Connectivity Theory of Autism: Use of Connectivity Measures in Assessing and Treating Autistic Disorders

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.

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.

EEG Correlates of Cognitive Functions and Neuropsychiatric Disorders: A Review of Oscillatory Activity and Neural Synchrony Abnormalities

Background:

A large body of evidence suggested that disruption of neural rhythms and synchronization of brain oscillations are correlated with a variety of cognitive and perceptual processes. Cognitive deficits are common features of psychiatric disorders that complicate treatment of the motivational, affective and emotional symptoms.

Objective:

Electrophysiological correlates of cognitive functions will contribute to understanding of neural circuits controlling cognition, the causes of their perturbation in psychiatric disorders and developing novel targets for the treatment of cognitive impairments.

Methods:

This review includes a description of brain oscillations in Alzheimer’s disease, bipolar disorder, attention-deficit/hyperactivity disorder, major depression, obsessive compulsive disorders, anxiety disorders, schizophrenia and autism.

Results:

The review clearly shows that the reviewed neuropsychiatric diseases are associated with fundamental changes in both spectral power and coherence of EEG oscillations.

Conclusion:

In this article, we examined the nature of brain oscillations, the association of brain rhythms with cognitive functions and the relationship between EEG oscillations and neuropsychiatric diseases. Accordingly, EEG oscillations can most likely be used as biomarkers in psychiatric disorders.

Increased EEG coherence in long-distance and short-distance connectivity in children with autism spectrum disorders

INTRODUCTION

Autism spectrum disorder (ASD) is a complex and prevalent neurodevelopmental disorder characterized by deficits in social communication and social interaction as well as repetitive behaviors. Alterations in function connectivity are widely recognized in recent electroencephalogram (EEG) studies. However, most studies have not reached consistent conclusions, which could be due to the developmental nature and the heterogeneity of ASD.

METHODS

Here, EEG coherence analysis was used in a cohort of children with ASD (n = 13) and matched typically developing controls (TD, n = 15) to examine the functional connectivity characteristics in long-distance and short-distance electrode pairs. Subsequently, we explore the association between the connectivity strength of coherence and symptom severity in children with ASD.

RESULTS

Compared with TD group, individuals with ASD showed increased coherence in short-distance electrode pairs in the right temporal-parietal region (delta, alpha, beta bands), left temporal-parietal region (all frequency bands), occipital region (theta, alpha, beta bands), right central-parietal region (delta, alpha, beta bands), and the prefrontal region (only beta band). In the long-distance coherence analysis, the ASD group showed increased coherence in bilateral frontal region, temporal region, parietal region, and frontal-occipital region in alpha and beta bands. The strength of such connections was associated with symptom severity.

DISCUSSION

Our study indicates that abnormal connectivity patterns in neuroelectrophysiology may be of critical importance to acknowledge the underlying brain mechanism.

Analysis of EEG Characteristics and Coherence in Patients Diagnosed as Borderline Personality

Borderline personality disorder is a clinically important psychiatric diagnosis that is distinct from major depressive, bipolar and posttraumatic stress disorders, despite the overlapping symptoms. The diagnosis is mainly clinical and must follow the DMS 5 (or ICD 10) characteristics. The most common age at first presentation is in late adolescence, but the disorder frequently can be stay as misdiagnosed. Our study is concerned to QEEG characteristics, as well as coherence in borderline patients compared with healthy group, matched by number, gender and age and selected randomly. Our obtained results showed that electrophysiological characteristics for borderlines are fairly without statistical differences, except in low bands (delta and theta), which showed significantly lower frequencies and coherence compared to a healthy group. Future research in this filed with more patients is highly recommended.

