• DocumentCode
    3383887
  • Title

    A VLSI network of spiking neurons with plastic fully configurable “stop-learning” synapses

  • Author

    Giulioni, M. ; Camilleri, P. ; Dante, V. ; Badoni, D. ; Indiveri, G. ; Braun, J. ; Giudice, P. Del

  • fYear
    2008
  • fDate
    Aug. 31 2008-Sept. 3 2008
  • Firstpage
    678
  • Lastpage
    681
  • Abstract
    We describe and demonstrate a neuromorphic, analog VLSI chip (termed F-LANN) hosting 128 integrate-and-fire (IF) neurons with spike-frequency adaptation, and 16,384 plastic bistable synapses implementing a self-regulated form of Hebbian, spike-driven, stochastic plasticity. The chip is designed to offer a high degree of reconfigurability: each synapse may be individually configured at any time to be either excitatory or inhibitory and to receive either recurrent input from an on-chip neuron or AER-based input from an off-chip neuron. The initial state of each synapse can be set as potentiated or depressed, and the state of each synapse can be read and stored on a computer.
  • Keywords
    VLSI; networks (circuits); VLSI network; integrate-and-fire neurons; plastic stop-learning synapses; spike-frequency adaptation; spiking neurons; Biological system modeling; Biology computing; Computational modeling; Dynamic range; Neuromorphics; Neurons; Plastics; Stochastic processes; Uniform resource locators; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Circuits and Systems, 2008. ICECS 2008. 15th IEEE International Conference on
  • Conference_Location
    St. Julien´s
  • Print_ISBN
    978-1-4244-2181-7
  • Electronic_ISBN
    978-1-4244-2182-4
  • Type

    conf

  • DOI
    10.1109/ICECS.2008.4674944
  • Filename
    4674944