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I'd be interested in working through some stuff. However, I strongly recommend against that textbook unless you are far more mathematically inclined than biologically inclined. A book I regularly hear is better is https://www.amazon.com/Fundamentals-Computational-Neuroscience-Thomas-Trappenberg-ebook/dp/B00F1D7K90/ref=pd_sim_351_5/142-8547797-4404628?_encoding=UTF8&pd_rd_i=B00F1D7K90&pd_rd_r=94bccf74-72a6-11e9-a70e-fdfd69152f1b&pd_rd_w=BAcvA&pd_rd_wg=OSgsO&pf_rd_p=90485860-83e9-4fd9-b838-b28a9b7fda30&pf_rd_r=P95Z6WQ78BG4FXFDSHPC&psc=1&refRID=P95Z6WQ78BG4FXFDSHPC

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I have it and find it far more approachable, and thoughtfully put together. I took a class with Abbott and he himself didn't seem to think particularly highly of the text.

I also liked the Dayan & Abbott book.

I also liked the Neuronal Dynamics book by Gerstner, which has accompanying online resources.

The books you've mentioned are good, and I will also recommend "Spikes: Exploring the Neural Code" https://www.amazon.com/Spikes-Exploring-Neural-Computational-Neuroscience/dp/0262681080

Depends on the level at which you are looking. Cellular stuff? Signal processing and calculus. Population dynamics? Linear algebra and calculus. Brain regions/networks/whole brain? Graph theory and linear algebra.

And for all of them, statistics will be the tool to understand what's happening within the mathematical formulations.

On side note: if you're looking at the level of behavior, many other discrete methods become much more important in my opinion. However, it is fairly uncommon for people to use a behavioral approach these days without linking it to some other measurement one of the levels I mentioned before.

See From Neuron to Cognition, Fundamentals of Computational Neuroscience, and Theoretical Neuroscience for some foundational understanding.