Objective measures in cochlear implanted patients: A computational framework to evaluate artifact rejection methodologies

Auditory steady-state responses (ASSRs) constitute a reliable measure of auditory perception in normal hearing subjects. The use of these measures in cochlear implanted patients is hindered by the vast diffusion of the electrical cochlear stimulation artifact that highly contaminates EEG scalp recordings. Therefore, attenuating or moreover suppressing this artifact ahead of response detection is crucial. Yet, the currently used denoising algorithms may have unpredictable effects on these responses (ASSRs). In this paper, we propose a computational framework that allows the simulation of the mixture of the stimulation artifact and its corresponding evoked ASSRs on EEG scalp electrodes. The utility of this relatively basic model resides in its usefulness in quantifying the effects of any applied denoising method on the information contained in the signal of interest (responses known a priori). Here, an application to two independent component analysis algorithms (infomax and infomax extended) is presented. The model predicts a better performance for infomax compared to infomax extended.