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Showing 1–7 of 7 results
Advanced filters: Author: Anna Levina Clear advanced filters

  • Sensitivity to small changes is essential for organisms to make timely and reliable decisions, but operating near criticality also amplifies fluctuations and hinders information accumulation. Here, the authors show that when information is integrated over a finite time, as in biological readouts, the optimal sensitivity for a given integration time is achieved away from criticality, approaching criticality only as longer integration becomes available.

    • Sahel Azizpour
    • Viola Priesemann
    • Anna Levina
    ResearchOpen Access
    Communications Physics
    Volume: 9, P: 1-7

  • We can often observe only a small fraction of a system, which leads to biases in the inference of its global properties. Here, the authors develop a framework that enables overcoming subsampling effects, apply it to recordings from developing neural networks, and find that neural networks become critical as they mature.

    • A. Levina
    • V. Priesemann
    ResearchOpen Access
    Nature Communications
    Volume: 8, P: 1-9

  • The nature of the percolation transition—how links add to a system until it is extensively connected—crucially underlies the structure and function of virtually all growing complex networks. Percolation transitions have long been thought to be continuous, but recent numerical work suggests that certain percolating systems exhibit discontinuous phase transitions. This study explains the key microscopic mechanisms underlying such ‘explosive percolation’.

    • Jan Nagler
    • Anna Levina
    • Marc Timme
    Research
    Nature Physics
    Volume: 7, P: 265-270

  • Not much is known about how intrinsic timescales, which characterize the dynamics of endogenous fluctuations in neural activity, change during cognitive tasks. Here, the authors show that intrinsic timescales of neural activity in the primate visual cortex change during spatial attention. Experimental data were best explained by a network model in which timescales arise from spatially arranged connectivity.

    • Roxana Zeraati
    • Yan-Liang Shi
    • Tatiana A. Engel
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-19

  • A Bayesian method is presented for unbiased estimation of timescales from different types of experimental data; the method quantifies the estimation uncertainty and allows for comparing the alternative hypotheses on the underlying dynamics.

    • Roxana Zeraati
    • Tatiana A. Engel
    • Anna Levina
    ResearchOpen Access
    Nature Computational Science
    Volume: 2, P: 193-204

  • For many complex or living systems, it is impossible to individually sample all their units, but subsampling can heavily bias the inference about their collective properties. This Perspective presents the subsampling problem and reviews recent developments to overcome this fundamental limitation.

    • Anna Levina
    • Viola Priesemann
    • Johannes Zierenberg
    Reviews
    Nature Reviews Physics
    Volume: 4, P: 770-784