Mathematical and computational modelling of cochlear responses to environmental noise exposure: A preliminary...

Environmental noise is recognised by the World Health Organization and the European Environment Agency as a major environmental risk factor. However, the biophysical mechanisms linking acoustic exposure to cochlear mechanical and neural responses remain incompletely characterised.

This preliminary study organises established cochlear modelling approaches within a multiscale computational framework to examine how environmental sound levels are translated into passive mechanical responses and simulated neural activity.

Passive in silico simulations were performed using three complementary computational modules: (i) a one-dimensional transmission-line model of longitudinal cochlear mechanics; (ii) a three-dimensional finite-difference time-domain model incorporating cochlear-fluid propagation and fluid-basilar-membrane coupling; and (iii) a perceptual post-processing pipeline based on equivalent rectangular bandwidth filtering, inner hair cell transduction, and stochastic auditory-nerve activity. Acoustic inputs included synthetic and environmental signals calibrated between 30 and 85 dB SPL. Both mechanical models were implemented under passive linear assumptions and did not include outer-hair-cell-mediated amplification, compressive nonlinearity, or level-dependent active tuning.

Higher acoustic input levels produced greater basilar membrane displacement in the 1D and 3D mechanical models, increased pressure magnitude in the three-dimensional fluid domain, and greater simulated neural activity and burstiness in the perceptual module. In the passive 1D model, increasing the input from 30 to 85 dB SPL produced an approximately 55 dB increase in basilar membrane displacement level while the normalised frequency-position ridge geometry remained essentially unchanged, consistent with proportional linear scaling. The derived characteristic-frequency and Q10 distributions reproduced the expected longitudinal tonotopic gradient within the frequency range reliably resolved by the simulations, although their extension into the most apical region was limited by the 200 Hz lower-frequency boundary and the peak-identification criteria. The Environmental Auditory Risk Index was used as an exploratory, model-derived composite indicator for integrating the mechanical and simulated neural outputs evaluated in the study.

The proposed framework provides a controlled computational representation of how environmental acoustic inputs are translated into passive cochlear mechanics and simulated neural activity across complementary modelling domains. The results should not be interpreted as evidence of active cochlear amplification, physiological injury, or clinically validated auditory risk. Incorporation of nonlinear outer hair cell mechanics, extension of the low-frequency simulation range, sensitivity analysis, and experimental or clinical validation will be required before the framework or its derived indicators can support predictive applications.