Higher-Order Color: From Cones to Postreceptoral Mechanisms

颜色视觉通常被认为是理解大脑-行为关系的模型系统：感觉输入是明确的，眼睛的初始处理是相当清楚的，并且在大多数情况下，有意识的颜色体验的维度(色调、亮度和饱和度)是一致同意的。然而，关于颜色视觉系统如何完成其最基本的任务--检测、辨别和色调显现--的理论还没有达成共识。这项综合性研究中的实验将为人类颜色视觉的基本操作提供一个完整的计算模型。这个模型是完全机械化的，从这个意义上说，它是由简单的电路构建的，这些电路可以很容易地构建到人工视觉系统中，使用颜色来检测物体、识别人脸和解码情绪。该模型将为其他神经学家测试提供具体的假设：它为单细胞生理学研究和功能神经成像研究做出预测。该模型甚至可以用于人为因素工程、纺织和市场营销等应用领域，在这些领域中，理解颜色歧视至关重要。该模型的一个子集已经被测试，并被证明在有限的条件下为检测、颜色匹配和颜色辨别提供了非常成功的预测。所需要的是在所有颜色空间中设置模型参数的基础数据。这项拟议的项目将提供这些数据，拟合完整的模型，并测试其在多个感知任务中的应用。自从1986年Krauskopf和他的同事发现‘主轴’颜色模型的错误以来，该领域一直缺乏关于颜色检测和辨别的接收者后机制的共识模型。在我们之前的工作中，我们证明了一个简单的模型，只有8个机制，可以解释颜色空间中一个平面的检测和颜色匹配，试点数据表明它也解释了阈值下的强迫选择歧视。没有其他颜色机制模型被证明能如此好地解释如此多不同的感知现象。该项目将从两个方面扩展我们以前的研究：(1)以前的实验局限于锥体空间中的单个平面，而新的实验将探索整个三维颜色刺激空间；(2)另外两个程序，强制选择色度辨别和色调缩放，将被用于定义颜色机制的属性和检验模型预测。所有测量将在三种不同的色度噪声掩蔽条件下进行，所有受试者将在所有条件下进行测试，以考虑个体差异。因为它建立在我们之前的成功基础上，这项研究很有可能解决该领域的核心问题，开发一个完全可计算的模型来解释在整个3D颜色空间中的检测和辨别。综合组织系统部门的行为系统集群参与了该奖项的共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Color vision has often been considered a model system for understanding brain-behavior relationships: the sensory inputs are well-defined, the initial processing in the eye is fairly well-understood, and for the most part the dimensions of conscious color experience (hue, brightness, and saturation) are agreed-upon. Yet there is no consensus on a theory of how the color visual system accomplishes its most basic tasks: detection, discrimination, and hue appearance. The experiments in this comprehensive study will provide a complete, computational model for the basic operations of human color vision. The model is fully mechanistic, in the sense that it is built from simple circuits that could easily be built into artificial vision systems that use color for detecting objects, recognizing faces, and decoding emotions. The model will offer concrete hypotheses for other neuroscientists to test: it makes predictions for studies of single-cell physiology as well as for functional neuroimaging. The model can even be used in applied domains such as human factors engineering, textiles, and marketing, example fields where understanding color discrimination is vital. A subset of the model has already been tested and shown to provide remarkably successful predictions for detection, color matching and color discrimination in limited conditions. What is needed is the basic data to set the model parameters in all of color space. The proposed project will provide that data, fit the complete model, and test its application to multiple perceptual tasks.Since 1986, when failures of the 'cardinal axis' color model were discovered by Krauskopf and colleagues, the field has lacked an agreed-upon model of the postreceptoral mechanisms of color detection and discrimination. In our previous work, we showed that a simple model, with only 8 mechanisms, can account for detection and color matching in one plane of color space, and pilot data shows it also accounts for forced-choice discrimination at threshold. No other color mechanism model has been shown to account so well for so many different perceptual phenomena. The project will extend our previous studies in two ways: (1) whereas the previous experiments were limited to a single plane in cone space, the new ones will explore the entire 3-dimensional space of color stimuli; (2) two additional procedures, forced-choice chromatic discrimination and hue scaling, will be used to define the properties of the color mechanisms and test the model predictions. All the measurements will take place under three different chromatic noise masking conditions, and all the subjects will be tested in all of the conditions, to allow for individual differences. Because it builds upon our prior successes, the research is highly-likely to solve the central problem in the field, developing a fully-computable model to explain detection and discrimination in the full 3D color space.The Behavioral Systems Cluster in the Division of Integrative Organismal Systems participated in co-funding of the award.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.