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QEEG-Guided Neurofeedback for Autism: Clinical Observations and Outcomes

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Abstract

During the 40-plus-year history of EEG biofeedback, now also called neurofeedback (NF), the approach has been used clinically to address attentional problems in attention deficit-hyperactivity disorder (ADHD). Initially, NF was based on the theta/beta ratio, which was measured with eyes open, at the vertex, or the Cz electrode in the International 10–20 Electrode placement system. Generally, the early NF work was based on enhancing beta and reducing the slower theta content (Monastra et al. 1999).
... Current resting EEG research in the ASD population suggests that children, adolescents and adults with ASD generally demonstrate increased power at low frequency (delta, theta) and high frequency bands (beta, gamma), but decreased power at the middle frequency band (alpha), as opposed to the typically developing 'control' participants (i.e. people without any neurodevelopmental disorders such as ASD), who demonstrate the opposite pattern (Murias et al., 2007;Coben et al., 2008;Linden and Gunkelman, 2013;Wang et al., 2013;Elhabashy et al., 2015). These abnormalities in the ASD population have been found primarily in the frontal and temporal cortical regions (Linden and Gunkelman, 2013;Wang et al., 2013). ...
... people without any neurodevelopmental disorders such as ASD), who demonstrate the opposite pattern (Murias et al., 2007;Coben et al., 2008;Linden and Gunkelman, 2013;Wang et al., 2013;Elhabashy et al., 2015). These abnormalities in the ASD population have been found primarily in the frontal and temporal cortical regions (Linden and Gunkelman, 2013;Wang et al., 2013). Additionally, the participants' mu rhythm activity (mu is the part of alpha frequency ranging from 8 to 13 Hz, which is generated from the sensorimotor cortex, and typically in the 8-10 Hz range) is also altered, with mu suppression present in the frontal and central regions (Linden and Gunkelman, 2013). ...
... These abnormalities in the ASD population have been found primarily in the frontal and temporal cortical regions (Linden and Gunkelman, 2013;Wang et al., 2013). Additionally, the participants' mu rhythm activity (mu is the part of alpha frequency ranging from 8 to 13 Hz, which is generated from the sensorimotor cortex, and typically in the 8-10 Hz range) is also altered, with mu suppression present in the frontal and central regions (Linden and Gunkelman, 2013). However, some studies have shown contradictory findings. ...
Article
Autism spectrum disorder (ASD) is a neurodevelopmental condition affecting about 1 in 100 children and is currently incurable. ASD represents a challenge to traditional methods of assessment and diagnosis, and it has been suggested that direct measures of brain activity and connectivity between brain regions during demanding tasks represents a potential pathway to building more accurate models of underlying brain function and ASD. One of the key behavioural diagnostic indicators of ASD consists of sensory features (SF), often characterised by over- or under-reactivity to environmental stimuli. SF are associated with behavioural difficulties that impede social and education success in these children as well as anxiety and depression. This review examines the previous literature on the measurement of EEG connectivity and SF observed in individuals with ASD.
... Several papers reviewed application of neurofeedback for ASD treatment and many of them provide evidence that some of the core symptoms of autism can be improved by using neurofeedback training (Coben, 2013;Jarusiewicz, 2002;Kouijzer et al., 2009Kouijzer et al., , 2013Linden & Gunkelman, 2013;Wang et al., 2016). Most of them used suppression of theta at P R O O F x fronto-central or central sites, enhancement of low beta (13-21 Hz, sometimes 13-18 Hz) sub-band, or enhancement of sensory-motor rhythm (SMR,(12)(13)(14)(15) at the central sites (C3,Cz,C4). ...
... Another line of treatment based on neurofeedback focuses on mu-rhythm training (Pineda et al., 2014). Some protocols use quantitative EEG-guided and coherence measures (Coben, 2013;Linden & Gunkelman, 2013). Our group's approach included neurofeedback training at the prefrontal topography, specifically at the midline prefrontal site. ...
