EEG Biofeedback Treatment of ADD

Multi-channel EEG emotion recognition through residual graph attention neural network

In this paper, a novel EEG emotion recognition method based on residual graph attention neural network is proposed. The method constructs a three-dimensional sparse feature matrix according to the relative position of electrode channels, and inputs it into the residual network to extract high-level abstract features containing electrode spatial position information. At the same time, the adjacency matrix representing the connection relationship of electrode channels is constructed, and the time-domain features of multi-channel EEG are modeled using graph. Then, the graph attention neural network is utilized to learn the intrinsic connection relationship between EEG channels located in different brain regions from the adjacency matrix and the constructed graph structure data. Finally, the high-level abstract features extracted from the two networks are fused to judge the emotional state. The experiment is carried out on DEAP data set. The experimental results show that the spatial domain information of electrode channels and the intrinsic connection relationship between different channels contain salient information related to emotional state, and the proposed model can effectively fuse these information to improve the performance of multi-channel EEG emotion recognition.

Emotion Recognition in a Health Continuum: Comparison of Healthy Adults of Advancing Age, Community Dwelling Adults Bearing Vascular Risk Factors and People Diagnosed with Mild Cognitive Impairment

The identification of basic emotions plays an important role in social relationships and behaviors linked to survival. In neurodegenerative conditions such as Alzheimer's disease (AD), the ability to recognize emotions may already be impaired at early stages of the disease, such as the stage of Mild Cognitive Impairment (MCI). However, as regards vascular pathologies related to cognitive impairment, very little is known about emotion recognition in people bearing vascular risk factors (VRF). Therefore, the aim of the present study was to examine emotion recognition ability in the health continuum "healthy advancing age-advancing age with VRF-MCI". The sample consisted of 106 adults divided in three diagnostic groups; 43 adults with MCI, 41 adults bearing one or more VRF, and 22 healthy controls of advancing age (HC). Since HC were more educated and younger than the other two groups, the age-group and level of educational were taken into account in the statistical analyses. A dynamic visual test was administered to examine recognition of basic emotions and emotionally neutral conditions. The results showed only a significant diagnostic group x educational level interaction as regards total emotion recognition ability, F (4, 28.910) = 4.117 p = 0.004 η2 = 0.166. High educational level seems to contribute to a high-level-emotion-recognition-performance both in healthy adults of advancing age and in adults bearing vascular risk factors. Medium educational level appears to play the same role only in healthy adults. Neither educational level can help MCI people to enhance their significantly lower emotion recognition ability.

Human-Computer Interaction with Detection of Speaker Emotions Using Convolution Neural Networks

Emotions play an essential role in human relationships, and many real-time applications rely on interpreting the speaker’s emotion from their words. Speech emotion recognition (SER) modules aid human-computer interface (HCI) applications, but they are challenging to implement because of the lack of balanced data for training and clarity about which features are sufficient for categorization. This research discusses the impact of the classification approach, identifying the most appropriate combination of features and data augmentation on speech emotion detection accuracy. Selection of the correct combination of handcrafted features with the classifier plays an integral part in reducing computation complexity. The suggested classification model, a 1D convolutional neural network (1D CNN), outperforms traditional machine learning approaches in classification. Unlike most earlier studies, which examined emotions primarily through a single language lens, our analysis looks at numerous language data sets. With the most discriminating features and data augmentation, our technique achieves 97.09%, 96.44%, and 83.33% accuracy for the BAVED, ANAD, and SAVEE data sets, respectively.

Smart Sensor Based on Biofeedback to Measure Child Relaxation in Out-of-Home Care

Children from out-of-home care are a vulnerable population that faces high stress and anxiety levels due to stressful experiences, such as being abused, being raped, and violence. This problem could have negative effects on their bio-psycho-social well-being if they are not provided with comprehensive psychological treatment. Numerous methods have been developed to help them relax, but there are no current approaches for assessing the relaxation level they reach. Based on this, a novel smart sensor that can evaluate the level of relaxation a child experiences is developed in this paper. It evaluates changes in thermal biomarkers (forehead, right and left cheek, chin, and maxillary) and heart rate (HR). Then, through a k-nearest neighbors (K-NN) intelligent classifier, four possible levels of relaxation can be obtained: no-relax, low-relax, relax, and very-relax. Additionally, an application (called i-CARE) for anxiety management, which is based on biofeedback diaphragmatic breathing, guided imagery, and video games, is evaluated. After testing the developed smart sensor, an 89.7% accuracy is obtained. The smart sensor used provides a reliable measurement of relaxation levels and the i-CARE application is effective for anxiety management, both of which are focused on children exposed to out-of-home care conditions.

