Revealing Changes in Brain Functional Networks Caused by Focused-Attention Meditation Using Tucker3 Clustering
Revealing Changes in Brain Functional Networks Caused by Focused-Attention Meditation Using Tucker3 Clustering
复制标题
DOI：
10.3389/fnhum.2019.00473
复制
发表时间：
2020-01-22
影响因子：
2.9
通讯作者：
Hiwa, Satoru
中科院分区：
文献类型：
--
作者：
Miyoshi, Takuma;Tanioka, Kensuke;Hiwa, Satoru
这项研究探讨了集中注意力冥想对冥想新手大脑功能状态的影响。大脑功能状态有许多特征指标，例如功能连接性、图论指标和低频波动幅度 (ALFF)。有必要选择适当的指标，并从多个大脑区域中指定感兴趣区域（ROI）。在这里，我们使用 Tucker3 聚类方法，该方法同时选择特征向量（图理论指标和分数 ALFF）和可以根据给定数据的特征区分静息状态和冥想状态的 ROI。在这项研究中，使用了呼吸计数冥想（最流行的集中注意力冥想形式之一），并通过功能磁共振成像测量了休息和冥想状态下的大脑活动。结果表明，通过冥想，额叶 Inf Oper L、枕叶 Inf R、海马旁 R、小脑 10 R、扣带中 R、小脑 Crus1 L、枕叶 Inf L 和旁中央小叶 R 8 个脑区的聚类系数有所增加。我们的研究还提供了数据驱动的大脑功能分析框架，并证实了其在分析集中注意力冥想的神经基础方面的有效性。
This study examines the effects of focused-attention meditation on functional brain states in novice meditators. There are a number of feature metrics for functional brain states, such as functional connectivity, graph theoretical metrics, and amplitude of low frequency fluctuation (ALFF). It is necessary to choose appropriate metrics and also to specify the region of interests (ROIs) from a number of brain regions. Here, we use a Tucker3 clustering method, which simultaneously selects the feature vectors (graph theoretical metrics and fractional ALFF) and the ROIs that can discriminate between resting and meditative states based on the characteristics of the given data. In this study, breath-counting meditation, one of the most popular forms of focused-attention meditation, was used and brain activities during resting and meditation states were measured by functional magnetic resonance imaging. The results indicated that the clustering coefficients of the eight brain regions, Frontal Inf Oper L, Occipital Inf R, ParaHippocampal R, Cerebellum 10 R, Cingulum Mid R, Cerebellum Crus1 L, Occipital Inf L, and Paracentral Lobule R increased through the meditation. Our study also provided the framework of data-driven brain functional analysis and confirmed its effectiveness on analyzing neural basis of focused-attention meditation.