• DocumentCode
    1349700
  • Title

    Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI

  • Author

    Yu, Theodore ; Sejnowski, Terrence J. ; Cauwenberghs, Gert

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of California San Diego, La Jolla, CA, USA
  • Volume
    5
  • Issue
    5
  • fYear
    2011
  • Firstpage
    420
  • Lastpage
    429
  • Abstract
    We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.
  • Keywords
    CMOS analogue integrated circuits; VLSI; circuit simulation; neurophysiology; potassium; reconfigurable architectures; CMOS; Hodgkin-Huxley model; Morris-Lecar model; NeuroDyn chip; biophysical membrane dynamics; biophysical neural spiking; biophysical parameters; bursting; circuit simulations; excitability dynamics; generalized channel kinetics; neural emulation platform; neuromorphic silicon-neuron interfaces; potassium activation; power 1.29 mW; reconfigurable analog VLSI; silicon models; single conductance parameter; size 0.5 mum; size 3 mm; spike frequency adaptation dynamics; synapse continuous-time analog VLSI programmable; Adaptation models; Biological system modeling; Biomembranes; Calcium; Integrated circuit modeling; Kinetic theory; Neurons; Analog VLSI; biophysical neural dynamics; neuromorphic engineering; programmable channel kinetics; silicon neuron interfaces; spiking neuron models;
  • fLanguage
    English
  • Journal_Title
    Biomedical Circuits and Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1932-4545
  • Type

    jour

  • DOI
    10.1109/TBCAS.2011.2169794
  • Filename
    6044731