Is there an association between attention deficit hyperactivity disorder in children and adolescents and the occurrence of bruxism? A systematic review and meta-analysis

Aim of the present systematic review was to evaluate whether children and adolescents with attention-deficit/hyperactivity disorder (ADHD) are at greater chance of developing bruxism compared to individuals without this disorder. Observational studies that evaluated the occurrence of bruxism in children and adolescents with ADHD were included. The quality of the evidence was evaluated using the Grading of Recommendations, Assessment, Development and Evaluation criteria. Thirty-two studies involving a total of 2629 children/adolescents with ADHD and 1739 with bruxism (1629 with sleep bruxism and 110 with awake bruxism) were included. The prevalence of bruxism, irrespective of type, in the children/adolescents was 31% (95% CI: 0.22-0.41, I² = 93%). ADHD was associated with an increased chance of bruxism (OR: 2.94, 95% CI: 2.12-4.07, I² = 61%), independently of the type [sleep bruxism (OR: 2.77, 95% CI: 1.90-4.03, I² = 66%) or awake bruxism (OR: 10.64, 95% CI: 2.41-47.03, I² = 65%)]. The presence of signs of ADHD without a diagnostic confirmation was not associated with an increased chance of bruxism (OR: 3.26, 95% CI: 0.76-14.04, I² = 61%). Children and adolescents with a definitive diagnosis of ADHD are at greater chance of developing sleep and awake bruxism than those without this disorder.

Dynamic processes in regulation and some implications for biofeedback and biobehavioral interventions

Systems theory has long been used in psychology, biology, and sociology. This paper applies newer methods of control systems modeling for assessing system stability in health and disease. Control systems can be characterized as open or closed systems with feedback loops. Feedback produces oscillatory activity, and the complexity of naturally occurring oscillatory patterns reflects the multiplicity of feedback mechanisms, such that many mechanisms operate simultaneously to control the system. Unstable systems, often associated with poor health, are characterized by absence of oscillation, random noise, or a very simple pattern of oscillation. This modeling approach can be applied to a diverse range of phenomena, including cardiovascular and brain activity, mood and thermal regulation, and social system stability. External system stressors such as disease, psychological stress, injury, or interpersonal conflict may perturb a system, yet simultaneously stimulate oscillatory processes and exercise control mechanisms. Resonance can occur in systems with negative feedback loops, causing high-amplitude oscillations at a single frequency. Resonance effects can be used to strengthen modulatory oscillations, but may obscure other information and control mechanisms, and weaken system stability. Positive as well as negative feedback loops are important for system function and stability. Examples are presented of oscillatory processes in heart rate variability, and regulation of autonomic, thermal, pancreatic and central nervous system processes, as well as in social/organizational systems such as marriages and business organizations. Resonance in negative feedback loops can help stimulate oscillations and exercise control reflexes, but also can deprive the system of important information. Empirical hypotheses derived from this approach are presented, including that moderate stress may enhance health and functioning.

Clinical utility of EEG in attention-deficit/hyperactivity disorder: a research update

Psychiatric research applications of electroencephalography (EEG), the earliest approach to imaging human cortical brain activity, are attracting increasing scientific and clinical interest. For more than 40 years, EEG research has attempted to characterize and quantify the neurophysiology of attention-deficit/hyperactivity disorder (ADHD), most consistently associating it with increased frontocentral theta band activity and increased theta to beta (θ/β) power ratio during rest compared to non-ADHD controls. Recent reports suggest that while these EEG measures demonstrate strong discriminant validity for ADHD, significant EEG heterogeneity also exists across ADHD-diagnosed individuals. In particular, additional studies validating the use of the θ/β power ratio measure appear to be needed before it can be used for clinical diagnosis. In recent years, the number and the scientific quality of research reports on EEG-based neurofeedback (NF) for ADHD have grown considerably, although the studies reviewed here do not yet support NF training as a first-line, stand-alone treatment modality. In particular, more research is needed comparing NF to placebo control and other effective treatments for ADHD. Currently, after a long period of relative stasis, the neurophysiological specificity of measures used in EEG research is rapidly increasing. It is likely, therefore, that new EEG studies of ADHD using higher density recordings and new measures drawn from viewing EEG as a 3-dimensional functional imaging modality, as well as intensive re-analyses of existing EEG study data, can better characterize the neurophysiological differences between and within ADHD and non-ADHD subjects, and lead to more precise diagnostic measures and effective NF approaches.

