Not sure about that. The same abstract model could be used for both (symbols generated in sequence). For language the symbols have meaning in the context of language. For non-language thought they don't. Nature seems to work this way in general: re-using/purposing the same underlying mechanism over and over at different levels in the stack. All of this could be a fancy version of very old hardware that had the purpose of controlling swimming direction in fish. Each symbol is a flick of the tail.
I like to think of the non-verbal portions as the biological equivalents of ASICs. even skills like riding a bicycle might start out as conscious effort (a vision model, a verbal intention to ride and a reinforcement learning teacher) but is then replaced by a trained model to do the job without needing the careful intentional planning. some of the skills in the bag of tricks are fine tuned by evolution.
ultimately, there's no reason that a general algorithm couldn't do the job of a specific one, just less efficiently.
