• DocumentCode
    59500
  • Title

    Neuron Array With Plastic Synapses and Programmable Dendrites

  • Author

    Ramakrishnan, Shankar ; Wunderlich, Ralf ; Hasler, J. ; George, Saly

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    7
  • Issue
    5
  • fYear
    2013
  • fDate
    Oct. 2013
  • Firstpage
    631
  • Lastpage
    642
  • Abstract
    We describe a novel neuromorphic chip architecture that models neurons for efficient computation. Traditional architectures of neuron array chips consist of large scale systems that are interfaced with AER for implementing intra- or inter-chip connectivity. We present a chip that uses AER for inter-chip communication but uses fast, reconfigurable FPGA-style routing with local memory for intra-chip connectivity. We model neurons with biologically realistic channel models, synapses and dendrites. This chip is suitable for small-scale network simulations and can also be used for sequence detection, utilizing directional selectivity properties of dendrites, ultimately for use in word recognition.
  • Keywords
    field programmable gate arrays; neurophysiology; reconfigurable architectures; AER; address event representation; biologically realistic channel models; directional selectivity properties; interchip communication; interchip connectivity; intrachip connectivity; local memory; neuromorphic chip architecture; neuron array; neuron array chips; plastic synapses; programmable dendrites; reconfigurable FPGA-style routing; sequence detection; small-scale network simulations; word recognition; Arrays; Computational modeling; Field programmable gate arrays; Neurons; Routing; Dendritic computation and processing; field programmable analog arrays (FPAA); floating-gate devices; on-chip learning; Dendrites; Microarray Analysis; Models, Neurological; Neural Networks (Computer); Neurons; Plastics; Synapses;
  • fLanguage
    English
  • Journal_Title
    Biomedical Circuits and Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1932-4545
  • Type

    jour

  • DOI
    10.1109/TBCAS.2013.2282616
  • Filename
    6637106