Literature DB >> 21053066

Predicting successful learning of SMR neurofeedback in healthy participants: methodological considerations.

E Weber1, A Köberl, S Frank, M Doppelmayr.   

Abstract

Neurofeedback (NF) is a tool that has proven helpful in the treatment of various disorders such as epilepsy or attention deficit disorder (ADHD). Depending on the respective application, a high number of training sessions might be necessary before participants can voluntarily modulate the electroencephalographic (EEG) rhythms as instructed. In addition, many individuals never learn to do so despite numerous training sessions. Thus, we are interested in determining whether or not performance during the early training sessions can be used to predict if a participant will learn to regulate the EEG rhythms. Here, we propose an easy to use, but accurate method for predicting the performance of individual participants. We used a sample set of sensorimotor rhythm (SMR 12-15 Hz) NF training sessions (experiment 1) to predict the performance of the participants of another study (experiment 2). We then used the data obtained in experiment 2 to predict the performance of participants in experiment 1. We correctly predicted the performance of 12 out of 13 participants in the first group and all 14 participants in the second group; however, we were not able to make these predictions before the end of the eleventh training session.

Entities:  

Mesh:

Year:  2011        PMID: 21053066     DOI: 10.1007/s10484-010-9142-x

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


  34 in total

Review 1.  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

Review 2.  Clinical utility of EEG in attention-deficit/hyperactivity disorder: a research update.

Authors:  Sandra K Loo; Scott Makeig
Journal:  Neurotherapeutics       Date:  2012-07       Impact factor: 7.620

Review 3.  Process-based framework for precise neuromodulation.

Authors:  Nitzan Lubianiker; Noam Goldway; Tom Fruchtman-Steinbok; Christian Paret; Jacob N Keynan; Neomi Singer; Avihay Cohen; Kathrin Cohen Kadosh; David E J Linden; Talma Hendler
Journal:  Nat Hum Behav       Date:  2019-04-15

4.  Attention neuroenhancement through tDCS or neurofeedback: a randomized, single-blind, controlled trial.

Authors:  Gabriel Gaudencio Rêgo; Óscar F Gonçalves; Paulo Sérgio Boggio
Journal:  Sci Rep       Date:  2022-10-20       Impact factor: 4.996

5.  Functional near-infrared spectroscopy-based affective neurofeedback: feedback effect, illiteracy phenomena, and whole-connectivity profiles.

Authors:  Lucas R Trambaiolli; Claudinei E Biazoli; André M Cravo; Tiago H Falk; João R Sato
Journal:  Neurophotonics       Date:  2018-09-18       Impact factor: 3.593

6.  Evaluation of artifact-corrected electroencephalographic (EEG) training: a pilot study.

Authors:  Jeffry P La Marca; Daniel Cruz; Jennifer Fandino; Fabiana R Cacciaguerra; Joseph J Fresco; Austin T Guerra
Journal:  J Neural Transm (Vienna)       Date:  2018-03-26       Impact factor: 3.575

Review 7.  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

8.  Learning to modulate one's own brain activity: the effect of spontaneous mental strategies.

Authors:  Silvia E Kober; Matthias Witte; Manuel Ninaus; Christa Neuper; Guilherme Wood
Journal:  Front Hum Neurosci       Date:  2013-10-18       Impact factor: 3.169

9.  A Novel Cognition-Guided Neurofeedback BCI Dataset on Nicotine Addiction.

Authors:  Junjie Bu; Chang Liu; Huixing Gou; Hefan Gan; Yan Cheng; Mengyuan Liu; Rui Ni; Zhen Liang; Guanbao Cui; Ginger Qinghong Zeng; Xiaochu Zhang
Journal:  Front Neurosci       Date:  2021-07-06       Impact factor: 4.677

10.  Training Efficiency and Transfer Success in an Extended Real-Time Functional MRI Neurofeedback Training of the Somatomotor Cortex of Healthy Subjects.

Authors:  Tibor Auer; Renate Schweizer; Jens Frahm
Journal:  Front Hum Neurosci       Date:  2015-10-09       Impact factor: 3.169

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