The Study Of Dynamic Correlation Of Neurons In Rat Primary Visual Cortex Under The Grating Stimulus

The visual system is the main way for mammals to receive information from outside world.The primary visual cortex is the main part of brain for processing the visual information. The information processing in brain is achieved by dynamic interaction of neurons on network level. The dynamic change of correlation between neurons reflects the dynamic connection tightness between neurons and it is the basis of information transmission in neural network. Therefore, the research of dynamic correlation between neurons is one of the key issues in the field of neuroscience and it is important for revealing the mechanism of information encoding of animal visual system.With the development of signal acquisition system, the difficulties for researching correlation between neurons focused on the lack of methods. The conventional methods can only research correlation between two neurons and they can hardly obtain the dynamic correlation of neurons. In this paper, a novel method called state-space log-linear model(SLM) is used to research the second order and third order dynamic correlation of neurons under stimulus with different orientation gratings. The main contents are as follows:(1) The screening of corrected neurons. In order to provide neurons with correlation for the SLM, we used conventional cross-correlogram to screening neurons with correlation from the neurons population obtained by the multi-channel signal acquisition system. We used the selected neurons to form paired neurons and group of three neurons.(2) Optimizing the confidence interval of estimated values of the model. The SLM uses Bayesian methods to estimate the parameters to obtain the correlation in different orders and Bayesian estimation gives the confidence interval as well as the estimated values. In this paper, we extract the features of input data to research the effect of input data on the width of confidence interval, and then we propose to optimize the confidence interval by screening the input data. (3) The research of second-order dynamic correlation between paired neurons. By extracting the characteristics of second-order correlation curve, we studied relationship between the synchronization of paired neurons and orientation gratings. First, by extracting the mean value of amplitudes of curves, we researched the changing strength of second-order correlation under different orientation gratings. Then, by extracting the slope of fitting straight line, we studied the increase and decrease characteristics of second-order correlation under different orientation gratings. Finally, by extracting the variance of the curve, we studied the volatility of second-order correlation under different orientation gratings.(4) The research of third-order dynamic correlation of group of three neurons. By extracting the characteristic of curves of third-order correlation, we studied relationship between the synchronization of three neurons and orientation gratings. First, we introduced the calculation of the third order correlation and the difference between the second order and the third order. Then, by extracting the mean value of amplitudes of curves, we researched the changing strength of third-order correlation under different orientation gratings. we researched the difference between third-order correlation and second-order correlation by comparing the mean amplitude of their curves.Then, by extracting the slope of fitting straight line, we studied the increase and decrease characteristics of third-order correlation under different orientation gratings. Finally, by extracting the variance of the curve, we studied the volatility of third-order correlation under different orientation gratings.