Title |
Inferring collective dynamical states from widely unobserved systems
|
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Published in |
Nature Communications, June 2018
|
DOI | 10.1038/s41467-018-04725-4 |
Pubmed ID | |
Authors |
Jens Wilting, Viola Priesemann |
Abstract |
When assessing spatially extended complex systems, one can rarely sample the states of all components. We show that this spatial subsampling typically leads to severe underestimation of the risk of instability in systems with propagating events. We derive a subsampling-invariant estimator, and demonstrate that it correctly infers the infectiousness of various diseases under subsampling, making it particularly useful in countries with unreliable case reports. In neuroscience, recordings are strongly limited by subsampling. Here, the subsampling-invariant estimator allows to revisit two prominent hypotheses about the brain's collective spiking dynamics: asynchronous-irregular or critical. We identify consistently for rat, cat, and monkey a state that combines features of both and allows input to reverberate in the network for hundreds of milliseconds. Overall, owing to its ready applicability, the novel estimator paves the way to novel insight for the study of spatially extended dynamical systems. |
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Germany | 25 | 40% |
Canada | 3 | 5% |
Spain | 1 | 2% |
Austria | 1 | 2% |
United States | 1 | 2% |
Switzerland | 1 | 2% |
Australia | 1 | 2% |
United Kingdom | 1 | 2% |
Unknown | 28 | 45% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 51 | 82% |
Scientists | 11 | 18% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 143 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 32 | 22% |
Student > Ph. D. Student | 29 | 20% |
Student > Bachelor | 18 | 13% |
Student > Master | 13 | 9% |
Professor | 9 | 6% |
Other | 19 | 13% |
Unknown | 23 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 40 | 28% |
Physics and Astronomy | 23 | 16% |
Agricultural and Biological Sciences | 11 | 8% |
Engineering | 9 | 6% |
Computer Science | 7 | 5% |
Other | 25 | 17% |
Unknown | 28 | 20% |