BIC: Pattern Generating Circuits for Computation and Control

BIC：用于计算和控制的模式生成电路

• 批准号: 0736514
• 负责人: Bijoy Ghosh
• 金额: $ 29.18万
• 依托单位: Texas Tech University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-01-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0736514&HistoricalAwards=false
• 关键词: BIC; Pattern; Generating; Circuits; Computation

In this project, the PI from Washington University in St. Louis, Missouri and Co-PI from Texas Tech University in Lubbock, Texas propose to study the role of oscillatory patterns as an analog computational device. Specifically, the oscillatory patterns are generated by a spatially distributed array of weakly coupled dynamical systems, where the coupling is predominantly local, with perhaps a few long range interactions. Additionally, some of the dynamical systems in the network are driven by external inputs which modulate the spatiotemporal signal generated by the entire network.The pattern generating circuit would be implemented in an array of MEMS (micro electro mechanical systems), in an array of coupled LASERS and in an array of coupled NEURONS. Each of the three arrays is well known for their ability to generate oscillatory patterns. For example, in the visual cortex of turtles, coupled neurons produce a propagating wave of activity that seems to respond to the visual input to the turtle retina. Like wise, an array of coupled LASERS seems to phase-lock into a sustained level of oscillation with a certain phase relation between two adjacent LASERS. Finally, an array of MEMS devices can be used to implement electro-statically controlled micro-actuators. These can be used to control locomotion of a land crawler or a swimmer.For each of the three pattern generating circuits, the relationship between the controlled input and the generated oscillatory pattern would be studied with the following two specific tasks in mind. If the input is a sensory input, viz. visual input to the retina, the generated oscillatory patterns encode the sensory signals. For example, the location and velocity of a target is encoded in the spatiotemporal response of the generated cortical waves. An important task is to localize targets and to predict its future location by measuring the oscillatory patterns in the circuit. If the input to the circuit is a control input, viz. electrostatic input to a MEMS array, each element of the array is viewed as a signal generator that provides control input to a local actuator. An important task in locomotion is "gait control" which involves maintaining and switching between gaits. To achieve this task one needs to switch from one oscillatory pattern to another, perhaps as quickly as possible. In summary, pattern generating circuits will be used for the purpose of sensory encoding and decoding with a specific aim towards "target tracking". They will also be used to provide coordinated control signals to a large number of actuators with a specific aim towards "locomotion control". An important extension of the proposed problem is "gait control" which involves smoothly switching between patterns in minimum time.

在这个项目中，来自密苏里州圣路易斯的华盛顿大学的PI和来自德克萨斯州拉伯克的德克萨斯理工大学的Co-PI提出研究振荡模式作为模拟计算设备的作用。 具体而言，振荡模式产生的空间分布阵列的弱耦合动力系统，其中的耦合主要是本地的，也许有一些长距离的相互作用。 此外，网络中的一些动力系统由外部输入驱动，这些外部输入调制整个网络产生的时空信号。图案生成电路将在MEMS（微机电系统）阵列、耦合激光器阵列和耦合神经元阵列中实现。 三个阵列中的每一个都以其产生振荡图案的能力而闻名。 例如，在海龟的视觉皮层中，耦合的神经元产生一种传播的活动波，似乎是对海龟视网膜的视觉输入做出反应。 类似地，耦合激光器阵列似乎锁相到在两个相邻激光器之间具有一定相位关系的持续振荡水平。 最后，MEMS器件阵列可用于实现静电控制的微致动器。这些可以用于控制陆地爬行器或游泳者的运动。对于三个模式生成电路中的每一个，将研究受控输入和所生成的振荡模式之间的关系，并记住以下两个特定任务。 如果输入是感觉输入，即对视网膜的视觉输入，则所生成的振荡模式对感觉信号进行编码。例如，目标的位置和速度被编码在所生成的皮层波的时空响应中。 一个重要的任务是通过测量电路中的振荡模式来定位目标并预测其未来位置。 如果电路的输入是控制输入，即MEMS阵列的静电输入，则阵列的每个元件被视为向本地致动器提供控制输入的信号发生器。运动中的一项重要任务是“步态控制”，它涉及保持和切换步态。为了完成这个任务，人们需要从一种振荡模式切换到另一种振荡模式，也许要尽可能快。 总之，模式生成电路将用于感官编码和解码的目的，具体目标是“目标跟踪”。它们还将用于向大量致动器提供协调控制信号，具体目标是“运动控制”。所提出的问题的一个重要的扩展是“步态控制”，其中包括在最短的时间内顺利切换模式。