The auditory nerve (AN) compound action potential (CAP) is an important tool for assessing auditory disorders and monitoring the health of the auditory periphery during surgical procedures. The CAP has been mathematically conceptualized as the convolution of a unit response (UR) waveform with the firing rate of a population of AN fibers. Here, an approach for predicting experimentally recorded CAPs in humans is proposed, which involves the use of human-based computational models to simulate AN activity. CAPs elicited by clicks, chirps, and amplitude-modulated carriers were simulated and compared with empirically recorded CAPs from human subjects. In addition, narrowband CAPs derived from noise-masked clicks and tone bursts were simulated. Many morphological, temporal, and spectral aspects of human CAPs were captured by the simulations for all stimuli tested. These findings support the use of model simulations of the human CAP to refine existing human-based models of the auditory periphery, aid in the design and analysis of auditory experiments, and predict the effects of hearing loss, synaptopathy, and other auditory disorders on the human CAP.

The auditory nerve (AN) compound action potential (CAP) is an important tool for assessing auditory disorders and monitoring the health of the auditory periphery during surgical procedures. The CAP has been mathematically conceptualized as the convolution of a unit response (UR) waveform with the firing rate of a population of AN fibers. Here, an approach for predicting experimentally recorded CAPs in humans is proposed, which involves the use of human-based computational models to simulate AN activity. CAPs elicited by clicks, chirps, and amplitude-modulated carriers were simulated and compared with empirically recorded CAPs from human subjects. In addition, narrowband CAPs derived from noise-masked clicks and tone bursts were simulated. Many morphological, temporal, and spectral aspects of human CAPs were captured by the simulations for all stimuli tested. These findings support the use of model simulations of the human CAP to refine existing human-based models of the auditory periphery, aid in the design and analysis of auditory experiments, and predict the effects of hearing loss, synaptopathy, and other auditory disorders on the human CAP.