In　this　talk,　we　will　describe　studying　on　granular　reasoning　of　human　and　Web　in　a　unified　way　from　the　viewpoint　of　Brain　Informatics.　We　consider　Web　granular　reasoning　as　an　application　of　human-inspired　granular　reasoning.　As　for　human　granular　reasoning,　based　on　the　previous　studies　about　basic-level　advantage　and　its　reversal　effect,　we　use　tMRIIERP　to　investigate　how　the　neural　system　cooperates　and　coordinates　with　each　other　when　the　starting　point　locates　in　the　basic　level　and　how　the　brain　modulates　and　adapts　to　the　change　when　the　starting　point　switches　to　a　more　general　level.　The　key　question　is　＇　＇can　we　fmd　a　new　cognitive　model　for　developing　human-level　Web　based　granular　reasoning　and　problem-solving?＇　In　order　to　answer　this　question,　we　investigate　the　cognitive　mechanism　and　neural　basis　of　human　problem　solving　and　reasoning,　for　developing　new　cognitively　inspired　Web　intelligence　models.　Based　on　the　above　results,　we　will　implement　Problem　Solver　Markup　Language　(PSML)　for　representing,　organizing,　retrieving,　and　selecting　Web　information　sources　with　multiple　levels　of　granularity,　and　develop　PSML　based　Web　inference　engines　for　personalized　wisdom　Web　problem　solving　and　services.　©　2009　IEEE.