Development of a Scalable High Performance Reconfigurable Real-Time Signal Processing Platform for Dynamic Data-Driven Neural Simulations and Modeling

这一提议为开发高性能、可重构的信号处理平台提供了支持，该平台将允许实时分析大规模多通道神经生理学数据，并随后用于模拟和建模。计算架构将是一个分布式、实时的模块化设计系统，由连接在三维网格中的计算节点组成。计算节点将包括浮点数字信号处理器(DSP)、现场可编程门阵列(FPGA)和本地存储器。该系统是可重构的，算法可以直接在硬件上实现。现场可编程门阵列可以作为通信处理器，为计算节点之间的通信提供巨大的带宽。将系统配置为三维网格将允许系统扩展到处理任意数量的实时I/O数据流所需的任意数量的计算节点。该平台将利用对简单神经系统--板球的神经信号处理的分析来开发。具体地说，该平台的开发将允许调查合作神经编码方案，该方案用于传输有关板球神经系统内气流的信息。该平台将能够对神经信息进行实时解码，从而能够在神经信号在多个外围传感器和中央处理神经节之间传输时对编码信息进行实验扰动。如果该平台开发成功，神经功能分析中的交互控制将达到前所未有的程度。这可能导致对神经计算的生物学基础的重大洞察，以及实验和计算神经科学的新范式，实验和理论神经学家可以在体内合作测试神经功能假说。这一提议为开发高性能、可重构的信号处理平台提供支持，该平台将允许实时分析大规模多通道神经生理数据，并随后用于模拟和建模。计算架构将是一个分布式、实时的模块化设计系统，由连接在三维网格中的计算节点组成。计算节点将包括浮点数字信号处理器(DSP)、现场可编程门阵列(FPGA)和本地存储器。该系统是可重构的，算法可以直接在硬件上实现。现场可编程门阵列可以作为通信处理器，为计算节点之间的通信提供巨大的带宽。将系统配置为三维网格将允许系统扩展到处理任意数量的实时I/O数据流所需的任意数量的计算节点。该平台将利用对简单神经系统--板球的神经信号处理的分析来开发。具体地说，该平台的开发将允许调查合作神经编码方案，该方案用于传输有关板球神经系统内气流的信息。该平台将能够对神经信息进行实时解码，从而能够在神经信号在多个外围传感器和中央处理神经节之间传输时对编码信息进行实验扰动。如果该平台开发成功，神经功能分析中的交互控制将达到前所未有的程度。这可能导致对神经计算的生物学基础的重大洞察，以及实验和计算神经科学的新范式，在这种范式中，实验和理论神经学家可以合作测试体内神经功能的假说。

This proposal provides support for development of a high performance, reconfigurable signal-processing platform that will permit real-time analysis of large-scale multi-channel neurophysiologic data and subsequent use in simulation and modeling. The computational architecture will be a distributed, real-time system of modular design consisting of computational nodes connected in a three-dimensional mesh. A computational node will include a floating-point digital signal processor (DSP), a field programmable gate array (FPGA), and local memory. This system to be used is reconfigurable, so that algorithms can be directly implemented in the hardware. The FPGAs can act as communication processors, allowing significant bandwidth for communication between computational nodes. Configuring the system as a three-dimensional mesh will allow the system to scale to any number of computational nodes required to process an arbitrary number of real-time I/O data streams. The platform will be developed using the analysis of neural signal processing in a simple nervous system, that of the cricket. Specifically, the platform will be developed to allow investigation of the cooperative neural encoding schemes used to transmit information about air currents within the cricket's nervous system. The platform will enable real-time decoding of neural information, and will thus enable experimental perturbation of the encoded information while the neural signals are in transit between multiple peripheral sensors and the central processing ganglia. If the platform is successfully developed, an unprecedented degree of interactive control in the analysis of neural function will result. This could lead to major insights into the biological basis of neural computation and a new paradigm in experimental and computational neuroscience, one where experimental and theoretical neuroscientists can work together to test hypotheses of neural function in vivo.This proposal provides support for development of a high performance, reconfigurable signal-processing platform that will permit real-time analysis of large-scale multi-channel neurophysiologic data and subsequent use in simulation and modeling. The computational architecture will be a distributed, real-time system of modular design consisting of computational nodes connected in a three-dimensional mesh. A computational node will include a floating-point digital signal processor (DSP), a field programmable gate array (FPGA), and local memory. This system to be used is reconfigurable, so that algorithms can be directly implemented in the hardware. The FPGAs can act as communication processors, allowing significant bandwidth for communication between computational nodes. Configuring the system as a three-dimensional mesh will allow the system to scale to any number of computational nodes required to process an arbitrary number of real-time I/O data streams. The platform will be developed using the analysis of neural signal processing in a simple nervous system, that of the cricket. Specifically, the platform will be developed to allow investigation of the cooperative neural encoding schemes used to transmit information about air currents within the cricket's nervous system. The platform will enable real-time decoding of neural information, and will thus enable experimental perturbation of the encoded information while the neural signals are in transit between multiple peripheral sensors and the central processing ganglia. If the platform is successfully developed, an unprecedented degree of interactive control in the analysis of neural function will result. This could lead to major insights into the biological basis of neural computation and a new paradigm in experimental and computational neuroscience, one where experimental and theoretical neuroscientists can work together to test hypotheses of neural function in vivo.