文献类型：期刊文献

英文题名：Simulation of retinal ganglion cell response using fast independent component analysis

作者：Wang, Guanzheng[2];Wang, Rubin[1,2];Kong, Wanzheng[1,3];Zhang, Jianhai[1,3]

机构：[1]Hangzhou Dianzi Univ, Coll Comp Sci, Hangzhou, Zhejiang, Peoples R China;[2]East China Univ Sci & Technol, Sch Sci, Inst Cognit Neurodynam, Meilong Rd 130, Shanghai 200237, Peoples R China;[3]Baiyang Rd 1158, Hangzhou 310018, Zhejiang, Peoples R China

年份：2018

卷号：12

期号：6

起止页码：615

外文期刊名：COGNITIVE NEURODYNAMICS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000452074700008)】；

基金：This study was funded by the National Natural Science Foundation of China (Nos. 11232005, 11472104).

语种：英文

外文关键词：Sparse coding; Independent component analysis; Kurtosis; Sparsity

摘要：Advances in neurobiology suggest that neuronal response of the primary visual cortex to natural stimuli may be attributed to sparse approximation of images, encoding stimuli to activate specific neurons although the underlying mechanisms are still unclear. The responses of retinal ganglion cells (RGCs) to natural and random checkerboard stimuli were simulated using fast independent component analysis. The neuronal response to stimuli was measured using kurtosis and Treves-Rolls sparseness, and the kurtosis, lifetime and population sparseness were analyzed. RGCs exhibited significant lifetime sparseness in response to natural stimuli and random checkerboard stimuli. About 65 and 72% of RGCs do not fire all the time in response to natural and random checkerboard stimuli, respectively. Both kurtosis of single neurons and lifetime response of single neurons values were larger in the case of natural than in random checkerboard stimuli. The population of RGCs fire much less in response to random checkerboard stimuli than natural stimuli. However, kurtosis of population sparseness and population response of the entire neurons were larger with natural than random checkerboard stimuli. RGCs fire more sparsely in response to natural stimuli. Individual neurons fire at a low rate, while the occasional burst of neuronal population transmits information efficiently.