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Understanding the hippocampus as an apex of the cortical hierarchy and self-supervised predictive learning engine.

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Τίτλος: Understanding the hippocampus as an apex of the cortical hierarchy and self-supervised predictive learning engine.
Συγγραφείς: DeKraker J; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada. Electronic address: jordan.dekraker@mail.mcGill.ca., Eichert N; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom., Hong SJ; Sungkyunkwan University, Suwon, South Korea., Evans AC; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada., Bernhardt BC; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
Πηγή: Neuroscience and biobehavioral reviews [Neurosci Biobehav Rev] 2026 Oct; Vol. 189, pp. 106890. Date of Electronic Publication: 2026 Jul 22.
Τύπος έκδοσης: Journal Article; Review
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Pergamon Press Country of Publication: United States NLM ID: 7806090 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-7528 (Electronic) Linking ISSN: 01497634 NLM ISO Abbreviation: Neurosci Biobehav Rev Subsets: MEDLINE
Imprint Name(s): Publication: New York Ny : Pergamon Press
Original Publication: Fayetteville, N. Y., ANKHO International Inc.
Ιατρικοί όροι (MeSH): Hippocampus*/physiology , Cerebral Cortex*/physiology , Learning*/physiology , Models, Neurological*, Memory/physiology ; Predictive Learning Models ; Supervised Machine Learning ; Humans
Περίληψη: 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.
(Copyright © 2026 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Contributed Indexing: Keywords: Complementary learning systems; Cortical gradients; Cortical hierarchy; Hippocampus; Memory replay; Neuro-inspired artificial intelligence; Pattern separation; Predictive learning; Representation learning; Self-supervised learning
Entry Date(s): Date Created: 20260722 Date Completed: 20260813 Latest Revision: 20260813
Update Code: 20260813
DOI: 10.1016/j.neubiorev.2026.106890
PMID: 42486213
Βάση Δεδομένων: MEDLINE
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  Data: <searchLink fieldCode="AU" term="%22DeKraker+J%22">DeKraker J</searchLink>; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada. Electronic address: jordan.dekraker@mail.mcGill.ca.<br /><searchLink fieldCode="AU" term="%22Eichert+N%22">Eichert N</searchLink>; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Hong+SJ%22">Hong SJ</searchLink>; Sungkyunkwan University, Suwon, South Korea.<br /><searchLink fieldCode="AU" term="%22Evans+AC%22">Evans AC</searchLink>; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.<br /><searchLink fieldCode="AU" term="%22Bernhardt+BC%22">Bernhardt BC</searchLink>; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
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  Data: 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.<br /> (Copyright © 2026 The Authors. Published by Elsevier Ltd.. All rights reserved.)
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