| Autor: |
Poel W; Institute for Theoretical Biology, Department of Biology, Humboldt Universität zu Berlin, D-10099 Berlin, Germany.; Bernstein Center for Computational Neuroscience Berlin, D-10115 Berlin, Germany., Daniels BC; School of Complex Adaptive Systems, Arizona State University, Tempe, AZ 85287, USA., Sosna MMG; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA., Twomey CR; Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA., Leblanc SP; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.; Blend Labs, San Francisco, CA 94108, USA., Couzin ID; Department of Collective Behaviour, Max Planck Institute of Animal Behavior, D-78547 Konstanz, Germany.; Department of Biology, University of Konstanz, D-78547 Konstanz, Germany.; Centre for the Advanced Study of Collective Behaviour, University of Konstanz, D-78547 Konstanz, Germany., Romanczuk P; Institute for Theoretical Biology, Department of Biology, Humboldt Universität zu Berlin, D-10099 Berlin, Germany.; Bernstein Center for Computational Neuroscience Berlin, D-10115 Berlin, Germany.; Science of Intelligence, Research Cluster of Excellence, Marchstr. 23, D-10587 Berlin, Germany. |
| Abstrakt: |
Theoretical physics predicts optimal information processing in living systems near transitions (or pseudo-critical points) in their collective dynamics. However, focusing on potential benefits of proximity to a critical point, such as maximal sensitivity to perturbations and fast dissemination of information, commonly disregards possible costs of criticality in the noisy, dynamic environmental contexts of biological systems. Here, we find that startle cascades in fish schools are subcritical (not maximally responsive to environmental cues) and that distance to criticality decreases when perceived risk increases. Considering individuals' costs related to two detection error types, associated to both true and false alarms, we argue that being subcritical, and modulating distance to criticality, can be understood as managing a trade-off between sensitivity and robustness according to the riskiness and noisiness of the environment. Our work emphasizes the need for an individual-based and context-dependent perspective on criticality and collective information processing and motivates future questions about the evolutionary forces that brought about a particular trade-off. |
