2016/08/31 by Jens Wilting, Viola Priesemann · 1 citation
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · #physics.data-an #q-bio.NC
paper · pdf · doi:10.1038/s41467-018-04725-4
published as Wilting, J. & Priesemann, V. Inferring collective dynamical states from widely unobserved systems. Nature Communications 9, 2325 (2018) · 7 pages + 12 pages supplementary information + 7 supplementary figures. Title changed to match journal reference
arxiv created 2018/07/05 · arxiv updated 2018/07/06
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.