Literature DB >> 26553293

Electroencephalographic neurofeedback: Level of evidence in mental and brain disorders and suggestions for good clinical practice.

J-A Micoulaud-Franchi1, A McGonigal2, R Lopez3, C Daudet4, I Kotwas5, F Bartolomei6.   

Abstract

The technique of electroencephalographic neurofeedback (EEG NF) emerged in the 1970s and is a technique that measures a subject's EEG signal, processes it in real time, extracts a parameter of interest and presents this information in visual or auditory form. The goal is to effectuate a behavioural modification by modulating brain activity. The EEG NF opens new therapeutic possibilities in the fields of psychiatry and neurology. However, the development of EEG NF in clinical practice requires (i) a good level of evidence of therapeutic efficacy of this technique, (ii) a good practice guide for this technique. Firstly, this article investigates selected trials with the following criteria: study design with controlled, randomized, and open or blind protocol, primary endpoint related to the mental and brain disorders treated and assessed with standardized measurement tools, identifiable EEG neurophysiological targets, underpinned by pathophysiological relevance. Trials were found for: epilepsies, migraine, stroke, chronic insomnia, attentional-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, major depressive disorder, anxiety disorders, addictive disorders, psychotic disorders. Secondly, this article investigates the principles of neurofeedback therapy in line with learning theory. Different underlying therapeutic models are presented didactically between two continua: a continuum between implicit and explicit learning and a continuum between the biomedical model (centred on "the disease") and integrative biopsychosocial model of health (centred on "the illness"). The main relevant learning model is to link neurofeedback therapy with the field of cognitive remediation techniques. The methodological specificity of neurofeedback is to be guided by biologically relevant neurophysiological parameters. Guidelines for good clinical practice of EEG NF concerning technical issues of electrophysiology and of learning are suggested. These require validation by institutional structures for the clinical practice of EEG NF.
Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Cognitive remediation; Courbes d’apprentissage; Evidence-based medicine; Learning curves; Model; Modèle; Médecine fondée sur des preuves; Neurofeedback; Remédiation cognitive

Mesh:

Year:  2015        PMID: 26553293     DOI: 10.1016/j.neucli.2015.10.077

Source DB:  PubMed          Journal:  Neurophysiol Clin        ISSN: 0987-7053            Impact factor:   3.734


  26 in total

1.  Assessment of mental stress effects on prefrontal cortical activities using canonical correlation analysis: an fNIRS-EEG study.

Authors:  Fares Al-Shargie; Tong Boon Tang; Masashi Kiguchi
Journal:  Biomed Opt Express       Date:  2017-04-19       Impact factor: 3.732

Review 2.  Review of the therapeutic neurofeedback method using electroencephalography: EEG Neurofeedback.

Authors:  Nina Omejc; Bojan Rojc; Piero Paolo Battaglini; Uros Marusic
Journal:  Bosn J Basic Med Sci       Date:  2019-08-20       Impact factor: 3.363

3.  Therapeutic Applications of BCI Technologies.

Authors:  Dennis J McFarland; Janis Daly; Chadwick Boulay; Muhammad Parvaz
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2017-04-10

4.  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

5.  Sensorimotor rhythm neurofeedback training relieves anxiety in healthy people.

Authors:  Shuang Liu; Xinyu Hao; Xiaoya Liu; Yuchen He; Ludan Zhang; Xingwei An; Xizi Song; Dong Ming
Journal:  Cogn Neurodyn       Date:  2021-12-02       Impact factor: 3.473

6.  Neurofeedback Training of Alpha Relative Power Improves the Performance of Motor Imagery Brain-Computer Interface.

Authors:  Qing Zhou; Ruidong Cheng; Lin Yao; Xiangming Ye; Kedi Xu
Journal:  Front Hum Neurosci       Date:  2022-04-08       Impact factor: 3.473

7.  The Treatment of Autism Spectrum Disorder With Auditory Neurofeedback: A Randomized Placebo Controlled Trial Using the Mente Autism Device.

Authors:  Frederick R Carrick; Guido Pagnacco; Ahmed Hankir; Mahera Abdulrahman; Rashid Zaman; Emily R Kalambaheti; Derek A Barton; Paul E Link; Elena Oggero
Journal:  Front Neurol       Date:  2018-07-05       Impact factor: 4.003

8.  COMPLEX TREATMENT OF AMYOTROPHIC LATERAL SCLEROSIS PATIENT.

Authors:  Joanna Białkowska; Dorota Mroczkowska; Margaret E Huflejt; Joanna Wojtkiewicz; Tomasz Siwek; Monika Barczewska; Wojciech Maksymowicz
Journal:  Acta Clin Croat       Date:  2019-12       Impact factor: 0.780

9.  Emotion self-regulation training in major depressive disorder using simultaneous real-time fMRI and EEG neurofeedback.

Authors:  Vadim Zotev; Ahmad Mayeli; Masaya Misaki; Jerzy Bodurka
Journal:  Neuroimage Clin       Date:  2020-06-27       Impact factor: 4.881

10.  The neuronal mechanisms underlying improvement of impulsivity in ADHD by theta/beta neurofeedback.

Authors:  Annet Bluschke; Felicia Broschwitz; Simon Kohl; Veit Roessner; Christian Beste
Journal:  Sci Rep       Date:  2016-08-12       Impact factor: 4.379

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