2026/07/01 by Jordan DeKraker, Nicole Eichert, Seok-Jun Hong +2 · 1 voice
Neuroscience · #Functional Brain Connectivity Studies #Memory and Neural Mechanisms #Neurogenesis and neuroplasticity mechanisms
paper · doi:10.1016/j.neubiorev.2026.106890
openalex publication_date 2026/07/01 · openalex created_date 2026/07/23 · openalex updated_date 2026/07/24
The mammalian cortex is organized along hierarchical gradients that extend from primary sensory regions to transmodal association networks. Converging neuroanatomical theory and data-driven analyses place the hippocampus at the apex of this hierarchy, where its subregional organization mirrors large-scale cortical networks and their evolutionary expansion. Building on these observations, we propose that the hippocampus functions as a predictive learning engine, generating latent training signals that support cortical learning. This view aligns with self-supervised machine learning frameworks, in which predictive processes occupy the top of hierarchical models. We suggest that hippocampal predictive learning constitutes a foundational mechanism of mammalian intelligence, linking cortical organization with principles underlying modern artificial systems.