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March 4, 2026Advances in Psychological Science0 citationsOpen Access

The role and predictive mechanisms of cognitive function and the central executive network in pain resilience

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YBYOU BeibeiNorth Sichuan Medical UniversityGHGU HuaifeiNorth Sichuan Medical UniversityWHWen HongWeiNorth Sichuan Medical University

Key Points

  • This research aims to identify key factors and mechanisms that enhance psychological resilience to pain through cognitive function and the central executive network.
  • Utilized self-report and brain functional MRI data across multiple centers and time points.
  • Employed cross-lagged analysis to uncover patterns in cognitive function and pain resilience.
  • Explored mediating role of resting-state functional connectivity of the central executive network.
  • Developed a multimodal predictive model for pain resilience using a gated recurrent unit deep learning algorithm.
  • Established a positive correlation between cognitive function and psychological resilience to pain.
  • Identified significant associations of gray matter volume and activity in the central executive network with pain resilience.
  • Developed a predictive model that successfully reflects the relationship between cognitive function and pain resilience.

Abstract

摘要: 慢性疼痛严重影响患者的身心健康和社会功能, 亟需有效的应对与管理策略。心理韧性对缓解疼痛的负面影响至关重要, 提升疼痛心理韧性成为患者应对身心挑战的关键, 然而哪些因素对疼痛心理韧性的提升具有关键作用及其机制尚未明确。既往研究表明, 心理韧性与认知功能呈正相关, 且认知功能干预可提升心理韧性。在此基础上, 有研究进一步采用神经影像与机器学习技术发现, 中央执行网络皮层区的灰质体积和功能活动水平与疼痛心理韧性相关。因此本研究假设“认知功能与中央执行网络不仅对提升疼痛心理韧性具有关键作用, 还能预测其发展”, 并拟采用多中心多时间点的自我报告和脑功能mri数据, ①运用交叉滞后分析揭示认知功能与疼痛心理韧性的关联模式; ②探索中央执行网络的静息态功能连接在认知功能与疼痛心理韧性关系中的中介角色; ③运用门控循环单元这一时序数据建模的深度学习算法构建并验证疼痛心理韧性的多模态预测模型。本研究为探索慢性疼痛应对的神经影像学基础开辟了新的视角, 为开发更有效的疼痛管理和精准治疗策略提供科学依据。

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Cite This Study

Beibei et al. (2026) studied this question.

synapsesocial.com/papers/69a7cdaed48f933b5eeda3a9https://doi.org/10.3724/sp.j.1042.2026.0583
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