A phenomenological model of myelinated nerve with a dynamic threshold

To evaluate coding strategies for cochlear implants a model of the human cochlear nerve is required. Nerve models based on voltage-clamp experiments, such as the Frankenhaeuser-Huxley model of myelinated nerve, can have over forty parameters and are not amenable for fitting to physiological data from a different animal or type of nerve. Phenomenological nerve models, such as leaky integrate-and-fire (LIF) models, have fewer parameters but have not been validated with a wide range of stimuli. In the absence of substantial cochlear nerve data, we have used data from a toad sciatic nerve for validation (50 Hz to 2 kHz with levels up to 20 dB above threshold). We show that the standard LIF model with fixed refractory properties and a single set of parameters cannot adequately predict the toad rate-level functions. Given the deficiency of this standard model, we have abstracted the dynamics of the sodium inactivation variable in the Frankenhaeuser-Huxley model to develop a phenomenological LIF model with a dynamic threshold. This nine-parameter model predicts the physiological rate-level functions much more accurately than the standard LIF model. Because of the low number of parameters, we expect to be able to optimize the model parameters so that the model is more appropriate for cochlear implant simulations