Funny how discoveries like this don't surprise me at all anymore. After embracing concepts such as fractal geometry, recursion and the demand for efficiency in nature, it makes sense that in nature everything has evolved in a way in which every layer is a part of the next layer above it (quarks -> electrons, protons -> elements -> compounds -> amino acids -> proteins -> information -> abstract information -> ..., or binary -> hexadecimal -> assembly -> low-level code -> high-level code -> abstractions -> ...), and everything has value in more than one way. DNA, proteins, muscles, neural clusters, even programming are all based around this principle. If you were building two programs that were identical in many ways why wouldn't you abstract out the commonalities, instead of building them twice?
The brain is no exception. I think musicians, for example, are better at math because at the heart of music and at the heart of math, many of the same brain circuits are involved. It is more efficient to have one copy of these circuits and just apply them to both music and math, rather than having two copies of nearly identical circuits. Proteins have more than one use in our bodies, because if each only had only one use we would need an inefficient number of them, possibly more than what exists. Same for neurotransmitters. When nature is limited by constraints it usually finds a way to fold into a higher dimension around that constraint (such as the neocortex wrinkling to increase surface area, or DNA containing information on more than a single level, or even how grass grows over a fallen log instead of "choosing" to just grow somewhere else, or if you are into String Theory, how the universe/multiverse has folded into 11 dimensions, possibly because that was the most efficient way for our universe to exist.)
It reminds me of a river when it is initially forming down the side of a mountain. The water takes the most efficient path at any given instance from the top of the mountain to the bottom. The process is like a greedy algorithm. The water cannot foresee where it will end up, it just flows. The water won't always find the most efficient solution, but give it enough time and will find an efficient-enough solution.