A Comparison of Cognitive and Psychosocial Function for Males Within the ADHD Continuum

Two case studies are presented illustrating neurophysiological dysfunction suggesting input or output deficits in ADHD assessed across multiple domains. Data included child and family history, behavior ratings, information processing, speed, cognitive, neurophysiological, and academic function. Pretreatment data indicated impaired processing speed, excessive slow to fast wave ratios indicative of attentional disregulation, and poor psychosocial function evident in both children. Posttreatment assessment indicated improvement in slow to fast wave ratios and psychosocial functioning for both children. Additional improvement was also noted in cognitive and academic function in MH, the child with learning disabilities, and in processing speed for CX, the child with elevated cognitive function. Neurophysiological disregulation in ADHD may result in input or output impairment differentially affecting cognitive, academic, and psychosocial functioning. Heterogeneity within the ADHD continuum underscores the need for multifaceted assessment to guide diagnosis and treatment. In ADHD children nonresponsive to stimulants, neurofeedback can be a viable treatment to enhance attentional focus and on-task behavior.

Psychosocial treatments for children with attention deficit/hyperactivity disorder

This article reviews studies examining the efficacy of behavioral interventions for the treatment of attention-deficit/hyperactivity disorder (ADHD). A specific emphasis is placed on evidence-based interventions that include parent training, classroom, academic, and peer interventions. Results indicate that school-aged children respond to behavioral interventions when they are appropriately implemented both at home and in the classroom setting. Combined treatments (behavioral management and stimulant medication) represent the gold standard in ADHD treatment and are often recommended as the first-line treatment option due to the many problems faced by children with ADHD. Diversity issues, although an important consideration in the treatment of ADHD, continue to remain an understudied area. Recommendations for future research are made pertaining to treatment sequencing with regard to behavior management as well as for subgroups of ADHD children who may respond best to specific treatments.

Interindividual variability in EEG correlates of attention and limits of functional mapping

In this study, we analyzed the EEG oscillatory activity induced during a simple visual task, in search of spectral correlate(s) of attention. This task has been previously analyzed by conventional event-related potential (ERP) computation, and Slow Potentials (SPs) were seen to be highly variable across subjects in topography and generators [Basile LF, Brunetti EP, Pereira JF Jr, Ballester G, Amaro E Jr, Anghinah R, Ribeiro P, Piedade R, Gattaz WF. (2006) Complex slow potential generators in a simplified attention paradigm. Int J Psychophysiol. 61(2):149-57]. We obtained 124-channel EEG recordings from 12 individuals and computed latency-corrected peak averaging in oscillatory bursts. We used current-density reconstruction to model the generators of attention-related activity that would not be seen in ERPs, which are restricted to stimulus-locked activity. We intended to compare a possibly found spectral correlate of attention, in topographic variability, with stimulus-related activity. The main results were (1) the detection of two bands of attention-induced beta range oscillations (around 25 and 21 Hz), whose scalp topography and current density cortical distribution were complex multi-focal, and highly variable across subjects (topographic dispersion significantly higher than sensory-related visual theta induced band-power), including prefrontal and posterior cortical areas. Most interesting, however, was the observation that (2) the generators of task-induced oscillations are largely the same individual-specific sets of cortical areas active during the pre-stimulus baseline. We concluded that attention-related electrical cortical activity is highly individual-specific, and possibly, to a great extent already established during mere resting wakefulness. We discuss the critical implications of those results, in combination with results from other methods that present individual data, to functional mapping of cortical association areas.

