A Novel Rodent Model for the Neurophysiology of Visual Object Recognition

人类如此毫不费力地识别视觉对象，以至于很容易忽视这是一项令人印象深刻的计算壮举。目前，人们对大脑如何实现稳健的视觉对象识别知之甚少，而复制这种能力仍然是构建有用的计算机视觉系统的主要绊脚石。在神经生物学研究中，啮齿动物模型长期以来一直因其优越的可及性而受到重视，广泛使用了一系列强大的实验技术。虽然啮齿动物传统上不被用作物体视觉的模型系统，但最近的行为证据表明，老鼠拥有令人惊讶的高级视觉物体识别能力。在这些发现的基础上，本项目试图利用微电极直接记录大鼠视觉系统中的神经元，来填补我们对视觉神经机制的知识空白。这项工作具有建立啮齿动物作为研究物体识别神经生理学的新的和强大的模型的巨大潜力。更简单、更容易获得的模型可以极大地加快破译大脑高级视觉的计算基础的进展，这反过来可以为构建用于机器人和机器图像理解的人工视觉系统提供信息。该项目还将为直接参与数据收集和分析的一名博士后研究员和两名本科生提供培训机会。

Humans recognize visual objects so effortlessly that is easy to overlook what an impressive computational feat this represents. At present, little is known about how the brain achieves robust visual object recognition, and reproducing this ability remains a major stumbling block in the construction of useful computer vision systems. In neurobiological research, rodent models have long been valued for their superior accessibility, with a wide range of powerful experimental techniques in widespread use. While rodents have not traditionally been used as a model system for object vision, recent behavioral evidence suggests that rats possess surprisingly advanced visual object recognition abilities. Building on these findings, the present project seeks to fill gaps in our knowledge of the neuronal mechanisms of vision using microelectrodes to record directly from neurons in the rat visual system. This work holds great potential to establish rodents as a new and powerful model for studying the neurophysiology of object recognition. The availability of a simpler, more accessible model can greatly accelerate progress in deciphering the computational underpinnings of high-level vision in the brain, which can, in turn, inform the construction of artificial vision systems for robotics and machine understanding of images. The project will also provide training opportunities for one postdoctoral fellow, and two undergraduate students, who will be directly involved in the data collection and analysis.