The ability to rapidly and accurately recognize complex objects is a crucial function of the human visual system. To recognize an object, we need to bind incoming visual features, such as color and form, together into cohesive neural representations and integrate these with our preexisting knowledge about the world. For some objects, typical color is a central feature for recognition; for example, a banana is typically yellow. Here, we applied multivariate pattern analysis on time-resolved neuroimaging (MEG) data to examine how object-color knowledge affects emerging object representations over time. Our results from 20 participants (11 female) show that the typicality of object-color combinations influences object representations, although not at the initial stages of object and color processing. We find evidence that color decoding peaks later for atypical object-color combinations compared with typical object-color combinations, illustrating the interplay between processing incoming object features and stored object knowledge. Together, these results provide new insights into the integration of incoming visual information with existing conceptual object knowledge.

SIGNIFICANCE STATEMENT To recognize objects, we have to be able to bind object features, such as color and shape, into one coherent representation and compare it with stored object knowledge. The MEG data presented here provide novel insights about the integration of incoming visual information with our knowledge about the world. Using color as a model to understand the interaction between seeing and knowing, we show that there is a unique pattern of brain activity for congruently colored objects (e.g., a yellow banana) relative to incongruently colored objects (e.g., a red banana). This effect of object-color knowledge only occurs after single object features are processed, demonstrating that conceptual knowledge is accessed relatively late in the visual processing hierarchy.

快速而准确地识别复杂物体的能力是人类视觉系统的关键功能。为了识别物体，我们需要将传入的视觉特征（例如颜色和形式）绑定在一起，形成内聚的神经表示，并将其与我们先前关于世界的知识相结合。对于某些对象，典型的颜色是识别的主要特征。例如，香蕉通常是黄色的。在这里，我们对时间分辨神经影像（MEG）数据应用了多元模式分析，以研究对象颜色知识如何随着时间影响新兴的对象表示。我们从20位参与者（11位女性）中获得的结果表明，对象-颜色组合的典型性会影响对象的表示形式，尽管并不在对象和颜色处理的初始阶段。我们发现有证据表明，与典型的对象颜色组合相比，非典型对象颜色组合的颜色解码峰值更高，说明了处理传入对象特征和存储的对象知识之间的相互作用。在一起，这些结果为传入的视觉信息与现有概念对象知识的集成提供了新的见解。

意义声明要识别对象，我们必须能够将对象的特征（例如颜色和形状）绑定到一个连贯的表示中，并将其与存储的对象知识进行比较。此处提供的MEG数据提供了有关传入视觉信息与我们对世界知识的集成的新颖见解。使用颜色作为模型来理解见与知之间的相互作用，我们表明，与颜色不一致的对象（例如，红色香蕉）相比，颜色一致的对象（例如，黄色香蕉）存在独特的大脑活动模式。对象颜色知识的这种效果仅在处理单个对象特征之后才会发生，这表明概念知识在视觉处理层次结构中的访问相对较晚。