Suppr超能文献

客观特质正念的动态功能连接标记物。

Dynamic functional connectivity markers of objective trait mindfulness.

机构信息

Center for Cognitive Neuroscience, Neurosciences and Behavioral Disorders Department, Duke-NUS Medical School, 169857, Singapore.

Center for Cognitive Neuroscience, Neurosciences and Behavioral Disorders Department, Duke-NUS Medical School, 169857, Singapore.

出版信息

Neuroimage. 2018 Aug 1;176:193-202. doi: 10.1016/j.neuroimage.2018.04.056. Epub 2018 Apr 27.

Abstract

While mindfulness is commonly viewed as a skill to be cultivated through practice, untrained individuals can also vary widely in dispositional mindfulness. Prior research has identified static neural connectivity correlates of this trait. Here, we use dynamic functional connectivity (DFC) analysis of resting-state fMRI to study time-varying connectivity patterns associated with naturally varying and objectively measured trait mindfulness. Participants were selected from the top and bottom tertiles of performers on a breath-counting task to form high trait mindfulness (HTM; N = 21) and low trait mindfulness (LTM; N = 18) groups. DFC analysis of resting state fMRI data revealed that the HTM group spent significantly more time in a brain state associated with task-readiness - a state characterized by high within-network connectivity and greater anti-correlations between task-positive networks and the default-mode network (DMN). The HTM group transitioned between brain states more frequently, but the dwell time in each episode of the task-ready state was equivalent between groups. These results persisted even after controlling for vigilance. Across individuals, certain connectivity metrics were weakly correlated with self-reported mindfulness as measured by the Five Facet Mindfulness Questionnaire, though these did not survive multiple comparisons correction. In the static connectivity maps, HTM individuals had greater within-network connectivity in the DMN and the salience network, and greater anti-correlations between the DMN and task-positive networks. In sum, DFC features robustly distinguish HTM and LTM individuals, and may be useful biological markers for the measurement of dispositional mindfulness.

摘要

虽然正念通常被视为一种可以通过练习来培养的技能,但未经训练的个体在性格正念方面也可能存在很大差异。先前的研究已经确定了这种特质的静态神经连通性相关物。在这里,我们使用静息状态 fMRI 的动态功能连通性(DFC)分析来研究与自然变化和客观测量的特质正念相关的时变连通模式。参与者是从呼吸计数任务的前三个三分位数和后三个三分位数中选出的,分为高特质正念(HTM;N=21)和低特质正念(LTM;N=18)组。对静息状态 fMRI 数据的 DFC 分析表明,HTM 组在与任务准备相关的大脑状态中花费的时间明显更多——这是一种表现为高网络内连通性和任务正性网络与默认模式网络(DMN)之间更强反相关的状态。HTM 组在大脑状态之间的转换更为频繁,但在每个任务准备状态的停留时间在两组之间相等。即使在控制警觉性后,这些结果仍然存在。在个体之间,某些连通性指标与五因素正念问卷(FFMQ)测量的自我报告正念呈弱相关,但这些指标在多次比较校正后并未存活。在静态连通性图中,HTM 个体在 DMN 和突显网络中具有更高的网络内连通性,以及 DMN 和任务正性网络之间更强的反相关性。总之,DFC 特征可以可靠地区分 HTM 和 LTM 个体,并且可能是测量性格正念的有用生物学标志物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验