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Dynamic Analysis of Neuronal Pathway by Engineering Identification Method for Non-linear Signal Processing

非线性信号处理工程辨识法神经通路动态分析

基本信息

批准号：
06640873
负责人：
SHIMOZAWA Tateo
金额：
$ 1.28万
依托单位：
Hokkaido University
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (C)
财政年份：
1994
资助国家：
日本
起止时间：
1994 至 1995
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-06640873/
关键词：
Non-linearity Neuron Signal processing Pulse density encoding Gaussian white noise Wiener's Analysis ウイナ-解析

项目摘要

Neuronal pathways, which operate as non-linear signal processors, were decomposed into several elements by using engineering method od informatics, and the internal mechanisms were revealed.First, accuracy of decomposition into sandwich system, a cascade of two linear filter elements sandwiching a nonmemory nonlinear element, was evaluated. The length of time domain data necessary for the element estimation ofinsect sensory system was determined for the z-transform method of the first and second Wiener kernels. Second, details of dynamics of the pulse density encoding mechanism of the insect wind receptor were extracted after removing the statistical response properties given by Wiener kernels. The refractory period of spike initiation was the origin of the hysteresis in the pulse density incoding.Third, input pathways to cercal sensory interneurons of cricket were studied. It was found that the spiking and nonspiking interneurons have different organizations of input pathway. Fourth, a new method for sandwich system decomposition, in which Laguerre functions were used to expand Wiener kernels, was developed. Fifth, by using the single electrode current clamp recording method, signal transfer from the synaptic current to spike train sequence in the cricket cercal sensory interneuron was determined. The post-synaptic membrane was confirmed as an integrating, passive low-pass filter, while the spike initiation area was identified as a band-pass active filter. Sixth, the stochastic resonance and the effects of noise in spike encoding were studied by numerical solution of the Hodgkin-Huxley model. Noise plays an essential role for spike encoding rather than deteriorating the signal.

利用信息学工程方法将神经元通路分解为若干个单元，揭示了神经元通路的内在机理.首先，评价了将神经元通路分解为两个线性滤波器单元级联一个非记忆非线性滤波器单元的三明治系统的精度.确定了第一、第二维纳核的z变换方法用于昆虫感觉系统元件估计所需的时域数据长度。其次，在去除由维纳核给出的统计响应特性之后，提取昆虫风感受器的脉冲密度编码机制的动力学细节。放电起始的不应期是脉冲密度编码滞后的根源。第三，研究了蟋蟀尾侧感觉中间神经元的输入通路。结果发现，发放和非发放中间神经元具有不同的输入通路组织。第四，提出了一种利用Laguerre函数扩展Wiener核的三明治系统分解方法。第五，采用单电极电流钳记录方法，研究了蟋蟀颈侧感觉中间神经元突触电流到锋电位序列的信号传递。突触后膜被证实为一个集成的，被动的低通滤波器，而尖峰起始区被确定为一个带通有源滤波器。第六，通过对Hodgkin-Huxley模型的数值求解，研究了棘波编码中的随机共振和噪声的影响。噪声对尖峰信号编码起着至关重要的作用，而不是使信号恶化。