Nanoscale Nonlinear dynamic characterization of the neuron-electrode junction.
Extracellular recordings from neurons using microelectrode and field effect transistor arrays suffer from many problems including low signal to noise ratio, signal attenuation due to counter-ion diffusion from the bulk extracellular medium and a modification of the shape of the cell-generated potentials due to the presence of a highly dispersive dielectric medium in the cell-electrode cleft. Attempts to date to study the neuron-electrode interface have focused on point or area contact linear-equivalent-circuit models. We present here the results obtained from a 'data-true' nonlinear dynamic characterization of the neuron-electrode junction using Volterra-Wiener modeling. For the characterization, NG108-15 cells were cultured on microelectrode arrays and stimulated with broadband Gaussian white noise under voltage clamp mode. A Volterra-Wiener model was then estimated using the input signal and the extracellular signal recorded on the microelectrode. The existence of the second order Wiener kernel confirmed that the recorded extracellular signal had a nonlinear component. The verification of the estimated model was carried out by employing the intracellular action potential as an input to the Volterra-Wiener model and comparing the predicted extracellular response with the corresponding extracellular signal recorded on the microelectrode. We believe that a 'data-true' Volterra-Wiener model of the neuron-electrode junction shall not only facilitate a direct insight into the physicochemical processes taking place at the interface during signal transduction but will also allow one to evolve strategies for engineering the neuron-electrode interface using surface chemical modification of the microelectrodes.
Thakore
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Nanoscience Technology Center, University of Central Florida.
Behal
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Molnar
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Leistritz
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Hickman
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