best accuracy (89.1%) validation regarding the learning index of increased alpha amplitude on average. This study performed a systematic analysis on NFT success, the performance of the 3 between-session learning indices, and the validation of ECRS alpha activity for responder prediction. The findings would assist researchers in obtaining insight into the training efficacy of individuals and then attempting to adapt an efficient strategy in NFT success.

The Effectiveness of Neurofeedback Therapy as an Alternative Treatment for Autism Spectrum Disorders in Children

Abstract. Findings for the effectiveness of neurofeedback in autism spectrum disorder are found to be inconsistent. Therefore, this review comprehensively and systematically reviewed literature on the effectiveness of neurofeedback for the treatment of autism spectrum disorders in children. A systematic search of Embase, Medline, Web of Science, PsycINFO, Cochrane, and Google Scholar was carried out in October 2017 to find relevant papers. We selected full journal articles that reported neurofeedback as a treatment for autism in children (0–17 years). The search yielded 587 articles and we included 20 references with a total of 443 participants. Ninety-four percent of nonrandomized controlled and experimental trials concerning neurofeedback for autism spectrum disorders found positive results. The evidence for effectiveness of neurofeedback therapy was even more robust when only randomized controlled studies were considered. Although there are only a few randomized controlled studies, results support effectiveness of neurofeedback for autism spectrum disorder, including long-term positive effects. In the future, optimal treatment protocols have to be developed to guide clinicians in their neurofeedback treatment. In conclusion, neurofeedback seems to be an alternative treatment for autism spectrum disorders, with space for improvement.

Trial by trial EEG based BCI for distress versus non distress classification in individuals with ASD

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is often accompanied by impaired emotion regulation (ER). There has been increasing emphasis on developing evidence-based approaches to improve ER in ASD. Electroencephalography (EEG) has shown success in reducing ASD symptoms when used in neurofeedback-based interventions. Also, certain EEG components are associated with ER. Our overarching goal is to develop a technology that will use EEG to monitor real-time changes in ER and perform intervention based on these changes. As a first step, an EEG-based brain computer interface that is based on an Affective Posner task was developed to identify patterns associated with ER on a single trial basis, and EEG data collected from 21 individuals with ASD. Accordingly, our aim in this study is to investigate EEG features that could differentiate between distress and non-distress conditions. Specifically, we investigate if the EEG time-locked to the visual feedback presentation could be used to classify between WIN (non-distress) and LOSE (distress) conditions in a game with deception. Results showed that the extracted EEG features could differentiate between WIN and LOSE conditions (average accuracy of 81%), LOSE and rest-EEG conditions (average accuracy 94.8%), and WIN and rest-EEG conditions (average accuracy 94.9%).

Individual Alpha Peak Frequency, an Important Biomarker for Live Z-Score Training Neurofeedback in Adolescents with Learning Disabilities

Learning disabilities (LDs) have an estimated prevalence between 5% and 9% in the pediatric population and are associated with difficulties in reading, arithmetic, and writing. Previous electroencephalography (EEG) research has reported a lag in alpha-band development in specific LD phenotypes, which seems to offer a possible explanation for differences in EEG maturation. In this study, 40 adolescents aged 10–15 years with LDs underwent 10 sessions of Live Z-Score Training Neurofeedback (LZT-NF) Training to improve their cognition and behavior. Based on the individual alpha peak frequency (i-APF) values from the spectrogram, a group with normal i-APF (ni-APF) and a group with low i-APF (li-APF) were compared in a pre-and-post-LZT-NF intervention. There were no statistical differences in age, gender, or the distribution of LDs between the groups. The li-APF group showed a higher theta absolute power in P4 (p = 0.016) at baseline and higher Hi-Beta absolute power in F3 (p = 0.007) post-treatment compared with the ni-APF group. In both groups, extreme waves (absolute Z-score of ≥1.5) were more likely to move toward the normative values, with better results in the ni-APF group. Conversely, the waves within the normal range at baseline were more likely to move out of the range after treatment in the li-APF group. Our results provide evidence of a viable biomarker for identifying optimal responders for the LZT-NF technique based on the i-APF metric reflecting the patient’s neurophysiological individuality.

