• DocumentCode
    868925
  • Title

    A multiconductance silicon neuron with biologically matched dynamics

  • Author

    Simoni, Mario F. ; Cymbalyuk, Gennady S. ; Sorensen, Michael E. ; Calabrese, Ronald L. ; DeWeerth, Stephen P.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    51
  • Issue
    2
  • fYear
    2004
  • Firstpage
    342
  • Lastpage
    354
  • Abstract
    We have designed, fabricated, and tested an analog integrated-circuit architecture to implement the conductance-based dynamics that model the electrical activity of neurons. The dynamics of this architecture are in accordance with the Hodgkin-Huxley formalism, a widely exploited, biophysically plausible model of the dynamics of living neurons. Furthermore the architecture is modular and compact in size so that we can implement networks of silicon neurons, each of desired complexity, on a single integrated circuit. We present in this paper a six-conductance silicon-neuron implementation, and characterize it in relation to the Hodgkin-Huxley formalism. This silicon neuron incorporates both fast and slow ionic conductances, which are required to model complex oscillatory behaviors (spiking, bursting, subthreshold oscillations).
  • Keywords
    CMOS analogue integrated circuits; VLSI; bioelectric potentials; neural chips; neurophysiology; operational amplifiers; Hodgkin-Huxley formalism; VLSI circuits; analog integrated-circuit; biologically matched dynamics; bursting; central pattern generators; complex oscillatory behaviors; conductance-based dynamics; fast ionic conductances; living neurons; modular architecture; multiconductance silicon neuron; neuromorphic engineering; neuron electrical activity; operational transconductance amplifiers; six-conductance silicon-neuron implementation; slow ionic conductances; spiking; subthreshold oscillations; voltage-dependent conductance; Biological neural networks; Biological system modeling; Biology computing; Circuits; Neural engineering; Neuromorphic engineering; Neurons; Silicon; Space technology; Very large scale integration; Action Potentials; Animals; Biological Clocks; Biomimetic Materials; Biomimetics; Computer Simulation; Electric Conductivity; Electronics; Equipment Design; Equipment Failure; Heart Conduction System; Interneurons; Leeches; Membrane Potentials; Models, Neurological; Neurons; Semiconductors;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2003.820390
  • Filename
    1262112