Oscillatory neural networks underlying resting-state, attentional control and social cognition task conditions in children with ASD, ADHD and ASD+ADHD

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are common and impairing neurodevelopmental disorders that frequently co-occur. The neurobiological mechanisms involved in ASD and ADHD are not fully understood. However, alterations in large-scale neural networks have been proposed as core deficits in both ASD and ADHD and may help to disentangle the neurobiological basis of these disorders and their co-occurrence. In this study, we examined similarities and differences in large-scale oscillatory neural networks between boys aged 8-13 years with ASD (n = 19), ADHD (n = 18), ASD + ADHD (n = 29) and typical development (Controls, n = 26). Oscillatory neural networks were computed using graph-theoretical methods from electroencephalographic (EEG) data collected during an eyes-open resting-state and attentional control and social cognition tasks in which we previously reported disorder-specific atypicalities in oscillatory power and event-related potentials (ERPs). We found that children with ASD showed significant hypoconnectivity in large-scale networks during all three task conditions compared to children without ASD. In contrast, children with ADHD showed significant hyperconnectivity in large-scale networks during the attentional control and social cognition tasks, but not during the resting-state, compared to children without ADHD. Children with co-occurring ASD + ADHD did not differ from children with ASD when paired with this group and vice versa when paired with the ADHD group, indicating that these children showed both ASD-like hypoconnectivity and ADHD-like hyperconnectivity. Our findings suggest that ASD and ADHD are associated with distinct alterations in large-scale oscillatory networks, and these atypicalities present together in children with both disorders. These alterations appear to be task-independent in ASD but task-related in ADHD, and may underlie other neurocognitive atypicalities in these disorders.

Assessing the Effectiveness of Neurofeedback Training in the Context of Clinical and Social Neuroscience

Social neuroscience benefits from the experimental manipulation of neuronal activity. One possible manipulation, neurofeedback, is an operant conditioning-based technique in which individuals sense, interact with, and manage their own physiological and mental states. Neurofeedback has been applied to a wide variety of psychiatric illnesses, as well as to treat sub-clinical symptoms, and even to enhance performance in healthy populations. Despite growing interest, there persists a level of distrust and/or bias in the medical and research communities in the USA toward neurofeedback and other functional interventions. As a result, neurofeedback has been largely ignored, or disregarded within social neuroscience. We propose a systematic, empirically-based approach for assessing the effectiveness, and utility of neurofeedback. To that end, we use the term perturbative physiologic plasticity to suggest that biological systems function as an integrated whole that can be perturbed and guided, either directly or indirectly, into different physiological states. When the intention is to normalize the system, e.g., via neurofeedback, we describe it as self-directed neuroplasticity, whose outcome is persistent functional, structural, and behavioral changes. We argue that changes in physiological, neuropsychological, behavioral, interpersonal, and societal functioning following neurofeedback can serve as objective indices and as the metrics necessary for assessing levels of efficacy. In this chapter, we examine the effects of neurofeedback on functional connectivity in a few clinical disorders as case studies for this approach. We believe this broader perspective will open new avenues of investigation, especially within social neuroscience, to further elucidate the mechanisms and effectiveness of these types of interventions, and their relevance to basic research.

How Useful Is Electroencephalography in the Diagnosis of Autism Spectrum Disorders and the Delineation of Subtypes: A Systematic Review

Autism spectrum disorders (ASD) are thought to be associated with abnormal neural connectivity. Presently, neural connectivity is a theoretical construct that cannot be easily measured. Research in network science and time series analysis suggests that neural network structure, a marker of neural activity, can be measured with electroencephalography (EEG). EEG can be quantified by different methods of analysis to potentially detect brain abnormalities. The aim of this review is to examine evidence for the utility of three methods of EEG signal analysis in the ASD diagnosis and subtype delineation. We conducted a review of literature in which 40 studies were identified and classified according to the principal method of EEG analysis in three categories: functional connectivity analysis, spectral power analysis, and information dynamics. All studies identified significant differences between ASD patients and non-ASD subjects. However, due to high heterogeneity in the results, generalizations could not be inferred and none of the methods alone are currently useful as a new diagnostic tool. The lack of studies prevented the analysis of these methods as tools for ASD subtypes delineation. These results confirm EEG abnormalities in ASD, but as yet not sufficient to help in the diagnosis. Future research with larger samples and more robust study designs could allow for higher sensitivity and consistency in characterizing ASD, paving the way for developing new means of diagnosis.