Comprehensive attention training system (CATS): A computerized executive-functioning training for school-aged children with autism spectrum disorder

OBJECTIVE

Theory suggests that impaired executive functioning (EF) might explain several symptoms of autism spectrum disorder (ASD) in children. However, only a few studies have examined the efficacy of EF training for the children using randomized control trial designs, and only two of them found significant benefits of the training.

METHOD

We designed Comprehensive Attention Training System (CATS), and tested this new EF intervention for children with ASD in a small-sampled randomized controlled trial. Twenty-five children with ASD aged six to twelve were randomly assigned to either the CATS or the control training and were assessed pre- and post-training.

RESULTS

Relative to the control group, the CATS group improved on EF as measured by the trail-making test, avoiding perseverative errors, and forming conceptual responses in the Wisconsin Card Sorting Task. There were also indications that CATS contributed to long-term communication skills as measured by the Vineland adaptive behavior scales.

CONCLUSIONS

We report preliminary evidence that the CATS intervention may improve the EF of school-aged children with ASD compared to a control intervention. We discuss the results in terms of their generalizability to other developmental disorders.

Neurofunctional and behavioural measures associated with fMRI-neurofeedback learning in adolescents with Attention-Deficit/Hyperactivity Disorder

Functional Magnetic Resonance Imaging Neurofeedback (fMRI-NF) targeting brain areas/networks shown to be dysfunctional by previous fMRI research is a promising novel neurotherapy for ADHD. Our pioneering study in 31 adolescents with ADHD showed that fMRI-NF of the right inferior frontal cortex (rIFC) and of the left parahippocampal gyrus (lPHG) was associated with clinical improvements. Previous studies using electro-encephalography-NF have shown, however, that not all ADHD patients learn to self-regulate, and the predictors of fMRI-NF self-regulation learning are not presently known. The aim of the current study was therefore to elucidate the potential predictors of fMRI-NF learning by investigating the relationship between fMRI-NF learning and baseline inhibitory brain function during an fMRI stop task, along with clinical and cognitive measures. fMRI-NF learning capacity was calculated for each participant by correlating the number of completed fMRI-NF runs with brain activation in their respective target regions from each run (rIFC or lPHG); higher correlation values were taken as a marker of better (linear) fMRI-NF learning. Linear correlations were then conducted between baseline measures and the participants' capacity for fMRI-NF learning. Better fMRI-NF learning was related to increased activation in left inferior fronto-striatal regions during the fMRI stop task. Poorer self-regulation during fMRI-NF training was associated with enhanced activation in posterior temporo-occipital and cerebellar regions. Cognitive and clinical measures were not associated with general fMRI-NF learning across all participants. A categorical analysis showed that 48% of adolescents with ADHD successfully learned fMRI-NF and this was also not associated with any baseline clinical or cognitive measures except that faster processing speed during inhibition and attention tasks predicted learning. Taken together, the findings suggest that imaging data are more predictive of fMRI-NF self-regulation skills in ADHD than behavioural data. Stronger baseline activation in fronto-striatal cognitive control regions predicts better fMRI-NF learning in ADHD.

Association of human serotonin receptor 4 promoter methylation with autism spectrum disorder

