Training with "trainscg" does not update the networks weights

I am trying to train a very complex though small NARX-Net (see picture).

The weights of the layers 4,5,6,7, as well as layer 2 have been set constant (by disabeling the .learn property of the weights). The transferfunction of the second layer is a sine. All of the layers have been unit tested independently. The backpropagation ect. for the custom sine function works fine.

My problem is, when trying to train the complete structure with train(net) and the trainscg trainFcn, the nntool "trains" the net, but doesn't update the weights. There is a relatively large gradient and also a performance is computed, but as the nntraintool runs through the epochs, the performance and the gradient stays constant. After stopping the training and checking the weights, the are the same as before the "training".

Has anybody experienced similar problems or has a idea what might have gone wrong?

Appreciate your Help,

Christoph