Network statistics of the whole-brain connectome of Drosophila.

Autor: Lin A; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.; Center for the Physics of Biological Function, Princeton University, Princeton, NJ, USA., Yang R; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.; Computer Science Department, Princeton University, Princeton, NJ, USA., Dorkenwald S; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.; Computer Science Department, Princeton University, Princeton, NJ, USA., Matsliah A; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., Sterling AR; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., Schlegel P; Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK.; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK., Yu SC; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., McKellar CE; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., Costa M; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK., Eichler K; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK., Bates AS; Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK.; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK.; Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK., Eckstein N; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA., Funke J; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA., Jefferis GSXE; Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK.; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK., Murthy M; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA. mmurthy@princeton.edu.
Jazyk: angličtina
Zdroj: Nature [Nature] 2024 Oct; Vol. 634 (8032), pp. 153-165. Date of Electronic Publication: 2024 Oct 02.
DOI: 10.1038/s41586-024-07968-y
Abstrakt: 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 connections 1-3 , 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 annotations 4,5 , 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.
(© 2024. The Author(s).)
Databáze: MEDLINE
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