Comparison of IT Neural Response Statistics with Simulations

doi:10.3389/fncom.2017.00060

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 机器人视觉团队

	Comparison of IT Neural Response Statistics with Simulations
	Dong, Qiulei1,2,3 ; Liu, Bo 1,2; Hu, Zhanyi1,2,3
刊名	FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
	2017-07-12
卷号	11
关键词	Synthetic Neuron Response Single-neuron Selectivity Population Sparseness Response Statistics
DOI	10.3389/fncom.2017.00060
文献子类	Article
英文摘要	Lehky et al. (2011) provided a statistical analysis on the responses of the recorded 674 neurons to 806 image stimuli in anterior inferotemporalm (AIT) cortex of two monkeys. In terms of kurtosis and Pareto tail index, they observed that the population sparseness of both unnormalized and normalized responses is always larger than their single-neuron selectivity, hence concluded that the critical features for individual neurons in primate AIT cortex are not very complex, but there is an indefinitely large number of them. In this work, we explore an "inverse problem" by simulation, that is, by simulating each neuron indeed only responds to a very limited number of stimuli among a very large number of neurons and stimuli, to assess whether the population sparseness is always larger than the single-neuron selectivity. Our simulation results show that the population sparseness exceeds the single-neuron selectivity in most cases even if the number of neurons and stimuli are much larger than several hundreds, which confirms the observations in Lehky et al. (2011). In addition, we found that the variances of the computed kurtosis and Pareto tail index are quite large in some cases, which reveals some limitations of these two criteria when used for neuron response evaluation.
WOS关键词	VISUAL-CORTEX ; HIERARCHICAL-MODELS ; SPARSENESS ; SELECTIVITY
WOS研究方向	Mathematical & Computational Biology ; Neurosciences & Neurology
语种	英语
WOS记录号	WOS:000406366700001
资助机构	Chinese Academy of Sciences(XDB02070002) ; National Natural Science Foundation of China(61421004 ; 61375042 ; 61573359)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/20702]
专题	自动化研究所_模式识别国家重点实验室_机器人视觉团队
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Dept Artificial Intelligence, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Dong, Qiulei,Liu, Bo,Hu, Zhanyi. Comparison of IT Neural Response Statistics with Simulations[J]. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE,2017,11.
APA	Dong, Qiulei,Liu, Bo,&Hu, Zhanyi.(2017).Comparison of IT Neural Response Statistics with Simulations.FRONTIERS IN COMPUTATIONAL NEUROSCIENCE,11.
MLA	Dong, Qiulei,et al."Comparison of IT Neural Response Statistics with Simulations".FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 11(2017).