• DocumentCode
    1247441
  • Title

    A bio-physically inspired silicon neuron

  • Author

    Farquhar, Ethan ; Hasler, Paul

  • Author_Institution
    Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    52
  • Issue
    3
  • fYear
    2005
  • fDate
    3/1/2005 12:00:00 AM
  • Firstpage
    477
  • Lastpage
    488
  • Abstract
    The physical principles governing ion flow in biological neurons share interesting similarities to electron flow through the channels of MOSFET transistors. Here, is described a circuit which exploits the similarities better than previous approaches to build an elegant circuit with electrical properties similar to real biological neurons. A two-channel model is discussed including sodium (Na+) and potassium (K+). The Na+ channel uses four transistors and two capacitors. The K+ channel uses two transistors and one capacitor. One more capacitor simulates the neuron membrane capacitance yielding a total circuit of four capacitors and six transistors. This circuit operates in real-time, is fabricated on standard CMOS processes, runs in subthreshold, and has a power supply similar to that of real biology. Voltage and current responses of this circuit correspond well with biology in terms of shape, magnitude, and time.
  • Keywords
    CMOS integrated circuits; MOSFET; bioelectric potentials; capacitors; neural nets; CMOS process; MOSFET transistor; analog circuits; bioelectric potentials; biological cells; biological neurons; biophysically inspired silicon neuron; capacitors; electron flow; nervous system; neuron membrane capacitance; two-channel model; Biological system modeling; Biomembranes; CMOS process; Capacitance; Capacitors; Circuit simulation; Electrons; MOSFET circuits; Neurons; Silicon; Analog circuits; bioelectric potentials; biological cells; nervous system;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems I: Regular Papers, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1549-8328
  • Type

    jour

  • DOI
    10.1109/TCSI.2004.842871
  • Filename
    1406175