@article{13267,
  abstract     = {Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.},
  author       = {Velicky, Philipp and Miguel Villalba, Eder and Michalska, Julia M and Lyudchik, Julia and Wei, Donglai and Lin, Zudi and Watson, Jake and Troidl, Jakob and Beyer, Johanna and Ben Simon, Yoav and Sommer, Christoph M and Jahr, Wiebke and Cenameri, Alban and Broichhagen, Johannes and Grant, Seth G.N. and Jonas, Peter M and Novarino, Gaia and Pfister, Hanspeter and Bickel, Bernd and Danzl, Johann G},
  issn         = {1548-7105},
  journal      = {Nature Methods},
  pages        = {1256--1265},
  publisher    = {Springer Nature},
  title        = {{Dense 4D nanoscale reconstruction of living brain tissue}},
  doi          = {10.1038/s41592-023-01936-6},
  volume       = {20},
  year         = {2023},
}

@article{14257,
  abstract     = {Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.},
  author       = {Michalska, Julia M and Lyudchik, Julia and Velicky, Philipp and Korinkova, Hana and Watson, Jake and Cenameri, Alban and Sommer, Christoph M and Amberg, Nicole and Venturino, Alessandro and Roessler, Karl and Czech, Thomas and Höftberger, Romana and Siegert, Sandra and Novarino, Gaia and Jonas, Peter M and Danzl, Johann G},
  issn         = {1546-1696},
  journal      = {Nature Biotechnology},
  publisher    = {Springer Nature},
  title        = {{Imaging brain tissue architecture across millimeter to nanometer scales}},
  doi          = {10.1038/s41587-023-01911-8},
  year         = {2023},
}

@phdthesis{12470,
  abstract     = {The brain is an exceptionally sophisticated organ consisting of billions of cells and trillions of 
connections that orchestrate our cognition and behavior. To decode its complex connectivity, it is 
pivotal to disentangle its intricate architecture spanning from cm-sized circuits down to tens of 
nm-small synapses.
To achieve this goal, I developed CATS – Comprehensive Analysis of nervous Tissue across 
Scales, a versatile toolbox for obtaining a holistic view of nervous tissue context with (superresolution) fluorescence microscopy. CATS combines comprehensive labeling of the extracellular
space, that is compatible with chemical fixation, with information on molecular markers, superresolved data acquisition and machine-learning based data analysis for segmentation and synapse 
identification.
I used CATS to analyze key features of nervous tissue connectivity, ranging from whole tissue 
architecture, neuronal in- and output-fields, down to synapse morphology.
Focusing on the hippocampal circuitry, I quantified synaptic transmission properties of mossy 
fiber boutons and analyzed the connectivity pattern of dentate gyrus granule cells with CA3 
pyramidal neurons. This shows that CATS is a viable tool to study hallmarks of neuronal 
connectivity with light microscopy.},
  author       = {Michalska, Julia M},
  isbn         = { 978-3-99078-026-8},
  issn         = {2663-337X},
  pages        = {201},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy}},
  doi          = {10.15479/at:ista:12470},
  year         = {2023},
}

@unpublished{11943,
  abstract     = {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 <jats:italic>in-silico</jats:italic> reconstruction<jats:sup>1–5</jats:sup>, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches<jats:sup>6–12</jats:sup> 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) microscopy<jats:sup>6,13</jats:sup> in extracellularly labelled tissue<jats:sup>14</jats:sup> for high SNR and near-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 single 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.},
  author       = {Velicky, Philipp and Miguel Villalba, Eder and Michalska, Julia M and Wei, Donglai and Lin, Zudi and Watson, Jake and Troidl, Jakob and Beyer, Johanna and Ben Simon, Yoav and Sommer, Christoph M and Jahr, Wiebke and Cenameri, Alban and Broichhagen, Johannes and Grant, Seth G. N. and Jonas, Peter M and Novarino, Gaia and Pfister, Hanspeter and Bickel, Bernd and Danzl, Johann G},
  booktitle    = {bioRxiv},
  publisher    = {Cold Spring Harbor Laboratory},
  title        = {{Saturated reconstruction of living brain tissue}},
  doi          = {10.1101/2022.03.16.484431},
  year         = {2022},
}

@unpublished{11950,
  abstract     = {Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanoscopic synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS leverages fixation-compatible extracellular labeling and advanced optical readout, in particular stimulated-emission depletion and expansion microscopy, to comprehensively delineate cellular structures. It enables 3D-reconstructing single synapses and mapping synaptic connectivity by identification and tailored analysis of putative synaptic cleft regions. Applying CATS to the hippocampal mossy fiber circuitry, we demonstrate its power to reveal the system’s molecularly informed ultrastructure across spatial scales and assess local connectivity by reconstructing and quantifying the synaptic input and output structure of identified neurons.},
  author       = {Michalska, Julia M and Lyudchik, Julia and Velicky, Philipp and Korinkova, Hana and Watson, Jake and Cenameri, Alban and Sommer, Christoph M and Venturino, Alessandro and Roessler, Karl and Czech, Thomas and Siegert, Sandra and Novarino, Gaia and Jonas, Peter M and Danzl, Johann G},
  booktitle    = {bioRxiv},
  publisher    = {Cold Spring Harbor Laboratory},
  title        = {{Uncovering brain tissue architecture across scales with super-resolution light microscopy}},
  doi          = {10.1101/2022.08.17.504272},
  year         = {2022},
}

