Representation learning of human cortical folding to reveal long lasting neurodevelopmental signatures — Paper

Abstract

-cross Abstract: The human brain folds in utero, primarily during late gestation. Shortly after birth, cortical folding patterns are established and remain stable thereafter, making them promising early neurodevelopmental markers. Yet it is unclear whether the representations given by current neuroimaging foundation models capture cortical folding variability. Here, we introduce Champollion, a self-supervised learning framework that learns interpretable local representations of cortical folding from structural MRI. Optimized on representative folding-related tasks, Champollion accurately captures known folding patterns across cortical regions and external datasets. In a comprehensive benchmark, it consistently outperforms neuroimaging and general-purpose foundation models. Furthermore, Champollion reveals richer genetic associations than conventional morphometric descriptors and identifies localized folding signatures associated with incomplete hippocampal inversion, prematurity, and maternal smoking. These results establish cortical folding as a rich and largely untapped source of neurodevelopmental information, and Champollion provides a unified framework for discovering, localizing and interpreting long lasting cortical folding signatures.

Authors 27

Julien Laval, Robin Guiavarch, Antoine Dufournet, Racim Menasria, Barth\'el\'emy Drabczuk, Cristobal Mendoza, Saeb Tounsi, Chikh Abdelghani Baroud, Merieme Bourenane, Vanessa Troiani, William Snyder, Marisa A Patti, Myl\`ene Moyal, Marion Plaze, Arnaud Cachia, Federica Santacroce, Giorgia Committeri, Claire Cury, Kevin De Matos, Olivier Colliot, Zhong Yi Sun, Clara Fischer, Vincent Frouin, Pietro Gori, Denis Rivi\`ere, Jo\"el Chavas, Jean-Fran\c{c}ois Mangin

Specification

Official page: arxiv.org/abs/2609.05438
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
Arxiv announce type: replace
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
arXiv id: 2609.05438
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
Categories: q-bio.QM, cs.CV, cs.LG
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
PDF: arxiv.org/pdf/2609.05438
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
Primary category: q-bio.QM
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

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9

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T19

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2 h ago

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None

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Authors: Julien Laval, Robin Guiavarch, Antoine Dufournet

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Value	Valid from → to	Status	Source	Confidence	Extractor
11 Sept 2026	11 Sept 2026 21:02 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

11 Sept 2026
New paperPaperRepresentation learning of human cortical folding to reveal long lasting neurodevelopmental signatures
New paper: Representation learning of human cortical folding to reveal long lasting neurodevelopmental signatures
arxiv
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Source documents
Source	Document	Type	Tier	Last observed	Snapshots
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.LG	feed	T1· Official	48 min ago	1

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