Human serotonin receptor 4 (HTR4) encodes a 5-HT4 receptor involved in learning, memory, depression, anxiety, and feeding behavior. The aim of this study was to investigate the association between the deoxyribonucleic acid (DNA) methylation of HTR4 promoter and autism spectrum disorder (ASD), a disease characterized by communication disorder and repetitive or restrictive behavior.Peripheral blood DNA was obtained from 61 ASD children and 66 healthy children, and the DNA methylation of HTR4 promoter was assessed by quantitative methylation-specific polymerase chain reaction. We used percentage of methylated reference (PMR) to represent DNA methylation level.Due to significant age differences between ASD cases and controls (3 [2, 5] years and 6 [5, 6] years, P = 3.34E-10), we used binary logistic regression analysis for adjustment. Our results showed that the DNA methylation levels of HTR4 promoter were significantly lower in children with ASD than in healthy children (median PMR: 66.23% vs 94.31%,P = .028, age-adjusted P = .034). In addition, the DNA methylation of HTR4 promoter was inversely associated with age in male ASD cases (total cases: r = -0.283, P = .027; male cases: r = -0.431, P = .002; female cases: r = -0.108, P = .752). Dual-luciferase reporter gene assay showed that the reporter gene expression in the strain with recombinant pGL3-promoter-HTR4 plasmid was significantly higher than that in the strain with pGL3-promoter plasmid (fold change = 2.01, P = .0065), indicating that the HTR4 promoter fragment may contain transcription factors to upregulate promoter activity.Our study suggested that hypomethylation of the HTR4 promoter is a potential biomarker for predicting the risk of male ASD.

Pathogenetical and Neurophysiological Features of Patients with Autism Spectrum Disorder: Phenomena and Diagnoses

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is accompanied by social deficits, repetitive and restricted interests, and altered brain development. The majority of ASD patients suffer not only from ASD itself but also from its neuropsychiatric comorbidities. Alterations in brain structure, synaptic development, and misregulation of neuroinflammation are considered risk factors for ASD and neuropsychiatric comorbidities. Electroencephalography has been developed to quantitatively explore effects of these neuronal changes of the brain in ASD. The pineal neurohormone melatonin is able to contribute to neural development. Also, this hormone has an inflammation-regulatory role and acts as a circadian key regulator to normalize sleep. These functions of melatonin may play crucial roles in the alleviation of ASD and its neuropsychiatric comorbidities. In this context, this article focuses on the presumable role of melatonin and suggests that this hormone could be a therapeutic agent for ASD and its related neuropsychiatric disorders.

Diagnostic Assessment Techniques and Non-Invasive Biomarkers for Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex heterogeneous neurological disorder that has led to a spectrum of diagnosis techniques. The screening instruments, medical and technological tools initiate the diagnosis process. Clinicians and psychologists propose therapies depending on the examination done by these methodologies. The literature has accounted dozens of diagnostic methods and alternative and complementary therapies but still lack in highlighting the proper biomarker for early detection and intervention. The emerging multi-modal neuro-imaging techniques have correlated the brain's functional and structural measures and diagnosed ASD with more sensitivity than individual approaches. The purpose of this review article is: (i) to provide an overview of the emerging ASD diagnosis methods and different markers and; (ii) to present the idea of integrating all the individual methods in to a multi-modal diagnostic system to enhance detection sensitivity. This system possesses the potential to diagnose and predict ASD clinically, neurologically & objectively with high detection sensitivity.

Control freaks: Towards optimal selection of control conditions for fMRI neurofeedback studies

fMRI Neurofeedback research employs many different control conditions. Currently, there is no consensus as to which control condition is best, and the answer depends on what aspects of the neurofeedback-training design one is trying to control for. These aspects can range from determining whether participants can learn to control brain activity via neurofeedback to determining whether there are clinically significant effects of the neurofeedback intervention. Lack of consensus over criteria for control conditions has hampered the design and interpretation of studies employing neurofeedback protocols. This paper presents an overview of the most commonly employed control conditions currently used in neurofeedback studies and discusses their advantages and disadvantages. Control conditions covered include no control, treatment-as-usual, bidirectional-regulation control, feedback of an alternative brain signal, sham feedback, and mental-rehearsal control. We conclude that the selection of the control condition(s) should be determined by the specific research goal of the study and best procedures that effectively control for relevant confounding factors.