Neurofeedback for Children with ADHD: A Comparison of SCP and Theta/Beta Protocols

Behavioral and cognitive improvements in children with ADHD have been consistently reported after neurofeedback-treatment. However, neurofeedback has not been commonly accepted as a treatment for ADHD. This study addresses previous methodological shortcomings while comparing a neurofeedback-training of Theta-Beta frequencies and training of slow cortical potentials (SCPs). The study aimed at answering (a) whether patients were able to demonstrate learning of cortical self-regulation, (b) if treatment leads to an improvement in cognition and behavior and (c) if the two experimental groups differ in cognitive and behavioral outcome variables. SCP participants were trained to produce positive and negative SCP-shifts while the Theta/Beta participants were trained to suppress Theta (4-8 Hz) while increasing Beta (12-20 Hz). Participants were blind to group assignment. Assessment included potentially confounding variables. Each group was comprised of 19 children with ADHD (aged 8-13 years). The treatment procedure consisted of three phases of 10 sessions each. Both groups were able to intentionally regulate cortical activity and improved in attention and IQ. Parents and teachers reported significant behavioral and cognitive improvements. Clinical effects for both groups remained stable six months after treatment. Groups did not differ in behavioural or cognitive outcome.

Neurofeedback for treating tinnitus

Many individuals with tinnitus have abnormal oscillatory brain activity. Led by this finding, we have developed a way to normalize such pathological activity by neurofeedback techniques (Weisz et al. (2005). PLoS Med., 2: e153). This is achieved mainly through enhancement of tau activity, i.e., oscillatory activity produced in perisylvian regions within the alpha frequency range (8-12 Hz) and concomitant reduction in delta power range (0.5-4 Hz). This activity is recorded from electrodes placed on the frontal scalp. We have found that modification of the tau-to-delta ratio significantly reduces tinnitus intensity. Participants who successfully modified their oscillatory pattern profited from the treatment to the extent that the tinnitus sensation became completely abolished. Overall, this neurofeedback training was significantly superiorin reducing tinnitus-related distress than frequency discrimination training.

Self-regulation of slow cortical potentials: a new treatment for children with attention-deficit/hyperactivity disorder

OBJECTIVE

We investigated the effects of self-regulation of slow cortical potentials for children with attention-deficit/hyperactivity disorder. Slow cortical potentials are slow event-related direct-current shifts of the electroencephalogram. Slow cortical potential shifts in the electrical negative direction reflect the depolarization of large cortical cell assemblies, reducing their excitation threshold. This training aims at regulation of cortical excitation thresholds considered to be impaired in children with attention-deficit/hyperactivity disorder. Electroencephalographic data from the training and the 6-month follow-up are reported, as are changes in behavior and cognition.

METHOD

Twenty-three children with attention-deficit/hyperactivity disorder aged between 8 and 13 years received 30 sessions of self-regulation training of slow cortical potentials in 3 phases of 10 sessions each. Increasing and decreasing slow cortical potentials at central brain regions was fed back visually and auditorily. Transfer trials without feedback were intermixed with feedback trials to allow generalization to everyday-life situations. In addition to the neurofeedback sessions, children exercised during the third training phase to apply the self-regulation strategy while doing their homework.

RESULTS

For the first time, electroencephalographic data during the course of slow cortical potential neurofeedback are reported. Measurement before and after the trials showed that children with attention-deficit/hyperactivity disorder learn to regulate negative slow cortical potentials. After training, significant improvement in behavior, attention, and IQ score was observed. The behavior ratings included Diagnostic and Statistical Manual of Mental Disorders criteria, number of problems, and social behavior at school and were conducted by parents and teachers. The cognitive variables were assessed with the Wechsler Intelligence Scale for Children and with a computerized test battery that measures several components of attention. All changes proved to be stable at 6 months' follow-up after the end of training. Clinical outcome was predicted by the ability to produce negative potential shifts in transfer sessions without feedback.

CONCLUSIONS

According to the guidelines of the efficacy of treatments, the evidence of the efficacy of slow cortical potential feedback found in this study reaches level 2: "possibly efficacious." In the absence of a control group, no causal relationship between observed improvements and the ability to regulate brain activity can be made. However, it could be shown for the first time that good performance in self-regulation predicts clinical outcome. "Good performance" was defined as the ability to produce negative potential shifts in trials without feedback, because it is known that the ability to self-regulate without feedback is impaired in children and adults with attention problems. Additional research should focus on the control of unspecific effects, medication, and subtypes to confirm the assumption that slow cortical potential feedback is a viable treatment option for attention-deficit/hyperactivity disorder. Regulation of slow cortical potentials may involve similar neurobiological pathways as medical treatment. It is suggested that regulation of frontocentral negative slow cortical potentials affects the cholinergic-dopaminergic balance and allows children to adapt to task requirements more flexibly.

