Pathologies underlying sensorineural hearing loss (SNHL) cannot yet be differentially diagnosed. We are developing means of pathology discrimination with an advanced SNHL simulator. The physiologically inspired model of the auditory periphery (MAP, Meddis et al., 1986~2018) simulates stimulus encoding at the auditory nerve (AN) level. Such encoding is then decoded/converted back to an acoustic signal to be presented to young, normally hearing listeners. For a speech-in-noise intelligibility task employing stimuli processed through the normal-hearing model, speech reception thresholds (SRTs) were just 1-2 dB higher than those obtained for unprocessed stimuli. By inserting a specific pathology in the model, we believe one can reveal the psychophysical signature of that pathology. A first study demonstrated the importance of efferent reflexes to the faithful coding of the temporal modulations that carry speech information. With both efferent reflexes knocked out, SRTs grew by 3-4 dB. Simulated AN rate-level functions illustrate how efferent reflexes enable the AN dynamic-range adaptation to context level that prevents information loss. A second study measured the impact of simulated pathologies on SRTs. While deactivating 70% of ANs or halving the endocochlear potential did not lead to any appreciable SRT inflation, total loss of outer haircells led to a significantly smaller SRT inflation than the 3-4 dB found when efferent reflexes were knocked out. A third study measured SRT elevation with growing deafferentiation. ~90% deafferentiation was found to be required to reflect performance found in hearing impaired listeners, an outcome consistent with the stochastic under-sampling predicted by Lopez-Poveda and Barrios (2013). A final study established changes in binaural masking level difference (BMLD) for the pathologies simulated in the second study. Comparing N0S0 to N0Spi thresholds of audibility of a 250 Hz tone in white noise, a significant BMLD drop was found for all simulated pathologies.