Low-power　and　low-variability　artificial　neuronal　devices　are　highly　desired　for　high-performance　neuromorphic　computing.　In　this　paper,　an　oscillation　neuron　based　on　a　low-variability　Ag　nanodots　(NDs)　threshold　switching　(TS)　device　with　low　operation　voltage,　large　on/off　ratio　and　high　uniformity　is　presented.　Measurement　results　indicate　that　this　neuron　demonstrates　self-oscillation　behavior　under　applied　voltages　as　low　as　1　V.　The　oscillation　frequency　increases　with　the　applied　voltage　pulse　amplitude　and　decreases　with　the　load　resistance.　It　can　then　be　used　to　evaluate　the　resistive　random-access　memory　(RRAM)　synaptic　weights　accurately　when　the　oscillation　neuron　is　connected　to　the　output　of　the　RRAM　crossbar　array　for　neuromorphic　computing.　Meanwhile,　simulation　results　show　that　a　large　RRAM　crossbar　array　(＞　128　x　128)　can　be　supported　by　our　oscillation　neuron　owing　to　the　high　on/off　ratio　(＞　10(8))　of　Ag　NDs　TS　device.　Moreover,　the　high　uniformity　of　the　Ag　NDs　TS　device　helps　improve　the　distribution　of　the　output　frequency　and　suppress　the　degradation　of　neural　network　recognition　accuracy　(＜　1%).　Therefore,　the　developed　oscillation　neuron　based　on　the　Ag　NDs　TS　device　shows　great　potential　for　future　neuromorphic　computing　applications.