... Several potential approaches for neurofeedback treatment have been examined in the literature with varying evidence, including 1) sensorimotor rhythm (SMR) and theta to beta ratio (TBR) training ( Kouijzer, de Moor, Gerrits, Congedo, van Schie,, 2009a;Kouijzer, de Moor, Gerrits, Buitelaar, & van Schie, 2009b;Kouijzer, van Schie, Gerrits, Buitelaar, & de Moor, 2013;Sichel, Fehmi, & Goldstein, 1995), 2) QEEG guided neurofeedback (Coben, 2013;Coben & Padolsky, 2007;Coben et al., 2014;Linden & Gunkelman, 2013), 3) mirror neuron (mu) activity (Datko, Pineda, & Müller, 2018;Friedrich et al., 2014Friedrich et al., , 2015Pineda et al., 2008Pineda et al., , 2014b, 4) connectivity-guided coherence neurofeedback (Coben & Padolsky, 2007;Coben et al., 2014), and 5) upregulation of gamma activity along with inhibition of high amplitude and low frequency rhythms (Wang, Y. et al., 2016) and the combination of transcranial magnetic stimulation (TMS) and neurofeedback to address gamma oscillations . ...
... The clinical efficacy of using NFB for ADHD treatments was supported by several meta-analyses of randomized clinical trials recently conducted (Lubar, 2003(Lubar, , 2004Arns et al., 2009;Gevensleben et al., 2009;Sokhadze et al., 2009;Lofthouse et al., 2010). Since many autistic children also show signs of attention-deficit and hyperactivity some attempts have been made to use this technique as a treatment modality for ASD (Linden et al., 1996;Coben and Padolsky, 2007;Coben, 2008Coben, , 2013Kouijzer et al., 2009aKouijzer et al., ,b, 2010Sherlin et al., 2010;Thompson et al., 2010a,b;Linden and Gunkelman, 2013). Several current papers review the use of neurofeedback for ASD treatment and many of them provide evidence that some of the core symptoms of autism can be improved this way (Jarusiewicz, 2002;Coben and Padolsky, 2007;Coben, 2008Coben, , 2013Kouijzer et al., 2009a,b;Sokhadze et al., 2014). ...
... There were several case, pilot and group studies (Sichel et al., 1995;Jarusiewicz, 2002) followed by controlled group studies (Coben and Padolsky, 2007;Kouijzer et al., 2009a,b;. More detailed accounts summarizing behavioral, cognitive, and neurophysiological data can be found in current reviews (Thompson et al., 2010a,b;Coben, 2013;Linden and Gunkelman, 2013). Among controlled studies should be specifically mentioned quantitative EEG (qEEG) and connectivity analysis guided studies conducted by Coben and his associate (Coben and Padolsky, 2007;Coben, 2013). ...
... QEEG based assessment of functional connectivity is proposed to guide neurofeedback intervention in autism. Some researchers use qEEG-based subtypes or so called endophenotypes to guide neurofeedback in ASD (Linden and Gunkelman, 2013). These techniques use individualized approaches to selection of neurofeedback-based treatment in autism. ...
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Neurofeedback is a mode of treatment that is potentially useful for improving self-regulation skills in persons with autism spectrum disorder. We proposed that operant conditioning of EEG in neurofeedback mode can be accompanied by changes in the relative power of EEG bands. However, the details on the change of the relative power of EEG bands during neurofeedback training course in autism are not yet well explored. In this study, we analyzed the EEG recordings of children diagnosed with autism and enrolled in a prefrontal neurofeedback treatment course. The protocol used in this training was aimed at increasing the ability to focus attention, and the procedure represented the wide band EEG amplitude suppression training along with upregulation of the relative power of gamma activity. Quantitative EEG analysis was completed for each session of neurofeedback using wavelet transform to determine the relative power of gamma and theta/beta ratio, and further to detect the statistical changes within and between sessions. We found a linear decrease of theta/beta ratio and a liner increase of relative power of gamma activity over 18 weekly sessions of neurofeedback in 18 high functioning children with autism. The study indicates that neurofeedback is an effective method for altering EEG characteristics associated with the autism spectrum disorder. Also, it provides information about specific changes of EEG activities and details the correlation between changes of EEG and neurofeedback indexes during the course of neurofeedback. This pilot study contributes to the development of more effective approaches to EEG data analysis during prefrontal neurofeedback training in autism. Key word: Electroencephalography, Neurofeedback, Autism Spectrum Disorder, Gamma activity, EEG bands’ ratios
... According to Arns et al. (2014), evaluation of neurofeedback for ADHD has gone through a long and winding road but still has to travel further in order to cover all grounds related to clinical effectivity and specificity. More details about specific protocols used in ASD can be found in several published studies on neurofeedback training in autism (Coben 2008(Coben , 2013Coben et al. , 2014Datko et al. 2017;Friedrich et al. 2014Friedrich et al. , 2015Kouijzer et al. 2009aKouijzer et al. , b, 2010Linden and Gunkelman 2013;Pineda et al. 2012Pineda et al. , 2014aSokhadze et al. 2014;Thompson and Thompson 2013;Wang et al. 2016;Zivoder et al. 2015). ...