Eyes-Closed Resting EEG Predicts the Learning of Alpha Down-Regulation in Neurofeedback Training

Neurofeedback training, which enables the trainee to learn self-control of the EEG activity of interest based on online feedback, has demonstrated benefits on cognitive and behavioral performance. Nevertheless, as a core mechanism of neurofeedback, learning of EEG regulation (i.e., EEG learning) has not been well understood. Moreover, a substantial number of non-learners who fail to achieve successful EEG learning have often been reported. This study investigated the EEG learning in alpha down-regulation neurofeedback, aiming to better understand the alpha learning and to early predict learner/non-learner. Twenty-nine participants received neurofeedback training to down-regulate alpha in two days, while eight of them were identified as non-learners who failed to reduce their alpha within sessions. Through a stepwise linear discriminant analysis, a prediction model was built based on participant's eyes-closed resting EEG activities in broad frequency bands including lower alpha, theta, sigma and beta 1 measured before training, which was validated in predicting learners/non-learners. The findings would assist in the early identification of the individuals who would not likely reduce their alpha during neurofeedback.

Resting and Initial Beta Amplitudes Predict Learning Ability in Beta/Theta Ratio Neurofeedback Training in Healthy Young Adults

Neurofeedback (NF) training has been proved beneficial in cognitive and behavioral performance improvement in healthy individuals. Unfortunately, the NF learning ability shows large individual difference and in a number of NF studies there are even some non-learners who cannot successfully self-regulate their brain activity by NF. This study aimed to find out the neurophysiological predictor of the learning ability in up-regulating beta-1 (15-18 Hz)/theta (4-7 Hz) ratio (BTR) training in healthy young adults. Eighteen volunteers finished five training sessions in successive 5 days. We found that low beta (12-15 Hz) amplitude in a 1-min eyes-open resting baseline measured before training and the beta-1 amplitude in the first training block with 4.5-min duration could predict the BTR learning ability across sessions. The results provide a low cost, convenient and easy way to predict the learning ability in up-regulating BTR training, and would be helpful in avoiding potential frustration and adjusting training protocol for the participants with poor learning ability.

QEEG spectral and coherence assessment of autistic children in three different experimental conditions

We studied autistics by quantitative EEG spectral and coherence analysis during three experimental conditions: basal, watching a cartoon with audio (V–A), and with muted audio band (VwA). Significant reductions were found for the absolute power spectral density (PSD) in the central region for delta and theta, and in the posterior region for sigma and beta bands, lateralized to the right hemisphere. When comparing VwA versus the V–A in the midline regions, we found significant decrements of absolute PSD for delta, theta and alpha, and increments for the beta and gamma bands. In autistics, VwA versus V–A tended to show lower coherence values in the right hemisphere. An impairment of visual and auditory sensory integration in autistics might explain our results.

The validity of individual frontal alpha asymmetry EEG neurofeedback

Frontal asymmetry in alpha oscillations is assumed to be associated with psychopathology and individual differences in emotional responding. Brain-activity-based feedback is a promising tool for the modulation of cortical activity. Here, we validated a neurofeedback protocol designed to change relative frontal asymmetry based on individual alpha peak frequencies, including real-time average referencing and eye-correction. Participants (N = 60) were randomly assigned to a right, left or placebo neurofeedback group. Results show a difference in trainability between groups, with a linear change in frontal alpha asymmetry over time for the right neurofeedback group during rest. Moreover, the asymmetry changes in the right group were frequency and location specific, even though trainability did not persist at 1 week and 1 month follow-ups. On the behavioral level, subjective stress on the second test day was reduced in the left and placebo neurofeedback groups, but not in the right neurofeedback group. We found individual differences in trainability that were dependent on training group, with participants in the right neurofeedback group being more likely to change their frontal asymmetry in the desired direction. Individual differences in trainability were also reflected in the ability to change frontal asymmetry during the feedback.

EEG biofeedback for autism spectrum disorder: a commentary on Kouijzer et al. (2013)

Research conducted by Kouijzer et al. (Appl Psychophysiol Biofeedback 38(1):17-28, 2013) compared the effects of skin conductance biofeedback and EEG-biofeedback on patients with autistic spectrum disorders to determine their relative efficacy. While they found a difference between treatment and control groups, there was no significant difference on many variables between the two treatment groups. From this, the increase in symptom alleviation from autistic spectrum disorder was attributed to non-specific factors surrounding the study. We now offer alternative explanations for their findings and propose different options for future studies. We hypothesize that the location and type of neurofeedback used adversely impacted the findings. We speculate that had they used a form of EEG-biofeedback that can combat deficiencies in connectivity and also trained the areas of the brain most affected by autism, there may have then been a significant difference between the effectiveness of EEG-biofeedback versus skin conductance biofeedback.

