Exploring the Embodied Mind: Functional Connectome Fingerprinting of Meditation Expertise

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Abstract

Background

Short mindfulness-based interventions have gained traction in research due to their positive impact on well-being, cognition, and clinical symptoms across various settings. However, these short-term trainings are viewed as preliminary steps within a more extensive transformative path, presumably leading to long-lasting trait changes. Despite this, little is still known about the brain correlates of these meditation traits.

Methods

To address this gap, we investigated the neural correlates of meditation expertise in long-term Buddhist practitioners, comparing the large-scale brain functional connectivity of 28 expert meditators with 47 matched novices. Our hypothesis posited that meditation expertise would be associated with specific and enduring patterns of functional connectivity present during both meditative (open monitoring/open presence and loving-kindness and compassion meditations) and nonmeditative resting states, as measured by connectivity gradients.

Results

Applying a support vector classifier to states not included in training, we successfully decoded expertise as a trait, demonstrating its non–state-dependent nature. The signature of expertise was further characterized by an increased integration of large-scale brain networks, including the dorsal and ventral attention, limbic, frontoparietal, and somatomotor networks. The latter correlated with a higher ability to create psychological distance from thoughts and emotions.

Conclusions

Such heightened integration of bodily maps with affective and attentional networks in meditation experts could point toward a signature of the embodied cognition cultivated in these contemplative practices.

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探索具身心灵:冥想专长的功能连接组指纹图谱
背景基于正念的短期干预对各种环境下的幸福感、认知和临床症状产生了积极影响,因此在研究中备受关注。然而,这些短期培训被视为更广泛的转化途径中的初步步骤,可能会导致长期的特质变化。为了填补这一空白,我们研究了长期佛教修行者禅修专长的神经相关性,比较了 28 名禅修专家和 47 名匹配新手的大规模大脑功能连接。我们的假设是,冥想专长将与冥想(开放式监控/开放式存在以及慈爱和慈悲冥想)和非冥想静息状态下存在的特定且持久的功能连接模式相关联,并通过连接梯度进行测量。结果将支持向量分类器应用于未纳入训练的状态,我们成功地将专长解码为一种特质,证明了其不依赖于状态的性质。专业知识的特征进一步表现为大规模大脑网络整合的增强,包括背侧和腹侧注意力网络、边缘网络、额顶网络和躯体运动网络。结论冥想专家身体图谱与情感和注意力网络的高度整合可能是这些沉思练习中培养的具身认知的特征。
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来源期刊
Biological psychiatry global open science
Biological psychiatry global open science Psychiatry and Mental Health
CiteScore
4.00
自引率
0.00%
发文量
0
审稿时长
91 days
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