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Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain

OBJECTIVE: Alpha-neurofeedback (α-NFB) is a novel therapy which trains individuals to volitionally increase their alpha power to improve pain. Learning during NFB is commonly measured using static parameters such as mean alpha power. Considering the biphasic nature of alpha rhythm (high and low alph...

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Autores principales: Patel, Kajal, Henshaw, James, Sutherland, Heather, Taylor, Jason R., Casson, Alexander J., Lopez-Diaz, Karen, Brown, Christopher A., Jones, Anthony K. P., Sivan, Manoj, Trujillo-Barreto, Nelson J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7958977/
https://www.ncbi.nlm.nih.gov/pubmed/33732101
http://dx.doi.org/10.3389/fnins.2020.620666
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author Patel, Kajal
Henshaw, James
Sutherland, Heather
Taylor, Jason R.
Casson, Alexander J.
Lopez-Diaz, Karen
Brown, Christopher A.
Jones, Anthony K. P.
Sivan, Manoj
Trujillo-Barreto, Nelson J.
author_facet Patel, Kajal
Henshaw, James
Sutherland, Heather
Taylor, Jason R.
Casson, Alexander J.
Lopez-Diaz, Karen
Brown, Christopher A.
Jones, Anthony K. P.
Sivan, Manoj
Trujillo-Barreto, Nelson J.
author_sort Patel, Kajal
collection PubMed
description OBJECTIVE: Alpha-neurofeedback (α-NFB) is a novel therapy which trains individuals to volitionally increase their alpha power to improve pain. Learning during NFB is commonly measured using static parameters such as mean alpha power. Considering the biphasic nature of alpha rhythm (high and low alpha), dynamic parameters describing the time spent by individuals in high alpha state and the pattern of transitioning between states might be more useful. Here, we quantify the changes during α-NFB for chronic pain in terms of dynamic changes in alpha states. METHODS: Four chronic pain and four healthy participants received five NFB sessions designed to increase frontal alpha power. Changes in pain resilience were measured using visual analogue scale (VAS) during repeated cold-pressor tests (CPT). Changes in alpha state static and dynamic parameters such as fractional occupancy (time in high alpha state), dwell time (length of high alpha state) and transition probability (probability of moving from low to high alpha state) were analyzed using Friedman’s Test and correlated with changes in pain scores using Pearson’s correlation. RESULTS: There was no significant change in mean frontal alpha power during NFB. There was a trend of an increase in fractional occupancy, mean dwell duration and transition probability of high alpha state over the five sessions in chronic pain patients only. Significant correlations were observed between change in pain scores and fractional occupancy (r = −0.45, p = 0.03), mean dwell time (r = -0.48, p = 0.04) and transition probability from a low to high state (r = -0.47, p = 0.03) in chronic pain patients but not in healthy participants. CONCLUSION: There is a differential effect between patients and healthy participants in terms of correlation between change in pain scores and alpha state parameters. Parameters providing a more precise description of the alpha power dynamics than the mean may help understand the therapeutic effect of neurofeedback on chronic pain.
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spelling pubmed-79589772021-03-16 Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain Patel, Kajal Henshaw, James Sutherland, Heather Taylor, Jason R. Casson, Alexander J. Lopez-Diaz, Karen Brown, Christopher A. Jones, Anthony K. P. Sivan, Manoj Trujillo-Barreto, Nelson J. Front Neurosci Neuroscience OBJECTIVE: Alpha-neurofeedback (α-NFB) is a novel therapy which trains individuals to volitionally increase their alpha power to improve pain. Learning during NFB is commonly measured using static parameters such as mean alpha power. Considering the biphasic nature of alpha rhythm (high and low alpha), dynamic parameters describing the time spent by individuals in high alpha state and the pattern of transitioning between states might be more useful. Here, we quantify the changes during α-NFB for chronic pain in terms of dynamic changes in alpha states. METHODS: Four chronic pain and four healthy participants received five NFB sessions designed to increase frontal alpha power. Changes in pain resilience were measured using visual analogue scale (VAS) during repeated cold-pressor tests (CPT). Changes in alpha state static and dynamic parameters such as fractional occupancy (time in high alpha state), dwell time (length of high alpha state) and transition probability (probability of moving from low to high alpha state) were analyzed using Friedman’s Test and correlated with changes in pain scores using Pearson’s correlation. RESULTS: There was no significant change in mean frontal alpha power during NFB. There was a trend of an increase in fractional occupancy, mean dwell duration and transition probability of high alpha state over the five sessions in chronic pain patients only. Significant correlations were observed between change in pain scores and fractional occupancy (r = −0.45, p = 0.03), mean dwell time (r = -0.48, p = 0.04) and transition probability from a low to high state (r = -0.47, p = 0.03) in chronic pain patients but not in healthy participants. CONCLUSION: There is a differential effect between patients and healthy participants in terms of correlation between change in pain scores and alpha state parameters. Parameters providing a more precise description of the alpha power dynamics than the mean may help understand the therapeutic effect of neurofeedback on chronic pain. Frontiers Media S.A. 2021-02-22 /pmc/articles/PMC7958977/ /pubmed/33732101 http://dx.doi.org/10.3389/fnins.2020.620666 Text en Copyright © 2021 Patel, Henshaw, Sutherland, Taylor, Casson, Lopez-Diaz, Brown, Jones, Sivan and Trujillo-Barreto. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Patel, Kajal
Henshaw, James
Sutherland, Heather
Taylor, Jason R.
Casson, Alexander J.
Lopez-Diaz, Karen
Brown, Christopher A.
Jones, Anthony K. P.
Sivan, Manoj
Trujillo-Barreto, Nelson J.
Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain
title Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain
title_full Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain
title_fullStr Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain
title_full_unstemmed Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain
title_short Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain
title_sort using eeg alpha states to understand learning during alpha neurofeedback training for chronic pain
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7958977/
https://www.ncbi.nlm.nih.gov/pubmed/33732101
http://dx.doi.org/10.3389/fnins.2020.620666
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