Literature DB >> 30885442

EEG neurofeedback research: A fertile ground for psychiatry?

J-M Batail1, S Bioulac2, F Cabestaing3, C Daudet4, D Drapier1, M Fouillen5, T Fovet6, A Hakoun7, R Jardri6, C Jeunet8, F Lotte9, E Maby5, J Mattout5, T Medani7, J-A Micoulaud-Franchi10, J Mladenovic9, L Perronet11, L Pillette9, T Ros12, F Vialatte7.   

Abstract

The clinical efficacy of neurofeedback is still a matter of debate. This paper analyzes the factors that should be taken into account in a transdisciplinary approach to evaluate the use of EEG NFB as a therapeutic tool in psychiatry. Neurofeedback is a neurocognitive therapy based on human-computer interaction that enables subjects to train voluntarily and modify functional biomarkers that are related to a defined mental disorder. We investigate three kinds of factors related to this definition of neurofeedback. We focus this article on EEG NFB. The first part of the paper investigates neurophysiological factors underlying the brain mechanisms driving NFB training and learning to modify a functional biomarker voluntarily. Two kinds of neuroplasticity involved in neurofeedback are analyzed: Hebbian neuroplasticity, i.e. long-term modification of neural membrane excitability and/or synaptic potentiation, and homeostatic neuroplasticity, i.e. homeostasis attempts to stabilize network activity. The second part investigates psychophysiological factors related to the targeted biomarker. It is demonstrated that neurofeedback involves clearly defining which kind of relationship between EEG biomarkers and clinical dimensions (symptoms or cognitive processes) is to be targeted. A nomenclature of accurate EEG biomarkers is proposed in the form of a short EEG encyclopedia (EEGcopia). The third part investigates human-computer interaction factors for optimizing NFB training and learning during the closed loop interaction. A model is proposed to summarize the different features that should be controlled to optimize learning. The need for accurate and reliable metrics of training and learning in line with human-computer interaction is also emphasized, including targeted biomarkers and neuroplasticity. All these factors related to neurofeedback show that it can be considered as a fertile ground for innovative research in psychiatry.
Copyright © 2019 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Brain–computer interface; EEG; Learning; Neurofeedback; Neurophysiology; Psychophysiology; Training

Year:  2019        PMID: 30885442     DOI: 10.1016/j.encep.2019.02.001

Source DB:  PubMed          Journal:  Encephale        ISSN: 0013-7006            Impact factor:   1.291


  10 in total

Review 1.  Effects of Transcranial Alternating Current Stimulation and Neurofeedback on Alpha (EEG) Dynamics: A Review.

Authors:  Mária Orendáčová; Eugen Kvašňák
Journal:  Front Hum Neurosci       Date:  2021-07-08       Impact factor: 3.169

Review 2.  Why we should systematically assess, control and report somatosensory impairments in BCI-based motor rehabilitation after stroke studies.

Authors:  Léa Pillette; Fabien Lotte; Bernard N'Kaoua; Pierre-Alain Joseph; Camille Jeunet; Bertrand Glize
Journal:  Neuroimage Clin       Date:  2020-09-15       Impact factor: 4.881

3.  Improving Clinical, Cognitive, and Psychosocial Dysfunctions in Patients with Schizophrenia: A Neurofeedback Randomized Control Trial.

Authors:  Renata Markiewicz; Agnieszka Markiewicz-Gospodarek; Beata Dobrowolska; Bartosz Łoza
Journal:  Neural Plast       Date:  2021-08-12       Impact factor: 3.599

Review 4.  Fragile X Premutation: Medications, Therapy and Lifestyle Advice.

Authors:  Deepika Kour Sodhi; Randi Hagerman
Journal:  Pharmgenomics Pers Med       Date:  2021-12-29

5.  Alpha activity neuromodulation induced by individual alpha-based neurofeedback learning in ecological context: a double-blind randomized study.

Authors:  Fanny Grosselin; Audrey Breton; Lydia Yahia-Cherif; Xi Wang; Giuseppe Spinelli; Laurent Hugueville; Philippe Fossati; Yohan Attal; Xavier Navarro-Sune; Mario Chavez; Nathalie George
Journal:  Sci Rep       Date:  2021-09-16       Impact factor: 4.379

6.  Development of a brain wave model based on the quantitative analysis of EEG and EEG biofeedback therapy in patients with panic attacks during the COVID-19 pandemic.

Authors:  Marta Kopańska; Danuta Ochojska; Wiktoria Mytych; Marcin W Lis; Agnieszka Banaś-Ząbczyk
Journal:  Sci Rep       Date:  2022-09-01       Impact factor: 4.996

7.  Comparison of QEEG Findings before and after Onset of Post-COVID-19 Brain Fog Symptoms.

Authors:  Marta Kopańska; Danuta Ochojska; Renata Muchacka; Agnieszka Dejnowicz-Velitchkov; Agnieszka Banaś-Ząbczyk; Jacek Szczygielski
Journal:  Sensors (Basel)       Date:  2022-09-01       Impact factor: 3.847

8.  Dissociation of early and late face-related processes in autism spectrum disorder and Williams syndrome.

Authors:  Alice Gomez; Guillaume Lio; Angela Sirigu; Manuela Costa; Caroline Demily
Journal:  Orphanet J Rare Dis       Date:  2022-06-22       Impact factor: 4.303

9.  Simplified Attachable EEG Revealed Child Development Dependent Neurofeedback Brain Acute Activities in Comparison with Visual Numerical Discrimination Task and Resting.

Authors:  Kazuyuki Oda; Ricki Colman; Mamiko Koshiba
Journal:  Sensors (Basel)       Date:  2022-09-23       Impact factor: 3.847

10.  Initial Results of Tests Using GSR Biofeedback as a New Neurorehabilitation Technology Complementing Pharmacological Treatment of Patients with Schizophrenia.

Authors:  Renata Markiewicz; Beata Dobrowolska
Journal:  Biomed Res Int       Date:  2021-06-10       Impact factor: 3.411

  10 in total

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