• DocumentCode
    1185132
  • Title

    Analog CMOS synaptic learning circuits adapted from invertebrate biology

  • Author

    Schneider, Christian ; Card, Howard

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
  • Volume
    38
  • Issue
    12
  • fYear
    1991
  • fDate
    12/1/1991 12:00:00 AM
  • Firstpage
    1430
  • Lastpage
    1438
  • Abstract
    Analog CMOS circuits implementing abstractions of certain biological synaptic processes are presented. In particular, the circuits extract features of synaptic learning observed in the marine mollusk Aplysia. Two types of nonassociative learning, habituation and sensitization, as well as associative learning (classical conditioning), are modeled. The synaptic learning rules used by Aplysia are considerably more complex than those typically used in artificial neural networks (ANNs), leading to the speculation that additional biological detail may be beneficial in ANN models. The synaptic circuitry described is expected to be useful as a basic primitive in ANNs with higher order synapses and learning rules that perform temporal association of multiple inputs
  • Keywords
    CMOS integrated circuits; analogue circuits; learning systems; neural nets; ANNs; Aplysia; analogue CMOS synaptic learning circuits; associative learning; biological synaptic processes; habituation; invertebrate biology; learning rules; marine mollusk; multiple inputs; nonassociative learning; sensitization; synaptic circuitry; temporal association; Artificial neural networks; Biological neural networks; Biological system modeling; Biology computing; CMOS analog integrated circuits; CMOS process; Computational biology; Feature extraction; Semiconductor device modeling; Transconductance;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0098-4094
  • Type

    jour

  • DOI
    10.1109/31.108497
  • Filename
    108497