Back

Computational model of the human cochlea with motion of the layered osseous spiral lamina

Tubelli, A.; Secchia, P.; Nakajima, H. H.; Puria, S.

2024-08-19 biophysics
10.1101/2024.08.16.608342 bioRxiv
Show abstract

PurposeIn the base of the human cochlea, the partition anatomy is distinct from the commonly recognized anatomy of laboratory animals. The human features a radially wide, osseous spiral lamina (OSL) and a soft-tissue bridge region that connects the OSL to the basilar membrane proper. In addition to the basilar membrane, the human OSL and bridge move considerably. We investigated the complex cochlear partition in human emphasizing the layered structure of the OSL with a finite element model. Model results were calibrated with experimental measurements of motion from optical coherence tomography. MethodsThe box model contained two fluid chambers separated by a cochlear partition and a helicotrema. Model geometrical and material properties either came from literature, measurements, or were tuned to produce a frequency-place map for the passive human cochlea as well as motion results similar to experimental measurements. ResultsThe model motion results of the cochlear partition were similar to experimental results mostly within 5 dB but with differences at the high frequencies in both magnitude and phase beyond the best frequency. Around the best frequency location, the radial profile of cochlear partition motion was generally similar in both shape and magnitude. Sensitivity analysis, changing material-property parameters of the middle layer where the cochlear nerve fibers run between the layers of OSL plates, produced small changes in the model response and also showed negligible stress compared to the outer OSL plates. ConclusionThese results suggest that the layered OSL anatomy is favorable as a conduit and protection for the nerve fibers while simultaneously functioning as a mechanical lever.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.