ArticleScience advances2019
Fluctuation-induced distributed resonances in oscillatory networks.
Article in Science advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- The frequency response of networks as open systems.Nature communications · 2026Article
- Recurrent dynamics in the cerebral cortex: Integration of sensory evidence with stored knowledge.Proceedings of the National Academy of Sciences of the United States of America · 2021Review
- Open database analysis of scaling and spatio-temporal properties of power grid frequencies.Nature communications · 2020Article
- Low-frequency oscillations in coupled phase oscillators with inertia.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Across physics, biology, and engineering, the collective dynamics of oscillatory networks often evolve into self-organized operating states. How such networks respond to external fluctuating signals fundamentally underlies their function, yet is not well understood. Here, we present a theory of dynamic network response patterns and reveal how distributed resonance patterns emerge in oscillatory networks once the dynamics of the oscillatory units become more than one-dimensional. The network resonances are topology specific and emerge at an intermediate frequency content of the input signals, between global yet homogeneous responses at low frequencies and localized responses at high frequencies. Our analysis reveals why these patterns arise and where in the network they are most prominent. These results may thus provide general theoretical insights into how fluctuating signals induce response patterns in networked systems and simultaneously help to develop practical guiding principles for real-world network design and control.
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Registered trials
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