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Neural Algebra and Consciousness: A Theory of Structural Functionality in Neural Nets

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 5147)

Abstract

Thoughts are spatio-temporal patterns of coalitions of firing neurons and their interconnections. Neural algebras represent these patterns as formal algebraic objects, and a suitable composition operation reflects their interaction. Thus, a neural algebra is associated with any neural net. The present paper presents this formalization and develops the basic algebraic tools for formulating and solving the problem of finding the neural correlates of concepts such as reflection, association, coordination, etc. The main application is to the notion of consciousness, whose structural and functional basis is made explicit as the emergence of a set of solutions to a fixpoint equation.

Keywords

  • Neural nets
  • combinatory algebra
  • functional structures
  • emergent properties
  • models of consciousness

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Engeler, E. (2008). Neural Algebra and Consciousness: A Theory of Structural Functionality in Neural Nets. In: Horimoto, K., Regensburger, G., Rosenkranz, M., Yoshida, H. (eds) Algebraic Biology. AB 2008. Lecture Notes in Computer Science, vol 5147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85101-1_8

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  • DOI: https://doi.org/10.1007/978-3-540-85101-1_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85100-4

  • Online ISBN: 978-3-540-85101-1

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