Autism spectrum disorder (ASD)
Research Papers
Showing 6 of 22Individual brain regulation as learned via neurofeedback is related to affective changes in adolescents with autism spectrum disorder
Abstract Background Emotions often play a role in neurofeedback (NF) regulation strategies. However, investigations of the relationship between the induced neuronal changes and improvements in affective domains are scarce in electroencephalography-based studies. Thus, we extended the findings of the first study on slow cortical potential (SCP) NF in autism spectrum disorder (ASD) by linking affective changes to whole-brain activity during rest and regulation. Methods Forty-one male adolescents with ASD were scanned twice at rest using functional magnetic resonance imaging. Between scans, half underwent NF training, whereas the other half received treatment as usual. Furthermore, parents reported on their child’s affective characteristics at each measurement. The NF group had to alternatingly produce negative and positive SCP shifts during training and was additionally scanned using functional magnetic resonance imaging while applying their developed regulation strategies. Results No significant treatment group-by-time interactions in affective or resting-state measures were found. However, we found increases of resting activity in the anterior cingulate cortex and right inferior temporal gyrus as well as improvements in affective characteristics over both groups. Activation corresponding to SCP differentiation in these regions correlated with the affective improvements. A further correlation was found for Rolandic operculum activation corresponding to positive SCP shifts. There were no significant correlations with the respective achieved SCP regulation during NF training. Conclusion SCP NF in ASD did not lead to superior improvements in neuronal or affective functioning compared to treatment as usual. However, the affective changes might be related to the individual strategies and their corresponding activation patterns as indicated by significant correlations on the whole-brain level. Trial registration This clinical trial was registered at drks.de (DRKS00012339) on 20th April, 2017.
View Full Paper →Characterizing the ASD–ADHD phenotype: measurement structure and invariance in a clinical sample
Background: Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) have considerable overlap, supporting the need for a dimensional framework that examines neurodevelopmental domains which cross traditional diagnostic boundaries. In the following study, we use factor analysis to deconstruct the ASD–ADHD phenotype into its underlying phenotypic domains and test for measurement invariance across adaptive functioning, age, gender and ASD/ADHD clinical diagnoses. Methods: Participants included children and youth (aged 3–20 years) with a clinical diagnosis of ASD (n = 727) or ADHD (n = 770) for a total of 1,497 participants. Parents of these children completed the Social Communication Questionnaire (SCQ), a measure of autism symptoms, and the Strengths and Weaknesses of ADHD and Normal Behaviour (SWAN) questionnaire, a measure of ADHD symptoms. An exploratory factor analysis (EFA) was performed on combined SCQ and SWAN items. This was followed by a confirmatory factor analysis (CFA) and tests of measurement invariance. Results: EFA revealed a four-factor solution (inattention, hyperactivity/impulsivity, social-communication, and restricted, repetitive, behaviours and interests (RRBI)) and a CFA confirmed good model fit. This solution also showed good model fit across subgroups of interest. Conclusions: Our study shows that a combined ASD–ADHD phenotype is characterized by two latent ASD domains (social communication and RRBIs) and two latent ADHD domains (inattention and hyperactivity/impulsivity). We established measurement invariance of the derived measurement model across adaptive functioning, age, gender and ASD/ADHD diagnoses
View Full Paper →Effectivity of ILF Neurofeedback on Autism Spectrum Disorder—A Case Study
Autism spectrum disorder (ASD) is a neural and mental developmental disorder that impacts brain connectivity and information processing. Although application of the infra-low frequency (ILF) neurofeedback procedure has been shown to lead to significant changes in functional connectivity in multiple areas and neuronal networks of the brain, rather limited data are available in the literature for the efficacy of this technique in a therapeutic context to treat ASD. Here we present the case study of a 5-year-old boy with ASD, who received a treatment of 26 sessions of ILF neurofeedback over a 6-month period. A systematic and quantitative tracking of core ASD symptoms in several categories was used to document behavioral changes over time. The ILF neurofeedback intervention decreased the average symptom severity of every category to a remarkable degree, with the strongest effect (80 and 77% mean severity reduction) for physical and sleep symptoms and the lowest influence on behavioral symptoms (15% mean severity reduction). This case study is representative of clinical experience, and thus shows that ILF neurofeedback is a practical and effective therapeutic instrument to treat ASD in children.
