Heuristic　search　is　the　largest　qualitative　gap　between　human　performance　and　computer　performance.　The　dominant　study　in　heuristic　search　is　an　empirical　way　in　computer　science　especially　in　artificial　intelligence.　In　this　paper,　we　examine　the　factors　that　are　impact　heuristic　search　from　the　perspective　of　human　brain.　Subjects　performed　a　set　of　heuristic　problems　in　functional　Magnetic　Resonance　Imaging　(fMRI)　environment.　Then　a　computational　cognitive　model　is　set　up　to　simulate　processes　of　information　processing　of　the　heuristics　problem　solving.　During　the　modeling,　we　found　that　two　main　factors,　visual　attention　and　goal　control,　are　responsible　for　speeding　up　heuristic　search　in　problem　solving,　where　visual　attention　captures　a　target　selectively　with　the　goal　state-directed　control.　The　interaction　between　these　two　cognitive　systems　speeds　up　the　heuristic　search,　which　is　superior　to　machine　intelligence.　We　demonstrate　this　conclusion　by　results　of　modeling,　including　cost　analysis　in　time,　information　processing　operations,　and　fitness　of　fMRI　results　and　model　prediction.