正念的脑机制
The Brain Mechanism of Mindfulness
DOI: 10.12677/AP.2020.108144, PDF, HTML, XML, 下载: 609  浏览: 3,731  科研立项经费支持
作者: 李 娜:西南大学心理学部,重庆
关键词: 正念脑机制大脑区域激活功能连接性变化Mindfulness Brain Mechanism Activation of Brain Regions Changes in Functional Connectivity
摘要: 正念是对此时此刻状态的觉知,是有目的地、有意识地关注、觉察当下的一切,是一种专注于当前体验的非判断性关注。随着正念冥想训练在临床医学和心理治疗等领域的广泛应用及其疗效的凸显,越来越多的研究者开始对正念作用的机制感兴趣,特别是其脑机制。当前有关正念作用的脑机制研究主要集中于正念引起的大脑相关区域的激活以及功能连接性的变化。
Abstract: Mindfulness is the awareness of the state at the moment. It is a purposeful and conscious attention and awareness of everything in the present moment. It is a non-judgmental focus that pays close attention to the current experience. With the widespread application of mindfulness meditation training in clinical medicine and psychotherapy and the highlight of its efficacy, more and more researchers begin to be interested in the mechanism of mindfulness, especially its brain mechanism. The current research on the brain mechanism of mindfulness mainly focuses on the activation of relevant areas of the brain and changes in functional connectivity caused by mindfulness.
文章引用:李娜, 余林 (2020). 正念的脑机制. 心理学进展, 10(8), 1230-1237. https://doi.org/10.12677/AP.2020.108144

1. 引言

正念是一种意识状态,其特征在于对当前时刻经验的注意力自我调节,以及对这些经验的接受性和非判断性立场(Bishop et al., 2004)。正念需要我们关注此时此刻,用开放和接纳的态度去体会当下所发生的一切。正念的大多数定义都包含两个特征:首先,正念将注意力和觉知放在当下体验中。一个人关注当下体验可以采取多种来源,包括他的身体感觉、情绪反应、心理形象、心理对话和知觉体验(如:声音);其次,正念认为对一个人的经历采取开放或接纳的态度是至关重要的。这种开放和接纳的态度包括以一种好奇的、超然的和非反应性的方向来关注体验。重要的是,这种接纳经验的态度并不是对当前环境的被动顺从,而是鼓励体验(Creswell, 2017)。

自美国心理学家卡巴金将正念减压疗法(MBSR)应用于长期慢性疼痛的治疗并取得良好疗效后,正念便在临床医学和心理治疗等领域逐渐兴起,进而得到广泛传播和应用。并因此发展出了正念认知行为疗法(MBCT)、辩证行为疗法(DBT)、接受和承诺疗法(ACT)和基于正念的复发预防(MBRP)等心理干预和治疗方法(Simkin & Black, 2014)。正念干预在心理健康领域的应用最为广泛,影响也最大,不仅能够有效缓解抑郁、焦虑症状和上瘾行为等;同时,对大多数心身疾病(例如慢性疼痛,糖尿病,心血管疾病和癌症)的辅助治疗也非常有效(Creswell, 2017)。随着越来越多的证据表明正念对个体身心健康的有效性,研究者也逐渐开始对其如何产生这种有效性的作用机制感兴趣,有关正念的作用机制的研究也日渐丰富(Zou, Wu, & Fan, 2016)。本文将从三个方面对当前有关正念作用的脑机制的研究进行系统梳理。

2. 正念的脑机制

2.1. 正念对大脑结构与功能的影响

正念冥想训练是将意识集中和重新聚焦于当前时刻的内部和外部体验。正念冥想会使涉及注意力的额叶大脑区域的激活增加,可能有助于减轻注意力回避和增加注意力分配以及对分散注意力事件的更强处理(Goldin & Gross, 2010; Hölzel et al., 2007)。其中,简短的正念冥想训练能够使维持和监视注意力集中区域(背外侧前额叶)中的激活增加(Tomasino & Fabbro, 2016)。在进行集中呼吸时,特质正念维度上得分较高的人,其颞顶交界处,顶叶小叶和背外侧前额叶皮层上的激活比在这方面得分低的人更大(Dickenson et al., 2013)。也有研究发现,正念冥想使注意力的提高与后扣带皮层和背外侧前额叶皮层的静态连接性增强有关(Kral et al., 2019)。