... It is necessary that for the evaluation of efficacy and specificity of NFB in autism, strict methodological standards should be adhered in the study design along with scientific rationale for the selection of the targets of EEG self-regulation. Several reviews and metastudies (Coben 2013;Hurt et al. 2014;Linden and Gunkelman 2013;Pineda et al. 2014a, b) have demonstrated the potential efficacy of NFB training with regard to the improvement of ASD symptoms. Whether NFB is efficacious and, at the same time, specific in neurotherapy of autism with comorbid ADHD still needs further investigation and rigorous research, which should go beyond analyzing pre-post changes and must include analyses of the dynamic of targeted EEG indexes and monitor EEG and autonomic parameters during the process of EEG self-regulation skill acquisition. ...
Chapter
Neurofeedback training is a treatment modality of potential use for improving self-regulation skills in autism spectrum disorder (ASD). Multiple studies using neurofeedback to target symptoms of ASD have been reported. These studies differ among themselves in the type of training (e.g., theta-to-beta ratio, coherence, etc.), topography (Cz or Pz), guidance by quantitative EEG (qEEG), and number of sessions (e.g., 20 vs. 30, etc.). In our study, we proposed that prefrontal neurofeedback training would be accompanied by changes in relative power of EEG bands (e.g., 40 Hz-centered gamma band) and ratios of individual bands (e.g., theta-to-beta ratio) and changes in autonomic activity. Outcome measures included EEG, autonomic measures (heart rate, heart rate variability [HRV] indexes, respiration rate, and skin conductance level [SCL]), and behavioral ratings by parents/caregivers. In this pilot feasibility study on 14 children with ASD with comorbid ADHD (~10.28 years SD = 1.93, 3 females), we administered a 24 session-long course of neurofeedback from the AFz site. The protocol used training for wide-band EEG amplitude suppression (“InhibitAll”) with simultaneous upregulation of the index of 40 Hz-centered gamma activity. Quantitative EEG (QEEG) analysis at the prefrontal training site was completed for each session of neurofeedback in order to determine the amplitude of the individual bands (delta, theta, alpha, beta, and gamma), the ratio of the EEG bands of interest (e.g., theta-to-beta ratio [TBR]), and relative power of 40 Hz-centered gamma across neurofeedback sessions. In this study, we analyzed Aberrant Behavior Checklist (ABC), Social Responsiveness Scale (SRS-2), and Achenbach’s ASEBA ratings by caregivers (pre- and posttreatment). We found a significant reduction in Irritability and Hyperactivity subscales of the ABC, decrease of T-score on SRS-2, and decrease in Attention Deficit scores of the ASEBA posttreatment. Successful neurofeedback sessions were featured by the changes in SCL, decreased HR, increased HRV (reflected in decreased LF/HF ratio of HRV and increased RMSSD of HRV), and decreased respiration rate. Profiles of psychophysiological changes during individual sessions and across the whole course of neurofeedback training showed active engagement of participants during training process, resulting in gradual decrease of anxiety markers across the whole course of experimental intervention using prefrontal neurofeedback training. Future research is needed to assess QEEG changes in other topographies using brain mapping, more prolonged courses, and other outcome measures including clinical behavioral evaluations to judge the clinical utility of prefrontal neurofeedback in children with ASD with co-occurring ADHD. The current series support a need to address various factors affecting outcome of neurofeedback-based intervention, specifically the question of length of treatment.
