Recognizing the people, objects, and actions in the world around us is a crucial aspect of human perception that allows us to plan and act in our environment. Remarkably, our proficiency in recognizing semantic categories from visual input is unhindered by transformations that substantially alter their appearance (e.g., changes in lighting or position). The ability to generalize across these complex transformations is a hallmark of human visual intelligence, which has been the focus of wide-ranging investigation in systems and computational neuroscience. However, while the neural machinery of human visual perception has been thoroughly described, the computational principles dictating its functioning remain unknown. Here, we review recent results in brain imaging, neurophysiology, and computational neuroscience in support of the hypothesis that the ability to support the invariant recognition of semantic entities in the visual world shapes which neural representations of sensory input are computed by human visual cortex.

中文翻译：

---

不变识别塑造视觉输入的神经表示。

认识我们周围世界中的人，物体和行为是人类感知的关键方面，它使我们能够在环境中进行计划和采取行动。值得注意的是，我们从视觉输入中识别语义类别的熟练程度不受实质上改变其外观（例如，照明或位置的更改）的转换的影响。概括这些复杂转换的能力是人类视觉智能的标志，这已成为系统和计算神经科学领域广泛研究的重点。然而，尽管已经充分描述了人类视觉感知的神经机制，但指示其功能的计算原理仍然未知。在这里，我们回顾了脑成像，神经生理学，