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BIFURCATION BOUNDARIES. “This limitation does not apply to pigmentation patterns. Although the same averaging procedure is being used on each parameter of the neural-network model, it is possible, and even likely, that a set of estimated parameters will be in a region of parameter space not inhabited by any living species.” https://lnkd.in/dwfZQzE View in LinkedIn

BINARY OUTCOMES. “The role of bifurcation boundaries in evolution was recognized in earlier studies of limb morphogenesis. This feature of our results is quite different from what is usually found when inferring ancestral states of continuously variable characters. A well known limitation of methods for estimating ancestral states is that it is impossible for estimates to fall outside the range of the living species analyzed.” https://lnkd.in/dwfZQzE View in LinkedIn

STEPWISE PATTERNINGS. “The patterns generated by the neural-network model are not necessarily smooth functions of the parameter values. Instead, they can vary discontinuously when parameter values move into a different bifurcation region that produces qualitatively different patterns.” https://lnkd.in/dwfZQzE View in LinkedIn

DISCONNECT OVER GENERATIONS. “A unique feature of our results is that the inferred pigmentation patterns of ancestors may be quite different from the patterns of their descendants.” https://lnkd.in/dwfZQzE View in LinkedIn

SHELL PATTERNINGS. “Our analyses have allowed us to estimate the shell pigmentation patterns of ancestral species, identify lineages in which one or more parameters have evolved rapidly, and measure the degree to which different parameters correlate with the phylogeny.” https://lnkd.in/dwfZQzE View in LinkedIn

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GRADUAL PHYLOGENY. “The model parameters fitted to observed patterns show a substantial phylogenetic signal, indicating that the processes governing evolutionary change in shell patterns are, to some extent, gradual across the phylogeny.” https://lnkd.in/dwfZQzE View in LinkedIn

NEURAL PATTERNING. “We have taken a step in applying modern phylogenetic methods to understanding the development of complex phenotypic characters. The pigmentation patterns of Conus shells can be generated by a neural-network model that has a sound anatomical and physiological basis.” https://lnkd.in/dwfZQzE View in LinkedIn

SIMILARITIES AND DIFFERENCES. “Each set of parameter values for a node was then input into the neural-network model to produce a depiction of the possible ancestor. Some shell patterns appear to occupy larger regions of parameter space, and are thus more robust to perturbation. However, similarities can still be discerned even in shells that appear quite different at first glance.” https://lnkd.in/dwfZQzE View in LinkedIn