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Comparison of IT Neural Response Statistics with Simulations
Dong, Qiulei1,2,3; Liu, Bo1,2; Hu, Zhanyi1,2,3
Source PublicationFRONTIERS IN COMPUTATIONAL NEUROSCIENCE
2017-07-12
Volume11
SubtypeArticle
AbstractLehky 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.
KeywordSynthetic Neuron Response Single-neuron Selectivity Population Sparseness Response Statistics
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.3389/fncom.2017.00060
WOS KeywordVISUAL-CORTEX ; HIERARCHICAL-MODELS ; SPARSENESS ; SELECTIVITY
Indexed BySCI
Language英语
Funding OrganizationChinese Academy of Sciences(XDB02070002) ; National Natural Science Foundation of China(61421004 ; 61375042 ; 61573359)
WOS Research AreaMathematical & Computational Biology ; Neurosciences & Neurology
WOS SubjectMathematical & Computational Biology ; Neurosciences
WOS IDWOS:000406366700001
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20702
Collection模式识别国家重点实验室_机器人视觉
Affiliation1.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
Recommended Citation
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).
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