Perception and Control: A Dynamic Perspective

感知与控制：动态视角

• 批准号: 9976174
• 负责人: Bijoy Ghosh
• 金额: $ 24万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2002-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9976174&HistoricalAwards=false
• 关键词: Perception; Control; Dynamic; Perspective

An intelligent system needs to control the flow of information through judicious choice of its scarce resources. In Biology and in Engineering, Motion and Shape Estimation is probably the most important subtask that the visual pathway needs to perform. In this research, we concentrate on MOTION and study how an Artificial Turtle might visually attend to its prey or in engineering, how a robot might control its gaze and lock on to a moving target. Our starting problem is the engineering problem of generating reasonable motion models that describe the optical flow on the retina, how the retinal flow is represented by neural signals and how these motion parameters can be estimated using robust filters operating on a sequence of noisy observed spikes. Our second problem, is to study how the optical flow is internalized by the visual pathway. This involves representation of an analog signal by the neural circuit, stable communication of the neural code, from retina to cortex and finally computation at each stage but predominantly at the cortex. Our third problem is to view the cortex dynamically and study the feedback and feedforward interconnection of the various cells. We introduce a new neurodynamical system with Automatic Gain Control and plan to compare our model with known experimental data. We would like to know under what condition the cortex remains a stable dynamical system. We also propose to study the frequency response of the cortical interconnection. Our last problem is to study the motor control problem pertaining to the eye movement. If the turtle has to stare at its prey, both the instantaneous position of the prey and in input to the eye-movement control system are analog signals that have to be represented by neural codes. Such a tracking problem with both the tracking signals and the control signals are represented neurally has never been studied. Specifically, we would like to design a neural circuit that would generate the required control inputs to maintain a given eye position or to gaze at a given target.This research is about Dynamics and Control with neural encoding, interneuron communication and computation with the eventual goal to perceive and act intelligently in a dynamic environment

智能系统需要通过明智地选择其稀缺资源来控制信息流。 在生物学和工程学中，运动和形状估计可能是视觉通路需要执行的最重要的子任务。 在这项研究中，我们专注于运动，并研究人工海龟如何在视觉上关注它的猎物，或者在工程上，机器人如何控制它的目光并锁定移动目标。 我们的起始问题是产生合理的运动模型，描述视网膜上的光流，视网膜流是如何表示的神经信号，以及如何使用鲁棒滤波器操作的噪声观测尖峰序列，这些运动参数可以估计的工程问题。 我们的第二个问题是研究光流是如何被视觉通路内化的。 这涉及到神经回路对模拟信号的表示，从视网膜到皮层的神经代码的稳定通信，以及最终在每个阶段但主要在皮层的计算。 我们的第三个问题是动态地观察皮层，研究各种细胞的反馈和前馈互连。 我们介绍了一个新的神经动力学系统与自动增益控制，并计划将我们的模型与已知的实验数据进行比较。 我们想知道在什么条件下皮层仍然是一个稳定的动力系统。 我们还建议研究皮层互连的频率响应。 我们的最后一个问题是研究与眼球运动有关的运动控制问题。 如果海龟必须盯着它的猎物，猎物的瞬时位置和输入到眼睛运动控制系统的信号都是模拟信号，必须由神经代码表示。 这样的跟踪问题与跟踪信号和控制信号都表示神经从来没有研究过。 具体来说，我们想设计一个神经回路，它可以产生所需的控制输入，以保持给定的眼睛位置或凝视给定的目标，本研究是关于动力学和控制的神经编码，神经元间的通信和计算，最终目标是在动态环境中感知和智能行动