The neurobiology of human sequential signal prediction: Insights from language, music, and mathematics

Humans use various sequential signals, such as language, music, and mathematics, to convey complex information and facilitate communication. Previous research has identified two fundamental frameworks underlying human sequential signal processing: a structural framework, emphasizing rule-based hierarchical organization (e.g., syntax), and a predictive framework, which focuses on the brain's capacity to anticipate upcoming inputs based on statistical regularities. While the structural approach underscores human-specific abilities, the predictive approach highlights mechanisms shared with non-human animals. We review behavioral and neural evidence across domains, demonstrating overlapping neural substrates, particularly in the inferior frontal gyrus, involved in structural processing of language, music, and mathematics. Likewise, predictive processing, indexed by ERP components such as N400 and P600, operates across domains to detect violations of expectation. Importantly, we argue that these frameworks are not mutually exclusive: structural knowledge can inform prediction, and predictive processes can, in turn, influence perceived structure. Cross-domain experiments and computational modeling suggest shared cognitive mechanisms, although domain-specific variations remain. We propose that the human brain integrates hierarchical structures with statistical learning to support flexible and generalized sequence processing. Future research should aim to develop unified models across domains, leveraging neuroimaging techniques and large language models.