正念冥想训练注重当下的体验,关注此时此刻。我们的大脑在事情不需要积极思考处理时,大脑通常倾向于思考当前未发生的事情(Mason et al., 2007),而这种思维徘徊与默认网络系统密切相关,默认网络主要的脑区包括内侧前额叶皮层、后扣带回等。该网络显示出在思想游荡、自我参照式思维,或回忆过去和对未来的思考中活动的增加(Andrews-Hanna, 2012)。正念冥想可以减少默认网络的活动,使注意力更多的关注当下,从而增加心理健康(Bauer, Whitfield-Gabrieli, Díaz, Pasaye, & Barrios, 2019; Brewer et al., 2011)。正念倾向更高的老年人与默认网络(DMN)更强的连通性有关,特别是后扣带皮层背侧和楔前叶(Prakash et al., 2012)。轻度认知障碍者在进行正念冥想训练后,发现默认网络中的功能连接性有增加,同时,可以减少轻度认知障碍中海马体积萎缩(Wells et al., 2013)。在此前的研究中发现,大脑中的默认网络和执行网络之间存在反相关,执行网络是任务阳性网络,而默认网络是任务阴性网络,参与了外部和内部之间注意力的持续切换(Fox et al., 2005; Kelly, Uddin, Biswal, Castellanos, & Milham, 2008)。中央执行网络包括了外侧前额叶皮层和顶叶等,其核心区域为背外侧前额叶皮层,它涉及执行过程,包括注意力控制,记忆,语言和视觉过程(Bressler & Menon, 2010)。简短的正念训练可增强执行控制网络中枢与参与认知控制的背侧和腹侧皮质回路之间的功能连接(Taren et al., 2017)。因而正念训练可以提高注意网络(任务阳性网络)而减少默认网络的活动,进而减少思维游荡更多的关注当下(Parkinson, Kornelsen, & Smith, 2019)。突显网络被认为在默认网络和中央执行网络之间的激活切换中发挥作用(Goulden et al., 2014)。它由前脑岛和前扣带组成,涉及将个人的注意力定向到外部和内部事件(Bressler & Menon, 2010)。研究发现脑岛和前扣带的体积、激活和功能连接随着正念冥想练习不断增加(Lim, Teng, Patanaik, Tandi, & Massar, 2018)。此外,三个网络系统之间也存在连接性,正念特质越高的人大脑状态之间的转换更多,总体上在一些连接状态中花费的时间更少,在突显网络和中央执行网络之间的连接性减少(Marusak et al., 2018),在默认网络和突显网络的网络内连接性更高(Lim et al., 2018),默认网络与中央执行网络之间的连通性增强(Bauer, Whitfield-Gabrieli et al., 2019)。

2.2. 正念干预的脑机制

2.2.1. 正念减压的脑机制

正念减压是正念应用中最主要的领域。正念冥想的减压机制主要与杏仁核、海马、扣带回和背外侧前额叶皮层有关。在压力大的健康人群中进行正念减压训练后,发现感知压力的降低与右侧杏仁核中灰质密度的降低相关(Hölzel et al., 2010)。在对儿童进行正念减压干预后,也发现可以减轻压力并促进大脑功能的改变,特别是能够有效减少杏仁核对负刺激的反应(Bauer, Caballero et al., 2019)。研究还发现,健康人群中较高的压力感与更大的双侧杏仁核–前扣带回皮层的静息状态功能连接性相关,而在对有压力的失业者进行为期3天的正念减压训练后,能够有效减少杏仁核–前扣带回皮层的静息状态功能连接性,可见正念减压训练可以促进功能性神经塑性改变(Taren et al., 2015)。在另外一个研究中,对压力大的失业者进行3天正念减压干预后,发现增加了后扣带回和背外侧前额叶皮层之间的静息状态功能连接性(Creswell et al., 2016)。通过对高压力参与者进行正念训练的干预,发现正念减压主要是通过增加背外侧前额叶与背侧神经网络(上顶小叶,额中回)和腹侧网络(右下额回,颞中区和角回)之间的静止状态功能连接实现的(Taren et al., 2017)。