... According to Arns et al. (2014), evaluation of neurofeedback for ADHD has gone through a long and winding road but still has to travel further in order to cover all grounds related to clinical effectivity and specificity. More details about specific protocols used in ASD can be found in several published studies on neurofeedback training in autism (Coben 2008(Coben , 2013Coben et al. , 2014Datko et al. 2017;Friedrich et al. 2014Friedrich et al. , 2015Kouijzer et al. 2009aKouijzer et al. , b, 2010Linden and Gunkelman 2013;Pineda et al. 2012Pineda et al. , 2014aSokhadze et al. 2014;Thompson and Thompson 2013;Wang et al. 2016;Zivoder et al. 2015). ...
... It is necessary that for the evaluation of efficacy and specificity of NFB in autism, strict methodological standards should be adhered in the study design along with scientific rationale for the selection of the targets of EEG self-regulation. Several reviews and metastudies (Coben 2013;Hurt et al. 2014;Linden and Gunkelman 2013;Pineda et al. 2014a, b) have demonstrated the potential efficacy of NFB training with regard to the improvement of ASD symptoms. Whether NFB is efficacious and, at the same time, specific in neurotherapy of autism with comorbid ADHD still needs further investigation and rigorous research, which should go beyond analyzing pre-post changes and must include analyses of the dynamic of targeted EEG indexes and monitor EEG and autonomic parameters during the process of EEG self-regulation skill acquisition. ...
Chapter
Neuropathological studies in autism spectrum disorder (ASD) suggest the presence of a neuronal migrational disorder that alters the excitatory–inhibitory bias of the cerebral cortex. More specifically, in ASD, there appears to be widespread loss of parvalbumin (PV)-positive interneurons manifested as abnormalities in gamma oscillations (neural network instabilities), epileptogenesis, and impaired cognitive functions. Transcranial magnetic stimulation (TMS) is one of the first treatment to target this putative core pathological feature of ASD. Studies show that low-frequency TMS over the dorsolateral prefrontal cortex (DLPC) of individuals with ASD decreases the power of gamma activity while improving both executive function skills related to self-monitoring behaviors as well as the ability to apply corrective actions. Studies from our group have also shown that low-frequency TMS in ASD provides a reduction of stimulus-bound behaviors and diminished sympathetic arousal. Results become more significant with an increasing number of sessions and bear synergism when used along with neurofeedback.
... The relevant ASD literature using EEG to measure power spectra and connectivity under resting or task-based experimental conditions has reported abnormalities mainly within and between Frontal, Temporal, and Occipital brain regions (Linden & Gunkelman, 2013;O'Reilly et al., 2017;Simon et al., 2017;Wang et al., 2013). In particular, research measuring event-related potentials (ERP) and power spectra to identify sensory features (SF) in autistic children and adolescents has found impairments primarily in Frontal and Temporal regions (Baum et al., 2015;Jeste & Nelson, 2009;Linden & Gunkelman, 2013;Marco et al., 2011). ...
... The relevant ASD literature using EEG to measure power spectra and connectivity under resting or task-based experimental conditions has reported abnormalities mainly within and between Frontal, Temporal, and Occipital brain regions (Linden & Gunkelman, 2013;O'Reilly et al., 2017;Simon et al., 2017;Wang et al., 2013). In particular, research measuring event-related potentials (ERP) and power spectra to identify sensory features (SF) in autistic children and adolescents has found impairments primarily in Frontal and Temporal regions (Baum et al., 2015;Jeste & Nelson, 2009;Linden & Gunkelman, 2013;Marco et al., 2011). ...
