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Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction

BACKGROUND: The high rate of long-term relapse is a major cause of smoking cessation failure. Recently, neurofeedback training has been widely used in the treatment of nicotine addiction; however, approximately 30% of subjects fail to benefit from this intervention. Our previous randomised clinical...

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Autores principales: Meng, Qiujian, Zhu, Ying, Yuan, Ye, Yang, Li, Liu, Jiafang, Zhang, Xiaochu, Bu, Junjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471848/
https://www.ncbi.nlm.nih.gov/pubmed/37663053
http://dx.doi.org/10.1136/gpsych-2023-101091
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author Meng, Qiujian
Zhu, Ying
Yuan, Ye
Yang, Li
Liu, Jiafang
Zhang, Xiaochu
Bu, Junjie
author_facet Meng, Qiujian
Zhu, Ying
Yuan, Ye
Yang, Li
Liu, Jiafang
Zhang, Xiaochu
Bu, Junjie
author_sort Meng, Qiujian
collection PubMed
description BACKGROUND: The high rate of long-term relapse is a major cause of smoking cessation failure. Recently, neurofeedback training has been widely used in the treatment of nicotine addiction; however, approximately 30% of subjects fail to benefit from this intervention. Our previous randomised clinical trial (RCT) examined cognition-guided neurofeedback and demonstrated a significant decrease in daily cigarette consumption at the 4-month follow-up. However, significant individual differences were observed in the 4-month follow-up effects of decreased cigarette consumption. Therefore, it is critical to identify who will benefit from pre-neurofeedback. AIMS: We examined whether the resting-state electroencephalography (EEG) characteristics from pre-neurofeedback predicted the 4-month follow-up effects and explored the possible mechanisms. METHODS: This was a double-blind RCT. A total of 60 participants with nicotine dependence were randomly assigned to either the real-feedback or yoked-feedback group. They underwent 6 min closed-eye resting EEG recordings both before and after two neurofeedback sessions. A follow-up assessment was conducted after 4 months. RESULTS: The frontal resting-state theta power spectral density (PSD) was significantly altered in the real-feedback group after two neurofeedback visits. Higher theta PSD in the real-feedback group before neurofeedback was the only predictor of decreased cigarette consumption at the 4-month follow-up. Further reliability analysis revealed a significant positive correlation between theta PSD pre-neurofeedback and post-neurofeedback. A leave-one-out cross-validated linear regression of the theta PSD pre-neurofeedback demonstrated a significant correlation between the predicted and observed reductions in cigarette consumption at the 4-month follow-up. Finally, source analysis revealed that the brain mechanisms of the theta PSD predictor were located in the orbital frontal cortex. CONCLUSIONS: Our study demonstrated changes in the resting-state theta PSD following neurofeedback training. Moreover, the resting-state theta PSD may serve as a prognostic marker of neurofeedback effects. A higher resting-state theta PSD predicts a better long-term response to neurofeedback treatment, which may facilitate the selection of individualised interventions. TRIAL REGISTRATION NUMBER: ChiCTR-IPR-17011710.
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spelling pubmed-104718482023-09-02 Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction Meng, Qiujian Zhu, Ying Yuan, Ye Yang, Li Liu, Jiafang Zhang, Xiaochu Bu, Junjie Gen Psychiatr Original Research BACKGROUND: The high rate of long-term relapse is a major cause of smoking cessation failure. Recently, neurofeedback training has been widely used in the treatment of nicotine addiction; however, approximately 30% of subjects fail to benefit from this intervention. Our previous randomised clinical trial (RCT) examined cognition-guided neurofeedback and demonstrated a significant decrease in daily cigarette consumption at the 4-month follow-up. However, significant individual differences were observed in the 4-month follow-up effects of decreased cigarette consumption. Therefore, it is critical to identify who will benefit from pre-neurofeedback. AIMS: We examined whether the resting-state electroencephalography (EEG) characteristics from pre-neurofeedback predicted the 4-month follow-up effects and explored the possible mechanisms. METHODS: This was a double-blind RCT. A total of 60 participants with nicotine dependence were randomly assigned to either the real-feedback or yoked-feedback group. They underwent 6 min closed-eye resting EEG recordings both before and after two neurofeedback sessions. A follow-up assessment was conducted after 4 months. RESULTS: The frontal resting-state theta power spectral density (PSD) was significantly altered in the real-feedback group after two neurofeedback visits. Higher theta PSD in the real-feedback group before neurofeedback was the only predictor of decreased cigarette consumption at the 4-month follow-up. Further reliability analysis revealed a significant positive correlation between theta PSD pre-neurofeedback and post-neurofeedback. A leave-one-out cross-validated linear regression of the theta PSD pre-neurofeedback demonstrated a significant correlation between the predicted and observed reductions in cigarette consumption at the 4-month follow-up. Finally, source analysis revealed that the brain mechanisms of the theta PSD predictor were located in the orbital frontal cortex. CONCLUSIONS: Our study demonstrated changes in the resting-state theta PSD following neurofeedback training. Moreover, the resting-state theta PSD may serve as a prognostic marker of neurofeedback effects. A higher resting-state theta PSD predicts a better long-term response to neurofeedback treatment, which may facilitate the selection of individualised interventions. TRIAL REGISTRATION NUMBER: ChiCTR-IPR-17011710. BMJ Publishing Group 2023-08-30 /pmc/articles/PMC10471848/ /pubmed/37663053 http://dx.doi.org/10.1136/gpsych-2023-101091 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Meng, Qiujian
Zhu, Ying
Yuan, Ye
Yang, Li
Liu, Jiafang
Zhang, Xiaochu
Bu, Junjie
Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction
title Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction
title_full Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction
title_fullStr Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction
title_full_unstemmed Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction
title_short Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction
title_sort resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471848/
https://www.ncbi.nlm.nih.gov/pubmed/37663053
http://dx.doi.org/10.1136/gpsych-2023-101091
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