PT  - JOURNAL ARTICLE
AU  - Philipp Velicky
AU  - Eder Miguel
AU  - Julia M. Michalska
AU  - Donglai Wei
AU  - Zudi Lin
AU  - Jake F. Watson
AU  - Jakob Troidl
AU  - Johanna Beyer
AU  - Yoav Ben-Simon
AU  - Christoph Sommer
AU  - Wiebke Jahr
AU  - Alban Cenameri
AU  - Johannes Broichhagen
AU  - Seth G. N. Grant
AU  - Peter Jonas
AU  - Gaia Novarino
AU  - Hanspeter Pfister
AU  - Bernd Bickel
AU  - Johann G. Danzl
TI  - Saturated reconstruction of living brain tissue
AID  - 10.1101/2022.03.16.484431
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.03.16.484431
4099  - http://biorxiv.org/content/early/2022/03/18/2022.03.16.484431.short
4100  - http://biorxiv.org/content/early/2022/03/18/2022.03.16.484431.full
AB  - Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive visualization of the architecture of living brain tissue with its cellular and molecular components would open up major opportunities. However, electron microscopy (EM) provides nanometre-scale resolution required for full in-silico reconstruction1–6, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches7–15 facilitating nanoscale visualization, but comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue. We developed an integrated imaging and analysis technology, adapting stimulated emission depletion (STED) microscopy7,16 in extracellularly labelled tissue17 for high SNR and isotropic resolution. Centrally, a two-stage deep-learning approach leveraged previously obtained information on sample structure to drastically reduce photo-burden and enable automated volumetric reconstruction down to synapse level. Live reconstruction provides unbiased analysis of tissue architecture across time in relation to functional activity and targeted activation, and contextual understanding of molecular labelling. This adoptable technology will facilitate novel insights into the dynamic functional architecture of living brain tissue.Competing Interest StatementThe authors have declared no competing interest.