Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY 10027, USA.
Laboratoire de Physique de l'Ecole Normale Supérieure, CNRS, Ecole Normale Supérieure, PSL University, Sorbonne Université, Université de Paris, Paris, France.
Philos Trans R Soc Lond B Biol Sci. 2022 Oct 24;377(1862):20210280. doi: 10.1098/rstb.2021.0280. Epub 2022 Sep 5.
Colour vision represents a vital aspect of perception that ultimately enables a wide variety of species to thrive in the natural world. However, unified methods for constructing chromatic visual stimuli in a laboratory setting are lacking. Here, we present stimulus design methods and an accompanying programming package to efficiently probe the colour space of any species in which the photoreceptor spectral sensitivities are known. Our hardware-agnostic approach incorporates photoreceptor models within the framework of the principle of univariance. This enables experimenters to identify the most effective way to combine multiple light sources to create desired distributions of light, and thus easily construct relevant stimuli for mapping the colour space of an organism. We include methodology to handle uncertainty of photoreceptor spectral sensitivity as well as to optimally reconstruct hyperspectral images given recent hardware advances. Our methods support broad applications in colour vision science and provide a framework for uniform stimulus designs across experimental systems. This article is part of the theme issue 'Understanding colour vision: molecular, physiological, neuronal and behavioural studies in arthropods'.
颜色视觉是感知的一个重要方面，它最终使各种各样的物种能够在自然界中繁衍生息。然而，在实验室环境中构建色觉刺激的统一方法仍然缺乏。在这里，我们提出了刺激设计方法和一个配套的编程包，以有效地探测任何已知感光器光谱灵敏度的物种的颜色空间。我们的与硬件无关的方法将感光器模型纳入不变性原理的框架内。这使实验者能够确定组合多个光源以创建所需的光分布的最有效方法，从而轻松构建用于绘制生物体颜色空间的相关刺激。我们包括处理感光器光谱灵敏度不确定性的方法，以及在最近的硬件进步的基础上优化重建高光谱图像的方法。我们的方法支持广泛的颜色视觉科学应用，并为跨实验系统的统一刺激设计提供了一个框架。本文是主题为“理解颜色视觉：节肢动物的分子、生理、神经元和行为研究”的一部分。
