DocumentCode :
1289162
Title :
A silicon model of the Hirudo swim oscillator
Author :
Wolpert, Seth ; Friesen, W. Otto ; Laffely, Andrew J.
Author_Institution :
Dept. of Electr. Eng., Pennsylvania State Univ. Harrisburg, Middletown, PA, USA
Volume :
19
Issue :
1
fYear :
2000
Firstpage :
64
Lastpage :
75
Abstract :
Discusses using VLSI-based technology for recreating living neuronal circuits. The authors describe a study in which one subunit of the oscillatory network of the leech Hirudo medicinalis was reconstructed on a cell-by-cell, synapse-by-synapse basis using dedicated IC-based neural elements. The network consists of 11 cells in which 34 distinct multicellular oscillators are embedded. In functional tests, the circuit displayed rhythms and waveforms that closely resembled those of its living counterparts. In parametric tests, the network displayed remarkable robustness over a broad range of intracellular and synaptic parameters. From these tests, analysis of the network imparted insights into its design and function. The comprehensive nature of the neuronal element´s design and the efficiency afforded by very-large-scale-integrated (VLSI) technology has greatly facilitated the endeavour of modeling neuronal networks and processes in analog electronic circuitry.
Keywords :
VLSI; biological techniques; cellular biophysics; neural nets; neurophysiology; zoology; Hirudo medicinalis; Hirudo swim oscillator; VLSI-based technology; analog electronic circuitry; dedicated IC-based neural elements; functional tests; intracellular parameters; leech; living neuronal circuits recreation; multicellular oscillators; oscillatory network subunit; rhythms; silicon model; synaptic parameters; waveforms; Biomembranes; Circuit testing; Integrated circuit modeling; Large Hadron Collider; Neural networks; Neurons; Oscillators; Rhythm; Silicon; Very large scale integration; Action Potentials; Animals; Axons; Computer Simulation; Dendrites; Electric Conductivity; Electric Impedance; Electronics, Medical; Ganglia, Invertebrate; Leeches; Membrane Potentials; Models, Neurological; Nerve Net; Neural Inhibition; Neurons; Oscillometry; Refractory Period, Electrophysiological; Silicon; Swimming; Synapses;
fLanguage :
English
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
Publisher :
ieee
ISSN :
0739-5175
Type :
jour
DOI :
10.1109/51.816245
Filename :
816245
Link To Document :
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