Implementation and Analysis of Pulse Propagating Networks

最近的生理学和数学研究表明，大脑皮层神经元利用非同步传入兴奋性动作电位的精细时间结构来实现复杂的信息处理。这样的神经元充当时空输入脉冲串之间的重合检测器。连续变量和时间在具有重合检测器神经元的时空网络中很重要，因为它们可以进行实数处理。实数处理能力很强，但普通数字计算机无法实现，本研究采用模拟集成电路技术实现了具有连续时间和电压、电流等变量的时空处理网络。首先，提出了异步脉冲传播网络的核心元件--异步脉冲神经元模型。研究了单个神经元和多个神经元组成的神经网络的响应特性。结果表明，单神经元的混沌响应是可见的，而且在网络中形成了动态的集合。动态集合是时空信息编码的候选对象之一.其次，提出了模型神经元、突触和轴突的模拟电路。轴突回路中传播脉冲的延迟时间可以连续控制。此外，突触电路的权重可以数字地改变。最后，建议的电路制造使用1.2妈妈CMOS半导体技术。测量了电路的特性。结果，从芯片确认了混沌响应。此外，还观察到轴突回路中的脉冲延迟。通过IC实现，说明了用异步脉冲传播网络进行实数处理的可能性

Recent physiological and mathematical studies suggest that the neuron in cortex uses fine time structure of asynchronously incoming excitatoiy action potentials to achieve sophisticated information processing in the brain. Such a neuron functions as a coincident detector among spatio-temporal input pule trains. Continuous variables and time are important in the spatio- temporal network with coincident detector neurons, because real-number processing is possible with them. The real-number processing is very powerful but cannot be realized by the ordinary digital computer.In this research, the spatio-temporal processing network is implemented using analog integrated circuit technology where continuous time and variables such as voltage and current are available, First of all, an asynchronous pulse neuron model that is the core element of the asynchronous pulse propagating network is proposed. The response characteristics of the single neuron and neural network composed of numbers of neurons are investigated. As the results, chaotic responses are observed from single neuron, furthermore, dynamical assembly is organized in the network. The dynamical assembly is one candidate of the information coding in the Spatio- temporal processing. Secondly, analog circuits for the model neuron, the synapse and the axon are proposed. The delay time of the propagating pulses in the axon circuits can be controlled continuously. Moreover, weight of the synaptic circuit can be altered digitally. Finally, the proposed circuits are fabricated using 1.2mum CMOS semiconductor technology. Characteritics of the circuits are measured. As a consequence, chaotic responses are confirmed from the chip. Furthermore, pulse delay in the axon circuit is also observed. The possibility of the real-number processing using asynchronous pulse propagating network is shown through the IC implementation