ArticleProceedings of the National Academy of Sciences of the United States of America2025
Symmetries and synchronization from whole-neural activity in the
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Inferring effective neuronal circuits via network flux counting.PLoS computational biology · 2026Article
- Synchronization properties in C. elegans: Relating behavioral circuits to structural and functional neuronal connectivity.PLoS computational biology · 2026Article
- Organization of mouse prefrontal cortex subnetwork revealed by spatial single-cell multi-omic analysis of SPIDER-Seq.National science review · 2026Article
- The role of fibration symmetries in geometric deep learning.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Symmetries and synchronization from whole-neural activity in theProceedings of the National Academy of Sciences of the United States of America · 2025Article
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7 authors.
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Abstract
Understanding the dynamical behavior of complex systems from their underlying network architectures is a long-standing question in complexity theory. Therefore, many metrics have been devised to extract network features like motifs, centrality, and modularity measures. It has previously been proposed that network symmetries are of particular importance since they are expected to underlie the synchronization of a system's units, which is ubiquitously observed in nervous system activity patterns. However, perfectly symmetrical structures are difficult to assess in noisy measurements of biological systems, like neuronal connectomes. Here, we devise a principled method to infer network symmetries from combined connectome and neuronal activity data. Using nervous system-wide population activity recordings of the
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