The　human　brain　is　one　of　the　most　sophisticated　and　intelligent　functional　organization　systems　found　by　the　human　at　present,　and　its　complexity　lies　in:　(i)　Tens　of　thousands　of　neurons　are　interconnected　by　synapses　to　form　the　complex　human　brain　structure,　which　is　the　material　and　physiological　basis　of　the　brain　normal　work.　(ii)　These　neurons　connected　to　each　other　exhibit　complex　and　diverse　brain　activities　by　their　interactions,　such　as　visual　information　processing,　logical　reasoning　and　language　expression　and　so　on.　More　importantly　after　a　long　period　of　evolution,　the　human　brain　is　highly　intelligent,　which　makes　that　the　human　not　only　can　adapt　to　the　environment,　but　also　can　transform　the　world.　This　diversity　and　intelligence　of　the　human　brain　function　arouse　great　interest　from　researchers　and　have　also　been　the　most　important　contents　in　the　study　of　the　brain　science.　Last　more　than　20　years,　nuclear　magnetic　imaging　technologies　have　got　rapid　development　on　nuclear　magnetic　imaging　technologies,　such　as　electroencephalography,　magneto　encephalography　and　functional　magnetic　resonance　imaging　(fMRI),　which　greatly　promote　the　development　of　the　human　brain　function　research.　Especially,　fMRI　has　the　advantages　of　no　invasiveness,　high　resolution　and　the　simplicity　and　repeatability　of　the　operation,　and　has　brought　a　new　development　opportunity　for　the　research　of　the　human　brain　function.　Recently,　based　on　fMRI　data,　some　computational　methods　have　been　used　to　divide　the　human　brain　functionally　where　the　functional　parcellation　methods　of　the　human　brain　divide　full　brain　regions　or　local　brain　regions　into　disjoint　subregions　according　to　the　functional　consistency　measurements,　thus　depicts　the　segmentation　of　the　human　brain　function　and　plays　a　fundamental　role　in　the　study　of　the　brain　function.　Studies　have　shown　that　the　functional　consistency　of　the　subregions　obtained　by　the　human　functional　parcellation　is　higher　than　that　of　brain　regions　acquired　in　the　human　structural　atlases.　Namely,　the　human　brain　functional　parcellation　is　more　suitable　for　the　functional　analysis　of　the　human　brain.　Further,　the　more　real　brain　functional　networks　and　the　more　interpretability　results　could　be　obtained　by　applying　divided　functional　subregions,　which　can　provide　a　new　approach　for　the　research　and　exploration　of　the　human　brain　disease　mechanisms.　In　this　review,　the　principle　of　fMRI,　the　acquisition　process　and　characteristics　of　fMRI　data　are　first　introduced,　which　can　help　researchers　understand　in　depth　fMRI　data　and　associated　calculation　methods.　On　this　basis,　the　general　flow　of　the　human　brain　functional　parcellation　is　elaborated,　where　the　human　brain　functional　parcellation　is　a　key　step.　And　then,　the　paper　gives　a　classification　system　of　the　human　brain　functional　parcellation　methods　and　discusses　the　major　human　brain　functional　parcellation　algorithms　and　their　characteristics　in　detail,　which　enables　researchers　to　have　a　more　systematic　and　in-depth　understanding　on　the　research　field.　To　make　an　objective　comparison,　the　similarity　measures　and　evaluations　commonly　used　in　the　human　brain　functional　parcellation　algorithms　are　listed　and　their　characteristics　are　also　outlined　to　guide　the　further　study　of　the　human　brain　functions.　Next,　the　paper　summarizes　the　application　of　the　human　brain　functional　parcellation　at　the　aspects　of　the　human　brain　functional　network　construction,　a　neurological　disease　research　and　the　state　forecast　of　subjects.　Finally,　the　challenging　problems　and　future　research　directions　are　deeply　analyzed　from　the　perspective　of　both　scientific　and　technical　issues.　This　work　is　hopefully　beneficial　to　the　researchers　engaged　in　the　human　brain　function　research.　©　2016,　Science　Press.　All　right　reserved.