Dense reconstruction of synaptic connectivity requires high-resolution electron microscopy images of entire brains and tools to efficiently trace neuronal wires across the volume. To generate such a resource, we sectioned and imaged a larval zebrafish brain by serial block-face electron microscopy at a voxel size of 14âÃâ14âÃâ25ânm(3). We segmented the resulting dataset with the flood-filling network algorithm, automated the detection of chemical synapses and validated the results by comparisons to transmission electron microscopic images and light-microscopic reconstructions. Neurons and their connections are stored in the form of a queryable and expandable digital address book. We reconstructed a network of 208 neurons involved in visual motion processing, most of them located in the pretectum, which had been functionally characterized in the same specimen by two-photon calcium imaging. Moreover, we mapped all 407 presynaptic and postsynaptic partners of two superficial interneurons in the tectum. The resource developed here serves as a foundation for synaptic-resolution circuit analyses in the zebrafish nervous system.
Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain.
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作者:Svara Fabian, Förster Dominique, Kubo Fumi, Januszewski MichaÅ, Dal Maschio Marco, Schubert Philipp J, Kornfeld Jörgen, Wanner Adrian A, Laurell Eva, Denk Winfried, Baier Herwig
| 期刊: | Nature Methods | 影响因子: | 32.100 |
| 时间: | 2022 | 起止号: | 2022 Nov;19(11):1357-1366 |
| doi: | 10.1038/s41592-022-01621-0 | ||
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