Get probable input based on a given output in a neural network

I'm starting to learn neural networks, and I just made a program that learned how to recognize handwritten digits with pretty good accuracy (trained with backpropagation). Now I want to be able to see what the network thinks a perfect number looks like (essentially getting a pixel array which produces a desired number but is not from the dataset). My research has come up empty, but I posted on another site and was suggested to look at backpropagating to the input. I don't have much of a math background, so could someone point me in the right direction on how to implement that (or any other method of achieving my goal)?

via Chebli Mohamed