Evidence map›Paper›PMID 41992818›Full record

ArticleBrain and behavior2026

The Phase-Amplitude Coupling Induced by Drug Cues in Individuals With Methamphetamine Use Disorder During Withdrawal.

Yu Tian, Yaqi Zhang, Yongxin Cheng, Juan Wang, Yuxin Ma, Yimiao Li, Jinliang Liu, Dingming Chang, Ting Xue, Kai Yuan and 4 more

Abstract read
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In one paragraph

Article in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Yu TianSchool of Digital and Intelligent Industry, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Yaqi ZhangHenan Key Laboratory of Medical Tissue Regeneration, Henan Medical University, Xinxiang, Henan, China.
Yongxin ChengSchool of Digital and Intelligent Industry, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Juan WangSchool of Digital and Intelligent Industry, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Yuxin MaSchool of Digital and Intelligent Industry, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Yimiao LiSchool of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Jinliang LiuSchool of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Dingming ChangSchool of Digital and Intelligent Industry, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Ting XueSchool of Science, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Kai YuanSchool of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.
Gengdi HuangDepartment of Addiction Medicine, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, China.
Dahua YuSchool of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.ORCID https://orcid.org/0000-0001-7850-7512
Yanxue XueSchool of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.ORCID https://orcid.org/0000-0003-2979-0045
Fang DongSchool of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China.ORCID https://orcid.org/0009-0003-9081-8948

Funding

Chinese National Programs for Brain Science and Brain-like Intelligence TechnologyDevelopment Program for Young Talents of Science and Technology in Universities of Inner MongoliaFundamental Research Funds for the Universities of Inner MongoliaNational Natural Science Foundation of ChinaNatural Science Foundation of Inner MongoliaSTI2030-Major Projects
6 · The paper itself

Abstract

introductionSubstance use disorder (SUD) is a major global health challenge, with methamphetamine use disorder (MUD) being particularly severe due to its high addictiveness and relapse rate. The neurophysiological basis of MUD remains unclear. AIMS AND

methodsThis study investigated cross-frequency coupling in 46 male abstinent individuals with MUD to examine multi-scale neural information integration. Electroencephalography (EEG) was recorded during exposure to drug-related and neutral cues. Phase-amplitude coupling (PAC) and phase slope index (PSI) were used to assess local and directed network connectivity, respectively.

resultsCue-induced PAC enhancements correlated significantly with craving: left prefrontal AF3 PAC (10-14 Hz/60-82 Hz) was negatively correlated (r = -0.34 to -0.63, p < 0.05), whereas centro-parietal CP2 PAC (6-11 Hz/74-94 Hz) was positively correlated (r = 0.33-0.49, p < 0.05). PSI analysis showed reversed prefrontal-to-occipital flow (p < 0.05) and disrupted centro-parietal to sensorimotor connectivity (p < 0.05) under drug cues.

conclusionsDrug-related cues may exacerbate craving by weakening top-down prefrontal regulation and amplifying bottom-up sensorimotor drive. PAC and PSI represent promising cue-reactive predictive biomarkers for evaluating the neural substrates of drug cue-induced craving severity in individuals with MUD.

Indexed as

Amphetamine-Related DisordersBrainCuesMethamphetamineSubstance Withdrawal SyndromeAdultCravingElectroencephalographyHumansMalePrefrontal CortexMethamphetamineelectroencephalographyfunctional connectivitymethamphetamine use disorderphase‐amplitude coupling

Identifiers

PMID41992818
PMCPMC13087525

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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.