此前有研究发现,感知压力的变化与杏仁核的结构变化相关,与海马体的变化不相关(Hölzel et al., 2010)。但在此后的研究中发现正念冥想能增强海马体中的灰质密度,而这与压力的减少有关,同时发现在进行正念减压训练后,后扣带皮层、颞顶叶交界处和小脑观察到区域灰质密度增加,而这些大脑区域与学习和记忆过程、情绪调节、自我参照过程和观点采择等有关(Hölzel et al., 2011)。正念冥想训练后海马灰质强度的增加预示着海马与背外侧前额叶皮层和压后皮层之间的连接性增强,通过这种机制,基于正念的干预措施可以消除恐惧记忆并增强对压力的应变能力(Sevinc et al., 2019)。接受正念训练的海军陆战队员在厌恶的内感受状态中,右前岛叶和前扣带皮层活动减弱,使个体更有效地处理厌恶的内感受刺激,这可能有助于提高压力的应对能力(Haase et al., 2016)。

2.2.2. 正念调节情绪的脑机制

正念冥想对于情绪调节涉及的脑区主要包括杏仁核和前额叶。研究发现,正念冥想训练通过降低杏仁核的反应来改善情感反应,而情感刺激中杏仁核–腹内侧前额叶皮层连接的增强可能反映了正念冥想对情绪调节能力发挥作用的潜在机制(Kral et al., 2018)。也有研究发现正念冥想是通过内侧前额叶皮层的功能连接来调节杏仁核的功能,进而实现对情绪的调节(Murakami et al., 2015)。此外,在正念初学者进行简短的正念冥想后发现负性情绪减少,而这与顶叶皮层有更强的参与倾向有关。这项研究为短期正念冥想优化情绪处理提供了新的证据(Xiao et al., 2019)。研究发现,简短的正念冥想练习能够有效调节厌恶情绪,在情绪刺激和正念练习过程中杏仁核激活减少,外侧和内侧前额顶叶皮层激活增加;杏仁核–前额叶皮层功能连接性增加与参与者的正念的提高有关(Doll et al., 2016)。有研究发现一致的结果,正念干预后前额叶区域在对负性或潜在负性图片的预期时的活动增加。同时,在对负面刺激的感知过程中,与情绪处理有关的区域(杏仁核、海马旁回)的激活程度降低(Lutz et al., 2014)。当期待负性图片时,特质正念越高的参与者前额叶和右岛叶的激活越低,这表明,正念特质更高的个体只需要较少的调节资源就能够减弱情绪唤起。

正念练习中的社交焦虑者在呼吸集中注意力任务中表现出负面情绪体验减少,杏仁核活动减少,从而实现减少情绪反应,增强情绪调节的能力(Goldin & Gross, 2010)。在对双相情感障碍进行正念干预时发现,正念任务期间内侧前额叶的活性增加,以及内侧前额叶和正念的信号变化之间呈现出相关性(Ives-Deliperi, Howells, Stein, Meintjes, & Horn, 2013)。对广泛性焦虑症患者进行正念干预后,他们的腹侧前额叶激活更大,杏仁核和前额叶皮层的多个区域之间的连接性增加,焦虑症状随之减轻(Hölzel et al., 2013)。正念冥想训练不仅可以改善抑郁症相关症状,而且还可以改变整个大脑网络的连接状态;在正念冥想过程中,楔前叶和颞顶叶交界处的内部一致性增强,而额叶大脑区域的内部一致性降低,经过冥想训练后,前扣带和背侧前额叶皮层在静息状态下的功能连通性降低以及抑郁和焦虑水平降低(Yang et al., 2016)。因此,这些发现表明正念冥想对情感障碍具有治疗作用。

