Visual Selection and Attention Shifting Based on FitzHugh-Nagumo Equations

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.

• Type: Conference
• Year: 2010
• Where: ISNN
• Authors: Haili Wang, Yuanhua Qiao, Lijuan Duan, Faming Fang, Jun Miao, Bingpeng Ma
• Keywords: ISNN 2010, Neural Networks, Neurons, Salient Object, Visual Input