Neurorehabilitation of social dysfunctions: a model-based neurofeedback approach for low and high-functioning autism

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

In recent years, the scientific community has begun tо explore the efficacy оf an integrated neurofeedback + biofeedback approach іn various conditions, both pathological and non-pathological. Although several studies have contributed valuable insights into its potential benefits, this review aims tо further investigate its effectiveness by synthesizing current findings and identifying areas for future research. Our goal іs tо provide a comprehensive overview that may highlight gaps іn the existing literature and propose directions for subsequent studies. The search for articles was conducted on the digital databases PubMed, Scopus, and Web of Science. Studies to have used the integrated neurofeedback + biofeedback approach published between 2014 and 2023 and reviews to have analyzed the efficacy of neurofeedback and biofeedback, separately, related to the same time interval and topics were selected. The search identified five studies compatible with the objectives of the review, related to several conditions: nicotine addiction, sports performance, Autism Spectrum Disorder (ASD), and Attention Deficit Hyperactivity Disorder (ADHD). The integrated neurofeedback + biofeedback approach has been shown to be effective in improving several aspects of these conditions, such as a reduction in the presence of psychiatric symptoms, anxiety, depression, and withdrawal symptoms and an increase in self-esteem in smokers; improvements in communication, imitation, social/cognitive awareness, and social behavior in ASD subjects; improvements in attention, alertness, and reaction time in sports champions; and improvements in attention and inhibitory control in ADHD subjects. Further research, characterized by greater methodological rigor, is therefore needed to determine the effectiveness of this method and the superiority, if any, of this type of training over the single administration of either. This review іs intended tо serve as a catalyst for future research, signaling promising directions for the advancement оf biofeedback and neurofeedback methodologies.

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.

Cardiac Startle Response and Clinical Outcomes in Preschool Children With Fragile X Syndrome and Autism Spectrum Disorder

Objective: Poor physiological regulation in response to threat is linked to multiple negative developmental outcomes including anxiety, which is highly prevalent and impairing in young children with neurodevelopmental disabilities like fragile X syndrome (FXS) and autism spectrum disorder (ASD). The present study contrasted cardiac startle response in pre-school-aged children with FXS, with and without ASD, to children with non-syndromic ASD (nsASD) and neurotypical controls (NT). The relationship of cardiac startle to non-verbal mental age (NVMA), ASD severity, and parent-reported anxiety was also examined. Method: Four age-matched groups of pre-school children participated including those with FXS without ASD (FXS-Only, n = 21), FXS with ASD (FXS+ASD, n = 17), nsASD (n = 42), and NT children (n = 27). Participants viewed a silent movie during which a single 200 ms 98-decibel white noise burst occurred. Cardiac activity was analyzed for pre-stimulus respiratory sinus arrhythmia (RSA) and the inter-beat intervals (IBI) at the auditory stimulus and 10 s post-stimulus. The Spence Pre-school Anxiety Scale, Autism Diagnostic Observation Schedule-2nd Edition, and Mullen Scales of Early Learning were examined in relation to startle response. Results: The nsASD group demonstrated heightened cardiac activity at the auditory stimulus and 10 s post-stimulus compared to the NT controls. Neither of the FXS groups showed differences from any other group. Higher pre-stimulus RSA was associated with reduced cardiac response across groups, while the relationship between cognitive ability and ASD severity to cardiac response varied between groups. Parent-reported anxiety was not associated with cardiac response for any group. Conclusion: These findings demonstrate group distinctions in cardiac responses to auditory startle. Although FXS and ASD share behavioral characteristics, the nsASD group showed a heightened cardiac startle response compared to the NT group that was not present in the FXS groups with or without ASD. Non-verbal mental age was associated with greater stimulus or post-stimulus reactivity for all groups except the FXS+ASD group, which showed no association between startle response and any clinical outcomes. Increased understanding of the relationship between physiological regulation and clinical outcomes will assist in identifying the timing and targets for effective interventions for individuals with neurodevelopmental disabilities.

Brain computer interface based applications for training and rehabilitation of students with neurodevelopmental disorders. A literature review

The aim of this article is to explore a paradigm shift on Brain Computer Interface (BCI) research, as well as on intervention best practices for training and rehabilitation of students with neurodevelopmental disorders. Recent studies indicate that BCI devices have positive impact on students' attention skills and working memory as well as on other skills, such as visuospatial, social, imaginative and emotional abilities. BCI applications aim to emulate humans' brain and address the appropriate understanding for each student's neurodevelopmental disorders. Studies conducted to provide knowledge about BCI-based intervention applications regarding memory, attention, visuospatial, learning, collaboration, and communication, social, creative and emotional skills are highlighted. Only non-invasive BCI type of applications are being investigated based upon representative, non-exhaustive and state-of-the-art studies within the field. This article examines the progress of BCI research so far, while different BCI paradigms are investigated. BCI-based applications could successfully regulate students' cognitive abilities when used for their training and rehabilitation. Future directions to investigate BCI-based applications for training and rehabilitation of students with neurodevelopmental disorders concerning the different populations involved are discussed.

