Information flow, cell types and stereotypy in a full olfactory connectome
- MRC Laboratory of Molecular Biology, United Kingdom
- University of Cambridge, United Kingdom
- Howard Hughes Medical Institute, United States
- Harvard Medical School, United States
- Janelia Research Campus, Howard Hughes Medical Institute, United States
Abstract
The hemibrain connectome provides large scale connectivity and morphology information for the majority of the central brain of Drosophila melanogaster. Using this data set, we provide a complete description of the Drosophila olfactory system, covering all first, second and lateral horn-associated third-order neurons. We develop a generally applicable strategy to extract information flow and layered organisation from connectome graphs, mapping olfactory input to descending interneurons. This identifies a range of motifs including highly lateralised circuits in the antennal lobe and patterns of convergence downstream of the mushroom body and lateral horn. Leveraging a second data set we provide a first quantitative assessment of inter- versus intra-individual stereotypy. Comparing neurons across two brains (three hemispheres) reveals striking similarity in neuronal morphology across brains. Connectivity correlates with morphology and neurons of the same morphological type show similar connection variability within the same brain as across two brains.
Data availability
The hemibrain connectome including our annotations is hosted via neuPrint at https://neuprint.janelia.orgPublished data (neuronal reconstructions and connectivity) from the FAFB EM data set is hosted by Virtual Fly Brain (VFB) at https://catmaid.virtualflybrain.org. A snapshot of the FAFB data used in this study will be shared with VFB prior to publication.Meta data (e.g. neuron classifications, axon-dendrite splits, glomeruli meshes, etc) are included in the manuscript and supporting files.In addition, we maintain Github repositories with meta data (https://github.com/flyconnectome/hemibrain_olf_data) and code examples (https://github.com/flyconnectome/2020hemibrain_examples).
Article and author information
Author details
Alexander Shakeel Bates
Sridhar R Jagannathan
Gregory SXE Jefferis
Funding
Wellcome Trust (Collaborative Award,203261/Z/16/Z)
- Philipp Schlegel
- Tomke Stürner
- Sridhar R Jagannathan
- Nikolas Drummond
- Joseph Hsu
- Laia Serratosa Capdevila
- Alexandre Javier
- Elizabeth C Marin
- Imaan FM Tamimi
- Feng Li
- Gerald M Rubin
- Marta Costa
- Gregory SXE Jefferis
European Research Council (Consolidator grant,649111)
- Laia Serratosa Capdevila
- Alexandre Javier
- Gregory SXE Jefferis
Medical Research Council (Core support,MC-U105188491)
- Alexander Shakeel Bates
- Gregory SXE Jefferis
National Institutes of Health (BRAIN Initiative grant,1RF1MH120679-01)
- Philipp Schlegel
- Tomke Stürner
- Gregory SXE Jefferis
National Institutes of Health (F31 fellowship,DC016196)
- Asa Barth-Maron
Boehringer Ingelheim Fonds (PhD Fellowship)
- Alexander Shakeel Bates
Herchel Smith (Studentship)
- Alexander Shakeel Bates
National Institutes of Health (R01DC008174)
- Asa Barth-Maron
Howard Hughes Medical Institute
- Gerald M Rubin
- Stephen M Plaza
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Schlegel et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Information flow, cell types and stereotypy in a full olfactory connectome
eLife 10:e66018.
https://doi.org/10.7554/eLife.66018
Further reading
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- Computational and Systems Biology
- Neuroscience
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.
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