Literature DB >> 22903518

Is EEG-biofeedback an effective treatment in autism spectrum disorders? A randomized controlled trial.

Mirjam E J Kouijzer1, Hein T van Schie, Berrie J L Gerrits, Jan K Buitelaar, Jan M H de Moor.   

Abstract

EEG-biofeedback has been reported to reduce symptoms of autism spectrum disorders (ASD) in several studies. However, these studies did not control for nonspecific effects of EEG-biofeedback and did not distinguish between participants who succeeded in influencing their own EEG activity and participants who did not. To overcome these methodological shortcomings, this study evaluated the effects of EEG-biofeedback in ASD in a randomized pretest-posttest control group design with blinded active comparator and six months follow-up. Thirty-eight participants were randomly allocated to the EEG-biofeedback, skin conductance (SC)-biofeedback or waiting list group. EEG- and SC-biofeedback sessions were similar and participants were blinded to the type of feedback they received. Assessments pre-treatment, post-treatment, and after 6 months included parent ratings of symptoms of ASD, executive function tasks, and 19-channel EEG recordings. Fifty-four percent of the participants significantly reduced delta and/or theta power during EEG-biofeedback sessions and were identified as EEG-regulators. In these EEG-regulators, no statistically significant reductions of symptoms of ASD were observed, but they showed significant improvement in cognitive flexibility as compared to participants who managed to regulate SC. EEG-biofeedback seems to be an applicable tool to regulate EEG activity and has specific effects on cognitive flexibility, but it did not result in significant reductions in symptoms of ASD. An important finding was that no nonspecific effects of EEG-biofeedback were demonstrated.

Entities:  

Mesh:

Year:  2013        PMID: 22903518     DOI: 10.1007/s10484-012-9204-3

Source DB:  PubMed          Journal:  Appl Psychophysiol Biofeedback        ISSN: 1090-0586


  18 in total

1.  Impaired timing and frequency discrimination in high-functioning autism spectrum disorders.

Authors:  Anjali Bhatara; Talin Babikian; Elizabeth Laugeson; Raffi Tachdjian; Yvonne S Sininger
Journal:  J Autism Dev Disord       Date:  2013-10

2.  Control freaks: Towards optimal selection of control conditions for fMRI neurofeedback studies.

Authors:  Bettina Sorger; Frank Scharnowski; David E J Linden; Michelle Hampson; Kymberly D Young
Journal:  Neuroimage       Date:  2018-11-10       Impact factor: 6.556

3.  The validity of individual frontal alpha asymmetry EEG neurofeedback.

Authors:  C W E M Quaedflieg; F T Y Smulders; T Meyer; F Peeters; H Merckelbach; T Smeets
Journal:  Soc Cogn Affect Neurosci       Date:  2015-07-10       Impact factor: 3.436

4.  Comprehensive attention training system (CATS): A computerized executive-functioning training for school-aged children with autism spectrum disorder.

Authors:  Meng-Ting Chen; Yen-Ping Chang; Marisa E Marraccini; Miao-Chun Cho; Nai-Wen Guo
Journal:  Int J Dev Disabil       Date:  2020-10-05

Review 5.  Are treatment effects of neurofeedback training in children with ADHD related to the successful regulation of brain activity? A review on the learning of regulation of brain activity and a contribution to the discussion on specificity.

Authors:  Agnieszka Zuberer; Daniel Brandeis; Renate Drechsler
Journal:  Front Hum Neurosci       Date:  2015-03-27       Impact factor: 3.169

6.  QEEG spectral and coherence assessment of autistic children in three different experimental conditions.

Authors:  Calixto Machado; Mario Estévez; Gerry Leisman; Robert Melillo; Rafael Rodríguez; Phillip DeFina; Adrián Hernández; Jesús Pérez-Nellar; Rolando Naranjo; Mauricio Chinchilla; Nicolás Garófalo; José Vargas; Carlos Beltrán
Journal:  J Autism Dev Disord       Date:  2015-02

7.  Neurofunctional and behavioural measures associated with fMRI-neurofeedback learning in adolescents with Attention-Deficit/Hyperactivity Disorder.

Authors:  Sheut-Ling Lam; Marion Criaud; Analucia Alegria; Gareth J Barker; Vincent Giampietro; Katya Rubia
Journal:  Neuroimage Clin       Date:  2020-05-26       Impact factor: 4.881

8.  Eyes-Closed Resting EEG Predicts the Learning of Alpha Down-Regulation in Neurofeedback Training.

Authors:  Wenya Nan; Feng Wan; Qi Tang; Chi Man Wong; Boyu Wang; Agostinho Rosa
Journal:  Front Psychol       Date:  2018-08-28

9.  Resting and Initial Beta Amplitudes Predict Learning Ability in Beta/Theta Ratio Neurofeedback Training in Healthy Young Adults.

Authors:  Wenya Nan; Feng Wan; Mang I Vai; Agostinho C Da Rosa
Journal:  Front Hum Neurosci       Date:  2015-12-21       Impact factor: 3.169

10.  Resting alpha activity predicts learning ability in alpha neurofeedback.

Authors:  Feng Wan; Wenya Nan; Mang I Vai; Agostinho Rosa
Journal:  Front Hum Neurosci       Date:  2014-07-14       Impact factor: 3.169

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