Evidence map›Paper›PMID 38151021›Full record

ArticleCell reports. Medicine2024

An electroencephalographic signature predicts craving for methamphetamine.

Weiwen Tian, Di Zhao, Jinjun Ding, Shulu Zhan, Yi Zhang, Amit Etkin, Wei Wu, Ti-Fei Yuan

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

Article in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 7% 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, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. [Applications and prospects of electroencephalography technology in neurorehabilitation assessment and treatment].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024
    Review
  10. Article
  11. An electroencephalography connectome predictive model of craving for methamphetamine.International journal of clinical and health psychology : IJCHP
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Weiwen TianShanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
Di ZhaoShanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
Jinjun DingShanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
Shulu ZhanShanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
Yi ZhangShanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
Amit EtkinDepartment of Psychiatry and Behavioral Science, Stanford University, Stanford, CA 94305, USA; Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA 94305, USA; Alto Neuroscience, Inc., Los Altos, CA 94022, USA.
Wei WuDepartment of Psychiatry and Behavioral Science, Stanford University, Stanford, CA 94305, USA; Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA 94305, USA; Alto Neuroscience, Inc., Los Altos, CA 94022, USA. Electronic address: weiwuneuro@gmail.com.
Ti-Fei YuanShanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China; Institute of Mental Health and Drug Discovery, Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang 325000, China; Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu 226019, China. Electronic address: ytf0707@126.com.
Shanghai Mental Health Center · CNNeurosciences Institute · USNantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Craving is central to methamphetamine use disorder (MUD) and both characterizes the disease and predicts relapse. However, there is currently a lack of robust and reliable biomarkers for monitoring craving and diagnosing MUD. Here, we seek to identify a neurobiological signature of craving based on individual-level functional connectivity pattern differences between healthy control and MUD subjects. We train high-density electroencephalography (EEG)-based models using data recorded during the resting state and then calculate imaginary coherence features between the band-limited time series across different brain regions of interest. Our prediction model demonstrates that eyes-open beta functional connectivity networks have significant predictive value for craving at the individual level and can also identify individuals with MUD. These findings advance the neurobiological understanding of craving through an EEG-tailored computational model of the brain connectome. Dissecting neurophysiological features provides a clinical avenue for personalized treatment of MUD.

Indexed as

MethamphetamineBrainCravingElectroencephalographyHumansMethamphetaminebrain functional connectivitycravingEEG biomarkermethamphetamine use disorderresting-state EEG

Identifiers

PMID38151021
PMCPMC10829728
OpenAlexW4390227171

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.