Evidence map›Paper›PMID 36064187›Full record

ArticleBiological psychiatry. Cognitive neuroscience and neuroimaging2023

Disrupted Dynamic Interactions Between Large-Scale Brain Networks in Cocaine Users Are Associated With Dependence Severity.

Tianye Zhai, Hong Gu, Betty Jo Salmeron, Elliot A Stein, Yihong Yang

Open access · greenAbstract read
In one paragraph

Article in Biological psychiatry. Cognitive neuroscience and neuroimaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Benchmarking fMRI Denoising Pipelines.Human brain mapping · 2026
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  14. Disrupted brain state dynamics in opioid and alcohol use disorder: attenuation by nicotine use.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Article
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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

5 authors at 2 institutions in 1 country.

Tianye ZhaiNeuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland.
Hong GuNeuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland.
Betty Jo SalmeronNeuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland.
Elliot A SteinNeuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland.
Yihong YangNeuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland. Electronic address: yihongyang@intra.nida.nih.gov.
National Institutes of Health · USNational Institute on Drug Abuse · US

Funding

Development of MRI Techniques for Drug-Abuse ApplicationsZIADA000469 · NIDA · NATIONAL INSTITUTE ON DRUG ABUSE · PI YANG, YIHONG · 2009 to 2025
$23.5M
Develop of MRI Techniques for Drug-Abuse ApplicationsZ01DA000469 · NIDA · NATIONAL INSTITUTE ON DRUG ABUSE · PI YANG, YIHONG · 2004 to 2008
$5.7M
Intramural NIH HHS Z01 DA000469Intramural NIH HHS Z99 DA999999Intramural NIH HHS ZIA DA000469
6 · The paper itself

Abstract

backgroundSubstance use disorder is conceptualized as a neuropsychiatric disease with multifaceted phenotypic manifestations including disrupted interactions between brain networks. While the current understanding of brain network interactions is mostly based on static functional connectivity, accumulating evidence suggests that temporal dynamics of these network interactions may better reflect brain function and disease-related dysfunction. We thus investigated brain dynamics in cocaine use disorder and assessed their relationship with cocaine dependence severity.

methodsUsing a time frame analytical approach on resting-state functional magnetic resonance imaging data of 54 cocaine users and 54 age- and sex-matched healthy control participants, we identified temporally recurring brain network configuration patterns, termed brain states. With Menon's triple network model as a guide, we characterized these state dynamics by quantifying their occurrence rate and transition probability. Group differences in the state dynamics and their association with cocaine dependence were assessed.

resultsThree recurrent brain states with spatial patterns resembling the default mode, salience, and executive control networks were identified. Compared with healthy control subjects, cocaine users showed a higher default mode state occurrence rate and higher probability of transitioning from the salience state to the default mode state, with the former being attributed to the latter. A composite state transition probability negatively correlated with cocaine dependence severity.

conclusionsOur results provide novel evidence supporting the triple network model. While confirming hyperactivity of default mode network in cocaine users, our findings indicate the failure of salience network in toggling between default mode and executive control networks in cocaine use disorder.

Indexed as

CocaineCocaine-Related DisordersBrainBrain MappingHumansMagnetic Resonance ImagingCocaineAddictionBrain statesDependence severityNetwork interactionResting-state fMRITemporal dynamics

Identifiers

PMID36064187
PMCPMC12238966
OpenAlexW4294647359

What OpenQuestion holds

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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.