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Social Neuroeconomics : A dynamical systems perspective

Author

Listed:
  • Olivier Oullier
  • J. A. Scott Kelso
  • Alan P. Kirman

Abstract

In this article we examine social neuroeconomics from a complex systems point of view, that is rooted in the theory and methods of informationally coupled self-organizing dynamical systems. Our contribution focuses on establishinng a theoretical perspective within which one can interpret experiments recently published in the field of neuroeconomics. We explain how the concepts and methods of coordination dynamics may impact future neuroeconomics research. We address the non-equivalence problem between different levels of analysis that has received little if no attention in neuroeconomics. We also discuss how coordination dynamics might provide novel routes to studying the relation between brain activity and decision-making. One should not reduce economics to physics, nor should one aim at providing a single framework for economics and neuroscience. Rather one should seek, in these fields, to define more clearly the various levels of description and their shared dynamics. This should help us to understand interactions between various levels of analysis in neuroeconomics.

Suggested Citation

  • Olivier Oullier & J. A. Scott Kelso & Alan P. Kirman, 2008. "Social Neuroeconomics : A dynamical systems perspective," Revue d'├ęconomie politique, Dalloz, vol. 118(1), pages 51-62.
  • Handle: RePEc:cai:repdal:redp_181_0051
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