Evidence map›Paper›PMID 37663053›Full record

ArticleGeneral psychiatry2023

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

Qiujian Meng, Ying Zhu, Ye Yuan, Li Yang, Jiafang Liu, Xiaochu Zhang, Junjie Bu

Open access · diamondAbstract read
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Article in General psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Qiujian MengDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, Anhui, China.ORCID 0009-0000-8511-6544
Ying ZhuDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, Anhui, China.ORCID 0009-0008-8815-427X
Ye YuanDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, Anhui, China.ORCID 0009-0006-1197-6107
Li YangDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, Anhui, China.ORCID 0009-0009-8155-768X
Jiafang LiuDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, Anhui, China.ORCID 0009-0006-0611-2099
Xiaochu ZhangDepartment of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, Anhui, China.
Junjie BuDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, Anhui, China.ORCID 0000-0003-1995-8545
Anhui Medical University · CNUniversity of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

behavior, addictivebraincognition

Identifiers

PMID37663053
PMCPMC10471848
OpenAlexW4386304430

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.