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随着社会认知神经科学的蓬勃发展,研究者们发现对自我的表征主要涉及两个神经网络,即通过自动模拟机制提供具身性自我表征的镜像神经元网络,与处理自我离身概念信息的默认网络。我们分别从单个网络与网络整合的角度,回顾讨论了这两个网络对自我信息表征加工的作用。默认网络与镜像神经网络在具身和离身层面对自我的表征,为我们理解自我提供了新的视角。默认网络与镜像神经网络之间相互作用的机制,也为我们理解具身认知与离身认知的关系提供了基础,帮助我们更加清晰地认识人类认知或心智的本质。
With the rapid development of social cognitive neuroscience, researchers found that the representation of the self mainly involves two neural networks, that is, a mirror network of neurons that provides self-representation through self-simulation mechanisms, The default network. We review the role of these two networks in the processing of self-information representation from the perspective of integrating a single network with the network respectively. The default network and mirror neural network in the body and the self-manifestation of the sub-level for us to understand self provides a new perspective. The mechanism of the interaction between the default network and the mirror neural network also provides a basis for us to understand the relationship between the cognitive body and the cognitive body, helping us to understand more clearly the essence of human cognition or mind.