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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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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. |
format | Online Article Text |
id | pubmed-10471848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
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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