Nature MethodsNeurosciencePeer-reviewed journal article
Saturated reconstruction of living brain tissue
Philipp VelickyiD, Eder MigueliD, Julia M. MichalskaiD, Julia LyudchikiD, Donglai WeiiD, Zudi LiniD, Jake F. WatsoniD, Jakob TroidliD, Johanna BeyeriD, Yoav Ben‐SimoniD, Christoph SommeriD, Wiebke JahriD, Alban Cenameri, Johannes BroichhageniD, Seth G. N. GrantiD, Péter JónásiD, Gaia NovarinoiD, Hanspeter PfisteriD, Bernd BickeliD, Johann Georg DanzliD
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 in-silico reconstruction1-5, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches6-12 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) microscopy6,13 in extracellularly labelled tissue14 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.
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