Light-microscopy-based connectomic reconstruction of mammalian brain tissue

Mojtaba R. Tavakoli, Julia Lyudchik, Michał Januszewski, Vitali Vistunou, Nathalie Agudelo Dueñas, Jakob Vorlaufer, Christoph Sommer, Caroline Kreuzinger, Bárbara Oliveira, Alban Cenameri, Gaia Novarino, Viren Jain and Johann G. Danzl ()
Additional contact information
Mojtaba R. Tavakoli: Institute of Science and Technology Austria
Julia Lyudchik: Institute of Science and Technology Austria
Michał Januszewski: Google Research
Vitali Vistunou: Institute of Science and Technology Austria
Nathalie Agudelo Dueñas: Institute of Science and Technology Austria
Jakob Vorlaufer: Institute of Science and Technology Austria
Christoph Sommer: Institute of Science and Technology Austria
Caroline Kreuzinger: Institute of Science and Technology Austria
Bárbara Oliveira: Institute of Science and Technology Austria
Alban Cenameri: Institute of Science and Technology Austria
Gaia Novarino: Institute of Science and Technology Austria
Viren Jain: Google Research
Johann G. Danzl: Institute of Science and Technology Austria

Nature, 2025, vol. 642, issue 8067, 398-410

Abstract: Abstract The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution1,2 with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules, but dense, synapse-level circuit reconstruction by light microscopy has been out of reach, owing to limitations in resolution, contrast and volumetric imaging capability. Here we describe light-microscopy-based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning-based segmentation and analysis of connectivity, thereby directly incorporating molecular information into synapse-level reconstructions of brain tissue. LICONN will allow synapse-level phenotyping of brain tissue in biological experiments in a readily adoptable manner.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41586-025-08985-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:642:y:2025:i:8067:d:10.1038_s41586-025-08985-1

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/s41586-025-08985-1

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().