Clinical Utility of EEG in Attention Deficit Hyperactivity Disorder

Electrophysiological measures were among the first to be used to study brain processes in children with attention deficit hyperactivity disorder (ADHD; Diagnostic and Statistical Manual of Mental Disorders [4th ed.], American Psychiatric Association, 1994) and have been used as such for over 30 years (see Hastings & Barkley, 1978, for an early review). More recently, electroencephalography (EEG) has been used both in research to describe and quantify the underlying neurophysiology of ADHD, but also clinically in the assessment, diagnosis, and treatment of ADHD. This review will first provide a brief overview of EEG and then present some of the research findings of EEG correlates in ADHD. Then, the utility of EEG in making an ADHD diagnosis and predicting stimulant response will be examined. Finally, and more controversially, we will review the results of the most recent studies on EEG biofeedback (neurofeedback) as a treatment for ADHD and the issues that remain to be addressed in the research examining the efficacy this therapeutic approach.

Old and new controversies in the alternative treatment of attention-deficit hyperactivity disorder

Use of complementary and alternative medicine (CAM) for treatment of attention-deficit hyperactivity disorder (ADHD) has become widespread in both referral and primary care populations. We review the purported mechanism of action and available evidence for selected CAM therapies for ADHD. Enduring controversies, such as elimination of artificial food additives, colors, and/or preservatives; the effect of sugar on behavior in children; and the use of EEG biofeedback, have been well studied but lack support as effective sole treatments for ADHD. The initial evidence for some emerging CAM therapies, such as essential fatty acid supplementation, yoga, massage, homeopathy, and green outdoor spaces, suggests potential benefits as part of an overall ADHD treatment plan. More rigorously designed studies are needed to evaluate their effectiveness as single therapy for ADHD.

Neurofeedback in der Behandlung der Aufmerksamkeitsdefizit-Hyperaktivitätsstörung (ADHS) im Kindes- und Jugendalter

Zusammenfassung: Einleitung: In der Therapie der Aufmerksamkeitsdefizit-Hyperaktivitätsstörung (ADHS) sind viele nicht-medikamentöse Behandlungsmethoden den Nachweis ihrer Wirksamkeit schuldig geblieben. Für das Neurofeedback (auch EEG-Biofeedback) hat sich die Evidenzbasis in den vergangenen Jahren verbessert. Neurofeedback bewirkt abhängig vom Trainings-Protokoll Veränderungen des EEG-Frequenzspektrums oder der ereigniskorrelierten Potentiale bei ADHS und strebt über die gelernte Modifikation dieser Parameter eine Verbesserung der ADHS-Kernsymptome an. Methoden: In dieser Übersichtsarbeit werden die vorliegenden Forschungsbefunde detailliert dargelegt. Ergebnisse: Die durch das Neurofeedback erreichten kurzfristigen Verbesserungen entsprachen in drei kontrollierten Studien denen einer pharmakotherapeutischen Stimulanzien-Behandlung. Neurofeedback führte zu einer signifikanten Reduktion von Unaufmerksamkeit, Impulsivität und Hyperaktivität. Darüber hinaus fand sich eine anhaltende Normalisierung des Spontan-EEGs, während eine Stimulanzientherapie keine vergleichbare Normalisierung bewirkte; es traten keine unerwünschten Wirkungen auf. Untersuchungen zur Wirkdauer der Neurofeedback-Effekte sind ermutigend, stützen sich aber auf kleine Patientenzahlen. Schlussfolgerung: Neurofeedback ist ein viel versprechender Ansatz in der Behandlung aufmerksamkeitsgestörter, hyperaktiver Kinder. Gleichwohl besteht Bedarf an weiteren kontrollierten Studien mit einheitlichen diagnostischen Kriterien, ausreichend großen Stichproben, geeigneten Veränderungsmaßen und Katamnese-Untersuchungen.