I used to build BMI systems in graduate school, from the lowest level (mixed-signal analog design for 70 uV extracelleular signals) to DSP (128 DSPs doing real time analysis) to the network (built my own ethernet MAC, foolishly!) to all the vis and RT-linux-based analysis. I left the area and switched into ML in grad school, but if I had to do it all over again there's one thing I think is missing:

Optics. Optics optics optics.

A tremendous amount of neural interfacing, especially in non-human primates and other organisms, is done via optics. ~All the advances in neural data acquisition over the past decade have been optical. Microscopy is the future for a tremendous amount of neuroscience and more and more people are considering it seriously for human-scale BMI.

I know optics isn't always thought of in an EE context, but it should be! Many people doing amazing computational imaging and optics work are in EE departments. Computational imaging is the new hotness and can let you combine your existing CS skills with signal processing and optics to do things like build a lensless camera! https://waller-lab.github.io/DiffuserCam/

If I were you I would ditch the RF part of your plan and study optics. Yeah, it's all EM, but the order-of-magnitude differences in the frequencies involved makes the underlying engineering quite different.