Search Results (7)

Background: Electroencephalography (EEG) is a non-invasive technique that records millisecond-scale cortical electrical activity using scalp electrodes. In EEG-based neurofeedback (NFB), these signals are processed to provide real-time feedback that supports self-regulation of targeted brain rhythms; evidence suggests improvements in cognitive and neurophysiological performance in athletes and non-athletes. However, methodological inconsistencies—such as limited blinding, poor sham control, and outdated approaches to EEG spectral analysis—restrict reproducibility and hinder cumulative progress in the field. Methods: This scoping review aimed to identify and analyze the methodological characteristics, outcome measures, and reproducibility gaps in EEG-based NFB studies involving athletes and non-athletes. Following PRISMA-ScR guidelines, we systematically searched academic databases (PubMed, Embase, Scopus, Web of Science, PsycINFO, and Cochrane Library), as well as gray literature sources (ProQuest Dissertations, LILACS, Tripdatabase, and Google Scholar). Of 48 included studies, 44 were published in international peer-reviewed journals and 4 in regional journals. Data were extracted on study design, participant population, NFB protocols, targeted EEG rhythms, cognitive and neurophysiological outcomes, and methodological rigor. Results: The review revealed substantial heterogeneity in targeted rhythms, protocols, and reporting standards. None of the studies employed modern spectral parameterization methods (e.g., FOOOF), while only 29% used active sham protocols and 6% employed inert sham conditions. Reporting blinding procedures and follow-up assessments was limited or absent in most studies. Discussion: This review highlights critical methodological shortcomings that may bias interpretations of NFB effects in sport and cognitive domains. To strengthen future research, studies should rigorously implement sham and blinding procedures, ensure transparent reporting of EEG metrics, and adopt open-science practices, including modern approaches to spectral parameterization. Full article

This paper presents a mobile, easy-to-maintain wireless electroencephalograph (EEG) system designed for work with children in a school environment. This EEG data acquisition platform is a small-sized, battery-powered system with a high sampling rate that is scalable to different channel numbers. The system was validated in a study of live z-score neurofeedback training for quantitative EEG (zNF-qEEG) for typical-reading children and those with developmental dyslexia (DD). This system reads and controls real-time neurofeedback (zNF) signals, synchronizing visual stimuli (low spatial frequency (LSF) illusions) with the alpha/theta (z-α/θ) score neural oscillations. The NF sessions were applied during discrimination of LSF illusions with different contrasts. Visual feedback was provided with color cues to remodulate neural activity in children with DD and their cognitive abilities. The combined zNF-qEEG and training with different visual magnocellular and parvocellular tasks (VTs) compensated for the deficits in the temporal areas affecting the occipitotemporal pathway more in the left-hemispheric ventral brain areas of the post-training children with dyslexia in the low-contrast LSF illusion and dorsal dysfunction in the high-contrast LSF illusion. The better α/θ scores for postD in the temporoparietal and middle occipital regions can be associated with an improvement in special frequency processing, while the better scores in the precentral and parietal cortices were due to an advancement in the temporal processing of the illusion. The improvements in the reading speeds were twice as high after 4 months of qEEG z-NF-VT training, with three times fewer omitted words and errors. Full article

EEG-based brain–computer interfaces (BCI) have promising therapeutic potential beyond traditional neurofeedback training, such as enabling personalized and optimized virtual reality (VR) neurorehabilitation paradigms where the timing and parameters of the visual experience is synchronized with specific brain states. While BCI algorithms are often designed to focus on whichever portion of a signal is most informative, in these brain-state-synchronized applications, it is of critical importance that the resulting decoder is sensitive to physiological brain activity representative of various mental states, and not to artifacts, such as those arising from naturalistic movements. In this study, we compare the relative classification accuracy with which different motor tasks can be decoded from both extracted brain activity and artifacts contained in the EEG signal. EEG data were collected from 17 chronic stroke patients while performing six different head, hand, and arm movements in a realistic VR-based neurorehabilitation paradigm. Results show that the artifactual component of the EEG signal is significantly more informative than brain activity with respect to classification accuracy. This finding is consistent across different feature extraction methods and classification pipelines. While informative brain signals can be recovered with suitable cleaning procedures, we recommend that features should not be designed solely to maximize classification accuracy, as this could select for remaining artifactual components. We also propose the use of machine learning approaches that are interpretable to verify that classification is driven by physiological brain states. In summary, whereas informative artifacts are a helpful friend in BCI-based communication applications, they can be a problematic foe in the estimation of physiological brain states. Full article

