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基于激活似然估计(ALE)元分析的冥想神经认知模型。

A neurocognitive model of meditation based on activation likelihood estimation (ALE) meta-analysis.

机构信息

CNRS, FRE 3292, Laboratoire de Psychologie et Neuropsychologie Cognitives, Paris, France.

出版信息

Conscious Cogn. 2012 Mar;21(1):269-76. doi: 10.1016/j.concog.2011.09.019. Epub 2011 Oct 17.

Abstract

Meditation comprises a series of practices mainly developed in eastern cultures aiming at controlling emotions and enhancing attentional processes. Several authors proposed to divide meditation techniques in focused attention (FA) and open monitoring (OM) techniques. Previous studies have reported differences in brain networks underlying FA and OM. On the other hand common activations across different meditative practices have been reported. Despite differences between forms of meditation and their underlying cognitive processes, we propose that all meditative techniques could share a central process that would be supported by a core network for meditation since their general common goal is to induce relaxation, regulating attention and developing an attitude of detachment from one's own thoughts. To test this hypothesis, we conducted a quantitative meta-analysis based on activation likelihood estimation (ALE) of 10 neuroimaging studies (91 subjects) on different meditative techniques to evidence the core cortical network subserving meditation. We showed activation of basal ganglia (caudate body), limbic system (enthorinal cortex) and medial prefrontal cortex (MPFC). We discuss the functional role of these structures in meditation and we tentatively propose a neurocognitive model of meditation that could guide future research.

摘要

冥想由一系列主要在东方文化中发展起来的实践组成,旨在控制情绪和增强注意力过程。一些作者提出将冥想技术分为专注于注意力的技术(FA)和开放监测的技术(OM)。先前的研究报告了基础于 FA 和 OM 的大脑网络的差异。另一方面,也有报道称在不同的冥想实践中存在共同的激活。尽管冥想的形式和其潜在的认知过程存在差异,但我们提出,所有的冥想技术都可以共享一个核心过程,该过程将由冥想的核心网络来支持,因为它们的一般共同目标是诱导放松,调节注意力,并培养一种与自身思维分离的态度。为了检验这一假设,我们对 10 项不同冥想技术的神经影像学研究(91 名受试者)进行了基于激活可能性估计(ALE)的定量荟萃分析,以证明冥想的核心皮质网络。我们发现基底神经节(尾状核体)、边缘系统(内嗅皮层)和内侧前额叶皮层(MPFC)的激活。我们讨论了这些结构在冥想中的功能作用,并提出了一个冥想的神经认知模型,这可以指导未来的研究。

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