Recently,　a　growing　number　of　studies　have　shown　that　machine　learning　technologies　can　be　used　to　decode　mental　state　from　functional　magnetic　resonance　imaging　(fMRI)　data.　It　has　achieved　the　functional　positioning　of　the　brain　activity　using　fMRI　technology　to　interpret　the　thinking　data.But　how　to　run　the　specific　operation　of　the　brain＇s　thinking　process　is　still　unknown.　The　analytical　methods　to　better　reveal　the　thinking　process　need　to　be　further　studied.　Through　adopting　two　stimuli　tasks　of　solving　the　4×4　Sudoku　problems　and　image　emotional　reaction,　the　thinking　process　data　which　interpret　the　different　state　of　mind　is　gotten,　and　different　ways　of　thinking　data　analysis　methods　are　explored.　The　experiments　proved　that　the　feature　selection　methods　of　t-test,　the　feature　extraction　methods　of　the　peak　time　and　the　classification　algorithm　of　SVM　are　more　suitable　for　analyzing　the　fMRI　data,　especially　to　two　different　states　of　mind　data　above,　which　can　reveal　the　correct　state　of　mind.　This　essay　should　provide　the　theory　basis　and　data　for　promoting　the　fMRI　technology　to　interpret　the　thinking　data.