2.2.3. 正念缓解疼痛的脑机制

正念缓解疼痛的相关脑区主要涉及扣带回和前岛。研究很早就发现,正念冥想可减轻慢性疼痛患者的疼痛(Kabat-Zinn, 1982),而不仅仅是充当安慰剂,正念疼痛缓解的神经机制与眶额皮质,前扣带皮层和右前岛更大的激活有关(Zeidan et al., 2015)。在短暂的正念冥想训练后,被试的疼痛等级降低,同时前扣带回皮质和前岛的激活增加(Zeidan et al., 2011)。有研究进一步验证了这一结果,发现长期正念冥想者与只有短暂冥想经验的人相比,能够在相同的疼痛刺激中表现出更少的不适感,这种差异与背部前岛叶和前部中扣带皮层的活动增强有关(Lutz, McFarlin, Perlman, Salomons, & Davidson, 2013)。

研究还发现,在热痛实验期间进行简短的正念冥想训练后,较高的正念特质与较低的疼痛敏感性和默认模式网络的后中线节点更大的失活显著相关,正念特质高的被试楔前叶到后扣带皮层的大脑区域在热痛中有更大程度的失活,这意味着后扣带皮层是正念对疼痛治疗的重要脑区(Zeidan et al., 2018)。在对患有中度或重度痛苦的被试为期6周的正念训练后,观察到疼痛明显减轻,并发现从前岛叶皮质到背侧前扣带回皮质的连接性增加,这种连接性的增加可能与自我认知和自我控制能力的增强有关,表明正念训练可以调节潜在的主观疼痛的大脑网络动态水平(Su et al., 2016)。在电刺激的疼痛实验中发现了不一样的结果,正念练习者能够在正念状态下减少疼痛不适感和预期焦虑感,而这与外侧前额叶皮层的激活减少以及右后岛的激活增加有关,揭示了正念对疼痛调节的独特机制(Gard et al., 2012)。

3. 研究展望

当前正念作用的脑机制研究主要来自神经影像学的结果,现有研究表明,正念冥想会引起相应脑区和脑功能连接的变化,主要包括背外侧前额叶、扣带回、杏仁核、海马体等。尽管现有作用机制的研究已经取得很大进展,但仍然存在很多的争议和不足,未来的研究可以进一步在以下方面进行探讨:

首先,目前的研究几乎都依赖于相关数据,导致仍然不清楚正念在多大程度上可以直接影响相关脑区的功能或结构。这与当前的研究多采用横向研究设计有关,许多研究都是通过正念量表测试被试的正念特质,对不同正念特质的个体进行脑机制的对比分析。此外一些研究则是横向比较长期正念冥想与短期正念冥想经历的人,这类研究很难控制除了正念冥想以外的额外变量,如:生活习惯,饮食方式,运动等这些变量对于脑结构的影响。同时,对于短暂的正念训练后能够维持多长时间的效果,也很少有追踪研究。尽管越来越多的研究试图通过正念训练来探讨其作用的脑机制,但这些研究绝大多数都是持续时间较短的干预训练,其对大脑结构和功能的影响有待进一步探讨。未来的研究可以增加更多的纵向研究以进一步验证已有的结果以及在一定程度上增加因果推论。

其次,被试的异质性对研究结论的影响也是未来研究需要考虑的一个问题。当前有关正念作用脑机制的研究中很大一部分是在健康个体中进行的。目前的研究发现,正念训练对有心身疾病的个体其大脑的激活模式会存在部分差异,如:在对双相情感障碍进行正念干预后发现内侧前额叶的活性增加(Ives-Deliperi et al., 2013),而在广泛性焦虑症患者发现腹侧前额叶激活更大(Hölzel et al., 2013),社交焦虑者在简短的正念训练后杏仁核活动减少(Goldin & Gross, 2010)。而对于正念缓解疼痛和压力的脑机制方面则很少有关于心身疾病患者进行的研究。这可能也与正念脑区相关研究采用的被试量都相对比较少也有关系,在一定程度上影响了重复实验的结果;此外,正念研究者本身对于正念的态度也会对研究结果有影响,被试可能会存在期望效应,从而对研究结果产生影响,在以后的研究中,研究者可以用更加客观的态度来进行正念的相关研究。

