• DocumentCode
    2778342
  • Title

    Modeling attentional loop in the insect Mushroom Bodies

  • Author

    Arena, Paolo ; Patané, Luca ; Termini, Pietro Savio

  • Author_Institution
    Dipt. di Ing. Elettr., Elettron. e Inf., Univ. degli Studi di Catania, Catania, Italy
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Insects show advanced capabilities and a rich behavioral repertoire in task solving and thus they are becoming a reference point in Neuroscience for studying simple cognitive structures. In particular, thanks to many neurogenetic tools, the fruit fly Drosophila melanogaster became a relevant source of inspiration for Robotics. Mushroom Bodies (MBs) are very interesting neural structures involved in the regulation of behaviors in fruit fly, even if their main role regards olfactory conditioning. In this paper a novel bio-inspired neural architecture is presented, where the MBs role in attention tasks is focused. The model is a multi-layer spiking neural network where the MBs and their direct and or indirect interactions to other key elements of the insect brain, the Central Complex and the Lateral Horns, are modeled. The biological background of the proposed model is presented together with a detailed description of the architecture; simulation results and remarks on the biological counterpart are also reported.
  • Keywords
    multilayer perceptrons; neural net architecture; robots; attentional loop modeling; behavioral repertoire; bioinspired neural architecture; biological background; central complex; cognitive structure; fruit fly Drosophila melanogaster; insect brain; insect mushroom body; lateral horn; multilayer spiking neural network; neural structure; neurogenetic tool; neuroscience; olfactory conditioning; robotics; task solving; Biological system modeling; Brain modeling; Insects; Lattices; Neurons; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2012 International Joint Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-1488-6
  • Electronic_ISBN
    2161-4393
  • Type

    conf

  • DOI
    10.1109/IJCNN.2012.6252833
  • Filename
    6252833