Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain

Researchers from the Max Planck Institute for Biological Intelligence, Google Inc. and the Paul Scherrer Institute published a new method and data resource that makes connectomic analyses of the entire larval zebrafish brain possible. The scientists identified approximately 121,000 neurons and their synaptic connections by combining serial block-face electron microscopy (SBEM) with automated segmentation and synapse detection. The easy-to-use computational framework and data resource will enable the research community to study the neuronal networks in the zebrafish brain at unprecedented detail.

Abstract
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 14 × 14 × 25 nm³. 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.