I'm not going to claim to be an expert in the field of computational neuroscience haha, but I'm well versed in the surrounding subjects so if you ever want to ask my advice on something, I'm all ears. Like I said, you guys are working on like my absolute favorite stuff in the world.
Anyway, I'm pretty sure you'll see that by adjusting your energy function the spinning will stop. That is of course, assuming that they have 360 degree vision, which was my understanding. If not, then it's possible that you'll still see spinning behavior because your food pellets appear randomly and your Zappies move randomly.
Also along the same lines, I know that you're hoping to see more complex behaviors like using color as camouflage and Goopies hunting Goopies and etc, but those types of behaviors only arise when there is reason for them to arise. The reason that you saw the occasional hunters cropping up was because you provided an incentive; that being that dead Goopies provide more energy than pellets. If you want to see Goopies using colors then there has to exist some kind of advantage to it. Otherwise if changing colors costs energy but it helps you in exactly no way what so ever, no Goopies will ever use it. If on the other hand it costs no energy you'll probably evolve disco Goopies if you run enough simulations kind of like you saw with the Nascar Goopies.
I want to say that "there has to be a reason for everything and anything" but I don't know if that's precisely the best way to put it. I feel a slightly truer to life way of phrasing it would be to think of things in terms of a your fitness function and your energy function. You can think of all the possible things that can happen in your energy function like a 3D plane. There will be peaks and valleys on that function depending on various behaviors and ultimately the "law of the universe" is to hang out in stable states (just look at chemistry, physics, biology, etc); which in your case will be the valleys of your energy map because that's where minimal energy is being used (or again you can rephrase it and say the peaks which is where you acquire the most energy, just depends on the problem at hand). So for example if you change your pellet generation from being uniformly distributed to say being a single pole Gaussian, you might find that one of the "optimal" solutions to your fitness function (which we'll get to in a minute) would be to simply figure out where pellets tend to appear, move to that location, and then just sit there because food shows up often enough that you'll be able to gain energy without expending any extraneous movement-based energy. Right? So what I'm getting at is that for most types of behaviors, like communication, team work, hunting, or etc, the gains have to out way the cost otherwise there really won't be any reason for them to evolve. Just because you add in an appendage doesn't mean anyone will choose to use it.
The other thing besides your energy function (which you can think of as the reason why anything gets done) which you need to consider is your fitness function (which you can think of as the solution to a problem, in this case staying alive). I think in your case your fitness function is simply "whoever stays around the longest is the winner and moves to the next round." Correct? (If I'm wrong please correct me, but regardless my point here will still be pertinent) This is the biggest reason why your Nascar drivers crop up uniformly. You're mostly correct in your "genetic inheritance" explanation of why everyone adopts that behavior, but it isn't the reason
(which makes absolutely no sense). See the problem is, everyone is basically everyone's clone. It isn't that the Goopies are a tight knit family if the guy who wins the "I stayed alive the longest" contest is the guy whose "neural genes" get passed on to the next generation, rather everyone is just a slightly altered clone of him. This is why you might see hunting behaviors crop up but then never really catch on, because that guy doesn't ever get the chance to have kids so someone from the next generation has to re-figure out that behavior essentially. (Again, assuming I understand your model. everything I've said thus far applies to the idea that you're only selection one Goopie based off of that one criteria to "breed"). Much like how your energy function can be thought of a 3D plane, your fitness function can also be thought of as a 3D plane, or at least you want to think of it that way if you want to "solve" problems. Ultimately that's what both neural networks and genetic algorithms do and what they're for. They're meant to traverse the problem landscape in search of those peaks and valleys, and settling in. So you might not get the mathematically perfect algorithm, but you'll get pretty dang close. And if there are multiple solutions (peaks/valleys depending on how you describe your problem) then again, depending on the luck of the draw, you might find one good solution, run a new experiment and find a completely different solution. Right now because your fitness function is so limiting you aren't traversing that problem landscape very well. Instead of picking the best guy and keeping him around, you could alter your fitness function to say drop the worst X amount, reproduce two of the top Y guys (or even just the top 1 guy), and reproduce one of everyone else. Again, just an example you can play with it as you will, but with this example, while your gene pool is still small, it'll be more closely relatable to families of Goopies which is what will allow for different and more interesting behaviors.
At the end of the day, the more complex your "world" is the more complex behavior that will not only be allowed to evolve, but that will have a "reason" to evolve.