Abstract
The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain.
Highlights
In order to overcome the aberration of a large field of view, we developed a novel tiling approach without sample stage movement, in which the imaging parameters of each tile are individually optimized through an in-line auto focus routine without overhead(Xu et al, 2018)
We evaluated the accuracy of the flood-filling networks (FFNs) segmentation of the hemibrain using metrics for expected run length (ERL) and merge rate(Januszewski et al, 2018)
Using the above semi-automated procedures, we identified 55 types for visual projection neurons (VPNs), 159 types in the antennal lobe (AL), 68 types in mushroom body (MB), and 264 types in CX, which in aggregate apply to a total of
Summary
Most arbors in volume (uncropped) Neurons traced, large (≥ 1000 connections) but cropped by edge of volume Remaining traced, small (< 1000 connections) and cropped Presynaptic sites (T-Bars) in uncropped/traced/total T-bars Postsynaptic densities(PSDs) in uncropped/traced/total. Producing this data set required advances in sample preparation, imaging, image alignment, machine segmentation of cells, synapse detection, data storage, proofreading software, and protocols to arbitrate each decision. A number of new tests for estimating the completeness and accuracy were required and developed, in order to verify the correctness of the connectome
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