Connectionist and usage-based models (Tomasello, Elman) demonstrate that abstract grammatical structure can emerge from domain-general learning mechanisms operating over sufficiently rich input.

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Abstract grammatical structure(as used in linguistics): The general rules and patterns of language (like how to form sentences) that apply across many different situations, not tied to any specific words.
Domain-general learning mechanisms(as used in cognitive science): Basic learning processes that work across many different areas (like vision, language, memory) rather than being specialized for just one specific task.
Jeffrey Elman(as a researcher cited in computational linguistics): A cognitive scientist who pioneered connectionist approaches to understanding language, showing that neural networks can learn grammar patterns from examples without being explicitly programmed with rules.
Michael Tomasello(the theorist cited in this statement): A cognitive scientist and psychologist who studies how children learn language and argues that kids figure out grammar by paying attention to how people actually use words, not from innate linguistic knowledge.

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