鸽视顶盖快速显著感知编码模型研究

doi:10.16182/j.issn1004731x.joss.201811006

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (11): 4086-4099.doi: 10.16182/j.issn1004731x.joss.201811006

鸽视顶盖快速显著感知编码模型研究

王松伟¹, 黄淑漫³, 师丽^1,2, 王梦珂³

1.郑州大学电气工程学院,河南郑州 450001;
2.清华大学自动化系,北京 100084;
3.郑州大学产业技术研究院,河南郑州 450001

收稿日期:2018-05-30 修回日期:2018-07-16 发布日期:2019-01-04
作者简介:王松伟(1979-),男,回族,河南周口,博士,讲师,研究方向为生物视觉机制研究与建模;黄淑漫(1994-),女,河南鲁山,博士生,研究方向为控制科学与工程。
基金资助:
国家自然科学基金(U1304602)

Neural Coding Model for Fast and Significant Perceptual in the Pigeon Optic Tectum

Wang Songwei¹, Huang Shuman³, Shi Li^1,2, Wang Mengke³

1.School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China;
2.Department of Automation, Tsinghua University, Beijing 100084, China;
3.Industrial Technology Research Institute, Zhengzhou University, Zhengzhou 450001, China

Received:2018-05-30 Revised:2018-07-16 Published:2019-01-04

摘要/Abstract

摘要： 在经典目标识别理论中,哺乳动物的视网膜和LGN中许多神经元执行了DoG (Difference of Gaussian)操作,其功能一般认为是白化,祛除冗余,并增强了边缘。通过对鸽视顶盖的ON-OFF神经元进行电生理研究,发现其利用FSL(First-Spike Latency)进行场景整体信息粗略快速的传递,利用发放率对场景中显著性特征进行相续的传递。通过解析神经元响应模式,提出了OT(Optic Tectum)的ON-OFF神经元工作机制的一种假设,搭建了模型架构。该研究对新型的Spike神经网络的研究具有一定的借鉴意义。

关键词: 视顶盖, 显著性表征, spike神经网络, 延时编码

Abstract: In the classical target recognition theory, many neurons in the mammalian retina and LGN perform DoG operations. Their functions are generally considered to be whitening, eliminating redundancy, and enhancing edges. Where is the redundant information? In this paper, the electrophysiological study of the ON-OFF neurons of the dove optic roof was performed. It was found that the FSL was used to carry out the rough and fast transfer of the whole scene information, and then the salient features in the scene were successively transmitted using the issue rate. For this reason, by analyzing the response pattern of neurons, this paper proposes an assumption of the ON-OFF neuron working mechanism of OT (Optic Tectum) and builds a model architecture. This research has certain reference significance for the research of the new Spike neural network.

Key words: optic tectum, significant characterization, spike neural network, delayed encoding

中图分类号:

Q424

王松伟, 黄淑漫, 师丽, 王梦珂. 鸽视顶盖快速显著感知编码模型研究[J]. 系统仿真学报, 2018, 30(11): 4086-4099.

Wang Songwei, Huang Shuman, Shi Li, Wang Mengke. Neural Coding Model for Fast and Significant Perceptual in the Pigeon Optic Tectum[J]. Journal of System Simulation, 2018, 30(11): 4086-4099.

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鸽视顶盖快速显著感知编码模型研究

Neural Coding Model for Fast and Significant Perceptual in the Pigeon Optic Tectum

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