The multilayer connectome of Caenorhabditis elegans
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Abstract (arXiv)
Connectomics has focused primarily on the mapping of synaptic links in the brain; yet it is well established that extrasynaptic volume transmission, especially via monoamines and neuropeptides, is also critical to brain function. Here we present a draft monoamine connectome, along with a partial neuropeptide connectome, for the nematode C. elegans, based on new and published expression data for biosynthetic genes and receptors. Thus, the neuronal connectome can be represented as a multiplex network, with synaptic, gap junction, and neuromodulatory layers representing alternative modes of interneuronal interaction and with distinct network structures. In particular, the monoamine network exhibits novel topological properties, with a highly disassortative star-like structure and a rich-club of interconnected broadcasting hubs. Despite the low degree of overlap between layers, we find highly significant modes of interaction, pinpointing network locations and multilink motifs where aminergic and neuropeptide signalling modulate synaptic activity. The multilayer connectome of C. elegans represents a clear exemplar of a biological multiplex network and provides a prototype for understanding how extrasynaptic signalling can be integrated into the wired circuitry in larger brains.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Aug 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 2.
5 papers.
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- 2023Learning the Right Layers: a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphscited by 0
- 2024Learning dynamic representations of the functional connectome in neurobiological networkscited by 0
- 2024Agnosticism About Artificial Consciousness17 Dec 2024
- 2024Learning dynamic representations of the functional connectome in neurobiological networks21 Feb 2024
- 2023Expressive probabilistic sampling in recurrent neural networks22 Aug 2023
- 2023Learning the Right Layers: a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs31 May 2023
- 2021Propagation on Multi-relational Graphs for Node Regression15 Oct 2021