DocumentCode
873547
Title
Modeling the neuron-microtransducer junction: from extracellular to patch recording
Author
Grattarola, Massimo ; Martinoia, Sergio
Author_Institution
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
Volume
40
Issue
1
fYear
1993
Firstpage
35
Lastpage
41
Abstract
A detailed characterization of the neuron-to-microtransducer junction, based on the equivalent electric-circuit approach, is provided. The recording of action potentials is then simulated with the general-purpose network-analysis program SPICE. Both noble-metal microelectrodes and insulated-gate FETs are considered. The responses of such devices are characterized as functions of several parameters, e.g. sealing impedance, density of ionic currents in the cell membrane, and spatial discontinuities of the adhesion process. It is shown that the various signal shapes reported in the literature can be reproduced and interpreted in terms of time derivatives of the action potential. In this way, the shape of any experimental signal can be interpreted on the basis of a specific sealing condition. Possible future improvements in microtransducer design, based on the proposed approach, are also suggested.
Keywords
bioelectric potentials; biological techniques and instruments; cellular biophysics; equivalent circuits; neurophysiology; physiological models; SPICE; action potential time derivatives; adhesion process; cell membrane; equivalent electric-circuit approach; experimental signal shape; extracellular recording; general-purpose network-analysis program; insulated-gate FETs; ionic currents density; neural modeling; neuron-to-microtransducer junction; noble-metal microelectrodes; patch recording; sealing impedance; spatial discontinuities; Adhesives; Biomembranes; Cells (biology); Extracellular; FETs; Impedance; Insulation; Microelectrodes; SPICE; Shape; Action Potentials; Cell Adhesion; Computer Simulation; Electric Impedance; Electrodes, Implanted; Equipment Design; Evaluation Studies as Topic; Extracellular Space; Microelectrodes; Models, Neurological; Nerve Net; Signal Processing, Computer-Assisted; Software;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/10.204769
Filename
204769
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