Have you heard of swarming? That is historically the type of process we use to find the best parameters in a large space. We face similar challenges to DL systems in that there are a lot of parameters that can be changed. And it might make a big difference in some situations but not in others. You will serve yourself in the long run by creating some comparable metric so you can run many models over time and gauge how well they are doing at your task.
You cannot extract the sequences without some form of pooling layer (another topic). But I have a ton of HTM visualizations tools laying around. If you are running NuPIC and you know some JavaScript, you can play with them yourself: How to Run HTM School Visualizations.