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Several lines of research suggest that autism is a neurological phenomenon, but the precise associations between neurological activity and the key diagnostic symptoms of autism are yet to be completely clarified. This study examined EEG connectivity and Sensory Features (SF) in a sample of young autistic males by examining bi-directional neural connectivity between separate brain regions as the key potential correlate of SF. Forty male autistic participants aged between 6 and 17 years, with an IQ of at least 70, underwent EEG measurements of their Frontal, Occipital and Temporal region responses to low-, medium-, and high-intensity audiovisual stimulus conditions. EEG connectivity data were analysed via Granger Causality. SF was measured via parent responses about their sons on the Child Sensory Profile (2nd ed.) (CSP-2). There were significant (p < .05) correlations between right hemisphere Frontal and Temporal connectivity and CSP-2 dominant scores, largely due to lower Temporal-to-Frontal than Frontal-to-Temporal connectivity. There were no significant correlations between general CSP-2 scores and EEG connectivity data collected during audiovisual stimuli. These results confirm and extend previous findings by adding bi-directional connectivity as an index of brain activity to other studies that used only uni-directional connectivity data when measuring SF. Although there may be a discrepancy between the kinds of information collected via instruments such as the CSP-2 and actual brain electrical connectivity across major regions, these results hold implications for the use of brain-training interventions with autistic boys.
... The avatars addressing the users in the VR world were demonstrated to look like the participants and were driven by standard QWERTY keyboard. All participants were trained with 10 sessions of VR training and showed slight enhancements yet upgrades were seen in all the targeted skills sets and the vast majority of the scenarios [113]. ...
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This article presents a broad writing survey of innovation based intervention systems for individuals confronting autism spectrum disorder (ASD). Investigated approaches include, "computer vision assisted technologies(CVAT), contemporary computer aided systems(CAS), and visual reality (VR) or artificial intelligence (AI)-assisted interventions ". The research over the previous decade has provided enough showings that individuals with ASD have a strong interest in innovation based interventions, which are valuable in both, clinical settings just as at home and classrooms. Regardless of showing extraordinary guarantee, research in fostering a trend setting innovation based intervention that is clinically quantitative for ASD is minimal. Also, the clinicians are not persuaded about the capability of the technology based interventions because of non-observational nature of distributed outcomes. A significant explanation for this absence of agreeableness is that a greater part of studies on distinct intervention methodologies don't observe a particular guideline or research design. We concluded from our findings that there stays a gap between the research community of computer science, psychology and neuroscience to foster an AI assisted technology for individuals experiencing ASD. Following the improvement of a standardized AI assisted interventional technology, a data base should be developed, to devise effective AI algorithms.
... NFB treatment is considered one of the successful and salient ways of treatment for attention deficit/hyperactive children (ADHD) (Lofthouse et al. 2010). Given that many children with autism may represent with symptoms and signs of ADHD, studies had attempted to use this new therapy as a treatment multimodality for ASD (Coben 2013;Kouijzer et al. 2010;Linden and Gunkelman 2013). ...
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Background Neurofeedback (NFB) has been conceded as a convenient measure for both identifying and remodeling neural pliability of brain cells; it is a mean through which participants can have voluntary control on their brain waves being expressed on the EEG. Forty-two autistic children received a NFB therapy aiming at improving their cognitive abilities. Results NFB succeeded to decrease children’s high theta/beta ratio by inhibiting theta activity and intensifying beta activity over different sessions. Following therapy, the children’s cognitive functions were found to show comparative improvement compared to pre-treatment assessment on a range of different tasks. Auxiliary improvements were found in their social, thought and attention domains. Conclusion These findings propose a basic cognitive function impairment in autism spectrum disorder that can be reduced through specific NFB treatment.
... Resting-state QEEG has been proven to be highly reliable and reproducible (Salinsky et al., 1991;Burgess and Gruzelier, 1993;Corsi-Cabrera et al., 1997;Hughes and John, 1999;Thatcher and Lubar, 2009). In many developmental disorders including ADHD (Clarke et al., , 2001aMonastra et al., 1999Monastra et al., , 2001; see Barry et al., 2003 for a review;Arns et al., 2008), dyslexia (Duffy et al., 1980;Arns et al., 2007), or autism (Pop-Jordanova et al., 2010Linden and Gunkelman, 2013 for a review) different abnormal bioelectrical activity patterns have been reported. These outcomes indicate that QEEG may be an adequate tool for investigating EEG activity, specific to a core auditory deficit in children with listening difficulties. ...
