Mental　arithmetic　is　the　complete　use　of　brain　functions　to　complete　the　basic　arithmetic　process　without　the　aid　of　other　tools　and　equipment.　Neuroimaging　studies　of　mental　arithmetic　have　revealed　some　brain　regions　and　networks　associated　with　them.　However,　there　are　still　many　unsolved　problems　about　the　brain　function　network　structure　in　mental　arithmetic.　We　designed　a　mental　arithmetic　experiment　consisting　of　four　experimental　conditions,　and　a　group　of　21　subjects　were　recruited　in　the　experiment.　The　collected　fMRI　data　was　used　to　construct　the　brain　functional　connectivity　network　with　atlas　of　Dosenbach-160.　We　used　graph　theoretic　based　network　analysis　method　to　calculate　the　small　world　attributes　and　network　efficiencies　of　each　subject＇s　brain　functional　network,　and　tested　the　statistical　differences　between　the　experimental　conditions.　The　results　show　that,　when　the　human　brain　performs　addition　or　subtraction,　the　functional　connectivity　network　statistically　shows　a　significant　characteristic　of　small　world　from　the　resting　state.　And　experiment　condition　of　resting　has　a　higher　clustering　coefficient　over　a　continuous　graph　density　than　number　matching,　showing　a　more　significant　small　world　property.　Results　of　network　efficiency　show　that　resting　has　slightly　higher　network-wide　information　exchange　productivity　than　number　matching.　Furthermore,　due　to　the　limitations　of　the　size　of　the　recruited　subjects,　the　report　results　can　only　be　an　exploratory　attempt,　which　needs　to　be　verified　by　a　larger　sample　of　data　in　the　future.