Hi. Thank you so much for this comment! Im in the bus atm and I won't be able to write a proper response until tomorrow, but I wanted to acknowledge your comment. :)
I'm in the process of writing a post oulining the motivation for this project and the next steps I plan to take.
You are absolutely correct about the low resolution of fMRI imaging. Exciting new techniques like calcium imaging provide much much higher resolution, both temporal and spacial. Most commonly neural decoding is performed using "traditional" ML techniques, and I'm sure I don't need to tell you how promising DL seems for achieving better results. These two developments are the reason I believe a breakthrough in neural decoding is more or less imminent.
And now regarding your concerns for collecting data. In image decoding, a label for a dataset consists of the video the subject was watching while the data was being collected. An example of such a dataset and how to work with it is at http://nilearn.github.io/auto_examples/02_decoding/plot_miyawaki_reconstruction.html. The data I plan on using comes from mice.
All right, this is my stop. I hope Ive answered some of your questions. :))