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International Work-Conference on Artificial Neural Networks

IWANN 2011: Advances in Computational Intelligence pp 547–553Cite as

Realistic Modeling of Large-Scale Networks: Spatio-temporal Dynamics and Long-Term Synaptic Plasticity in the Cerebellum

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6691))

Abstract

A large-scale computational model of the cerebellum granular layer has been adapted to generate long-term synaptic plasticity in response to afferent mossy fiber bursts. A simple learning rule was elaborated in order to link the average granule cell depolarization to LTP and LTD. Briefly, LTP was generated for membrane potentials >-40 mV and LTD for membrane potentials <-40 mV. The result was to generate LTP and stronger excitation in the core of active clusters, which were surrounded by LTD. These changes were accompanied by a faster and stronger spike generation compared to the surround. These results reproduce the experimental observations and provide a valuable and efficient tool for implementing autonomous learning algorithms in the cerebellar neuronal network.

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Author information

Authors and Affiliations

  1. Department of Physiology, University of Pavia, Via Forlanini 6, I-27100, Pavia, Italy

    Egidio D’Angelo

  2. Brain Connectivity Center, Istituto Neurologico IRCCS Fondazione C. Mondino, Via Mondino 2, I-27100, Pavia, Italy

    Egidio D’Angelo & Sergio Solinas

  3. Consorzio Interuniversitario per le Scienze Fisiche della Materia (CNISM), Via Bassi 6, I-27100, Pavia, Italy

    Sergio Solinas

Authors
  1. Egidio D’Angelo
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  2. Sergio Solinas
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Editor information

Editors and Affiliations

  1. Departament d’Enginyeria Electrònica, Universitat Politècnica de Catalunya (UPC), Campus Nord, Edificio C4, c/ Gran Capità s/n, 08034, Barcelona, Spain

    Joan Cabestany

  2. Department of Computer Architecture and Computer Technology, University of Granada, C/ Periodista Daniel Saucedo Aranda, 18071, Granada, Spain

    Ignacio Rojas

  3. Departamento Tecnologia Eletrónica, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Gonzalo Joya

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© 2011 Springer-Verlag Berlin Heidelberg

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D’Angelo, E., Solinas, S. (2011). Realistic Modeling of Large-Scale Networks: Spatio-temporal Dynamics and Long-Term Synaptic Plasticity in the Cerebellum. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21501-8_68

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  • DOI: https://doi.org/10.1007/978-3-642-21501-8_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21500-1

  • Online ISBN: 978-3-642-21501-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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