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Comparison of IT Neural Response Statistics with Simulations
Dong, Qiulei1,2,3; Liu, Bo1,2; Hu, Zhanyi1,2,3
2017-07-12
发表期刊FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
卷号11
文章类型Article
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.
关键词Synthetic Neuron Response Single-neuron Selectivity Population Sparseness Response Statistics
WOS标题词Science & Technology ; Life Sciences & Biomedicine
DOI10.3389/fncom.2017.00060
关键词[WOS]VISUAL-CORTEX ; HIERARCHICAL-MODELS ; SPARSENESS ; SELECTIVITY
收录类别SCI
语种英语
项目资助者Chinese Academy of Sciences(XDB02070002) ; National Natural Science Foundation of China(61421004 ; 61375042 ; 61573359)
WOS研究方向Mathematical & Computational Biology ; Neurosciences & Neurology
WOS类目Mathematical & Computational Biology ; Neurosciences
WOS记录号WOS:000406366700001
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被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20702
专题模式识别国家重点实验室_机器人视觉
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
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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).
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