The analysis of dynamic correlation between neurons based on state-space log-linear model
[1]SHI Li,XU Kun-feng,NIU Xiao-ke.The analysis of dynamic correlation between neurons based on state-space log-linear model[J].Journal of Zhengzhou University (Engineering Science),2015,36(01):1-5.[doi:10.3969/ j.issn. 1671 -6833.2015.01.001]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
36卷
Number of periods:
2015 01
Page number:
1-5
Column:
Public date:
2015-01-10
- Title:
- The analysis of dynamic correlation between neurons based on state-space log-linear model
- CLC:
- TN911.7
- DOI:
- 10.3969/ j.issn. 1671 -6833.2015.01.001
- Abstract:
- The research on correlation between neurons is the foundation to understand the mechanism of infor-mation transmission and coding of neuronal population. A novel method called state-space log-linear model wasused to estimate the dynamic correlation between paired neurons,and data sieving methods were proposed toimprove the accuracy of model results for the effects of input data characteristics on the confidence interval ofthe model estimated values. By extracting the characteristics of dynamic correlation curves,changing charac-teristics of paired neurons’correlation was analyzed and then the effect on information coding of visual stimu-lus from synchronization between paired neurons was studied. Experimental verification was carried out in theprimary visual cortex of anesthetized rats.The results show that: the accuracy of the estimated value of themodel can be improved by removing the data with small firing rates,and synchronization between paired neu-rons encodes the information of different grating stimuli.
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