Facilitating Neurofeedback in Children with Autism and Intellectual Impairments Using TAGteach

Individuals with autism and intellectual impairments tend to be excluded from research due to their difficulties with methodological compliance. This study focuses on using Teaching with Acoustic Guidance-TAGteach-to behaviorally prepare children with autism and a IQ ≤ 80 to participate in a study on neurofeedback training (NFT). Seven children (ages 6-8) learned the prerequisite skills identified in a task analysis in an average of 5 h of TAGteach training, indicating that this is a feasible method of preparing intellectually-impaired children with autism to participate in NFT and task-dependent electroencephalography measures. TAGteach may thus have the potential to augment this population's ability to participate in less accessible treatments and behavioral neuroscientific studies.

Identification of lateralized compensatory neural activities within the social brain due to autism spectrum disorder in adolescent males

Socio-behavioral impairments are important characteristics of autism spectrum disorders (ASD) and MRI-based studies are pursued to identify a neurobiological basis behind these conditions. This paper presents an MRI-based study undertaken to (i) identify the differences in brain activities due to ASD, (ii) verify whether such differences exist within the 'social brain' circuit which is hypothesized to be responsible for social functions, and (iii) uncover potential compensatory mechanisms within the identified differences in brain activities. In this study, a whole-brain voxel-wise analysis is performed using resting-state fMRI data from 598 adolescent males, that is openly available from the ABIDE consortium. A new method is developed, which can (i) extract the discriminative brain activities, that provide high separability between the blood oxygenation time-series signals from ASD and neurotypical populations, (ii) select the activities that are relevant to ASD by evaluating the correlation between the separability and traditional severity scores, and (iii) map the spatial pattern of regions responsible for generating the discriminative activities. The results show that the most discriminative brain activities occur within a subset of the social brain that is involved with affective aspects of social processing, thereby supporting the idea of the social brain and also its fractionalization in ASD. Further, it has also been found that the diminished activities in the posterior cingulate area are potentially compensated by enhanced activities in the ventromedial prefrontal and anterior temporal areas within the social brain. Hemispherical lateralization is also observed on such compensatory activities.

Effectiveness Evaluation of Real-Time Scalp Signal Separating Algorithm on Near-Infrared Spectroscopy Neurofeedback

Near-infrared spectroscopy (NIRS), one of the candidates to be used in a neurofeedback system or brain-computer interface (BCI), measures the brain activity by monitoring the changes in cerebral hemoglobin concentration. However, hemodynamic changes in the scalp may affect the NIRS signals. In order to remove the superficial signals when NIRS is used in a neurofeedback system or BCI, real-time processing is necessary. Real-time scalp signal separating (RT-SSS) algorithm, which is capable of separating the scalp-blood signals from NIRS signals obtained in real-time, may thus be applied. To demonstrate its effectiveness, two separate neurofeedback experiments were conducted. In the first experiment, the feedback signal was the raw NIRS signal recorded while in the second experiment, deep signal extracted using RT-SSS algorithm was used as the feedback signal. In both experiments, participants were instructed to control the feedback signal to follow a predefined track. Accuracy scores were calculated based on the differences between the trace controlled by feedback signal and the targeted track. Overall, the second experiment yielded better performance in terms of accuracy scores. These findings proved that RT-SSS algorithm is beneficial for neurofeedback.

The Human Factors and Ergonomics of P300-Based Brain-Computer Interfaces

Individuals with severe neuromuscular impairments face many challenges in communication and manipulation of the environment. Brain-computer interfaces (BCIs) show promise in presenting real-world applications that can provide such individuals with the means to interact with the world using only brain waves. Although there has been a growing body of research in recent years, much relates only to technology, and not to technology in use-i.e., real-world assistive technology employed by users. This review examined the literature to highlight studies that implicate the human factors and ergonomics (HFE) of P300-based BCIs. We assessed 21 studies on three topics to speak directly to improving the HFE of these systems: (1) alternative signal evocation methods within the oddball paradigm; (2) environmental interventions to improve user performance and satisfaction within the constraints of current BCI systems; and (3) measures and methods of measuring user acceptance. We found that HFE is central to the performance of P300-based BCI systems, although researchers do not often make explicit this connection. Incorporation of measures of user acceptance and rigorous usability evaluations, increased engagement of disabled users as test participants, and greater realism in testing will help progress the advancement of P300-based BCI systems in assistive applications.