Month: September 2022

NEURAL MODELS. “Also, as the neural models are more general, they can generate a wider variety of patterns than can diffusible morphogen models. One other difference is fundamental.” https://lnkd.in/dwfZQzE View in LinkedIn

THE ISSUE OF PATTERN MEMORY. “Morphogen models described by diffusion-reaction dynamics unfold with no “memory” of the system state other than the current state. The neural model, however, is a sensory feedback system in which the current secretion depends on sensing the history of the pattern before the current state.” https://lnkd.in/dwfZQzE View in LinkedIn

COMPUTER MODEL. “Fig. 4. Maximum-likelihood estimates of ancestral shell patterns. Shells of living species are displayed at the tips; to the right of these are shells “grown” in the computer by using the neural-network model and the fitted parameters. https://lnkd.in/dwfZQzE View in LinkedIn

PROBABILITY CURVES. “By using a Brownian motion model for the evolution of continuous traits, the maximum-likelihood value was estimated for each neural network parameter at each node. The neural network model was used to produce the shells using the estimated parameters for each node. Color is not part of the neural network model, so it was added independently to the models of living shells, and then mapped onto the phylogeny (using maximum likelihood) as a binary trait (black/white or brown/white).” https://lnkd.in/dwfZQzE View in LinkedIn

INHERITABILITY. “Phenotypic traits like body size and shape typically exhibit a substantial degree of “phylogenetic signal,” meaning that they are inherited, and the phenotypes of closely related species are strongly correlated.” https://lnkd.in/dwfZQzE View in LinkedIn

STRIPE AND TRIANGLE MOTIFS. “Fig. 6 shows the distributions of stripes and triangles in this group and the maximum-likelihood assignment of ancestral states. The presence and absence of stripes, in particular, is scattered throughout the phylogeny, indicating that they are evolutionarily labile, although triangle presence/absence shows some correlation with large clades.” https://lnkd.in/dwfZQzE View in LinkedIn

PHYLOGENY CORRELATES. “These observations are confirmed by standard parsimony statistics and their comparison with randomized-tip null models; presence/absence of stripes, despite these being visually striking patterns used in identification, appear to lack significant phylogenetic signal in that they do not show significantly more congruence with the phylogeny than is expected under the null model in which character states have been randomly shuffled among the phylogeny tips.” https://lnkd.in/dwfZQzE View in LinkedIn

HEISENBERG IN SHELLS. “Fig. 7. Possible realizations of ancestors. For each neural network parameter at each node, five values were drawn from their estimated distribution by using the predicted uncertainty around the maximum-likelihood estimate.” 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

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