Modeling of spike trains in auditory nerves with self-exciting point processes of the von Mises type

This article presents the modeling of spike trains in auditory nerve fiber (ANF) models with a one-memory self-exciting point process (SEPP) of the von Mises type. The ANF models were acoustically stimulated by a synaptic current of inner hair cells, or electrically stimulated by sinusoidally amplitude-modulated pulsatile waveforms. It has been shown that the parameters of one-memory SEPP of the von Mises type could be estimated by numerically maximizing the likelihood function from sample realizations of the spike trains in response to acoustic or electric stimulus. Furthermore, it was found that period histograms of the one-memory SEPP generated artificially on the basis of the estimated von Mises parameters agreed well with those of acoustic or electric stimulus, by performing the uniform-scores test. It implies that the waveforms of pulsatile electric stimuli should be selected such that the spike trains can be represented by one-memory SEPP of the von Mises type with appropriate parameters, efficiently carrying information to the cochlear implant user's brain, like that in acoustic stimulation of the healthy ear. The findings presented in this paper may play an important role in determining optimal parameters of pulsatile electric stimuli by using one-memory SEPP of the von Mises type, and further in the design of better cochlear prostheses.