Literature DB >> 19760142

Identifying indices of learning for alpha neurofeedback training.

T Dempster1, D Vernon.   

Abstract

Neurofeedback has been around for decades and has applications for both clinical and healthy populations yet there is no standard method for measuring learning or a way of defining successful learning. Thus the aim of this study was to focus on alpha neurofeedback and examine changes in three different measures: amplitude, percent time, and integrated alpha, across four methods: within sessions, across sessions, within sessions compared to baseline, and across sessions compared to baseline. Participants completed 10 weekly sessions of eyes open alpha (8-12 Hz) neurofeedback training (NFT) at Pz. Whilst all three measures showed changes within sessions, the inclusion of baselines revealed that such changes represented a return to baseline levels rather than an increase in alpha. Changes across sessions were only evident in amplitude and inclusion of baseline showed that NFT did not elicit any changes beyond baseline levels. Given this a case is made for incorporating baseline measures when attempting to identify evidence of learning. It is also suggested that both amplitude and percent time measures are used independently rather than incorporate them into a more conservative and less sensitive integrated measure. Finally, focusing on within sessions changes may be a more useful approach in identifying changes resulting from NFT.

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Year:  2009        PMID: 19760142     DOI: 10.1007/s10484-009-9112-3

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


  24 in total

1.  The efficacy of EEG neurofeedback aimed at enhancing sensory-motor rhythm theta ratio in healthy subjects.

Authors:  Massimiliano de Zambotti; Marta Bianchin; Lorenzo Magazzini; Giorgia Gnesato; Alessandro Angrilli
Journal:  Exp Brain Res       Date:  2012-06-23       Impact factor: 1.972

2.  Distinguishing Voluntarily Upregulation of Localized Central Alpha from Widespread Posterior Alpha.

Authors:  Muhammad A Hasan; Hira Shahid; Hashim R Khan; Saad A Qazi; Matthew Fraser
Journal:  Appl Psychophysiol Biofeedback       Date:  2021-04-20

3.  Neurofeedback training of EEG alpha rhythm enhances episodic and working memory.

Authors:  Jen-Jui Hsueh; Tzu-Shan Chen; Jia-Jin Chen; Fu-Zen Shaw
Journal:  Hum Brain Mapp       Date:  2016-04-01       Impact factor: 5.038

Review 4.  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

5.  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

6.  The morphology of midcingulate cortex predicts frontal-midline theta neurofeedback success.

Authors:  Stefanie Enriquez-Geppert; René J Huster; Robert Scharfenort; Zacharais N Mokom; Johannes Vosskuhl; Christian Figge; Jörg Zimmermann; Christoph S Herrmann
Journal:  Front Hum Neurosci       Date:  2013-08-09       Impact factor: 3.169

7.  Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation.

Authors:  David J White; Marco Congedo; Joseph Ciorciari
Journal:  Front Behav Neurosci       Date:  2014-10-22       Impact factor: 3.558

Review 8.  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

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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