Under　spatially　averaged　measurements　(SAMs)　and　deception　attacks,　this　article　mainly　studies　the　problem　of　extended　dissipativity　output　synchronization　of　delayed　reaction-diffusion　neural　networks　via　an　adaptive　event-triggered　sampled-data　(AETSD)　control　strategy.　Compared　with　the　existing　ETSD　control　methods　with　constant　thresholds,　our　scheme　can　be　adaptively　adjusted　according　to　the　current　sampling　and　latest　transmitted　signals　and　is　realized　based　on　limited　sensors　and　actuators.　Firstly,　an　AETSD　control　scheme　is　proposed　to　save　the　limited　transmission　channel.　Secondly,　some　synchronization　criteria　under　SAMs　and　deception　attacks　are　established　by　utilizing　Lyapunov-Krasovskii　functional　and　inequality　techniques.　Then,　by　solving　linear　matrix　inequalities　(LMIs),　we　obtain　the　desired　AETSD　controller,　which　can　satisfy　the　specified　level　of　extended　dissipativity　behaviors.　Lastly,　one　numerical　example　is　given　to　demonstrate　the　validity　of　the　proposed　method.&　COPY;　2023　Elsevier　Ltd.　All　rights　reserved.