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Bessel Beam Illumination Reduces Random and Systematic Errors in Quantitative Functional Studies Using Light-Sheet Microscopy

  Articoli su Riviste JCR/ISI  (anno 2018)

Autori:  Muellenbroich M. C., Turrini L., Silvestri L., Alterini T., Gheisari A., Vanzi F., Sacconi L., Pavone F

Affiliazione Autori:  National Institute of Optics, National Research Council, Sesto Fiorentino, Italy; European Laboratory for Non-linear Spectroscopy, LENS, Sesto Fiorentino, Italy; Department of Biology, University of Florence, Sesto Fiorentino, Italy; Department of Physics and Astronomy, University of Florence, Sesto Fiorentino, Italy

Riassunto:  Light-sheet microscopy (LSM), in combination with intrinsically transparent zebrafish larvae, is a method of choice to observe brain function with high frame rates at cellular resolution. Inherently to LSM, however, residual opaque objects cause stripe artifacts, which obscure features of interest and, during functional imaging, modulate fluorescence variations related to neuronal activity. Here, we report how Bessel beams reduce streaking artifacts and produce high-fidelity quantitative data demonstrating a fivefold increase in sensitivity to calcium transients and a 20-fold increase in accuracy in the detection of activity correlations in functional imaging. Furthermore, using principal component analysis, we show that measurements obtained with Bessel beams are clean enough to reveal in one-shot experiments correlations that can not be averaged over trials after stimuli as is the case when studying spontaneous activity. Our results not only demonstrate the contamination of data by systematic and random errors through conventional Gaussian illumination and but,furthermore, quantify the increase in fidelity of such data when using Bessel beams.

Volume n.:  12      Pagine da: 315-1  a: 315-12
Ulteriori informazioni:  This project received funding from the European Union’s H2020 research and innovation programme under grant agreements No. 720270 (Human Brain Project) and 654148 (Laserlab-Europe), and from the EU programme H2020 EXCELLENT SCIENCE-European Research Council (ERC) under grant agreement ID n.692943 (BrainBIT). The project has also been supported by the Italian Ministry for Education, University, and Research in the framework of the Flagship Project NanoMAX and of Eurobioimaging Italian Nodes (ESFRI research infrastructure), and by Ente Cassa di Risparmio di Firenze (private foundation).
DOI: 10.3389/fncel.2018.00315

   *Citazioni: 4
data tratti da "WEB OF SCIENCE" (marchio registrato di Thomson Reuters) ed aggiornati a:  26/05/2019

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