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A System-Level Model of Noradrenergic Function

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Artificial Neural Networks and Machine Learning – ICANN 2016 (ICANN 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9886))

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Abstract

Neuromodulation is an interesting way to display different modes of functioning in a complex network. The effect of Noradrenaline has often been related to the exploration/exploitation trade-off and implemented in models by modulation of the gain of activation function. In this paper, we show that this mechanism is not sufficient for system-level networks and propose another way to implement it, exploiting reported inhibition of a striatal region by Noradrenaline. We describe here the corresponding model and report its performances in a reversal task.

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Author information

Authors and Affiliations

  1. LaBRI, Université de Bordeaux, Bordeaux INP, CNRS, UMR 5800, Talence, France

    Maxime Carrere & Frédéric Alexandre

  2. Inria Bordeaux Sud-Ouest, 200 Avenue de la Vieille Tour, 33405, Talence, France

    Maxime Carrere & Frédéric Alexandre

  3. IMN, Université de Bordeaux, CNRS, UMR 5293, Bordeaux, France

    Maxime Carrere & Frédéric Alexandre

Authors
  1. Maxime Carrere
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  2. Frédéric Alexandre
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Correspondence to Maxime Carrere .

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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Carrere, M., Alexandre, F. (2016). A System-Level Model of Noradrenergic Function. 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_25

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  • DOI: https://doi.org/10.1007/978-3-319-44778-0_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44777-3

  • Online ISBN: 978-3-319-44778-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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