Stochastic population model for electrical stimulation of the auditory nerve.
We have developed a biophysical model of a population of electrically stimulated auditory nerve fibers. It can be used to interpret results from physiological and behavioral experiments with cochlear implants and propose novel stimulation strategies. Our model consists of myelinated internodes described by a passive resistor-capacitor network, membrane capacitance, and leakage current at the nodes of Ranvier, as well as stochastic representations of nodal voltage-dependent channels. To approximate physiological properties measured in the auditory nerve (AN) of an acutely deafened cat, electrical parameters of the model fiber were chosen based on literature-reported values. Using our model, we have replicated the following properties within 10 % of the reported feline single-fiber measurements: relative spread (5.8 %), spike latency (630 micros), jitter (93 micros), chronaxie (238 micros), relative refractory period (4.6 ms), and conduction velocity (14 m/s). Moreover, we have successfully matched response characteristics of a population of fibers with the same number of diameter-distributed model fibers, enabling us to simulate responses of the entire AN. To demonstrate the performance of our model, we compare responses of a population of ANs stimulated with two speech encoding strategies, Continuous Interleaved Sampling and Compressed Analog.
Imennov
Nikita S
NS
Department of Bioengineering, University of Washington, Seattle, WA 98195, USA. imennov@u.washington.edu
Rubinstein
Jay T
JT
D000818:Animals; D002415:Cats; D003054:Cochlear Implants; D003056:Cochlear Nerve / Q000502:physiology*; D003198:Computer Simulation; D004558:Electric Stimulation / Q000379:methods*; D015640:Ion Channel Gating / Q000502:physiology; D008959:Models, Neurological; D009412:Nerve Fibers / Q000502:physiology; D011901:Ranvier's Nodes / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D013136:Spiral Ganglion / Q000502:physiology; D013269:Stochastic Processes