## 4 Discussion
The choice of only optimizing the insertion depth was based on unpublished preliminary experimentation during which the largest variance of the LAP was observed when insertion depths were varied, whereas only little variance of LAP was observed for parameters of frequency and level mapping. Moreover, different surgical approaches exist and may influence the outcome [35]. Thus, suggestions for future research include having a closer look at the remaining fitting parameters of the CI, and to test different stimulation strategies than only CIS, such as the AdvancedCombination Encoder (ACE) [36], specialized strategies for optogenetic stimulation [37], Stimulation based on Auditory Modelling (SAM) [38], or others [25]. Second, only root mean squared differences of AN firing rates were used for fitting and comparison. This choice neglects the plasticity of human central auditory processing, which enables impaired listeners to accommodate to impaired hearing to some degree [39]. An advanced objective for fitting and comparison instead of the LAP may be developed in the future with the aim of reflecting human ability to accommodate. An argument in favor of direct comparison of AN firing rates is that a proposal exists in which an electrical stimulation strategy aims at mimicking AN firing patterns of NH [38]. Moreover, a pursuit towards near physiological spectral selectivity is being observed [37]. Thus, we assume that hearing rehabilitation is more straightforward if recovered AN firing patterns are similar to natural ones. We also experimented using the structural similarity index (SSIM) instead of the LAP [40]. Results obtained using the SSIM, which is a measure for visual image similarity, are similar to results obtained with the LAP. Third, the hearing loss parameters used in our study are not easily transferable into hearing threshold levels versus frequency, i.e., pure tone audiograms, which limits the comparability of our results with existing clinical guidelines. In fact, CGL was reported to result in hearing threshold levels of up to 60 dB [9], while the CGL parameters of the used model result in complete loss of cochlear gain as soon as the hearing thresholds are elevated by 35 dB only [8]. Moreover, our parameters indicating IHCL reflect spatial density of functional IHCs and are not meant to directly correspond to hearing threshold levels. In the future, we suggest continuing with estimating cochlear parameters using audiometric methods. Evaluation of otoacoustic emissions, in particular transient-evoked otoacoustic emissions (TEOAEs) and distortion production otoacoustic emissions (DPOAEs), as well as the evaluation of cochlear microphonics (CMs), may enable the estimation of CGL parameters. Estimation of IHCL parameters may be enabled by additional evaluation of the compound action potential (CAP) obtained with invasive or non-invasive electrocohleography (ECochG), which is similar to Wave-I of the auditory brainstem response (ABR) but has a better signal-to-noise-ratio. Moreover, dead regions may be identified by the TEN(HL) test [41]. Personalized outer and middle ear filters may be obtained from measuring head-related transfer functions, and from tympanometry. A suggestion for the validation of the presented simulation study would be to obtain pre- and post-implantation measurements for patients and dichotomize them into groups of subjects with favorable and unfavorable implantation outcome. One may hypothesize that the proposed simulation may help to predict before implantation which of the individuals benefit from implantation. Finally, only monaural processing of a close-mic signal was simulated, which does not enable the studying of the human ability to externalize and localize sound (e.g., in CIs, [42]), limiting the possibilities of studying auditory stream segregation, e.g., such as in the cocktail party effect [43; 44; 45; 46]. In particular, difficulties of CI users in adverse listening conditions [47; 48] may be considered in the future.