[2511.01870] CytoNet: A Foundation Model for the Human Cerebral Cortex at Cellular Resolution

Quantitative Biology > Neurons and Cognition arXiv:2511.01870 (q-bio) [Submitted on 21 Oct 2025 (v1), last revised 5 Mar 2026 (this version, v2)] Title:CytoNet: A Foundation Model for the Human Cerebral Cortex at Cellular Resolution Authors:Christian Schiffer, Zeynep Boztoprak, Jan-Oliver Kropp, Julia Thönnißen, Katia Berr, Hannah Spitzer, Katrin Amunts, Timo Dickscheid View a PDF of the paper titled CytoNet: A Foundation Model for the Human Cerebral Cortex at Cellular Resolution, by Christian Schiffer and 7 other authors View PDF HTML (experimental) Abstract:Studying the cellular architecture of the human cerebral cortex is critical for understanding brain organization and function. It requires investigating complex texture patterns in histological images, yet automatic methods that scale across whole brains are still lacking. Here we introduce CytoNet, a foundation model trained on 1 million unlabeled microscopic image patches from over 4,000 histological sections spanning ten postmortem human brains. Using co-localization in the cortical sheet for self-supervision, CytoNet encodes complex cellular patterns into expressive and anatomically meaningful feature representations. CytoNet supports multiple downstream applications, including area classification, laminar segmentation, quantification of microarchitectural variation, and data-driven mapping of previously uncharted areas. In addition, CytoNet captures microarchitectural signatures of macroscale functional organizat...