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International Conference on Artificial Neural Networks

ICANN 2016: Artificial Neural Networks and Machine Learning – ICANN 2016 pp 145–152Cite as

On Higher Order Computations and Synaptic Meta-Plasticity in the Human Brain

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9887))

Abstract

Glia modify neuronal connectivity by creating structural changes in the neuronal connectome. Glia also influence the functional connectome by modifying the flow of information through neural networks (Fields et al. 2015 [6]). There are strong experimental evidences that glia are responsible for synaptic meta-plasticity. Synaptic plasticity is the modification of the strength of connections between neurons. Meta-plasticity, i.e. plasticity of synaptic plasticity, may be viewed as mechanisms for dynamic reconfiguration of neural circuits. Since synapse creation corresponds to the mathematical notion of function composition, the mechanisms may serve as a grounding for functionals, i.e. higher order functions that take functions as their arguments.

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Author information

Authors and Affiliations

  1. Siedlce University of Natural Sciences and Humanities, Siedlce, Poland

    Stanisław Ambroszkiewicz

  2. Institute of Computer Science, Polish Academy of Sciences, Warszawa, Poland

    Stanisław Ambroszkiewicz

Authors
  1. Stanisław Ambroszkiewicz
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Correspondence to Stanisław Ambroszkiewicz .

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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© 2016 Springer International Publishing Switzerland

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Ambroszkiewicz, S. (2016). On Higher Order Computations and Synaptic Meta-Plasticity in the Human Brain. 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 9887. Springer, Cham. https://doi.org/10.1007/978-3-319-44781-0_18

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  • DOI: https://doi.org/10.1007/978-3-319-44781-0_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44780-3

  • Online ISBN: 978-3-319-44781-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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