supported by the National Natural Science Foundation of China(No.41272325);the Natural Science Foundation of Jiangsu Province(No.BK20130787);the Fundamental Research Funds for the Central Universities(No.NS2014003);the Research Fund of Graduate Education and Teaching Reform of Nanjing University of Aeronautics and Astronautics(NUAA)(No.2017-2);the Research Fund of Education and Teaching Reform of College of Aerospace Engineering,NUAA(No.2017-5),China
目的 LNP(linear-nonlinear-Poisson)模型很好地解译了神经元的响应过程,其重要环节之一是线性滤波器的提取。针对传统i STAC(information-theoretic spike-triggered average and covariance)算法运用于LNP模型时的神经元特性表征不足...