View Full Paper →Impulsivity Moderates the Effect of Neurofeedback Training on the Contingent Negative Variation in Autism Spectrum Disorder
Background The contingent negative variation (CNV) is a well-studied indicator of attention- and expectancy-related processes in the human brain. An abnormal CNV amplitude has been found in diverse neurodevelopmental psychiatric disorders. However, its role as a potential biomarker of successful clinical interventions in autism spectrum disorder (ASD) remains unclear. Methods In this randomized controlled trial, we investigated how the CNV changes following an intensive neurofeedback training. Therefore, twenty-one adolescents with ASD underwent 24 sessions of slow cortical potential (SCP) neurofeedback training. Twenty additional adolescents with ASD formed a control group and received treatment as usual. CNV waveforms were obtained from a continuous performance test (CPT), which all adolescents performed before and after the corresponding 3-month long training period. In order to utilize all available neural time series, trial-based area under the curve values for all four electroencephalogram (EEG) channels were analyzed with a hierarchical Bayesian model. In addition, the model included impulsivity, inattention, and hyperactivity as potential moderators of change in CNV. Results Our model implies that impulsivity moderates the effects of neurofeedback training on CNV depending on group. In the control group, the average CNV amplitude decreased or did not change after treatment as usual. In the experimental group, the CNV changed depending on the severity of comorbid impulsivity symptoms. The average CNV amplitude of participants with low impulsivity scores decreased markedly, whereas the average CNV amplitude of participants with high impulsivity increased. Conclusion The degree of impulsivity seems to play a crucial role in the changeability of the CNV following an intensive neurofeedback training. Therefore, comorbid symptomatology should be recorded and analyzed in future EEG-based brain training interventions. Clinical Trial Registration https://www.drks.de , identifier DRKS00012339.
View Full Paper →Alpha oscillatory activity during attentional control in children with Autism Spectrum Disorder (ASD), Attention‐Deficit/Hyperactivity Disorder (ADHD), and ASD+ADHD
Background: Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) share impairments in top-down and bottom-up modulation of attention. However, it is not yet well understood if co-occurrence of ASD and ADHD reflects a distinct or additive profile of attention deficits. We aimed to characterise alpha oscillatory activity (stimulus-locked alpha desynchronisation and prestimulus alpha) as an index of integration of top-down and bottom-up attentional processes in ASD and ADHD. Methods: Children with ASD, ADHD, comorbid ASD+ADHD, and typically-developing children completed a fixed-choice reaction-time task (‘Fast task’) while neurophysiological activity was recorded. Outcome measures were derived from source-decomposed neurophysiological data. Main measures of interest were prestimulus alpha power and alpha desynchronisation (difference between poststimulus and prestimulus alpha). Poststimulus activity linked to attention allocation (P1, P3), attentional control (N2), and cognitive control (theta synchronisation, 100–600 ms) was also examined. ANOVA was used to test differences across diagnostics groups on these measures. Spearman’s correlations were used to investigate the relationship between attentional control processes (alpha oscillations), central executive functions (theta synchronisation), early visual processing (P1), and behavioural performance. Results: Children with ADHD (ADHD and ASD+ADHD) showed attenuated alpha desynchronisation, indicating poor integration of top-down and bottom-up attentional processes. Children with ADHD showed reduced N2 and P3 amplitudes, while children with ASD (ASD and ASD+ADHD) showed greater N2 amplitude, indicating atypical attentional control and attention allocation across ASD and ADHD. In the ASD group, prestimulus alpha and theta synchronisation were negatively correlated, and alpha desynchronisation and theta synchronisation were positively correlated, suggesting an atypical association between attentional control processes and executive functions. Conclusions: ASD and ADHD are associated with disorder-specific impairments, while children with ASD+ADHD overall presented an additive profile with attentional deficits of both disorders. Importantly, these findings may inform the improvement of transdiagnostic procedures and optimisation of personalised intervention approaches. Keywords: Autism Spectrum Disorder; ADHD; attention; comorbidity.
View Full Paper →Neurofeedback Training for Social Cognitive Deficits: A Systematic Review
<p><strong>Orndorff and his colleagues [1]</strong> suggested that if a neural activity is considered a treatment variable instead of outcome, it widens the scope of research and has a specific implication for social neuroscience. Given this, the empirical evidence is collected and analyzed where neural activity as self-manipulation design through neurofeedback training specifically for social cognition deficit is done. The objective of the present article is to provide a systematic review of 1) how NFT is utilized to treat social cognitive deficits, 2) how NFT is utilized to target Social Cognition Deficit in ASD, 3) examining the directions, strengths, and quality of evidence to support the use of NFT for ASD. The databases for studies were searched in PubMed, MEDLINE, EMBASE, Springer, Science Direct, Psychinfo, and Google Scholar, using combinations of the following keywords: ‘Neurofeedback,’ ‘Autism Spectrum Disorder,’ ‘Mu Rhythm’ and ‘Social Cognition.’ Studies were eligible for inclusion if they were specific to 1) autistic and typically developed population, 2) intervention study, 3) Delivered by NFT, 4) participants showed social cognitive deficit and/or improvement. Total one eighty-seven studies were found of key interest; out of which 17 studies were eligible for inclusion in this review. All studies reported the improvement in different domains of social cognition and were moderately methodologically sound. Eleven out of seventeen studies satisfied the trainability and interpretability criteria suggested by <strong>Zoefel and his colleagues [2].</strong> The conclusion from the present review is in line with comments of <strong>Marzbani and colleagues [3]</strong> that, ‘current research does not provide sufficient conclusive results about its efficacy.’ The patterns and directions concluded from studies related to protocol, methodology and results are discussed in detail in the present review.</p>
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