Author
Listed:
- Albert Lin
(Princeton University
Princeton University)
- Runzhe Yang
(Princeton University
Princeton University)
- Sven Dorkenwald
(Princeton University
Princeton University)
- Arie Matsliah
(Princeton University)
- Amy R. Sterling
(Princeton University)
- Philipp Schlegel
(MRC Laboratory of Molecular Biology
University of Cambridge)
- Szi-chieh Yu
(Princeton University)
- Claire E. McKellar
(Princeton University)
- Marta Costa
(University of Cambridge)
- Katharina Eichler
(University of Cambridge)
- Alexander Shakeel Bates
(MRC Laboratory of Molecular Biology
University of Cambridge
University of Oxford)
- Nils Eckstein
(Howard Hughes Medical Institute)
- Jan Funke
(Howard Hughes Medical Institute)
- Gregory S. X. E. Jefferis
(MRC Laboratory of Molecular Biology
University of Cambridge)
- Mala Murthy
(Princeton University)
Abstract
Brains comprise complex networks of neurons and connections, similar to the nodes and edges of artificial networks. Network analysis applied to the wiring diagrams of brains can offer insights into how they support computations and regulate the flow of information underlying perception and behaviour. The completion of the first whole-brain connectome of an adult fly, containing over 130,000 neurons and millions of synaptic connections1–3, offers an opportunity to analyse the statistical properties and topological features of a complete brain. Here we computed the prevalence of two- and three-node motifs, examined their strengths, related this information to both neurotransmitter composition and cell type annotations4,5, and compared these metrics with wiring diagrams of other animals. We found that the network of the fly brain displays rich-club organization, with a large population (30% of the connectome) of highly connected neurons. We identified subsets of rich-club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex ( https://codex.flywire.ai ) and should serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.
Suggested Citation
Albert Lin & Runzhe Yang & Sven Dorkenwald & Arie Matsliah & Amy R. Sterling & Philipp Schlegel & Szi-chieh Yu & Claire E. McKellar & Marta Costa & Katharina Eichler & Alexander Shakeel Bates & Nils E, 2024.
"Network statistics of the whole-brain connectome of Drosophila,"
Nature, Nature, vol. 634(8032), pages 153-165, October.
Handle:
RePEc:nat:nature:v:634:y:2024:i:8032:d:10.1038_s41586-024-07968-y
DOI: 10.1038/s41586-024-07968-y
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