第三,正念作用脑区的特异性,正念训练和特质正念对前额叶的亚区域涉及最多,关于正念训练对前额叶的亚区域激活存在差异。观察到的最一致的发现是在完成正念干预后杏仁核的活动减弱(Bauer, Caballero et al., 2019; Goldin & Gross, 2010; Hölzel et al., 2010; Kral et al., 2018),顶叶的激活都是增加(Dickenson et al., 2013; Xiao et al., 2019)。但是,海马、扣带回、岛叶在正念训练对于压力、情绪和疼痛的激活存在差异(Grant, Courtemanche, & Rainville, 2011; Haase et al., 2016; Sevinc et al., 2019; Zeidan et al., 2015),如:海马激活在压力调节的时候增加,在情绪调节的时候激活减少;后扣带回激活在调节压力增加、疼痛缓解减少,前扣带回与之相反;在缓解疼痛后岛叶激活增加,而在压力调节时活动减弱。在正念对压力调节时发现杏仁核–前扣带回皮层的静息状态功能连接性减少(Taren et al., 2015),正念对于疼痛缓解发现前岛叶皮质到背侧前扣带回皮质的连接性增加(Su et al., 2016)。因此可见,正念训练涉及的脑区会因为训练的目的不同而激活程度存在差异,这需要在以后的研究中进一步进行验证。

