CRI: Neuromorphic VLSI Modelling of Attention-Based Visual Search

IBN：9634357 PI：Niebur 为了避免信息过载，到目前为止， 我们感觉器官的输入必须被大脑丢弃，只有 精心挑选的部分可以影响行为， 达到长期记忆。这个过程被称为选择性注意， 它是心理学、神经生物学和 计算机科学在这个项目中，我们将设计和测试 模拟超大规模集成电路芯片，实现神经生物学上合理的模型 注意力选择的过程 以前。该系统将在标准视觉搜索上进行测试 在猴子的心理学实验中经常使用的范例 和人类实验对象。 建造这样的“神经形态”设备是人们所期望的 对生物感知的理解有很大的帮助， 一个工作和强大的系统的设计者必须克服，因此， 为了理解，许多相同的功能限制生物学 系统面临的问题（噪声、有限的连接可能性等）。 机器视觉也应该从这项工作中受益匪浅，因为 技术图像理解系统将面临同样的问题 生物有机体的信息过载问题，一旦 计算机视觉的原始阶段（与生物视觉相比） 愿景将被超越。 -- Ernst Niebur，博士 Krieger Mind/Brain Institute 神经科学助理教授 约翰霍普金斯大学 niebur@jhu.edu 北纬3400度查尔斯街 （410）516-8643，-8640（秘书），-8648（传真） 巴尔的摩，MD 21218

IBN: 9634357 PI: Niebur In order to avoid information overload, by far the largest part of the input to our sensory organs has to be discarded by the brain, and only carefully selected parts are allowed to influence behavior and to reach long-term memory. This process is called selective attention and it is the focus of intense research in psychology, neurobiology and the computational sciences. In this project, we will design and test analog VLSI chips which implement neurobiologically plausible models of the attentional selection process that we have developed previously. The system will be tested on standard visual search paradigms as used routinely in psychological experiments with monkey and human subjects. Building such "neuromorphic" devices is expected to greatly benefit the understanding of biological perception since the designer of a working and robust system has to overcome, and thus to understand, many of the same functional constraints biological systems are faced with (noise, limited connection possibilities etc). Also machine vision should benefit significantly from this work since technical image understanding systems will be confronted with the same problem of information overload as biological organisms are, once the still primitive stage of computer vision (compared to biological vision) will be surpassed. -- Ernst Niebur, PhD Krieger Mind/Brain Institute Asst. Prof. of Neuroscience Johns Hopkins University niebur@jhu.edu 3400 N. Charles Street (410)516-8643, -8640 (secr), -8648 (fax) Baltimore, MD 21218