A fast approximate method for predicting the behavior of auditory nerve fibers and the evoked compound action potential (ECAP) signal

Azam Ghanaei, S Mohammad Firoozabadi, Hamed Sadjedi

DOI: 10.4103/jmss.JMSS_28_20


Background: The goal of the current research is to develop a model based on computer simulations which describes both the behavior of the auditory nerve fibers and the cochlear implant system as a rehabilitation device. Methods: The approximate method was proposed as a low error and fast tool for predicting the behavior of auditory nerve fibers as well as the evoked compound action potential (ECAP) signal. In accurate methods every fiber is simulated; whereas, in approximate method information related to the response of every fiber and its characteristics such as the activation threshold of cochlear fibers are saved and interpolated to predict the behavior of a set of nerve fibers. Results: The approximate model can predict and analyze different stimulation techniques. Although precision is reduced to <1.66% of the accurate method, the required execution time for simulation is reduced by more than 98%. Conclusion: The amplitudes of the ECAP signal and the growth function were investigated by changing the parameters of the approximate model including geometrical parameters, electrical, and temporal parameters. In practice, an audiologist can tune the stimulation parameters to reach an effective restoration of the acoustic signal.


Approximate method, auditory nerve fiber, cochlear implant, evoked compound action potential growth function, model

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Zeng FG. Trends in cochlear implants. Trends Amplif 2004;8:1-34.

Yang H, Won JH, Choi I, Woo J. A computational study to model the effect of electrode-to-auditory nerve fiber distance on spectral resolution in cochlear implant. PLoS One 2020;15:e0236784.

Schvartz-Leyzac KC, Holden TA, Zwolan TA, Arts HA, Firszt JB, Buswinka CJ, et al. Effects of electrode location on estimates of neural health in humans with cochlear implants. J Assoc Res Otolaryngol 2020;21:259-75.

Bachmaier R, Encke J, Obando-Leitón M, Hemmert W, Bai S. Comparison of multi-compartment cable models of human auditory nerve fibers. Front Neurosci 2019;13:1173.

van Gendt MJ, Briaire JJ, Kalkman RK, Frijns JHM. Modeled auditory nerve responses to amplitude modulated cochlear implant stimulation. Hear Res 2017;351:19-33.

Bruce IC. Spatiotemporal coding of sound in the auditory nerve for cochlear implants. Univ Melbourne Depart Otolaryngol 1997.

Lai WK, Dillier N. A simple two-component model of the electrically evoked compound action potential in the human cochlea. Audiol Neurootol 2000;5:333-45.

He S, Teagle HF, Buchman CA. The electrically evoked compound action potential: From laboratory to clinic. Front Neurosci 2017;11:339.

Frijns JH, Briaire JJ, Schoonhoven R. Integrated use of volume conduction and neural models to simulate the response to cochlear implants. Simul Practi Theory 2000;8:75-97.

Cartee LA. Evaluation of a model of the cochlear neural membrane. II: Comparison of model and physiological measures of membrane properties measured in response to intrameatal electrical stimulation. Hear Res 2000;146:153-66.

Sadjedi H, Motamedi SA, Firoozabadi SM. A new modified multi-electrode stimulation method for ECAP recording in cochlear implant. Conf Proc IEEE Eng Med Biol Soc 2004;2004:4209-12.

Rattay F, Lutter P, Felix H. A model of the electrically excited human cochlear neuron: I. Contribution of neural substructures to the generation and propagation of spikes. Hear Res 2001;153:43-63.

Frijns JH, Mooij J, Ten Kate JH. A quantitative approach to modeling mammalian myelinated nerve fibers for electrical prosthesis design. IEEE Trans. Biomed Eng 1994;41:556-66.

Anabtawi N, Freeman S, Ferzli R. An auditory nerve stimulation chip with integrated AFE, sound processing, and power management for fully implantable cochlear implants. IEEE EMBS Int Conf Biomed Health Inform 2016;2016:616-9.

Briaire JJ, Frijns JH. Unraveling the electrically evoked compound action potential. Hear Res 2005;205:143-56.

Frijns JH, Briaire JJ, Grote JJ. The importance of human cochlear anatomy for the results of modiolus-hugging multichannel cochlear implants. Otol Neurotol 2001;22:340-9.

Cartee LA, van den Honert C, Finley CC, Miller RL. Evaluation of a model of the cochlear neural membrane. I. Physiological measurement of membrane characteristics in response to intrameatal electrical stimulation. Hear Res 2000;146:143-52.

Zarei E, Sadjedi H. A new approach for speech synthesis in cochlear implant systems based on electrophysiological factors. Technol Health Care 2017;25:221-35.

Miller CA, Abbas PJ, Robinson BK. Response properties of the refractory auditory nerve fiber. J Assoc Res Otolaryngol 2001;2:216-32.

Pfingst BE, Zhou N, Colesa DJ, Watts MM, Strahl SB, Garadat SN, et al. Importance of cochlear health for implant function. Hear Res 2015;322:77-88.

McKay CM, Smale N. The relation between ECAP measurements and the effect of rate on behavioral thresholds in cochlear implant users. Hear Res 2017;346:62-70.

Brill S, Müller J, Hagen R, Möltner A, Brockmeier SJ, Stark T, et al. Site of cochlear stimulation and its effect on electrically evoked compound action potentials using the MED-EL standard electrode array. Biomed Eng Online 2009;8:40.

van de Heyning P, Arauz SL, Atlas M, Baumgartner WD, Caversaccio M, Chester-Browne R, et al. Electrically evoked compound action potentials are different depending on the site of cochlear stimulation. Cochlear Implants Int 2016;17:251-62.

Hughes ML, Baudhuin JL, Goehring JL. The relation between auditory-nerve temporal responses and perceptual rate integration in cochlear implants. Hear Res 2014;316:44-56.


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