基金项目

本研究得到重庆市人文社会科学重点研究基地重点项目(No.16SKB026)的资助。

NOTES

*通讯作者。

参考文献

[1] Andrews-Hanna, J. R. (2012). The Brain’s Default Network and Its Adaptive Role in Internal Mentation. The Neuroscientist, 18, 251-270.
https://doi.org/10.1177/1073858411403316
[2] Bauer, C. C. C., Caballero, C., Scherer, E., West, M. R., Mrazek, M. D., Phillips, D. T. et al. (2019). Mindfulness Training Reduces Stress and Amygdala Reactivity to Fearful Faces in Middle-School Children. Behavioral Neuroscience, 133, 569-585.
https://doi.org/10.1037/bne0000337
[3] Bauer, C. C. C., Whitfield-Gabrieli, S., Díaz, J. L., Pasaye, E. H., & Barrios, F. A. (2019). From State-to-Trait Meditation: Reconfiguration of Central Executive and Default Mode Networks. eNeuro, 6, 1-17.
https://doi.org/10.1523/ENEURO.0335-18.2019
[4] Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J. et al. (2004). Mindfulness: A Proposed Operational Definition. Clinical Psychology: Science and Practice, 11, 230-241.
https://doi.org/10.1093/clipsy.bph077
[5] Bressler, S. L., & Menon, V. (2010). Large-Scale Brain Networks in Cognition: Emerging Methods and Principles. Trends in Cognitive Sciences, 14, 277-290.
https://doi.org/10.1016/j.tics.2010.04.004
[6] Brewer, J. A., Worhunsky, P. D., Gray, J. R., Tang, Y. Y., Weber, J., & Kober, H. (2011). Meditation Experience Is Associated with Differences in Default Mode Network Activity and Connectivity. Proceedings of the National Academy of Sciences of the United States of America, 108, 20254-20259.
https://doi.org/10.1073/pnas.1112029108
[7] Creswell, J. D. (2017). Mindfulness Interventions. Annual Review of Psychology, 68, 491-516.
https://doi.org/10.1146/annurev-psych-042716-051139
[8] Creswell, J. D., Taren, A. A., Lindsay, E. K., Greco, C. M., Gianaros, P. J., Fairgrieve, A. et al. (2016). Alterations in Resting-State Functional Connectivity Link Mindfulness Meditation with Reduced Interleukin-6: A Randomized Controlled Trial. Biological Psychiatry, 80, 53-61.
https://doi.org/10.1016/j.biopsych.2016.01.008
[9] Dickenson, J., Berkman, E. T., Arch, J., & Lieberman, M. D. (2013). Neural Correlates of Focused Attention during a Brief Mindfulness Induction. Social Cognitive and Affective Neuroscience, 8, 40-47.
https://doi.org/10.1093/scan/nss030
[10] Doll, A., Hölzel, B. K., Mulej Bratec, S., Boucard, C. C., Xie, X., Wohlschläger, A. M., & Sorg, C. (2016). Mindful Attention to Breath Regulates Emotions via Increased Amygdala-Prefrontal Cortex Connectivity. NeuroImage, 134, 305-313.
https://doi.org/10.1016/j.neuroimage.2016.03.041
[11] Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). The Human Brain Is Intrinsically Organized into Dynamic, Anticorrelated Functional Networks. Proceedings of the National Academy of Sciences of the United States of America, 102, 9673-9678.
https://doi.org/10.1073/pnas.0504136102
[12] Gard, T., Hölzel, B. K., Sack, A. T., Hempel, H., Lazar, S. W., Vaitl, D., & Ott, U. (2012). Pain Attenuation through Mindfulness Is Associated with Decreased Cognitive Control and Increased Sensory Processing in the Brain. Cerebral Cortex, 22, 2692-2702.
https://doi.org/10.1093/cercor/bhr352
[13] Goldin, P. R., & Gross, J. J. (2010). Effects of Mindfulness-Based Stress Reduction (MBSR) on Emotion Regulation in Social Anxiety Disorder. Emotion, 10, 83-91.
https://doi.org/10.1037/a0018441
[14] Goulden, N., Khusnulina, A., Davis, N. J., Bracewell, R. M., Bokde, A. L., McNulty, J. P., & Mullins, P. G. (2014). The Salience Network Is Responsible for Switching between the Default Mode Network and the Central Executive Network: Replication from DCM. NeuroImage, 99, 180-190.
https://doi.org/10.1016/j.neuroimage.2014.05.052
[15] Grant, J. A., Courtemanche, J., & Rainville, P. (2011). A Non-Elaborative Mental Stance and Decoupling of Executive and Pain-Related Cortices Predicts Low Pain Sensitivity in Zen Meditators. Pain, 152, 150-156.
https://doi.org/10.1016/j.pain.2010.10.006
[16] Haase, L., Thom, N. J., Shukla, A., Davenport, P. W., Simmons, A. N., Stanley, E. A. et al. (2016). Mindfulness-Based Training Attenuates Insula Response to an Aversive Interoceptive Challenge. Social Cognitive and Affective Neuroscience, 11, 182-190.
