Inspired　by　biological　neuromorphic　systems,　which　can　simultaneously　perceive,　remember,　and　process　enormous　information　through　parallel,　energy-efficient　processes,　artificial　synaptic　transistors　have　shown　great　potential　in　paving　a　way　to　overcome　the　von　Neumann　bottleneck　for　neuromorphic　computing.　Artificial　synapses　capable　of　effectively　emulating　both　the　excitatory　postsynaptic　current　(EPSC)　and　inhibitory　postsynaptic　current　(IPSC)　responses,　and　particularly　reconfiguration,　are　crucial　for　building　neuromorphic　systems　with　desirable　versatility.　However,　it　is　still　challenging　to　realize　emblematical　neurobehavior　in　unipolar　transistors　owing　to　the　unbalanced　carrier　concentration.　Therefore,　for　the　first　time,　a　facile　light-adjustable　organic　photoelectric　synaptic　transistor　based　on　bulk　heterojunction　blends　is　developed.　In　addition,　typical　synaptic　properties　including　the　excitatory/inhibition　postsynaptic　current,　paired　pulse　facilitation/inhibition,　frequency-dependent　characteristics,　the　transformation　from　short-term　to　long-term　plasticity　are　successfully　simulated　and　modulated　by　light　illumination.　Moreover,　the　mechanism　of　light　illumination　on　the　neuroplasticity　of　our　synaptic　device　is　discussed.　Notably,　the　recognition　accuracy　of　our　synaptic　device　can　be　efficaciously　modulated　by　the　light　intensity　and　achieves　86%　accuracy　with　appropriate　light　exposure　conditions.　The　artificial　synaptic　devices　based　on　bulk　heterojunction　open　up　a　whole　new　path　for　the　urgent　need　of　neuromorphic　computation,　in　which　light　illumination　can　be　utilized　for　modifying　the　circuit　learning　rate.