BIC: Pattern Generating Circuits for Computation and Control

在这个项目中，密苏里州圣路易斯市华盛顿大学的PI和德克萨斯州拉伯克市德克萨斯理工大学的Co-PI提议研究振荡模式作为模拟计算设备的作用。具体地说，振荡图案是由空间分布的弱耦合动力系统阵列产生的，其中耦合主要是局部的，可能有几个长程相互作用。此外，网络中的一些动态系统由外部输入驱动，这些输入调制整个网络产生的时空信号。图案产生电路将在MEMS(微型机电系统)阵列、耦合激光器阵列和耦合神经元阵列中实现。这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，在海龟的视觉皮质中，耦合的神经元产生一种传播的活动波，似乎对海龟视网膜的视觉输入做出反应。像WISE一样，一组耦合激光器似乎锁相成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，可以使用MEMS器件阵列来实现静电控制的微执行器。它们可以用来控制陆地爬行者或游泳者的运动。对于三个模式产生电路中的每一个，将考虑以下两个特定任务来研究受控输入和所产生的振荡模式之间的关系。如果输入是感官输入，即。视觉输入到视网膜，产生的振荡模式编码感觉信号。例如，目标的位置和速度被编码在所产生的皮层波的时空响应中。一项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。对于MEMS阵列的静电输入，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。步态控制是运动中的一项重要任务，它包括保持步态和在步态之间切换。为了完成这项任务，人们需要从一种振荡模式切换到另一种模式，可能要尽可能快。综上所述，模式产生电路将用于感官编码和解码的目的，其具体目标是“目标跟踪”。它们还将被用来向大量执行器提供协调控制信号，这些执行器的具体目标是“运动控制”。提出的问题的一个重要扩展是步态控制，它涉及在最小时间内平滑地在模式之间切换。

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.