A precise atlas of the human subcortex
Year: 2026
Type: preprint
Abstract: Clinical interventions and neuroimaging in the subcortex require anatomical definitions that exceed the resolution and anatomical detail of currently available deformable brain atlases. Here, we introduce a high-resolution human brain atlas comprising 95 manually segmented grey and white matter structures as well as 82 white matter tracts compiled from a multitude of resources including ex-vivo MRI, histology, fibre dissections, and neuroanatomy textbooks. The atlas is defined at an isotropic resolution of 100 μm and can be precisely deformed to individual subject brain anatomy. By providing precise definitions of both grey and white matter structures within and around the basal ganglia, thalamus, subthalamus, midbrain and cerebellum, the atlas provides a foundational resource for stereotactic surgery and subcortical brain imaging research, as well as for development of next-generation neuromodulation strategies.
Authors: Helen Friedrich, Ilkem Aysu Sahin, Eduardo J. L. Alho, Nanditha Rajamani, Vanessa Milanese Holanda, Simon Oxenford, Malte Brammerloh, Maike Mustin, Patricia Zvarova, Lara Krüger, Richard Demann, Lukas L. Goede, Garance M. Meyer, Evgeniya Kirilina, Cordula Matthies, Jens Volkmann, Julianna Pijar, Shiro Horisawa, Calvin Howard, Arun Garimella, Ningfei Li, Michael D. Fox, Maximilian U. Friedrich, Anja K. E. Horn, Brian L. Edlow, Clemens Neudorfer, Andreas Horn
Institutions: Brigham and Women's Hospital, Harvard University, University of Würzburg, Humboldt-Universität zu Berlin, University Hospital Cologne, Einstein Center for Neurosciences Berlin, Freie Universität Berlin, Charité - Universitätsmedizin Berlin, Beneficência Portuguesa de São Paulo, Mayo Clinic in Florida, Max Planck Institute for Human Cognitive and Brain Sciences, Universitätsklinikum Würzburg, University of Toronto, Tokyo Women's Medical University, Northwestern Polytechnical University, University Hospital Ulm, Massachusetts General Hospital, Anatomische Anstalt, Ludwig-Maximilians-Universität München, Athinoula A. Martinos Center for Biomedical Imaging
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7128957708