This mini-review is aimed at briefly summarizing the present status of functional near-infrared spectroscopy (fNIRS) and predicting where the technique should go in the next decade. This mini-review quotes 33 articles on the different fNIRS basics and technical developments and 44 reviews on the fNIRS applications published in the last eight years. The huge number of review articles about a wide spectrum of topics in the field of cognitive and social sciences, functional neuroimaging research, and medicine testifies to the maturity achieved by this non-invasive optical vascular-based functional neuroimaging technique. Today, fNIRS has started to be utilized on healthy subjects while moving freely in different naturalistic settings. Further instrumental developments are expected to be done in the near future to fully satisfy this latter important aspect. In addition, fNIRS procedures, including correction methods for the strong extracranial interferences, need to be standardized before using fNIRS as a clinical tool in individual patients. New research avenues such as interactive neurosciences, cortical activation modulated by different type of sport performance, and cortical activation during neurofeedback training are highlighted. Full article

Neurofeedback is a self-regulation technique that can be applied to learn to voluntarily control cerebral activity in specific brain regions. In this work, a Transcranial Doppler-based configurable neurofeedback system is proposed and described. The hardware configuration is based on the Red Pitaya board, which gives great flexibility and processing power to the system. The parameter to be trained can be selected between several temporal, spectral, or complexity features from the cerebral blood flow velocity signal in different vessels. As previous studies have found alterations in these parameters in chronic pain patients, the system could be applied to help them to voluntarily control these parameters. Two protocols based on different temporal lengths of the training periods have been proposed and tested with six healthy subjects that were randomly assigned to one of the protocols at the beginning of the procedure. For the purposes of the testing, the trained parameter was the mean cerebral blood flow velocity in the aggregated data from the two anterior cerebral arteries. Results show that, using the proposed neurofeedback system, the two groups of healthy volunteers can learn to self-regulate a parameter from their brain activity in a reduced number of training sessions. Full article

Conscious, pre-conscious, and unconscious mechanisms are implicated in modulating affective processing in daily activities. Specifically, mental practice fostering awareness and control of affective reactions to external stimuli and stressful events (such as mindfulness and neurofeedback protocols) can be used to improve our ability to manage unconscious negative emotions. Indeed, it is possible to empower self-monitoring and regulation skills, as well as our ability to manage stress and negative emotions coming from everyday events and activities. This can be accomplished, on the one hand, by regularly practicing self-observation and by promoting bodily awareness and an awareness of automatic responses (e.g., uncontrolled affective reactions); on the other hand, by undergoing implicit training protocols that take advantage of brain responses. The present paper elucidates the contribution of both conscious and unconscious levels in emotion regulation and stress management, with a focus on their neural correlates and their role in mindfulness practice and on the potential of body-sensing devices for supporting meditation sessions, for fostering motivation to practice, and for making meditation more appealing and sustainable. We will finally present preliminary evidence on the effect of an intensive technology-mediated meditation protocol based on mindfulness practices and supported by a brain-sensing wearable device. The experimental procedure included three levels of outcome indices: psychometric measures related to perceived stress; neuropsychological and behavioural measures related to cognitive performance; and instrumental measures (resting-state and task-related electroencephalographic markers—EEG-ERPs). Full article

Attention deficit hyperactivity disorder (ADHD) is the most common neuropsychiatric disorder in children and is increasing in prevalence. There has also been a related increase in prescribing stimulant medication despite some controversy whether ADHD medication makes a lasting difference in school performance or achievement. Families who are apprehensive about side effects and with concerns for efficacy of medication pursue integrative medicine as an alternative or adjunct to pharmacologic and cognitive behavioral treatment approaches. Integrative medicine incorporates evidence-based medicine, both conventional and complementary and alternative therapies, to deliver personalized care to the patient, emphasizing diet, nutrients, gut health, and environmental influences as a means to decrease symptoms associated with chronic disorders. Pediatric integrative medicine practitioners are increasing in number throughout the United States because of improvement in patient health outcomes. However, limited funding and poor research design interfere with generalizable treatment approaches utilizing integrative medicine. The use of research designs originally intended for drugs and procedures are not suitable for many integrative medicine approaches. This article serves to highlight integrative medicine approaches in use today for children with ADHD, including dietary therapies, nutritional supplements, environmental hygiene, and neurofeedback. Full article