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In this study, we showed an abnormal resting-state quantitative electroencephalogram (QEEG) pattern in children with central auditory processing disorder (CAPD). Twenty-seven children (16 male, 11 female; mean age = 10.7 years) with CAPD and no symptoms of other developmental disorders, as well as 23 age- and sex-matched, typically developing children (TDC, 11 male, 13 female; mean age = 11.8 years) underwent examination of central auditory processes (CAPs) and QEEG evaluation consisting of two randomly presented blocks of “Eyes Open” (EO) or “Eyes Closed” (EC) recordings. Significant correlations between individual frequency band powers and CAP tests performance were found. The QEEG studies revealed that in CAPD relative to TDC there was no effect of decreased delta absolute power (1.5–4 Hz) in EO compared to the EC condition. Furthermore, children with CAPD showed increased theta power (4–8 Hz) in the frontal area, a tendency toward elevated theta power in EO block, and reduced low-frequency beta power (12–15 Hz) in the bilateral occipital and the left temporo-occipital regions for both EO and EC conditions. Decreased middle-frequency beta power (15–18 Hz) in children with CAPD was observed only in the EC block. The findings of the present study suggest that QEEG could be an adequate tool to discriminate children with CAPD from normally developing children. Correlation analysis shows relationship between the individual EEG resting frequency bands and the CAPs. Increased power of slow waves and decreased power of fast rhythms could indicate abnormal functioning (hypoarousal of the cortex and/or an immaturity) of brain areas not specialized in auditory information processing.
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While much knowledge has been gained by the endeavor to link specific brain sites with specific cognitive functions, modern conceptualizations of brain activity focus much more on the function of networks of brain regions. A key construct in defining these networks has been the study of connectivity across regions. In this review, we discuss several methods of measuring connectivity and focus primarily on the utility of electroencephalographic (EEG) coherence. While over- and under-connectivity have been related to numerous clinical phenomena, we focus our discussion on the role of connectivity in reading and language disorders, and present a Neurocognitive Connectivity (NCC) framework for understanding these disorders. We argue that EEG coherence presents a unique target for treatment of these and other populations, in that the ability to modulate connectivity via EEG neurofeedback has been shown to be of significant clinical utility.
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Seven autistic children diagnosed with autism spectrum disorders (ASD) received a neurofeedback treatment that aimed to improve their level of executive control. Neurofeedback successfully reduced children's heightened theta/beta ratio by inhibiting theta activation and enhancing beta activation over sessions. Following treatment, children's executive capacities were found to have improved greatly relative to pre-treatment assessment on a range of executive function tasks. Additional improvements were found in children's social, communicative and typical behavior, relative to a waiting list control group. These findings suggest a basic executive function impairment in ASD that can be alleviated through specific neurofeedback treatment. Possible neural mechanisms that may underlie neurofeedback mediated improvement in executive functioning in autistic children are discussed.
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Article
Two electrophysiological studies tested the hypothesis that operant conditioning of mu rhythms via neurofeedback training can renormalize mu suppression, an index of mirror neuron activity, and improve behavior in children diagnosed with autism spectrum disorders (ASD). In Study 1, eight high-functioning ASD participants were assigned to placebo or experimental groups before 10 weeks of training of the mu frequency band (8–13 Hz). Following training, experimental participants showed decreased mu power and coherence, increased sustained attention ability, and improved scores on subscales of the ATEC compared to the placebo group. Both groups showed improvement in imitation ability. In Study 2, 19 high-functioning ASD children underwent a similar procedure with verified diagnoses, a modified double-blind protocol, and training of the high mu band (10–13 Hz). The results showed decreases in amplitude but increases in phase coherence in mu rhythms and normalization of mu rhythm suppression in experimental participants compared to placebo. Furthermore, like Study 1, participants showed improvements in sustained attention and in ATEC scores but no improvements in imitation following training. This suggests that training of the mu rhythm can be effective in producing changes in EEG and behavior in high-functioning ASD children, but does not affect imitation behavior per se.