意识整合理论 实现自我神经可塑性的心理学和遗传学途径

Foojan Zeine , Nicole Jafari , Mohammad Nami , Kenneth Blum
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引用次数: 0

摘要

自我意识技术有助于提高大脑与生俱来的能力,通过神经可塑性和自我引导的清晰度来适应变化,同时改善神经网络路径。人脑具有可塑性,能够进行修改和改变,实现路径连接。这种适应性既受到 DNA 多态性先决条件的影响,也受到环境引起的表观遗传学对蛋白质转录的积极或消极影响。具有神经可塑性的大脑外周部分使大脑能够根据新情况和新想法进行改变和调整。大脑的神经可塑性是神经系统改变和适应外部和内部刺激的一种能力,通过应用意识整合治疗理论,大脑的神经可塑性可以达到更高的效能水平。意识整合理论(AIT)是一种以证据为基础的技术,它引导和指导人们检查思想、情绪、行为、障碍和可塑性阻力,同时提供通往清晰和自我神经可塑性的途径。通过重组认知/情绪模式并与行为路径相连接,基于 AIT 的疗法可望帮助创建新的神经网络路径,从而更新功能性神经连接。作为一种释放创伤的方法,AIT 围绕核心信念、情绪和身体属性来获取原始记忆,并逐步实现功能神经网络的整合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Awareness integration theory A Psychological and genetic path to self-directed Neuroplasticity

The self-awareness technique is instrumental in increasing the efficacy of the brain's innate ability to adapt to change via neuroplasticity and self-directing clarity while improving neuro-network paths. The human brain is plastic and capable of modifiability and change, enabling pathway connectivity. This adaptability is affected by both DNA polymorphic antecedents and positive or negative environmental-induced epigenetic-induced alteration of protein transcription. The peripheral part of the brain, capable of neuroplasticity, enables the brain to change and adapt itself to new situations and novel ideas. The brain's neuroplasticity, a capability of the nervous system to change and adapt to external and internal stimuli, can reach a higher efficacy level by applying the awareness integration therapeutical theory. Awareness Integration Theory (AIT) is an evidence-based technique that guides and directs the process of examining thoughts, emotions, behaviors, obstacles, and resistance to plasticity while providing pathways to clarity and self-directed neuroplasticity. By restructuring cognitive/emotional schemas and linking to behavioral pathways, AIT-based therapy expectedly helps create new neural network paths, leading to a renewed functional neural connectivity. As a trauma-releasing approach, AIT revolves around core beliefs, emotions, and bodily attributes to access original memories and moves toward the integration of functional neural networks.

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来源期刊
Health sciences review (Oxford, England)
Health sciences review (Oxford, England) Medicine and Dentistry (General)
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