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Autism spectrum

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Abstracts

Coben R, Linden M, Myers TE. (2012). Neurofeedback for autistic spectrum disorder: a review of the literature. Appl Psychophysiol Biofeedback . 2010 Mar;35(1):83-105.


It has been reported that individuals with autism spectrum disorder (ASD) have abnormal responses to the sensory environment. For these individuals sensory overload can impair functioning, raise physiological stress, and adversely affect social interaction. Early-stage (i.e. within 200 ms of stimulus onset) auditory processing abnormalities have been widely examined in ASD using eventrelated potentials (ERP), while ERP studies investigating early-stage visual processing in ASD are less frequent. We wanted to test the hypothesis of early-stage visual processing abnormalities in ASD by investigating ERPs elicited in a visual oddball task using illusory figures. Our results indicate that individuals with ASD have abnormally large cortical responses to task irrelevant stimuli over both parieto-occipital and frontal regions-of interest (ROI) during early stages of visual processing compared to the control group. Furthermore, ASD patients showed signs of an overall disruption in stimulus discrimination, and had a significantly higher rate of motor response errors.




Coben, R., & Pudolsky, I. (2007). Assessment-guided neurofeedback for autistic spectrum disorder. Journal of Neurotherapy, 11(1), 5-23.


Background. Research reviewing the epidemiology of Autism (Medical Research Council, 2001) indicated that approximately 60 per 10,000 children (1/166) are diagnosed with Autistic Spectrum Disorder (ASD). Jarusiewicz (2002) published the only controlled study documenting the effectiveness of neurofeedback for Autism based on one outcome measure. The present study extended these findings with a larger sample size, broader range of assessments, and physiological measures of brain functioning. Methods. Assessment-guided neurofeedback was conducted in 20 sessions for 37 patients with ASD. The experimental and control groups were matched for age, gender, race, handedness, other treatments, and severity of ASD. Results. Improved ratings of ASD symptoms reflected an 89% success rate. Statistical analyses revealed significant improvement in Autistics who received Neurofeedback compared to a wait list control group. Other major findings included a 40% reduction in core ASD symptomatology (indicated by ATEC Total Scores), and 76% of the experimental group had decreased hyper-connectivity. Reduced cerebral hyperconnectivity was associated with positive clinical outcomes in this population. In all cases of reported improvement in ASD symptomatology, positive treatment outcomes were confirmed by neuropsychological and neurophysiological assessment. Conclusions. Evidence from multiple measures has demonstrated that neurofeedback can be an effective treatment for ASD. In this population, a crucial factor in explaining improved clinical outcomes in the experimental group may be the use of assessment-guided neurofeedback to reduce cerebral hyperconnectivity. Implications of these findings are discussed.




Hurt, E., Arnold, AE. & Lofthouse, N. (2014). Quantitative EEG neurofeedback for the treatment of pediatric attention-deficit hyperactivity disorder, autism spectrum disorders, learning disorders and epilepsy. Child and Adolescent Psychiatric Clinics of North America:23(3). 465-86.


Neurofeedback (NF) using surface electroencephalographic signals has been used to treat various child psychiatric disorders by providing patients with video/audio information about their brain's electrical activity in real-time. Research data are reviewed and clinical recommendations are made regarding NF treatment of youth with attention deficit/hyperactivity disorder, autism, learning disorders, and epilepsy. Most NF studies are limited by methodological issues, such as failure to use or test the validity of a full-blind or sham NF. The safety of NF treatment has not been thoroughly investigated in youth or adults, although clinical experience suggests reasonable safety autism




Jarusiewicz, G. (2007). Use of neurofeedback with autistic spectrum disorders . Chapter in J. R. Evans (Ed.), Handbook of Neurofeedback. Binghampton, NY: Haworth Medical Press, pp. 321-339. Kouijzer, M. E. UJ., de Moor, J. M. H., Gerrits, B. J. L., Buitelaar, J. K., & van Schie, H. T. (2009). Long-term effects of neurofeedback treatment in autism. Research in Autism Spectrum Disorders , 3, 496-501.


Previously we demonstrated significant improvement of executive functions and social behavior in children with autism spectrum disorders (ASD) treated with 40 sessions of EEG neurofeedback in a nonrandomized waiting list control group design. In this paper we extend these findings by reporting the long-term results of neurofeedback treatment in the same group of children with ASD after 12 months. The present study indicates maintenance of improvement of executive functions and social behavior after 12 months in comparison with the immediate outcomes. Neurofeedback mediated suppression of theta power is supposed to promote more flexible functioning of the brain by enhancing activation in the medial prefrontal cortex and improving flexibility of activation in the default mode network supporting the improvement of executive functions and theory of mind in ASD.




