TY - JOUR T1 - Spike-conducting integrate-and-fire model JF - eneuro JO - eNeuro DO - 10.1523/ENEURO.0112-18.2018 SP - ENEURO.0112-18.2018 AU - Go Ashida AU - Waldo Nogueira Y1 - 2018/08/27 UR - http://www.eneuro.org/content/early/2018/08/27/ENEURO.0112-18.2018.abstract N2 - Modeling is a useful tool for investigating various biophysical characteristics of neurons. Recent simulation studies of propagating action potentials (spike conduction) along axons include the investigation of neuronal activity evoked by electrical stimulation from implantable prosthetic devices. In contrast to point-neuron simulations, where a large variety of models are readily available, Hodgkin-Huxley (HH)-type conductance-based models have been almost the only option for simulating axonal spike conduction, as simpler models cannot faithfully replicate the waveforms of propagating spikes. Since the amount of available physiological data, especially in humans, is usually limited, calibration and justification of the large number of parameters of a complex model is generally difficult. In addition, not all simulation studies of axons require detailed descriptions of nonlinear ionic dynamics. In this study, we construct a simple model of spike generation and conduction based on the exponential integrate-and-fire model, which can simulate the rapid growth of the membrane potential at spike initiation. In terms of the number of parameters and equations, this model is much more compact than conventional models, but can still reliably simulate spike conduction along myelinated and unmyelinated axons that were stimulated intracellularly or extracellularly. Our simulations of auditory nerve fibers with this new model suggest that, because of the difference in intrinsic membrane properties, the axonal spike conduction of high-frequency nerve fibers is faster than that of low-frequency fibers. The simple model developed in this study can serve as a computationally efficient alternative to more complex models for future studies, including simulations of neuroprosthetic devices.Significance Statement Conduction of electrical impulses (action potentials) along the axon is essential for information transfer between neurons. Simulation studies of propagating action potentials, which earlier focused on the biophysical mechanisms of conduction, have progressed to investigations of pathological malfunctions of nerves and electrical stimulations via prostheses. In contrast to dimensionless, single-neuron modeling, for which a number of different approaches are available, simulation of nerve conduction generally requires a complex model of ionic conductances to reproduce propagating action potentials. In this study, we present a simplified phenomenological model of axonal conduction with increased computational efficiency and a reduced number of parameters. This simple model can be used as an alternative to conventional models, especially for applications including prosthetic simulations of nerve conduction. ER -