Multilayer Perceptron: What is the value used to update the weights in the hidden layers?
A Multilayer Perceptron changes your weights by an algorithm called "backpropagation". This algorithm uses gradient descent combined with a learning rate to change every weight in your MLP.

Basically the backpropagation functions by chaining together all functions that are called when calculating the output of one particular node (so chaining together all possible ways). Now using the chain rule a gradient is calculated which directs into the direction of minimal error and changes all weights accordingly.