Sichel, A. G., Fehmi, L. G., & Goldstein, D. M. (1995). Positive outcome with neurofeedback treatment of a case of mild autism. Journal of Neurotherapy , 1(1), 60- 64.


This article looks at the experience of Frankie, an autistic 8 ½ year old boy. He was diagnosed as mildly autistic by several specialis ts. Our specialists claimed he was brain damaged and “autistic-like” and that there was no hope for improvement. At Frankie’s mother’s request, neurotherapy diagnosis and treatment was begun. Affter 31 sessions, Frankie showed positive changes in all the diagnostic dimensions defining autism in DSM III-R. This has profound implications for treatment in a field with few low risk alternatives.




Sokhadze, E., Singh, S., El-Baz, A., Baruth, J., Mathai, G., Sears, L., &Casanova M. (2009). Effect of a low-frequency repetitive transcranial magnetic stimulation (rTMS) on induced gamma frequency oscillations and event-related potentials during processing of illusory figures in autism spectrum disorders. Journal of Autism and Developmental Disorders , 39, 619-634.


Previous studies by our group suggest that the neuropathology of autism is characterized by a disturbance of cortical modularity. In this model a decrease in the peripheral neuropil space of affected minicolumns provides for an inhibitory deficit and a readjustment in their signal to noise bias during information processing. In this study we proposed using low frequency transcranial magnetic stimulation (rTMS) as a way increasing the surround inhibition of minicolumns in autism. Thirteen patients (ADOS and ADI-R diagnosed) and equal number of controls participated in the study. Repetitive TMS was delivered at 0.5Hz, 2 times per week for 3 weeks. Outcome measures based on event-related potentials (ERP), induced gamma activity, and behavioral measures showed significant post-TMS improvement. The results suggest that rTMS offers a potential therapeutic intervention for autism.




Baruth, J., Casanova, M., Sears, L. & Sokhadze, E., (2010). Early -stage visual processing abnormalities in high-functioning autism spectrum disorder (ASD). Translational Neuroscience , 1(2), 177-187.


It has been reported that individuals with autism spectrum disorder (ASD) have abnormal responses to the sensory environment. For these individuals sensory overload can impair functioning, raise physiological stress, and adversely affect social interaction. Early-stage (i.e. within 200 ms of stimulus onset) auditory processing abnormalities have been widely examined in ASD using eventrelated potentials (ERP), while ERP studies investigating early-stage visual processing in ASD are less frequent. We wanted to test the hypothesis of early-stage visual processing abnormalities in ASD by investigating ERPs elicited in a visual oddball task using illusory figures. Our results indicate that individuals with ASD have abnormally large cortical responses to task irrelevant stimuli over both parieto-occipital and frontal regions-of interest (ROI) during early stages of visual processing compared to the control group. Furthermore, ASD patients showed signs of an overall disruption in stimulus discrimination, and had a significantly higher rate of motor response errors.




Coben, R., & Myers, T. E. (2010). The relative efficacy of connectivity guided and symptom based EEG biofeedback for autistic disorders. Applied Psychophysiology & Biofeedback , 35(1), 13-23.


Autism is a neurodevelopmental disorder characterized by deficits in communication, social interaction, and a limited range of interests with repetitive stereotypical behavior. Various abnormalities have been documented in the brains of individuals with autism, both anatomically and functionally. The connectivity theory of autism is a recently developed theory of the neurobiological cause of Autistic symptoms. Different patterns of hyper- and hypo-connectivity have been identified with the use of quantitative electroencephalography (QEEG), which may be amenable to neurofeedback. In this study, we compared the results of two published controlled studies examining the efficacy of neurofeedback in the treatment of autism. Specifically, we examined whether a symptom based approach or an assessment/connectivity guided based approach was more effective. Although both methods demonstrated significant improvement in symptoms of autism, connectivity guided neurofeedback demonstrated greater reduction on various subscales of the Autism Treatment Evaluation Checklist (ATEC). Furthermore, when individuals were matched for severity of symptoms, the amount of change per session was significantly higher in the Coben and Padolsky (J Neurother 11:5-23, 2007) study for all five measures of the ATEC. Our findings suggest that an approach guided by QEEG based connectivity assessment may be more efficacious in the treatment of autism. This permits the targeting and amelioration of abnormal connectivity patterns in the brains of people who are autistic.





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