Suppr超能文献

特质和状态反刍的共享和独特的大脑网络。

Shared and distinctive brain networks underlying trait and state rumination.

机构信息

Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China; School of Psychology, Jiangxi Normal University, Nanchang, China.

Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China.

出版信息

Behav Brain Res. 2024 Aug 24;472:115144. doi: 10.1016/j.bbr.2024.115144. Epub 2024 Jul 9.

Abstract

Although trait and state rumination play a central role in the exacerbation of negative affect, evidence suggests that they are weakly correlated and exert distinct influences on emotional reactivity to stressors. Whether trait and state rumination share a common or exhibit distinct neural substrate remains unclear. In this study, we utilized functional near-infrared spectroscopy (fNIRS) combined with connectome-based predictive modeling (CPM) to identify neural fingerprints associated with trait and state rumination. CPM identified distinctive functional connectivity (FC) profiles that contribute to the prediction of trait rumination, primarily involving FC within the default mode network (DMN) and the dorsal attention network (DAN) as well as FC between the DMN, control network (CN), DAN, and salience network (SN). Conversely, state rumination was predominantly associated with FC between the DMN and CN. Furthermore, the predictive features of trait rumination can be robustly generalized to predict state rumination, and vice versa. In conclusion, this study illuminates the importance of both DMN and non-DMN systems in the emergence and persistence of rumination. While trait rumination was associated with stronger and broader FC than state rumination, the generalizability of the predictive features underscores the presence of shared neural mechanisms between the two forms of rumination. These identified connectivity fingerprints may hold promise as targets for innovative therapeutic interventions aimed at mitigating rumination-related negative affect.

摘要

虽然特质和状态反刍在负性情绪的加剧中起着核心作用,但有证据表明它们相关性较弱,对压力源的情绪反应有不同的影响。特质和状态反刍是否共享共同的或表现出不同的神经基质仍不清楚。在这项研究中,我们利用功能近红外光谱(fNIRS)结合基于连接组的预测模型(CPM)来识别与特质和状态反刍相关的神经指纹。CPM 确定了独特的功能连接(FC)模式,有助于预测特质反刍,主要涉及默认模式网络(DMN)和背侧注意网络(DAN)内的 FC 以及 DMN、控制网络(CN)、DAN 和突显网络(SN)之间的 FC。相反,状态反刍主要与 DMN 和 CN 之间的 FC 相关。此外,特质反刍的预测特征可以稳健地推广来预测状态反刍,反之亦然。总之,这项研究阐明了 DMN 和非 DMN 系统在反刍的出现和持续中的重要性。虽然特质反刍与更强和更广泛的 FC 相关,但其预测特征的可推广性强调了这两种反刍形式之间存在共同的神经机制。这些确定的连接指纹可能有望成为旨在减轻反刍相关负性情绪的创新治疗干预的目标。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验