re training neural network from previous state using trainNetwork

I am training a deep neural network , using the following matlab function: net = trainNetwork(XTrain,YTrain,layers,options);   could I use the trainNetwork command to retrain the network (not from scratch), using the last network state from previous training?   I am sharing some of the code: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% layers = [   imageInputLayer([1 Nin 5],"Name","imageinput") convolution2dLayer([1 3],32,"Name","conv","Padding","same")% %batchNormalizationLayer('Name','batchDown') tanhLayer("Name","tanh1") convolution2dLayer([1 3],32,"Name","conv","Padding","same","DilationFactor",[1 3])% %batchNormalizationLayer('Name','batchDown1') tanhLayer("Name","tanh2") convolution2dLayer([1 3],2,"Name","conv","Padding","same","DilationFactor",[1 9])%   regressionLayer];     options = trainingOptions('adam', ... 'InitialLearnRate',0.001, ... 'MaxEpochs',50000, ... 'ExecutionEnvironment','parallel',... 'Verbose',false, ... 'Plots','training-progress');     Net1 = trainNetwork(XTrain1,YTrain1,layers,options); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%   now I would like to train again getting Net2 using new data, and starting the training from Net1 stage. for example: Net2 = trainNetwork(XTrain2,YTrain2,layers,options); however its not clear to me how to start the train process for Net2 using Net1 stage.