What always struck me about Chomskyists is that they chose a notion of interpretable model that required unrealistic amounts of working interpretation. So Chomsky grammars have significant polynomial memory and computational costs for grammars as they approach something resembling human grammar. And you say, ok, the human brain can handle much more computation than that, and that's fine. But (for example) context-free grammars aren't just O(n^3) in computational cost; for a realistic description of human language they're O(n^3)
in human-interpretable rules.
Other Chomsky-like models of human grammars have different asymptotic behavior and different choices of n, but the same fundamental problem; the big-O constant factor isn't neurons firing but rather human connections between the n inputs. How can you conceive of human minds being able to track O(n^3) (or whatever) cost where that n is everything being communicated -- words, concepts, symbols, representations, all that jazz and the polynomial relationships between them?
But I feel an apology is in order: I've had quite a few beers before coming home, and it's probably a mistake to try to express academically charged and difficult views on the Internet while in an inebriated state. Probably the alcohol has substantially decreased my mental computational power. However, it has only mildly impaired my ability to string together words and sentences in a grammatically complex fashion. In fact, I often feel that the more sober and clear-minded I am, the simpler my language is. Maybe human grammar is actually sub-polynomial. I have observed the same in ChatGPT; the more flowery and wordy it has become over time, the dumber its output.