A Novel Rodent Model for the Neurophysiology of Visual Object Recognition

用于视觉对象识别神经生理学的新型啮齿动物模型

• 批准号: 0947777
• 负责人: David Cox
• 金额: $ 15万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0947777&HistoricalAwards=false
• 关键词: Novel; Rodent; Model; Neurophysiology; Visual

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.

人类识别视觉对象如此轻松，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强大的视觉物体识别知之甚少，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，啮齿类动物模型一直以其上级可及性而受到重视，广泛使用的强大实验技术。 虽然啮齿动物传统上没有被用作物体视觉的模型系统，但最近的行为证据表明，大鼠具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，本项目旨在填补我们的知识空白的视觉神经元的机制，使用微电极记录直接从大鼠视觉系统的神经元。 这项工作具有很大的潜力，建立啮齿动物作为一个新的和强大的模型，研究对象识别的神经生理学。 一个更简单，更容易获得的模型的可用性可以大大加快破译大脑中高级视觉的计算基础的进展，这反过来可以为机器人和机器理解图像的人工视觉系统的构建提供信息。 该项目还将为一名博士后研究员和两名本科生提供培训机会，他们将直接参与数据收集和分析。