Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, USA.
Proc Natl Acad Sci U S A. 2012 Jan 31;109(5):E234-41. doi: 10.1073/pnas.1119859109. Epub 2012 Jan 4.
The pigmentation patterns of shells in the genus Conus can be generated by a neural-network model of the mantle. We fit model parameters to the shell pigmentation patterns of 19 living Conus species for which a well resolved phylogeny is available. We infer the evolutionary history of these parameters and use these results to infer the pigmentation patterns of ancestral species. The methods we use allow us to characterize the evolutionary history of a neural network, an organ that cannot be preserved in the fossil record. These results are also notable because the inferred patterns of ancestral species sometimes lie outside the range of patterns of their living descendants, and illustrate how development imposes constraints on the evolution of complex phenotypes.
贝壳的色素模式可以通过外套膜的神经网络模型生成。我们将模型参数拟合到 19 种现存的圆锥螺物种的贝壳色素模式上，这些物种都有明确的系统发育关系。我们推断了这些参数的进化历史，并利用这些结果推断了祖先物种的色素模式。我们使用的方法使我们能够描述神经网络的进化历史，而神经网络是一种无法在化石记录中保存的器官。这些结果也很重要，因为推断出的祖先物种的模式有时超出了其现存后代的模式范围，这说明了发育如何对复杂表型的进化施加限制。
