Biological　vision　is　very　effective　and　accurate　in　scene　classification　and　recognition.　Based　on　this,　this　paper　proposes　a　biological　visual　neural　computing　model　based　on　the　anatomical　structure　of　rat　brain,　which　is　characterized　by:　constructing　a　biological　visual　scene　memory　model　(visual　word　bag),　imitating　the　biological　brain＇s　storage　of　environmental　scene　information,　and　calculating　the　similarity　between　the　current　scene　information　and　the　visual　template;　designing　and　constructing　the　object　details　located　in　the　lateral　entorhinal　cortex　and　the　peripheral　olfactory　cortex　Cell　discharge　model.　Experimental　results　show　that　the　proposed　model　can　effectively　extract　image　features　and　generate　visual　word　bag　model　based　on　image　features.　Compared　with　ratslam　scan　line　strength　model,　the　retrieval　time　of　this　model　is　greatly　shortened;　The　object　cell　discharge　model　with　image　similarity　information　as　input　can　show　similar　expression　of　discharge　rate　as　physiological　research,　which　verifies　the　effectiveness　and　efficiency　of　the　proposed　model.　The　research　results　lay　a　foundation　for　the　research　of　robot　environment　cognition　method　based　on　brain　cognitive　mechanism.　©　2021　IEEE.