Compassion As an Intervention to Attune to Universal Suffering of Self and Others in Conflicts: A Translational Framework.
Compassion As an Intervention to Attune to Universal Suffering of Self and Others in Conflicts: A Translational Framework.
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DOI：
10.3389/fpsyg.2020.603385
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发表时间：
2020
影响因子：
3.8
通讯作者：
Swain JE
中科院分区：
文献类型：
--
作者：
Ho SS;Nakamura Y;Swain JE
随着世界上人际、种族、社会和国际冲突的加剧，保护受其影响的个人的心理健康非常重要。根据佛教的观念，“如果你想让别人快乐，就培养同情心；如果你想要快乐，那就练习慈悲吧。”慈悲的练习是一种干预，可以培养不受冲突影响的幸福感。在这里，同情练习指的是一种集中的冥想形式，在这种冥想中，练习者与朋友、敌人以及介于两者之间的人协调，想着：“我要（平等地）帮助他们。”慈悲冥想的基础是佛教哲学，即精神上的痛苦源于概念性的想法，这些想法会产生对自我和他人的一般心理形象，以及随后的偏见，以保持个人的利己主义，阻碍心灵的最终本质。为了科学地将慈悲冥想的背景化，我们采用贝叶斯主动推理框架来整合相关的佛教概念，包括心(i)、慈悲（karuna）、蕴（skandhas）、苦（duhkha）、具体化（samaropa）、概念性思想（vikalpa）和叠加（prapañca）。在这个框架中，一个人被认为是一个贝叶斯引擎，它基于形式、感觉、辨别、行动和意识的集合积极地构建现象。当一个人体现了关于自己和他人身份的僵化信念（身份把握信念）以及由此产生的自我保护偏见时，这个人的贝叶斯引擎就会失灵，无法利用预测错误来更新先前的信念。为了解决这个问题，在认识到痛苦的原因之后，慈悲禅修者的目标是平等地调谐所有其他人，朋友和敌人一样，暂停以身份为基础的概念思想，最终放下任何抓住身份的信仰和掩盖现实的自我保护偏见。我们提出了一个贝叶斯引擎的三个组成部分的大脑模型：(a)关系建模，(b)现实检查和(c)冲突警报，它们分别由(a)默认模式网络（DMN）， (b)额顶叶网络（FPN）和腹侧注意网络（VAN）以及(c)显著性网络（SN）提供服务。在感知冲突时，自我保护偏见的增强或减弱将主要取决于SN是否分别上调DMN或FPN/VAN。我们提出，慈悲冥想可以加强大脑中有利于暂停先前信念的区域，并增强对冲突中对应方的调谐。
As interpersonal, racial, social, and international conflicts intensify in the world, it is important to safeguard the mental health of individuals affected by them. According to a Buddhist notion “if you want others to be happy, practice compassion; if you want to be happy, practice compassion,” compassion practice is an intervention to cultivate conflict-proof well-being. Here, compassion practice refers to a form of concentrated meditation wherein a practitioner attunes to friend, enemy, and someone in between, thinking, “I’m going to help them (equally).” The compassion meditation is based on Buddhist philosophy that mental suffering is rooted in conceptual thoughts that give rise to generic mental images of self and others and subsequent biases to preserve one’s egoism, blocking the ultimate nature of mind. To contextualize compassion meditation scientifically, we adopted a Bayesian active inference framework to incorporate relevant Buddhist concepts, including mind (buddhi), compassion (karuna), aggregates (skandhas), suffering (duhkha), reification (samaropa), conceptual thoughts (vikalpa), and superimposition (prapañca). In this framework, a person is considered a Bayesian Engine that actively constructs phenomena based on the aggregates of forms, sensations, discriminations, actions, and consciousness. When the person embodies rigid beliefs about self and others’ identities (identity-grasping beliefs) and the resulting ego-preserving bias, the person’s Bayesian Engine malfunctions, failing to use prediction errors to update prior beliefs. To counter this problem, after recognizing the causes of sufferings, a practitioner of the compassion meditation aims to attune to all others equally, friends and enemies alike, suspend identity-based conceptual thoughts, and eventually let go of any identity-grasping belief and ego-preserving bias that obscure reality. We present a brain model for the Bayesian Engine of three components: (a) Relation-Modeling, (b) Reality-Checking, and (c) Conflict-Alarming, which are subserved by (a) the Default-Mode Network (DMN), (b) Frontoparietal Network (FPN) and Ventral Attention Network (VAN), and (c) Salience Network (SN), respectively. Upon perceiving conflicts, the strengthening or weakening of ego-preserving bias will critically depend on whether the SN up-regulates the DMN or FPN/VAN, respectively. We propose that compassion meditation can strengthen brain regions that are conducive for suspending prior beliefs and enhancing the attunements to the counterparts in conflicts.
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DOI：
10.1038/nrn3950
发表时间：
2015-07
期刊：
Nature reviews. Neuroscience
影响因子：
--
作者：
Barrett LF;Simmons WK
通讯作者：
Simmons WK
影响因子：
3
作者：
Campbell, John O.
通讯作者：
Campbell, John O.
影响因子：
2.9
作者：
Ekstrom AD;Arnold AE;Iaria G
通讯作者：
Iaria G
DOI：
10.1093/brain/awq010
发表时间：
2010-04
期刊：
Brain : a journal of neurology
影响因子：
--
作者：
Carhart-Harris RL;Friston KJ
通讯作者：
Friston KJ
影响因子：
3.8
作者：
Connolly P
通讯作者：
Connolly P