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Asymmetries in Synaptic Connections and the Nonlinear Fokker-Planck Formalism

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Abstract

In previous work we have developed illustrative, neurocomputational models to describe mechanisms associated with mental processes. In these efforts, we have considered mental processes in phenomena such as neurosis, creativity, consciousness/unconsciousness, and some characteristics of the psychoses. Memory associativity is a key feature in the theoretical description of these phenomena, and much of our work has focused on modeling this mechanism. In traditional neural network models of memory, the symmetry of synaptic connections is a necessary condition for reaching stationary states. The assumption of symmetric weights seems however to be biologically unrealistic. Efforts to model stationary network states with asymmetric weights are mathematically complex and are usually applied to restricted situations. This has motivated us to explore the possibility of a new approach to the synaptic symmetry problem, based on its analogies with some features of the nonlinear Fokker-Planck formalism.

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Acknowledgments

We acknowledge financial support from the Brazilian National Research Council (CNPq), the Rio de Janeiro State Research Foundation (FAPERJ) and the Brazilian agency which funds graduate studies (CAPES).

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Authors and Affiliations

  1. Instituto de Matemática e Estatística, Universidade do Estado do Rio de Janeiro, Rua São Francisco Xavier, 524, Rio de Janeiro, RJ, 20550-900, Brazil

    Roseli S. Wedemann

  2. CeBio, Universidad del Noroeste de la Provincia de Buenos Aires, UNNOBA-Conicet, Roque Saenz Peña 456, Junin, Argentina

    Angel R. Plastino

Authors
  1. Roseli S. Wedemann
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  2. Angel R. Plastino
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Correspondence to Roseli S. Wedemann .

Editor information

Editors and Affiliations

  1. University of Lausanne, Lausanne, Switzerland

    Alessandro E.P. Villa

  2. University of Lausanne, Lausanne, Switzerland

    Paolo Masulli

  3. Universitat Politécnica de Catalunya, Terrrassa, Spain

    Antonio Javier Pons Rivero

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Wedemann, R.S., Plastino, A.R. (2016). Asymmetries in Synaptic Connections and the Nonlinear Fokker-Planck Formalism. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9886. Springer, Cham. https://doi.org/10.1007/978-3-319-44778-0_3

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  • DOI: https://doi.org/10.1007/978-3-319-44778-0_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44777-3

  • Online ISBN: 978-3-319-44778-0

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