Spike　timing-dependent　plasticity　(STDP)　plays　an　important　role　in　sculpting　information-storing　circuits　in　the　hippocampus,　since　motor　learning　and　memory　are　thought　to　be　closely　linked　with　this　classical　plasticity.　To　further　understand　the　information　delivery　in　a　hippocampus　circuit,　we　build　a　computational　model　to　study　the　potential　role　of　linear　changes　in　the　synaptic　weight　and　synaptic　number.　Several　key　results　have　been　obtained:　(i)　Changes　in　the　synaptic　weight　and　numbers　lead　to　different　long-term　modifications;　(ii)　the　first　paired　spiking　from　two　neurons　significantly　influences　the　adjusted　subsequent　paired　spiking;　the　pre-post　spiking　pair　strengthens　the　following　paired　spiking;　however,　the　post-pre　spiking　pair　depresses　the　subsequent　spiking;　(iii)　when　the　synaptic　weight　and　synaptic　numbers　are　changed,　the　interval　of　the　first　spiking　pair　may　undergo　reduction,　and　(iv)　when　we　stimulate　a　stellate　neuron　weakly　or　decrease　the　capacitance　of　the　CA1　pyramidal　neuron,　LTP　is　more　easily　produced　than　LTD;　on　the　contrary,　LTD　is　more　easily　produced　in　an　opposite　situation;　increase　in　the　synaptic　numbers　can　promote　activation　of　the　CA1　pyramidal　neuron.