https://doi.org/10.1093/scan/nsu042
[17] Hölzel, B. K., Carmody, J., Evans, K. C., Hoge, E. A., Dusek, J. A., Morgan, L. et al. (2010). Stress Reduction Correlates with Structural Changes in the Amygdala. Social Cognitive and Affective Neuroscience, 5, 11-17.
https://doi.org/10.1093/scan/nsp034
[18] Hölzel, B. K., Carmody, J., Vangel, M., Congleton, C., Yerramsetti, S. M., Gard, T., & Lazar, S. W. (2011). Mindfulness Practice Leads to Increases in Regional Brain Gray Matter Density. Psychiatry Research: Neuroimaging, 191, 36-43.
https://doi.org/10.1016/j.pscychresns.2010.08.006
[19] Hölzel, B. K., Hoge, E. A., Greve, D. N., Gard, T., Creswell, J. D., Brown, K. W. et al. (2013). Neural Mechanisms of Symptom Improvements in Generalized Anxiety Disorder Following Mindfulness Training. NeuroImage: Clinical, 2, 448-458.
https://doi.org/10.1016/j.nicl.2013.03.011
[20] Hölzel, B. K., Ott, U., Hempel, H., Hackl, A., Wolf, K., Stark, R., & Vaitl, D. (2007). Differential Engagement of Anterior Cingulate and Adjacent Medial Frontal Cortex in Adept Meditators and Non-Meditators. Neuroscience Letters, 421, 16-21.
https://doi.org/10.1016/j.neulet.2007.04.074
[21] Ives-Deliperi, V. L., Howells, F., Stein, D. J., Meintjes, E. M., & Horn, N. (2013). The Effects of Mindfulness-Based Cognitive Therapy in Patients with Bipolar Disorder: A Controlled Functional MRI Investigation. Journal of Affective Disorders, 150, 1152-1157.
https://doi.org/10.1016/j.jad.2013.05.074
[22] Kabat-Zinn, J. (1982). An Outpatient Program in Behavioral Medicine for Chronic Pain Patients Based on the Practice of Mindfulness Meditation: Theoretical Considerations and Preliminary Results. General Hospital Psychiatry, 4, 33-47.
https://doi.org/10.1016/0163-8343(82)90026-3
[23] Kelly, A. M., Uddin, L. Q., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2008). Competition between Functional Brain Networks Mediates Behavioral Variability. NeuroImage, 39, 527-537.
https://doi.org/10.1016/j.neuroimage.2007.08.008
[24] Kral, K., Schuyler, B. S., Mumford, J. A., Rosenkranz, M. A., Lutz, A., & Davidson, R. J. (2018). Impact of Short- and Long-Term Mindfulness Meditation Training on Amygdala Reactivity to Emotional Stimuli. NeuroImage, 181, 301-313.
https://doi.org/10.1016/j.neuroimage.2018.07.013
[25] Kral, T. R. A., Imhoff-Smith, T., Dean, D. C., Grupe, D., Adluru, N., Patsenko, E. et al. (2019). Mindfulness-Based Stress Reduction-Related Changes in Posterior Cingulate Resting Brain Connectivity. Social Cognitive and Affective Neuroscience, 14, 777-787.
https://doi.org/10.1093/scan/nsz050
[26] Lim, J., Teng, J., Patanaik, A., Tandi, J., & Massar, S. A. A. (2018). Dynamic Functional Connectivity Markers of Objective Trait Mindfulness. NeuroImage, 176, 193-202.
https://doi.org/10.1016/j.neuroimage.2018.04.056
[27] Lutz, A., McFarlin, D. R., Perlman, D. M., Salomons, T. V., & Davidson, R. J. (2013). Altered Anterior Insula Activation during Anticipation and Experience of Painful Stimuli in Expert Meditators. NeuroImage, 64, 538-546.
https://doi.org/10.1016/j.neuroimage.2012.09.030
[28] Lutz, J., Herwig, U., Opialla, S., Hittmeyer, A., Jancke, L., Rufer, M. et al. (2014). Mindfulness and Emotion Regulation—An fMRI Study. Social Cognitive and Affective Neuroscience, 9, 776-785.
https://doi.org/10.1093/scan/nst043
[29] Marusak, H. A., Elrahal, F., Peters, C. A., Kundu, P., Lombardo, M. V., Calhoun, V. D. et al. (2018). Mindfulness and Dynamic Functional Neural Connectivity in Children and Adolescents. Behavioural Brain Research, 336, 211-218.
https://doi.org/10.1016/j.bbr.2017.09.010
[30] Mason, M. F., Norton, M. I., Van Horn, J. D., Wegner, D. M., Grafton, S. T., & Macrae, C. N. (2007). Wandering Minds: The Default Network and Stimulus-Independent Thought. Science, 315, 393-395.
https://doi.org/10.1126/science.1131295
[31] Murakami, H., Katsunuma, R., Oba, K., Terasawa, Y., Motomura, Y., Mishima, K., & Moriguchi, Y. (2015). Neural Networks for Mindfulness and Emotion Suppression. PLoS ONE, 10, e0128005.
https://doi.org/10.1371/journal.pone.0128005
