FB2026_02 , released June 18, 2026
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Citation
Kuan, A.T., Phelps, J.S., Thomas, L.A., Nguyen, T.M., Han, J., Chen, C.L., Azevedo, A.W., Tuthill, J.C., Funke, J., Cloetens, P., Pacureanu, A., Lee, W.A. (2020). Dense neuronal reconstruction through X-ray holographic nano-tomography.  Nat. Neurosci. 23(12): 1637--1643.
FlyBase ID
FBrf0247324
Publication Type
Research paper
Abstract
Imaging neuronal networks provides a foundation for understanding the nervous system, but resolving dense nanometer-scale structures over large volumes remains challenging for light microscopy (LM) and electron microscopy (EM). Here we show that X-ray holographic nano-tomography (XNH) can image millimeter-scale volumes with sub-100-nm resolution, enabling reconstruction of dense wiring in Drosophila melanogaster and mouse nervous tissue. We performed correlative XNH and EM to reconstruct hundreds of cortical pyramidal cells and show that more superficial cells receive stronger synaptic inhibition on their apical dendrites. By combining multiple XNH scans, we imaged an adult Drosophila leg with sufficient resolution to comprehensively catalog mechanosensory neurons and trace individual motor axons from muscles to the central nervous system. To accelerate neuronal reconstructions, we trained a convolutional neural network to automatically segment neurons from XNH volumes. Thus, XNH bridges a key gap between LM and EM, providing a new avenue for neural circuit discovery.
PubMed ID
PubMed Central ID
PMC8354006 (PMC) (EuropePMC)
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    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Nat. Neurosci.
    Title
    Nature Neuroscience
    Publication Year
    1998-
    ISBN/ISSN
    1097-6256
    Data From Reference
    Alleles (1)
    Genes (1)
    Natural transposons (1)
    Insertions (2)
    Experimental Tools (4)
    Transgenic Constructs (1)