Last Update: 08/23/2006 Printer Friendly Printer Friendly   Email This Page Email This Page  

Modeling The Excitability Of Mammalian Nerve Fibers: Function Follows Form
 
Cameron C. McIntyre, Andrew G. Richardson, and Warren M. Grill
Department of Biomedical Engineering, Case Western Reserve University

The goal of this project was to develop models of mammalian motor axons able to reproduce documented excitation characteristics. Existing models of mammalian peripheral nerve fibers have a wide range of limitations in their ability to reproduce experimental data and, as a result, there exists a need for improved models to extend understanding of the underlying biophysics of neural excitation. The newly developed models incorporated a double-cable structure, with explicit representation of the nodes of Ranvier, paranode and internodal sections of the axon, as well as a finite impedance myelin sheath. These models were able to match a wide range of independent experimental data sets. The combination of an accurate representation of the ion channels at the node (based on experimental studies of human, cat and rat) and matching the geometry of the node, paranode, internode and myelin to that of experimentally measured morphology (necessitating the double cable representation) allowed for accurate reproduction of experimentally measured excitation characteristics. Using these models we were able to determine the origin of the post-action potential recovery cycle. These models represent powerful tools for use in the design of stimulus waveforms for neuroprosthetic devices. This work was supported by the NSF (BES-9709488), NIH-NCMRR (HD-07500), and the Whitaker Foundation.

Model for Neuroprosthetic Devices

 

Figure 1: Models were generated with fiber diameters ranging from 5.7-16.0 mm with geometries based on experimental measurements. The internodal sections of the model were modeled with linear components while the nodal sections contained nonlinear fast and persistent sodium channels as well as slow potassium channels.