. The Biological bulletin. Biology; Zoology; Biology; Marine Biology. PEAK SLOPE ( / 25 ms PEAK SLOPE ( / 25 ms) Figure 9. Effect of averaging time on the probability distribution of maximum peak slopes representing chemoreceptors with different disadaptation times (A. B, C) from the continuous flow model. D is an expanded version of C. changing disadaptation times, the potential directional information content of the parameter stays constant also. The same was found for the other three peak param- eters. Therefore, receptor cells with different averaging periods cannot improve on
. The Biological bulletin. Biology; Zoology; Biology; Marine Biology. PEAK SLOPE ( / 25 ms PEAK SLOPE ( / 25 ms) Figure 9. Effect of averaging time on the probability distribution of maximum peak slopes representing chemoreceptors with different disadaptation times (A. B, C) from the continuous flow model. D is an expanded version of C. changing disadaptation times, the potential directional information content of the parameter stays constant also. The same was found for the other three peak param- eters. Therefore, receptor cells with different averaging periods cannot improve on this situation. Discussion This study accomplished two goals. First, we measured the turbulent spectrum in an odor plume scaled such that it might be realistic for a lobster searching for an odor source. Both the spatio-temporal scale of the plume itself and the spatial average taken by the "receptor," , the electrode size and spacing, were lobster-like. Second, we constructed a first-generation temporal filter model that reflects the biological reality that receptor cells adapt to ambient concentrations where electronics do not unless specifically instructed. Our instructions were based on preliminary physiological data on self-adaptation and disadaptation rates of chemoreceptor cells in situ, , including the boundary layer normally present. The filter model must be adjusted as physiological data and boundary layer measurements accumulate. The turbulent spectrum of any plume is highly depen- dent upon the physical conditions of the environment. To develop this first model, we chose one specific plume condition: a constantly pumping mussel under one lami- nar carrier flow condition and we sampled only at four locations. In the future, extensive sampling must be done under various flow conditions and with different odor sources encountered in the natural environment of the H. americanus. As the plume ages the physics of turbulent dispersal changes the values of
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Keywords: ., bookauthorlilliefrankrat, booksubjectbiology, booksubjectzoology
