Evidence map›Paper›PMID 36718768›Full record

ArticleBJPsych open2023

Correlation between abnormal brain network activity and electroencephalogram microstates on exposure to smoking-related cues.

Hefan Gan, Junjie Bu, Ginger Qinghong Zeng, Huixing Gou, Mengyuan Liu, Guanbao Cui, Xiaochu Zhang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BJPsych open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 9 citations in OpenAlex.

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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.

Hefan GanDepartment of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China.
Junjie BuSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Ginger Qinghong ZengInstitute of Advanced Technology, University of Science and Technology of China, Hefei, China.
Huixing GouDepartment of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China.
Mengyuan LiuDepartment of Psychology, School of Humanities and Social Science, University of Science and Technology of China, Hefei, China.
Guanbao CuiApplication Technology Center of Physical Therapy to Brain Disorders, Institute of Advanced Technology, University of Science and Technology of China, Hefei, China.
Xiaochu ZhangDepartment of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China; Department of Psychology, School of Humanities and Social Science, University of Science and Technology of China, Hefei, China; Application Technology Center of Physical Therapy to Brain Disorders, Institute of Advanced Technology, University of Science and Technology of China, Hefei, China; Biomedical Sciences and Health Laboratory of Anhui Province, University of Science and Technology of China, Hefei, China.ORCID https://orcid.org/0000-0002-7541-0130
University of Science and Technology of China · CNAnhui Medical University · CN

Funding

National Natural Science Foundation of China 32161143022National Natural Science Foundation of China 32171080
6 · The paper itself

Abstract

backgroundResearch into neural mechanisms underlying cue-induced cigarette craving has attracted considerable attention for its significant role in treatments. However, there is little understanding about the effects of exposure to smoking-related cues on electroencephalogram (EEG) microstates of smokers, which can reflect abnormal brain network activity in several psychiatric disorders.

aimsTo explore whether abnormal brain network activity in smokers on exposure to smoking-related cues would be captured by EEG microstates.

methodForty smokers were exposed to smoking and neutral imagery conditions (cues) during EEG recording. Behavioural data and parameters for microstate topographies associated with the auditory (A), visual (B), salience and memory (C) and dorsal attention networks (D) were compared between conditions. Correlations between microstate parameters and cigarette craving as well as nicotine addiction characteristics were also analysed.

resultsThe smoking condition elicited a significant increase in the duration of microstate classes B and C and in the duration and contribution of class D compared with the neutral condition. A significant positive correlation between the increased duration of class C (smoking minus neutral) and increased craving ratings was observed, which was fully mediated by increased posterior alpha power. The increased duration and contribution of class D were both positively correlated with years of smoking.

conclusionsOur results indicate that smokers showed abnormal EEG microstates when exposed to smoking-related cues compared with neutral cues. Importantly, microstate class C (duration) might be a biomarker of cue-induced cigarette craving, and class D (duration and contribution) might reflect the relationship between cue-elicited activation of the dorsal attention network and years of smoking.

Indexed as

cue-induced cravingEEG microstate analysisimagery scriptsNicotine-dependent smokerssmoking cue reactivity

Identifiers

PMID36718768
PMCPMC9970173
OpenAlexW4318616182

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.