Implementation and Analysis of Pulse Propagating Networks

近年来的生理学和数学研究表明，大脑尤其是皮层的复杂信息处理是由神经元对非同步传入兴奋性动作电位的精细时间结构作出敏感反应而实现的。神经元的功能是作为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。实数处理功能强大，但普通数字计算机无法实现，本研究利用模拟集成电路技术实现了时空处理网络，该网络可提供连续时间和电压、电流等变量。首先，提出了异步脉冲传播网络的核心单元--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

It is suggested, from the recent physiological and mathematical studies, that the sophisticated information processing in the brain, in particular in the cortex, is achieved by the neuron that sensitively responses to the fine time structure of asynchronously incoming excitatoly action potentials. The 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 1.2 mum CMOS semiconductor technology. Characteristics 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