Strategies for Improving Neural Signal Detection Using a Neural-Electronic Interface
© 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. The definitive version is available at http://dx.doi.org/10.1109/TNSRE.2003.810559.
NOTE: At the time of publication, the author Robert Szlavik was not yet affiliated with Cal Poly.
There have been various theoretical and experimental studies presented in the literature that focus on interfacing neurons with discrete electronic devices, such as transistors. From both a theoretical and experimental perspective, these studies have emphasized the variability in the characteristics of the detected action potential from the nerve cell. The demonstrated lack of reproducible fidelity of the nerve cell action potential at the device junction would make it impractical to implement these devices in any neural prosthetic application where reliable detection of the action potential was a prerequisite. In this study, the effects of several different physical parameters on the fidelity of the detected action potential at the device junction are investigated and discussed. The impact of variations in the extracellular resistivity, which directly affects the junction seal resistance, is studied along with the impact of variable nerve cell membrane capacitance and variations in the injected charge. These parameters are discussed in the context of their suitability to design manipulation for the purpose of improving the fidelity of the detected neural action potential. In addition to investigating the effects of variations in these parameters, the applicability of the linear equivalent circuit approach to calculating the junction potential is investigated.
Robert B. Szlavik. "Strategies for Improving Neural Signal Detection Using a Neural-Electronic Interface" IEEE Transactions on Neural Systems and Rehabilitation Engineering 11.1 (2003): 1-8.
Available at: http://works.bepress.com/rszlavik/3