CytoNet: A Foundation Model for the Human Cerebral Cortex

• URL: http://arxiv.org/abs/2511.01870v1
• Date: Tue, 21 Oct 2025 11:39:23 GMT
• Title: CytoNet: A Foundation Model for the Human Cerebral Cortex
• Authors: Christian Schiffer, Zeynep Boztoprak, Jan-Oliver Kropp, Julia Thönnißen, Katia Berr, Hannah Spitzer, Katrin Amunts, Timo Dickscheid,
• Abstract summary: CytoNet is a foundation model that encodes high-resolution microscopic image patches of the cerebral cortex into expressive feature representations.<n>We demonstrate top-tier performance in tasks such as cortical area classification, cortical layer segmentation, cell morphology estimation, and unsupervised brain region mapping.
• Score: 0.8431877864777443
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: To study how the human brain works, we need to explore the organization of the cerebral cortex and its detailed cellular architecture. We introduce CytoNet, a foundation model that encodes high-resolution microscopic image patches of the cerebral cortex into highly expressive feature representations, enabling comprehensive brain analyses. CytoNet employs self-supervised learning using spatial proximity as a powerful training signal, without requiring manual labelling. The resulting features are anatomically sound and biologically relevant. They encode general aspects of cortical architecture and unique brain-specific traits. We demonstrate top-tier performance in tasks such as cortical area classification, cortical layer segmentation, cell morphology estimation, and unsupervised brain region mapping. As a foundation model, CytoNet offers a consistent framework for studying cortical microarchitecture, supporting analyses of its relationship with other structural and functional brain features, and paving the way for diverse neuroscientific investigations.

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