Visual　context　plays　a　significant　role　in　humans＇　gaze　movement　for　target　searching.　How　to　transform　the　visual　context　into　the　internal　representation　of　a　brain-like　neural　network　is　an　interesting　issue.　Population　cell　coding　is　a　neural　representation　mechanism　which　was　widely　discovered　in　primates＇　visual　neural　system.　This　paper　presents　a　biologically　inspired　neural　network　model　which　uses　a　population　cell　coding　mechanism　for　visual　context　representation　and　target　searching.　Experimental　results　show　that　the　population-cell-coding　generally　performs　better　than　the　single-cell-coding　system.　©　2010　Springer-Verlag　Berlin　Heidelberg.