Are treatment effects of neurofeedback training in children with ADHD related to the successful regulation of brain activity? A review on the learning of regulation of brain activity and a contribution to the discussion on specificity

While issues of efficacy and specificity are crucial for the future of neurofeedback training, there may be alternative designs and control analyses to circumvent the methodological and ethical problems associated with double-blind placebo studies. Surprisingly, most NF studies do not report the most immediate result of their NF training, i.e., whether or not children with ADHD gain control over their brain activity during the training sessions. For the investigation of specificity, however, it seems essential to analyze the learning and adaptation processes that take place in the course of the training and to relate improvements in self-regulated brain activity across training sessions to behavioral, neuropsychological and electrophysiological outcomes. To this aim, a review of studies on neurofeedback training with ADHD patients which include the analysis of learning across training sessions or relate training performance to outcome is presented. Methods on how to evaluate and quantify learning of EEG regulation over time are discussed. “Non-learning” has been reported in a small number of ADHD-studies, but has not been a focus of general methodological discussion so far. For this reason, selected results from the brain-computer interface (BCI) research on the so-called “brain-computer illiteracy”, the inability to gain control over one’s brain activity, are also included. It is concluded that in the discussion on specificity, more attention should be devoted to the analysis of EEG regulation performance in the course of the training and its impact on clinical outcome. It is necessary to improve the knowledge on characteristic cross-session and within-session learning trajectories in ADHD and to provide the best conditions for learning.

Biofeedback for psychiatric disorders: a systematic review

Biofeedback potentially provides non-invasive, effective psychophysiological interventions for psychiatric disorders. The encompassing purpose of this review was to establish how biofeedback interventions have been used to treat select psychiatric disorders [anxiety, autistic spectrum disorders, depression, dissociation, eating disorders, schizophrenia and psychoses] to date and provide a useful reference for consultation by clinicians and researchers planning to administer a biofeedback treatment. A systematic search of EMBASE, MEDLINE, PsycINFO, and WOK databases and hand searches in Applied Psychophysiology and Biofeedback, and Journal of Neurotherapy, identified 227 articles; 63 of which are included within this review. Electroencephalographic neurofeedback constituted the most investigated modality (31.7%). Anxiety disorders were the most commonly treated (68.3%). Multi-modal biofeedback appeared most effective in significantly ameliorating symptoms, suggesting that targeting more than one physiological modality for bio-regulation increases therapeutic efficacy. Overall, 80.9% of articles reported some level of clinical amelioration related to biofeedback exposure, 65.0% to a statistically significant (p < .05) level of symptom reduction based on reported standardized clinical parameters. Although the heterogeneity of the included studies warrants caution before explicit efficacy statements can be made. Further development of standardized controlled methodological protocols tailored for specific disorders and guidelines to generate comprehensive reports may contribute towards establishing the value of biofeedback interventions within mainstream psychiatry.

Resting alpha activity predicts learning ability in alpha neurofeedback

Individuals differ in their ability to learn how to regulate the brain activity by neurofeedback. This study aimed to investigate whether the resting alpha activity can predict the learning ability in alpha neurofeedback. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback and the learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.

Quantitative EEG neurofeedback for the treatment of pediatric attention-deficit/hyperactivity disorder, autism spectrum disorders, learning disorders, and epilepsy

Neurofeedback (NF) using surface electroencephalographic signals has been used to treat various child psychiatric disorders by providing patients with video/audio information about their brain's electrical activity in real-time. Research data are reviewed and clinical recommendations are made regarding NF treatment of youth with attention deficit/hyperactivity disorder, autism, learning disorders, and epilepsy. Most NF studies are limited by methodological issues, such as failure to use or test the validity of a full-blind or sham NF. The safety of NF treatment has not been thoroughly investigated in youth or adults, although clinical experience suggests reasonable safety.