Tavakoli, M. R., Lyudchik, J., Januszewski, M., Vistunou, V., Agudelo Dueñas, N., Vorlaufer, J., … & Danzl, J. G. (2025). Light-microscopy-based connectomic reconstruction of mammalian brain tissue. Nature, 1-13. https://www.nature.com/articles/s41586-025-08985-1
Expansion Microscopy with Pan-Protein Staining and Deep-Learning Based Connectome Tracing
mouse primary somatosensory cortex
This paper’s technique, light-microscopy-based connectomics (LICONN), represents the biggest technological advancement in connectomics in a decade. Until this paper only electron microscopy (EM) techniques had been shown to have the 3D resolution needed to comprehensively trace all neuronal connections in a volume of brain tissue. LICONN allows such comprehensive tracing using fluorescence microscopy. Unlike EM which requires physical sectioning (ultrathin or ion ablation) to obtain 3D over large volumes, LICONN uses optical sectioning. This is an enormous simplification. Perhaps more importantly, the authors demonstrate that LICONN is compatible with immunolabeling of biomolecules like synaptic proteins. This ability to obtain molecularly annotated connectomes opens up many new experimental paths for memory research and memory decoding experiments.
“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.”