Turtle utricle dynamic behavior using a combined anatomically accurate model and experimentally measured hair bundle stiffness.

Anatomically correct turtle utricle geometry was incorporated into two finite element models. The geometrically accurate model included appropriately shaped macular surface and otoconial layer, compact gel and column filament (or shear) layer thicknesses and thickness distributions. The first model included a shear layer where the effects of hair bundle stiffness was included as part of the shear layer modulus. This solid model's undamped natural frequency was matched to an experimentally measured value. This frequency match established a realistic value of the effective shear layer Young's modulus of 16 Pa. We feel this is the most accurate prediction of this shear layer modulus and fits with other estimates (Kondrachuk, 2001b). The second model incorporated only beam elements in the shear layer to represent hair cell bundle stiffness. The beam element stiffness's were further distributed to represent their location on the neuroepithelial surface. Experimentally measured striola hair cell bundles mean stiffness values were used in the striolar region and the mean extrastriola hair cell bundles stiffness values were used in this region. The results from this second model indicated that hair cell bundle stiffness contributes approximately 40% to the overall stiffness of the shear layer-hair cell bundle complex. This analysis shows that high mass saccules, in general, achieve high gain at the sacrifice of frequency bandwidth. We propose the mechanism by which this can be achieved is through increase the otoconial layer mass. The theoretical difference in gain (deflection per acceleration) is shown for saccules with large otoconial layer mass relative to saccules and utricles with small otoconial layer mass. Also discussed is the necessity of these high mass saccules to increase their overall system shear layer stiffness. Undamped natural frequencies and mode shapes for these sensors are shown. Published by Elsevier B.V.