In this paper, we make some analysis on the FitzHugh-Nagumo model and improve it to build a neural network, and the network is used to implement visual selection and attention shifting. Each group of neurons representing one object of a visual input is synchronized; different groups of neurons representing different objects of a visual input are desynchronized. Cooperation and competition mechanism is also introduced to accelerate oscillating frequency of the salient object as well as to slow down other objects, which result in the most salient object jumping to a high frequency oscillation, while all other objects being silent. The object corresponding to high frequency oscillation is selected, then the selected object is inhibited and other neurons continue to oscillate to select the next salient object. © 2010 Springer-Verlag.
CITATION STYLE
Wang, H., Qiao, Y., Duan, L., Fang, F., Miao, J., & Ma, B. (2010). Visual selection and attention shifting based on FitzHugh-Nagumo equations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6064 LNCS, pp. 240–249). https://doi.org/10.1007/978-3-642-13318-3_31
Mendeley helps you to discover research relevant for your work.