Bio-Inspired Digital Sensing Laboratory, School of Media and Communication, RMIT University, Melbourne, VIC 3000, Australia.
National Vision Research Institute, Australian College of Optometry, Carlton, VIC 3053, Australia.
Proc Natl Acad Sci U S A. 2017 Jul 18;114(29):7713-7718. doi: 10.1073/pnas.1703454114. Epub 2017 Jul 3.
How can a pollinator, like the honey bee, perceive the same colors on visited flowers, despite continuous and rapid changes in ambient illumination and background color? A hundred years ago, von Kries proposed an elegant solution to this problem, color constancy, which is currently incorporated in many imaging and technological applications. However, empirical evidence on how this method can operate on animal brains remains tenuous. Our mathematical modeling proposes that the observed spectral tuning of simple ocellar photoreceptors in the honey bee allows for the necessary input for an optimal color constancy solution to most natural light environments. The model is fully supported by our detailed description of a neural pathway allowing for the integration of signals originating from the ocellar photoreceptors to the information processing regions in the bee brain. These findings reveal a neural implementation to the classic color constancy problem that can be easily translated into artificial color imaging systems.
传粉媒介（如蜜蜂）如何在不断变化的环境光照和背景颜色下感知到访问花朵的相同颜色？一百年前，冯·克里斯特（von Kries）提出了一个优雅的解决方案，即颜色恒常性，目前已被许多成像和技术应用所采用。然而，关于这种方法如何在动物大脑中运作的经验证据仍然很薄弱。我们的数学模型表明，在蜜蜂中观察到的简单小眼光感受器的光谱调谐允许为大多数自然光环境下的最佳颜色恒常性解决方案提供必要的输入。该模型得到了我们对允许小眼光感受器产生的信号整合到蜜蜂大脑信息处理区域的神经通路的详细描述的充分支持。这些发现揭示了经典颜色恒常性问题的神经实现，它可以很容易地转化为人工颜色成像系统。
