Implementation of V1 Area Contour Integration Mechanism and Attention Selection Based on Excitation-Inhibition Intersecting Cortical Model_Journal of Biomedical Engineering

Authors：

 GAOShan ¹ , BIDuyan ¹ , RENYuhuan ² , WEINa ¹

1. College of Engineering, The Air Force Engineering University, Xi'an 710038, China;
2. Guangzhou Military Region Air Force Unit 95007, Guangzhou 510000, China;

Corresponding author：

GAOShan, Email: 17709223919@163.com

Keywords：

intersecting cortical model; V1 region contour integration; object contour chain-code; attention selection

DOI：

10.7507/1001-5515.20160155

Video：

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Abstract Full text Figures/Tables Video References Cited by

This paper aims to utilize the intersecting cortical model (ICM), which imitates the biological neural cells sync pulse, to preliminary research about the contour integration mechanism and the selection of attention. The idea of "Excitement-Inhibition" oscillation is introduced into the ICM, and meanwhile, the target contour chain code is used as the high-level feedback to control the input. Thus, we propose the Excitation-Inhibition-ICM which contains both the BUTTON-UP and the TOP-DOWN mechanism. The experimental results showed that the proposed model could effectively suppress noise to make the smooth edge synchronization issue, thus completing the process of BOTTOM-UP. The introduction of the target contour chain code can obtain consistent target outline with the input target chain code, but other targets cannot form a closed contour since they do not match with the input target chain code, so as to realize the TOP-DOWN mechanism. The results proved that our proposed model could imitate the contour integration mechanism and the selection of attention of the visual cortex V1.

Citation： GAO Shan, BI Duyan, REN Yuhuan, WEI Na. Implementation of V1 Area Contour Integration Mechanism and Attention Selection Based on Excitation-Inhibition Intersecting Cortical Model. Journal of Biomedical Engineering, 2016, 33(5): 963-971. doi: 10.7507/1001-5515.20160155 Copy

1.	寿天德.视觉信息处理的脑机制[M].合肥:中国科学技术大学出版化, 2010:10.
2.	梅岩艾, 王建军, 王世强.生理学原理[M].北京:高等教育出版社, 2011.
3.	LI Zhaoping. A neural model of contour integration in the primary visual cortex[J]. Neural Comput, 1998, 10(4):903-940.
4.	LI Zhaoping. Neural dynamics in a recurrent network model of primary visual cortex[C]//Ninth International Conference on Artificial Neural Networks, 1999. Edinburgh:1999, 1:280-285.
5.	邓小木, 陈忠泽.基于视觉皮层机制的轮廓整合的神经网络模型[J].无线互联科技, 2012, (12):9-13.
6.	LI Zhaoping, DAYAN P. Computational differences between asymmetrical and symmetrical networks[J]. Network, 1999, 10(1):59-77.
7.	LI Zhaoping, ATICK J J. Towards a theory of the striate cortex[J]. Neural Comput, 1994, 6(1):127-146.
8.	ECKHORN R, REITBOECK H J, ARNDT M, et al. Feature linking via stimulus-evoked oscillations experimental results from cat visual cortex and functional implications from a network model[C]//International Joint Conference on Neural Networks, 1989. IJCNN. Washington DC, 1989, 1:723-730.
9.	EKBLAD U, KINSER J M. Theoretical foundation of the intersecting cortical model and its use for detection of aircrafts, cars and nuclear explosion tests[J]. Signal Processing, 2004, 84(7):1131-1146.
10.	EKBLAD U, KINSER J M, ATMER J, et al. The intersecting cortical model in image processing[J]. Nucl Instrum Methods Phys Res A, 2004, 525(1-2):392-396.
11.	周昌雄, 曹丰文, 崔鸣, 等.基于格式塔心理学原理的几何活动轮廓模型[J].中国图象图形学报, 2008, 13(5):924-929.
12.	库尔特·考夫卡.格式塔心理学原理(上、下)[M].李炜, 译.杭州:浙江教育出版社, 1997.
13.	ATICK J J, LI Zhaoping, REDLICH A N. Understanding retinal color coding from first principles[J]. Neural Comput, 1992, 4(4):559-572.
14.	FIELD D J, HAYES A, HESS R F. Contour integration by the human visual system:evidence for a local "association field"[J]. Vision Res, 1993, 33(2):173-193.
15.	KOVÁCS I, JULESZ B. A closed curve is much more than an incomplete one:effect of closure in figure-ground segmentation[J]. Proc Natl Acad Sci U S A, 1993, 90(16):7495-7497.
16.	刘献荣.基于PCNN目标轮廓整合模型[D].上海:复旦大学, 2000.
17.	马奇, 张立明.快速注意力选择计算及其在图像质量评价中的应用[J].计算机辅助设计与图形学学报, 2009, 21(7):973-983.
18.	过晨雷.带有以往的视觉记忆模型及其在注意力选择上的应用[J].模式识别与人工智能, 2008, 21(3):381-387.
19.	TERMAN D, WANG Deliang. Global competition and local cooperation in a network of neural oscillator[J]. Physica D:Nonlinear Phenomena, 1995, 81(1-2):148-176.
20.	WANG Deliang, TERMAN D. Image segmentation based on oscillatory correlation[J]. Neural Comput, 1997, 9(4):805-836.
21.	WANG Deliang. On connectedness:a solution based on oscillatory correlation[J]. Neural Comput, 2000, 12(1):131-139.

