Visual selection and attention shifting based on FitzHugh-Nagumo equations - Details

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EI Scopus

Abstract：

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.

Keyword：

Vision Neural networks Neurons

Author Community：

[ 1 ] [Wang, Haili]College of Applied Science, Beijing University of Technology, Beijing 100124, China
[ 2 ] [Qiao, Yuanhua]College of Applied Science, Beijing University of Technology, Beijing 100124, China
[ 3 ] [Duan, Lijuan]College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
[ 4 ] [Fang, Faming]College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
[ 5 ] [Miao, Jun]Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
[ 6 ] [Ma, Bingpeng]Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China