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International Conference on Artificial Neural Networks

ICANN 2017: Artificial Neural Networks and Machine Learning – ICANN 2017 pp 317–325Cite as

Weighted Clique Analysis Reveals Hierarchical Neuronal Network Dynamics

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10613))

Abstract

A biologically-plausible simulation of a neuronal network is studied as its topology is shaped by its activity by means of an encoding of its connectivity structure as a directed clique complex. Specially defined invariants of this mathematical structure, including the information about synaptic strength, are introduced and show how the initial topology of a network and its evolution during the simulation are tightly inter-related with the dynamical activity.

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Acknowledgments

This work was partially supported by the Swiss National Science Foundation grant CR13I1-138032.

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Authors and Affiliations

  1. NeuroHeuristic Research Group, University of Lausanne, Quartier Dorigny, 1015, Lausanne, Switzerland

    Paolo Masulli & Alessandro E. P. Villa

Authors
  1. Paolo Masulli
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  2. Alessandro E. P. Villa
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Corresponding author

Correspondence to Paolo Masulli .

Editor information

Editors and Affiliations

  1. University of Lausanne, Lausanne, Switzerland

    Alessandra Lintas

  2. University of Genoa, Genoa, Italy

    Stefano Rovetta

  3. Universitat Pompeu Fabra, Barcelona, Spain

    Paul F.M.J. Verschure

  4. University of Lausanne, Lausanne, Switzerland

    Alessandro E.P. Villa

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Masulli, P., Villa, A.E.P. (2017). Weighted Clique Analysis Reveals Hierarchical Neuronal Network Dynamics. In: Lintas, A., Rovetta, S., Verschure, P., Villa, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2017. ICANN 2017. Lecture Notes in Computer Science(), vol 10613. Springer, Cham. https://doi.org/10.1007/978-3-319-68600-4_37

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  • DOI: https://doi.org/10.1007/978-3-319-68600-4_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68599-1

  • Online ISBN: 978-3-319-68600-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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