How are per-layer-detected-patterns in a trained CNN plotted?
The image you posted is derived from figures which depict the basis functions of a Convolutional Restricted Boltzmann Machine.

I found them in this ICML paper (behind a paywall, sorry) and this PhD thesis, both are by Honglak Lee, who was advised by Andrew Ng.

Strictly speaking they are not visualizations of a feed-forward Convolutional Neural Network, which might be why you are having a hard time interpreting what they depict. I don't really know much about RBM's myself so I'm afraid I can't help with their interpretation.

As far as visualizing CNN's, there are several common methods. You can visualize filter weights directly, find input images which maximally activate a filter, plot activation as a function of image occlusion, etc.
This page has a good summary of techniques, also this paper may be useful.