Recently,　artificial　neurons　have　attracted　much　attention　due　to　their　excellent　energy　efficiency　and　scalability.　However,　there　are　still　few　reports　on　the　regulation　of　the　performance　of　artificial　neuron　based　on　single　device.　In　the　letter,　we　present　an　artificial　neuron　device　based　on　Ag/TaOx/Si　that　not　only　has　excellent　turn-on　and　turn-off　performance,　but　also　exhibits　sustained　stability　under　multiple　cycle　tests.　Moreover,　the　Integrate　-and-Fire　(IF)　neuron　model　is　successfully　simulated　at　room　temperature.　More　importantly,　we　find　that　an　increase　of　temperature　could　reduce　the　threshold　voltage　and　reset　voltage　of　neurons,　improve　the　probability　of　neuronal　firing,　and　promote　the　transformation　of　neurons　from　nonvolatile　to　volatile.　This　work　provides　an　effective　method　for　regulating　artificial　neurons　and　has　important　implications　for　studying　information　transfer　in　biology　and　adapting　complex　computations　in　a　memory　computing　framework.