Neurophysiological signatures of rumination’s impact on opioid withdrawal severity

Opioid withdrawal symptoms (OWS) represent a major clinical challenge during abstinence, imposing physiological distress and increasing psychological vulnerability to relapse. Psychological factors contributing to individual differences in OWS severity remain understood, and reliable biomarkers for OWS severity are still lacking, highlighting the need for early identification and timely intervention among high-risk heroin abstainers. Rumination is defined as uncontrollable negative thinking, potentially impairing the ability to suppress addiction-related negative thoughts. This study aims to investigate the neuroendocrine and neurophysiological mechanisms underlying the impact of rumination on OWS severity and use machine learning approaches to uncover neurophysiological signatures. Results revealed that, compared to heroin abstainers with lower rumination, those with higher rumination exhibited significantly higher scores on opiate withdrawal scale and stronger cortisol awakening response (CAR). EEG functional connectivity analysis revealed significantly enhanced alpha-band synchronization within default mode network (DMN)-related brain regions in the heroin abstainers with higher rumination, positively correlating with CAR and OWS severity. The Support Vector Machine model based on multimodal data effectively classified OWS severity, outperforming both the Random Forest and Logistic Regression models. To further analyze the interactions among key predictors, chain mediation analyses showed that rumination influences OWS severity through enhanced CAR and functional connectivity indirectly. These findings suggest that the rumination-driven negative thoughts exacerbate OWS severity through abnormal physiological and neural activities. By advancing the neurobiological understanding of OWS severity, we potentially offer a useful clinical diagnostic tool and provide empirical support for developing targeted dual-pathway clinical strategies during abstinence.

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Publication Details

Journal
NeuroImage
Published
2026-03-04
DOI
https://doi.org/10.1016/j.neuroimage.2026.121842
Primary Topic
Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Type
article
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article

Neurophysiological signatures of rumination’s impact on opioid withdrawal severity

Senqing Qi, Yujia Meng, Wenjuan Fu, Yifan Wang et al.
NeuroImage
Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
article

Neurophysiological signatures of rumination’s impact on opioid withdrawal severity

Senqing Qi, Yujia Meng, Wenjuan Fu, Yifan Wang, Xinyang Xu, Haijun Duan, Kai Yuan, Wanyi Li
article en

Abstract

Opioid withdrawal symptoms (OWS) represent a major clinical challenge during abstinence, imposing physiological distress and increasing psychological vulnerability to relapse. Psychological factors contributing to individual differences in OWS severity remain understood, and reliable biomarkers for OWS severity are still lacking, highlighting the need for early identification and timely intervention among high-risk heroin abstainers. Rumination is defined as uncontrollable negative thinking, potentially impairing the ability to suppress addiction-related negative thoughts. This study aims to investigate the neuroendocrine and neurophysiological mechanisms underlying the impact of rumination on OWS severity and use machine learning approaches to uncover neurophysiological signatures. Results revealed that, compared to heroin abstainers with lower rumination, those with higher rumination exhibited significantly higher scores on opiate withdrawal scale and stronger cortisol awakening response (CAR). EEG functional connectivity analysis revealed significantly enhanced alpha-band synchronization within default mode network (DMN)-related brain regions in the heroin abstainers with higher rumination, positively correlating with CAR and OWS severity. The Support Vector Machine model based on multimodal data effectively classified OWS severity, outperforming both the Random Forest and Logistic Regression models. To further analyze the interactions among key predictors, chain mediation analyses showed that rumination influences OWS severity through enhanced CAR and functional connectivity indirectly. These findings suggest that the rumination-driven negative thoughts exacerbate OWS severity through abnormal physiological and neural activities. By advancing the neurobiological understanding of OWS severity, we potentially offer a useful clinical diagnostic tool and provide empirical support for developing targeted dual-pathway clinical strategies during abstinence.

NeuroImageVol. 329
Xidian University (CN), Shaanxi Normal University (CN)
Good health and well-being
Openalex Percentile: Top 38%
Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
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