A mathematical model of cochlear processing is developed to account for the nonlinear dependence of frequency selectivity on intensity in inner hair cell and auditory nerve fiber responses. The model describes the transformation from acoustic stimulus to intracellular hair cell potentials in the cochlea. It incorporates a linear formulation of basilar membrane mechanics and subtectorial fluid-cilia displacement coupling, and a simplified description of the inner hair cell nonlinear transduction process. The analysis at this stage is restricted to low-frequency single tones. The computed responses to single tone inputs exhibit the experimentally observed nonlinear effects of increasing intensity such as the increase in the bandwidth of frequency selectivity and the downward shift of the best frequency. In the model, the first effect is primarily due to the saturating effect of the hair cell nonlinearity. The second results from the combined effects of both the nonlinearity and of the inner hair cell low-pass transfer function. In contrast to these shifts along the frequency axis, the model does not exhibit intensity dependent shifts of the spatial location along the cochlea of the peak response for a given single tone. The observed shifts therefore do not contradict an intensity invariant tonotopic code.
We study the equilibrium in the use of synonymous codons by eukaryotic organisms and find five equations involving substitution rates that we believe embody the important implications of equilibrium for the process of silent substitution. We then combine these five equations with additional criteria to determine sets of substitution rates applicable to eukaryotic organisms. One method employs the equilibrium equations and a principle of maximum entropy to find the most uniform set of rates consistent with equilibrium. In a second method we combine the equilibrium equations with data on the man-mouse divergence to determine that set of rates that is most neutral yet consistent with both types of data (i.e., equilibrium and divergence data). Simulations show this second method to be quite reliable in spite of significant saturation in the substitution process. We find that when divergence data are included in the calculation of rates, even though these rates are chosen to be as neutral as possible, the strength of selection inferred from the nonuniformity of the rates is approximately doubled. Both sets of rates are applied to estimate the human-mouse divergence time based on several independent subsets of the divergence data consisting of the quartet, C- or T-ending duet, and A- or G-ending duet codon sets. Both rate sets produce patterns of divergence times that are shortest for the quartet data, intermediate for the CT-ending duets, and longest for the AG-ending duets. This indicates that rates of transitions in the duet-codon sets are significantly higher than those in the quartet-codon sets; this effect is especially marked for A----G, the rate of which in duets must be about double that in quartets.
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