1. 寿天德.视觉信息处理的脑机制[M].合肥:中国科学技术大学出版化, 2010:10.
2. 梅岩艾, 王建军, 王世强.生理学原理[M].北京:高等教育出版社, 2011.
3. LI Zhaoping. A neural model of contour integration in the primary visual cortex[J]. Neural Comput, 1998, 10(4):903-940.
4. LI Zhaoping. Neural dynamics in a recurrent network model of primary visual cortex[C]//Ninth International Conference on Artificial Neural Networks, 1999. Edinburgh:1999, 1:280-285.
5. 邓小木, 陈忠泽.基于视觉皮层机制的轮廓整合的神经网络模型[J].无线互联科技, 2012, (12):9-13.
6. LI Zhaoping, DAYAN P. Computational differences between asymmetrical and symmetrical networks[J]. Network, 1999, 10(1):59-77.
7. LI Zhaoping, ATICK J J. Towards a theory of the striate cortex[J]. Neural Comput, 1994, 6(1):127-146.
8. ECKHORN R, REITBOECK H J, ARNDT M, et al. Feature linking via stimulus-evoked oscillations experimental results from cat visual cortex and functional implications from a network model[C]//International Joint Conference on Neural Networks, 1989. IJCNN. Washington DC, 1989, 1:723-730.
9. EKBLAD U, KINSER J M. Theoretical foundation of the intersecting cortical model and its use for detection of aircrafts, cars and nuclear explosion tests[J]. Signal Processing, 2004, 84(7):1131-1146.
10. EKBLAD U, KINSER J M, ATMER J, et al. The intersecting cortical model in image processing[J]. Nucl Instrum Methods Phys Res A, 2004, 525(1-2):392-396.
11. 周昌雄, 曹丰文, 崔鸣, 等.基于格式塔心理学原理的几何活动轮廓模型[J].中国图象图形学报, 2008, 13(5):924-929.
12. 库尔特·考夫卡.格式塔心理学原理(上、下)[M].李炜, 译.杭州:浙江教育出版社, 1997.
13. ATICK J J, LI Zhaoping, REDLICH A N. Understanding retinal color coding from first principles[J]. Neural Comput, 1992, 4(4):559-572.
14. FIELD D J, HAYES A, HESS R F. Contour integration by the human visual system:evidence for a local "association field"[J]. Vision Res, 1993, 33(2):173-193.
15. KOVÁCS I, JULESZ B. A closed curve is much more than an incomplete one:effect of closure in figure-ground segmentation[J]. Proc Natl Acad Sci U S A, 1993, 90(16):7495-7497.
16. 刘献荣.基于PCNN目标轮廓整合模型[D].上海:复旦大学, 2000.
17. 马奇, 张立明.快速注意力选择计算及其在图像质量评价中的应用[J].计算机辅助设计与图形学学报, 2009, 21(7):973-983.
18. 过晨雷.带有以往的视觉记忆模型及其在注意力选择上的应用[J].模式识别与人工智能, 2008, 21(3):381-387.
19. TERMAN D, WANG Deliang. Global competition and local cooperation in a network of neural oscillator[J]. Physica D:Nonlinear Phenomena, 1995, 81(1-2):148-176.
20. WANG Deliang, TERMAN D. Image segmentation based on oscillatory correlation[J]. Neural Comput, 1997, 9(4):805-836.
21. WANG Deliang. On connectedness:a solution based on oscillatory correlation[J]. Neural Comput, 2000, 12(1):131-139.

Journal of Biomedical Engineering

Implementation of V1 Area Contour Integration Mechanism and Attention Selection Based on Excitation-Inhibition Intersecting Cortical Model

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