The computational neuroscience of animal camouflage

从1859年《物种起源》出版的那一刻起，达尔文和他的同时代人就用动物的伪装来说明生存的改善是如何导致明显的设计的。早期进化生物学家的思想（很可能重要的是，许多人也是艺术家）反过来对两次世界大战中军队对迷彩的采用产生了强烈的影响。基本原则，那么先进，？如何融入背景，使用破坏性的图案来伪装形状和形式，以及模仿背景物体？基本保持不变，生物学和视觉科学的教科书用叶子状的飞蛾、细枝状的毛毛虫和奇怪条纹的青蛙的迷人照片来说明。然而，令人惊讶的是，许多伪装的基本原理仍然未经测试，重要的是，在现代视觉计算理论之前，语言就已经陈述了。我们的目标是使用现代视觉计算理论来理解动物伪装的设计，正如人类和动物捕食者所看到的那样。计算方法的巨大优势在于，它明确了人类或动物观察者的感知和认知机制，因此足够精确，可以生成可测试的预测。对生物学家来说也很重要的是，这些模型可以调整，以适应与我们自己的视觉系统不同的动物。如果我们对飞蛾为什么有一种特殊的颜色模式感兴趣，我们需要了解它的鸟类捕食者是如何看到这种模式的，鸟类不仅比人类拥有更丰富的颜色世界（例如，它们能看到紫外线），而且它们对对比度的敏锐度和敏感度也与我们不同。我们主要研究伪装的两种主要形式，背景匹配或混合，以及破坏性着色，使用计算机模型和实验室中的人类实验以及野外的野生鸟类。将视觉的计算神经科学引入生物学有明显的好处，但思想的流动不是单向的。因为视觉系统的进化是为了解决现实世界的问题，“破伪装”就是其中之一，那么人类视觉的许多设计特征应该可以用早期人类和其他灵长类动物的生态学来解释。正如我们试图通过注入计算神经科学的理论和技术来实现色彩生物学研究的现代化一样，我们也希望将后者从（通常未被认识到的）通过人眼模拟世界的限制中解放出来。

From the moment 'The Origin of Species' was published in 1859, Darwin and his contemporaries used animal camouflage to illustrate how improved survival leads to apparent design. The ideas of early evolutionary biologists (and it is probably significant that many were artists too) in turn had a strong influence on the adoption of camouflage by the military in both World Wars. The basic principles, advanced then,? of blending into the background, use of disruptive patterns to disguise shape and form, and mimicking of background objects -? have remained largely unchanged, textbooks in biology and the visual sciences illustrated by beguiling photos of leaf-like moths, twig-like caterpillars and oddly striped frogs. Surprisingly, however, many of the fundamental principles of camouflage remain untested and, importantly, are stated in language that predates modern computational theories of vision. Our aim is to use modern computational theories of vision to understand the design of animal camouflage, as seen by both humans and animal predators. The great advantage of a computational approach is that it is explicit about the mechanisms of perception and cognition of the human or animal viewer, and so sufficiently precise to generate testable predictions. Of great significance to biologists too, such models can be adjusted to cater for animals with different visual systems from our own. If we are interested in why a moth has a particular colour pattern, we need to understand how its bird predators would see that pattern, and birds not only have a richer colour world than humans (they can see ultraviolet light, for example) their acuity and sensitivity to contrast differs from us. We focus on the two major forms of camouflage, background matching or blending, and disruptive coloration, using computer models and experiments on humans in the lab and wild birds in the field. Bringing the computational neuroscience of vision to biology has clear benefits, but the flow of ideas is not one-way. Because visual systems have evolved to solve real-world problems, of which 'camouflage breaking' is one, then many design features of human vision should be explicable with reference to the ecology of early humans and other primates. Just as we seek to modernise the biological study of coloration through infusion of the theory and technology of computational neuroscience, so too we wish to free the latter of the (usually unrecognised) constraints of modelling the world through human eyes.