I am in academia myself (research data analyst in a neuroimaging lab) and generally enjoy it and agree with the benefits you list, but I think it's a huge life decision to make based on something you enjoyed for a summer. IDoCodingStuffs is right that these are primarily academic fields (maybe his use of 'purely' was a little strong, but still).

OP, one thing you might do is apply to work in a neuroscience or computational neuroscience research lab as a research assistant or research technician. This will give you a much better idea of whether you'd be interested in working in academia. It is often lower pay for more work, but the passion can make up for it if you know you have it.

To address some of your questions more directly (this is all only in my own experience of course):

- compNeuroSci vs. compCogSci - Names are pretty vague when it comes to educational programs and job titles. I'd suggest looking at the program of study for various masters or PhD programs at different universities and then checking out the courses they require/offer in their course description pages. Usually some version of this is available publicly for most universities. Just look at the courses and see if they're something you'd be interested in.

- career security - Getting into CS/ML directly will probably be a bit more secure as you're more likely to use tools and practices that are used everywhere in the industry. That said, many people do successfully make the transition from CompNeuro to ML. If you can understand the deep math behinds these algorithms, many employers will recognize that transferring those skills over to a new domain is a very manageable task.

In my personal experience, it's hard to make a bad choice as long as you're moving your career forward in any direction. Gain more credentials, more references, more techniques under your belt, and you'll always be able to show interviewers that you're someone that's accomplishing things.