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
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