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The Emergent Self: How Distributed Neural Networks Support Self-Representation

Part of the Handbooks of Sociology and Social Research book series (HSSR)

Abstract

The self has been conceptualized and divided into two main aspects—the mental/psychological and the physical/embodied self. This chapter describes how simulation by the mirror neuron system (MNS) may underlie a multitude of cognitions that constitute the self, including embodied self-representation and the understanding of other’s actions, and how the default mode network (DMN) may represent aspects of the mental self, including autobiographical memory and self-knowledge. Interactions of the DMN and MNS may subserve the integration of self-relevant traits within the context of autobiographical memory as well as future action goals—positioning the self as a “center of gravity” of one’s private and social behavior.

Keywords

  • Autism Spectrum Disorder
  • Diffusion Tensor Imaging
  • Default Mode Network
  • Autobiographical Memory
  • Inferior Parietal Lobule

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Molnar-Szakacs, I., Uddin, L.Q. (2013). The Emergent Self: How Distributed Neural Networks Support Self-Representation. In: Franks, D.D., Turner, J.H. (eds) Handbook of Neurosociology. Handbooks of Sociology and Social Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4473-8_13

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