Yes, but attention is not like the other analogies you highlighted. The word already HAS a meaning in biology.

So instead of being a useful, if imperfect, analogy from an outside domain, trying to use ML attention to understand biological attention just results in confusion (like this article).

Neuroscientists aren't going to tell ML researchers they can't use "attention", but nor are they going to pay attention to them (pun intended). Neural networks are almost always too divergent from biology to shed light on real neurons.