Linguistics and Human Brain: A Perspective of Computational Neuroscience

ABSTRACT

This paper provides a comprehensive perspective on the intersection of linguistics and computational neuroscience, exploring how modern language models and neural recording technologies can bridge the gap between abstract linguistic theory and biological implementation. We review the latest findings in neural representational geometry and its alignment with the hierarchical structures predicted by generative grammar. Furthermore, we propose a unified framework for 'computational neurolinguistics' that emphasizes the importance of predictive coding and uncertainty in the brain's language processing networks. This perspective aims to guide future research toward a more integrated understanding of how the human brain computes meaning and syntax.