Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome

Abstract
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Abstract

Comparing connectomes can help explain how neural connectivity is related to genetics, disease, development, learning, and behavior. However, making statistical inferences about the significance and nature of differences between two networks is an open problem, and such analysis has not been extensively applied to nanoscale connectomes. Here, we investigate this problem via a case study on the bilateral symmetry of a larval Drosophila brain connectome. We translate notions of'bilateral symmetry' to generative models of the network structure of the left and right hemispheres, allowing us to test and refine our understanding of symmetry. We find significant differences in connection probabilities both across the entire left and right networks and between specific cell types. By rescaling connection probabilities or removing certain edges based on weight, we also present adjusted definitions of bilateral symmetry exhibited by this connectome. This work shows how statistical inferences from networks can inform the study of connectomes, facilitating future comparisons of neural structures.

Data availability

All code used for analysis is available at https://github.com/neurodata/bilateral-connectome, and the version for this submission is archived at https://doi.org/10.5281/zenodo.7733481.All data analyzed in this study were generated in Winding, Pedigo et al. "The connectome of an insect brain," Science (2023) https://www.science.org/doi/10.1126/science.add9330.These data are also included for convenience in the code repository linked above and as Figure 1 - Source Data 1.

The following previously published data sets were used

1. Winding M
2. Pedigo BD
3. Barnes CL
4. Patsolic HG
5. Park Y
6. Kazimiers T
7. Fushiki A
8. Andrade IV
9. Khandelwal A
10. Valdes-Aleman J
11. Li F
12. Randel N
13. Barsotti E
14. Correia A
15. Fetter RD
16. Hartenstein V
17. Priebe CE
18. Vogelstein JT
19. Cardona A
20. Zlatic M
(2023) The connectome of an insect brain
N/A.

https://www.science.org/doi/10.1126/science.add9330

Article and author information

Author details

Benjamin D Pedigo

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, United States

For correspondence
bpedigo@jhu.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-9519-1190
Mike Powell

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, United States

Competing interests
The authors declare that no competing interests exist.
Eric W Bridgeford

Department of Biostatistics, Johns Hopkins University, Baltimore, United States

Competing interests
The authors declare that no competing interests exist.
Michael Winding

Department of Zoology, University of Cambridge, Cambridge, United Kingdom

Competing interests
The authors declare that no competing interests exist.
Carey E Priebe

Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, United States

Competing interests
The authors declare that no competing interests exist.
Joshua T Vogelstein

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, United States

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0003-2487-6237

Funding

National Science Foundation (DGE1746891)

Benjamin D Pedigo

National Science Foundation (1942963)

Joshua T Vogelstein

National Science Foundation (2014862)

Joshua T Vogelstein

National Institutes of Health (1RF1MH123233-01)

Carey E Priebe
Joshua T Vogelstein

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

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.