Altered Structural and Functional Connectivity in Late Preterm Preadolescence: An Anatomic Seed-Based Study of Resting State Networks Related to the Posteromedial and Lateral Parietal Cortex

OBJECTIVE

Late preterm birth confers increased risk of developmental delay, academic difficulties and social deficits. The late third trimester may represent a critical period of development of neural networks including the default mode network (DMN), which is essential to normal cognition. Our objective is to identify functional and structural connectivity differences in the posteromedial cortex related to late preterm birth.

METHODS

Thirty-eight preadolescents (ages 9-13; 19 born in the late preterm period (≥32 weeks gestational age) and 19 at term) without access to advanced neonatal care were recruited from a low socioeconomic status community in Brazil. Participants underwent neurocognitive testing, 3-dimensional T1-weighted imaging, diffusion-weighted imaging and resting state functional MRI (RS-fMRI). Seed-based probabilistic diffusion tractography and RS-fMRI analyses were performed using unilateral seeds within the posterior DMN (posterior cingulate cortex, precuneus) and lateral parietal DMN (superior marginal and angular gyri).

RESULTS

Late preterm children demonstrated increased functional connectivity within the posterior default mode networks and increased anti-correlation with the central-executive network when seeded from the posteromedial cortex (PMC). Key differences were demonstrated between PMC components with increased anti-correlation with the salience network seen only with posterior cingulate cortex seeding but not with precuneus seeding. Probabilistic tractography showed increased streamlines within the right inferior longitudinal fasciculus and inferior fronto-occipital fasciculus within late preterm children while decreased intrahemispheric streamlines were also observed. No significant differences in neurocognitive testing were demonstrated between groups.

CONCLUSION

Late preterm preadolescence is associated with altered functional connectivity from the PMC and lateral parietal cortex to known distributed functional cortical networks despite no significant executive neurocognitive differences. Selective increased structural connectivity was observed in the setting of decreased posterior interhemispheric connections. Future work is needed to determine if these findings represent a compensatory adaptation employing alternate neural circuitry or could reflect subtle pathology resulting in emotional processing deficits not seen with neurocognitive testing.

Enhanced cortical connectivity in absolute pitch musicians: a model for local hyperconnectivity

Connectivity in the human brain has received increased scientific interest in recent years. Although connection disorders can affect perception, production, learning, and memory, few studies have associated brain connectivity with graded variations in human behavior, especially among normal individuals. One group of normal individuals who possess unique characteristics in both behavior and brain structure is absolute pitch (AP) musicians, who can name the appropriate pitch class of any given tone without a reference. Using diffusion tensor imaging and tractography, we observed hyperconnectivity in bilateral superior temporal lobe structures linked to AP possession. Furthermore, volume of tracts connecting left superior temporal gyrus to left middle temporal gyrus predicted AP performance. These findings extend previous reports of exaggerated temporal lobe asymmetry, may explain the higher incidence of AP in special populations, and may provide a model for understanding the heightened connectivity that is thought to underlie savant skills and cases of exceptional creativity.

Neurofeedback for autistic spectrum disorder: a review of the literature

There is a need for effective interventions to address the core symptoms and problems associated with autistic spectrum disorder (ASD). Behavior therapy improves communication and behavioral functioning. Additional treatment options include psychopharmacological and biomedical interventions. Although these approaches help children with autistic problems, they may be associated with side effects, risks or require ongoing or long-term treatment. Neurofeedback is a noninvasive approach shown to enhance neuroregulation and metabolic function in ASD. We present a review of the literature on the application of Neurofeedback to the multiple problems associated with ASD. Directions for future research are discussed.