Motor　cortex　network　was　represented　as　a　directed　graph　and　implemented　as　a　dynamic　system　in　order　to　study　the　mechanisms　of　impairment　and　recovery.　Complexity　was　used　to　express　the　extent　to　which　a　system　is　both　functionally　segregated　and　functionally　integrated.　Motor　cortex　network　was　optimized　by　pattern　search　to　investigate　the　change　of　connectivity　in　rest,　movement　and　stroke　state.　The　simulation　results　show　that　motor　areas　have　stronger　connections　in　movement　state.　The　strength　decreases　in　stroke,　which　relates　to　disconnection　mode.　The　intra-hemisphere　connections　are　stronger　than　others　and　self-connections　are　week　in　either　state.　It　indicates　the　model　can　reflect　the　plasticity　of　cerebral　motor　cortex　qualitatively　according　to　clinical　trials.　An　understanding　of　the　connectivity　changes　in　cerebral　networks　following　stroke　will　facilitate　the　development　of　novel　therapeutic　techniques　that　are　based　on　neurobiological　principles　and　will　allow　the　delivery　of　specific　therapies　to　appropriately　targeted　patients　suffering　from　stroke.　©　2008　IEEE.