Create notebook showing how to work with NWB format

[EricThomson]

We currently have a py module showing how to work with NWB. It would be good to put this in a notebook and explain things a bit more: this is where most of our foot traffic goes. I just made a draft of one that seems to work well.

==== "Side" issue @bendichter I just learned of neuroconv which seems great! (https://github.com/catalystneuro/neuroconv) I'm not sure if there are any additional things we should be thinking about on our end when it comes to interoperability of Caiman and NWB, before I make this notebook.

Also, one worry I have is that our current NWB-functionality may be CNMF-centric: that things might be incomplete when users run CNMFE (e.g., for miniscope data). For instance, it seems to make heavy use of f and b, but these background components aren't typically used for CNMFE (i.e., we don't use the low-rank background model when running CNMFE: in some cases we actually use f and b being None as the indicator that CNMFE was run -- the ring model W forms the (higher dimensional) background model in the case of CNMFE).

Anyway, these are just first impressions, likely to change.