preprint draft Mojtaba Tavakoli author 3A0A06F4-F248-11E8-B48F-1D18A9856A870000-0002-7667-6854 Julia Lyudchik author 46E28B80-F248-11E8-B48F-1D18A9856A87 Michał Januszewski author Vitali Vistunou author 7e146587-8972-11ed-ae7b-d7a32ea86a81 Nathalie Agudelo Duenas author 40E7F008-F248-11E8-B48F-1D18A9856A87 Jakob Vorlaufer author 937696FA-C996-11E9-8C7C-CF13E66974250009-0000-7590-3501 Christoph M Sommer author 4DF26D8C-F248-11E8-B48F-1D18A9856A870000-0003-1216-9105 Caroline Kreuzinger author 382077BA-F248-11E8-B48F-1D18A9856A87 Bárbara Oliveira author 3B03AA1A-F248-11E8-B48F-1D18A9856A87 Alban Cenameri author 9ac8f577-2357-11eb-997a-e566c5550886 Gaia Novarino author 3E57A680-F248-11E8-B48F-1D18A9856A870000-0002-7673-7178 Viren Jain author Johann G Danzl author 42EFD3B6-F248-11E8-B48F-1D18A9856A870000-0001-8559-3973 GaNo department JoDa department Studying Organelle Structure and Function at Nanoscale Resolution with Expansion Microscopy project International IST Doctoral Program project Toward an understanding of the brain interstitial system and the extracellular proteome in health and autism spectrum disorders project Molecular Drug Targets project 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 resolution with dense cellular labeling. Light microscopy is uniquely positioned to visualize specific molecules but dense, synapse-level circuit reconstruction by light microscopy has been out of reach due to limitations in resolution, contrast, and volumetric imaging capability. Here we developed light-microscopy based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning based segmentation and analysis of connectivity, thus directly incorporating molecular information in synapse-level brain tissue reconstructions. LICONN will allow synapse-level brain tissue phenotyping in biological experiments in a readily adoptable manner. 2024 eng 10.1101/2024.03.01.582884 https://research-explorer.ista.ac.at/record/18674 https://research-explorer.ista.ac.at/record/19704 https://research-explorer.ista.ac.at/record/18681 Tavakoli, Mojtaba, Julia Lyudchik, Michał Januszewski, Vitali Vistunou, Nathalie Agudelo Duenas, Jakob Vorlaufer, Christoph M Sommer, et al. “Light-Microscopy Based Dense Connectomic Reconstruction of Mammalian Brain Tissue.” <i>BioRxiv</i>, n.d. <a href="https://doi.org/10.1101/2024.03.01.582884">https://doi.org/10.1101/2024.03.01.582884</a>. M. Tavakoli, J. Lyudchik, M. Januszewski, V. Vistunou, N. Agudelo Duenas, J. Vorlaufer, C.M. Sommer, C. Kreuzinger, B. Oliveira, A. Cenameri, G. Novarino, V. Jain, J.G. Danzl, BioRxiv (n.d.). Tavakoli, M., Lyudchik, J., Januszewski, M., Vistunou, V., Agudelo Duenas, N., Vorlaufer, J., … Danzl, J. G. (n.d.). Light-microscopy based dense connectomic reconstruction of mammalian brain tissue. <i>bioRxiv</i>. <a href="https://doi.org/10.1101/2024.03.01.582884">https://doi.org/10.1101/2024.03.01.582884</a> M. Tavakoli <i>et al.</i>, “Light-microscopy based dense connectomic reconstruction of mammalian brain tissue,” <i>bioRxiv</i>. . Tavakoli, Mojtaba, et al. “Light-Microscopy Based Dense Connectomic Reconstruction of Mammalian Brain Tissue.” <i>BioRxiv</i>, doi:<a href="https://doi.org/10.1101/2024.03.01.582884">10.1101/2024.03.01.582884</a>. Tavakoli M, Lyudchik J, Januszewski M, Vistunou V, Agudelo Duenas N, Vorlaufer J, Sommer CM, Kreuzinger C, Oliveira B, Cenameri A, Novarino G, Jain V, Danzl JG. Light-microscopy based dense connectomic reconstruction of mammalian brain tissue. bioRxiv, <a href="https://doi.org/10.1101/2024.03.01.582884">10.1101/2024.03.01.582884</a>. Tavakoli M, Lyudchik J, Januszewski M, et al. Light-microscopy based dense connectomic reconstruction of mammalian brain tissue. <i>bioRxiv</i>. doi:<a href="https://doi.org/10.1101/2024.03.01.582884">10.1101/2024.03.01.582884</a> 186772024-12-18T14:48:24Z2026-07-28T08:33:51Z