[32] Parkinson, T. D., Kornelsen, J., & Smith, S. D. (2019). Trait Mindfulness and Functional Connectivity in Cognitive and Attentional Resting State Networks. Frontiers in Human Neuroscience, 13, 112.
https://doi.org/10.3389/fnhum.2019.00112
[33] Prakash, R. S., De Leon, A. A., Klatt, M., Malarkey, W., & Patterson, B. (2012). Mindfulness Disposition and Default-Mode Network Connectivity in Older Adults. Social Cognitive and Affective Neuroscience, 8, 112-117.
https://doi.org/10.1093/scan/nss115
[34] Sevinc, G., Hölzel, B. K., Greenberg, J., Gard, T., Brunsch, V., Hashmi, J. A. et al. (2019). Strengthened Hippocampal Circuits Underlie Enhanced Retrieval of Extinguished Fear Memories Following Mindfulness Training. Biological Psychiatry, 86, 693-702.
https://doi.org/10.1016/j.biopsych.2019.05.017
[35] Simkin, D. R., & Black, N. B. (2014). Meditation and Mindfulness in Clinical Practice. Child and Adolescent Psychiatric Clinics of North America, 23, 487-534.
https://doi.org/10.1016/j.chc.2014.03.002
[36] Su, I. W., Wu, F. W., Liang, K. C., Cheng, K. Y., Hsieh, S. T., Sun, W. Z., & Chou, T. L. (2016). Pain Perception Can Be Modulated by Mindfulness Training: A Resting-State fMRI Study. Frontiers in Human Neuroscience, 10, 570.
https://doi.org/10.3389/fnhum.2016.00570
[37] Taren, A. A., Gianaros, P. J., Greco, C. M., Lindsay, E. K., Fairgrieve, A., Brown, K. W. et al. (2015). Mindfulness Meditation Training Alters Stress-Related Amygdala Resting State Functional Connectivity: A Randomized Controlled Trial. Social Cognitive and Affective Neuroscience, 10, 1758-1768.
https://doi.org/10.1093/scan/nsv066
[38] Taren, A. A., Gianaros, P. J., Greco, C. M., Lindsay, E. K., Fairgrieve, A., Brown, K. W. et al. (2017). Mindfulness Meditation Training and Executive Control Network Resting State Functional Connectivity: A Randomized Controlled Trial. Psychosomatic Medicine, 79, 674-683.
https://doi.org/10.1097/PSY.0000000000000466
[39] Tomasino, B., & Fabbro, F. (2016). Increases in the Right Dorsolateral Prefrontal Cortex and Decreases the Rostral Prefrontal Cortex Activation After-8 Weeks of Focused Attention Based Mindfulness Meditation. Brain and Cognition, 102, 46-54.
https://doi.org/10.1016/j.bandc.2015.12.004
[40] Wells, R. E., Yeh, G. Y., Kerr, C. E., Wolkin, J., Davis, R. B., Tan, Y. et al. (2013). Meditation’s Impact on Default Mode Network and Hippocampus in Mild Cognitive Impairment: A Pilot Study. Neuroscience Letters, 556, 15-19.
https://doi.org/10.1016/j.neulet.2013.10.001
[41] Xiao, Q., Zhao, X., Bi, G., Wu, L., Zhang, H., Liu, R. et al. (2019). Alterations of Regional Homogeneity and Functional Connectivity Following Short-Term Mindfulness Meditation in Healthy Volunteers. Frontiers in Human Neuroscience, 13, 376.
https://doi.org/10.3389/fnhum.2019.00376
[42] Yang, C. C., Barrós-Loscertales, A., Pinazo, D., Ventura-Campos, N., Borchardt, V., Bustamante, J. C. et al. (2016). State and Training Effects of Mindfulness Meditation on Brain Networks Reflect Neuronal Mechanisms of Its Antidepressant Effect. Neural Plasticity, 2016, Article ID: 9504642.
https://doi.org/10.1155/2016/9504642
[43] Zeidan, F., Emerson, N. M., Farris, S. R., Ray, J. N., Jung, Y., McHaffie, J. G., & Coghill, R. C. (2015). Mindfulness Meditation-Based Pain Relief Employs Different Neural Mechanisms than Placebo and Sham Mindfulness Meditation-Induced Analgesia. Journal of Neuroscience, 35, 15307-15325.
https://doi.org/10.1523/JNEUROSCI.2542-15.2015
[44] Zeidan, F., Martucci, K. T., Kraft, R. A., Gordon, N. S., McHaffie, J. G., & Coghill, R. C. (2011). Brain Mechanisms Supporting the Modulation of Pain by Mindfulness Meditation. Journal of Neuroscience, 31, 5540-5548.
https://doi.org/10.1523/JNEUROSCI.5791-10.2011
[45] Zeidan, F., Salomons, T., Farris, S. R., Emerson, N. M., Adler-Neal, A., Jung, Y., & Coghill, R. C. (2018). Neural Mechanisms Supporting the Relationship between Dispositional Mindfulness and Pain. Pain, 159, 2477-2485.
https://doi.org/10.1097/j.pain.0000000000001344
[46] Zou, T., Wu, C., & Fan, X. (2016). The Clinical Value, Principle, and Basic Practical Technique of Mindfulness Intervention. Shanghai Archives of Psychiatry, 28, 121-130.