They then modeled the size of the excitatory and inhibitory regions surrounding the secretory cells and the cells' firing thresholds nine parameters in all as a neural network that determines how much calcium and pigment is secreted.
Based solely on these nine parameters, Boettiger, Oster and Ermentrout were able to reproduce the shapes and patterns of almost every known sea mollusk.
Interestingly, they found that all shell patterns fall into three basic classes: stripes perpendicular to the growing edge, bands parallel to the growing edge, and complex patterns created by asymmetric "traveling waves" of pigment or calcium deposition.
The basic concept behind the neural net model, which was first described by physicist Ernst Mach in 1865 to explain visual illusions, is that centers of excitation in the retina, for example are surrounded by areas of inhibition. Local activation/lateral inhibition applies to many types of neuronal activity and underlies the extreme sensitivity of our eyes and visual system to edges the activation of cells at an edge inhibits neighboring cells, accentuating the discontinuity.
Famed computer scientist Alan Turing showed in 1952 how local activation/lateral inhibition could work chemically, and biologist Hans Meinhardt used this chemical model to create realistic seashell patterns in the 1970s, which he published in a 1995 book called "The algorithmic beauty of sea shells."
At that time, the neural basis of shell patterning hadn't been widely accepted, though Oster and Ermentrout published an earlier version of the neural model in the 1970s. One problem wi
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| Contact: Robert Sanders rsanders@berkeley.edu 510-643-6998 University of California - Berkeley Source:Eurekalert |