Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Division of Clinical Psychology and Psychiatry, Department of Psychology, University of Basel, Basel, Switzerland; Institute of Psychology, RWTH Aachen University, Germany.
Brain Cogn. 2023 Jul;169:106001. doi: 10.1016/j.bandc.2023.106001. Epub 2023 May 24.
We systematically investigated the link between trait mindfulness scores and functional connectivity (FC) features or behavioral data, to emphasize the importance of the reliability of self-report mindfulness scores. Sixty healthy young male participants underwent two functional MRI runs with three mindfulness or mind-wandering task blocks with an N-back task (NBT) block. The data from 49 participants (age: 23.3 ± 2.8) for whom two sets of the self-reported Mindfulness Attention Awareness Scale (MAAS) and NBT performance were available were analyzed. We divided participants into two groups based on the consistency level of their MAAS scores (i.e., a "consistent" and an "inconsistent" group). Then, the association between the MAAS scores and FC features or NBT performance was investigated using linear regression analysis with p-value correction and bootstrapping. Meaningful associations (a) between MAAS and NBT accuracy (slope = 0.41, CI = [0.10, 0.73], corrected p < 0.05), (b) between MAAS and the FC edges in the frontoparietal network, and (c) between the FC edges and NBT performance were only observed in the consistent group (n = 26). Our findings demonstrate the importance of appropriate screening mechanisms for self-report-based dispositional mindfulness scores when trait mindfulness scores are combined with neuronal features and behavioral data.
我们系统地研究了特质正念评分与功能连接(FC)特征或行为数据之间的联系,以强调自我报告正念评分可靠性的重要性。60 名健康年轻男性参与者进行了两次功能磁共振成像扫描,其中包括三个正念或走神任务块和一个 N -back 任务(NBT)块。分析了 49 名参与者(年龄:23.3±2.8)的数据,这些参与者有两组自我报告的正念注意意识量表(MAAS)和 NBT 表现。我们根据 MAAS 分数的一致性水平将参与者分为两组(即“一致”和“不一致”组)。然后,使用具有 p 值校正和引导的线性回归分析来研究 MAAS 分数与 FC 特征或 NBT 表现之间的关联。在一致性组(n=26)中仅观察到 MAAS 与 NBT 准确性之间的有意义关联(斜率=0.41,CI=[0.10,0.73],校正后的 p<0.05)、MAAS 与额顶网络中的 FC 边缘之间的关联,以及 FC 边缘与 NBT 表现之间的关联。我们的发现表明,当特质正念评分与神经元特征和行为数据相结合时,自我报告的基于特质的正念评分需要适当的筛选机制。