The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Inferring the rules of interaction of shoaling fish
Open accessAbstract
Collective motion, where large numbers of individuals move synchronously together, is achieved when individuals adopt interaction rules that determine how they respond to their neighbors’ movements and positions. These rules determine how group-living animals move, make decisions, and transmit information between individuals. Nonetheless, few studies have explicitly determined these interaction rules in moving groups, and very little is known about the interaction rules of fish. Here, we identify three key rules for the social interactions of mosquitofish (Gambusia holbrooki): (i) Attraction forces are important in maintaining group cohesion, while we find only weak evidence that fish align with their neighbor’s orientation; (ii) repulsion is mediated principally by changes in speed; (iii) although the positions and directions of all shoal members are highly correlated, individuals only respond to their single nearest neighbor. The last two of these rules are different from the classical models of collective animal motion, raising new questions about how fish and other animals self-organize on the move.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
Vicsek, T., & Zafeiris, A. (2012) · Physics Reports · doi:10.1016/j.physrep.2012.03.004 · Cited by 2,923
A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants
Neal, R. M., & Hinton, G. E. (1998) · Learning in Graphical Models · doi:10.1007/978-94-011-5014-9_12 · Cited by 2,187
How simple rules determine pedestrian behavior and crowd disasters
Moussaïd, M., Helbing, D., & Theraulaz, G. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1016507108 · Cited by 1,204
Inferring the structure and dynamics of interactions in schooling fish
Katz, Y., Tunstrøm, K., Ioannou, C. C., Huepe, C., & Couzin, I. D. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1107583108 · Cited by 927 · cited 1×
“, which addresses similar questions on a different fish species (42).”
BackgroundHow perceived threat increases synchronization in collectively moving animal groups
Bode, N. W. F., Faria, J. J., Franks, D. W., Krause, J., & Wood, A. J. (2010) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2010.0855 · Cited by 154
Cited by
Automated image-based tracking and its application in ecology
Dell, A. I., Bender, J. A., Branson, K., Couzin, I. D., de Polavieja, G. G., Noldus, L. P. J. J., Pérez-Escudero, A., Perona, P., Straw, A. D., Wikelski, M., et al. (2014) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2014.05.004 · Cited by 492
Consistent Individual Differences Drive Collective Behavior and Group Functioning of Schooling Fish
Jolles, J. W., Boogert, N. J., Sridhar, V. H., Couzin, I. D., & Manica, A. (2017) · Current Biology · doi:10.1016/j.cub.2017.08.004 · Cited by 357
Deciphering Interactions in Moving Animal Groups
Gautrais, J., Ginelli, F., Fournier, R., Blanco, S., Soria, M., Chaté, H., & Theraulaz, G. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002678 · Cited by 346
Tuned, driven, and active soft matter
Menzel, A. M. (2015) · Physics Reports · doi:10.1016/j.physrep.2014.10.001 · Cited by 295
Reality mining of animal social systems
Krause, J., Krause, S., Arlinghaus, R., Psorakis, I., Roberts, S., & Rutz, C. (2013) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2013.06.002 · Cited by 269
Metadata
- Authors
- Herbert-Read, J. E., Perna, A., Mann, R. P., Schaerf, T. M., Sumpter, D. J. T., & Ward, A. J. W.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2011-11-07
- Volume
- 108
- Issue
- 46
- Pages
- 18726-18731
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1973893299
- Cited by
- 555
- References
- 6
- FWCI
- 39.66
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Inferring the rules of interaction of shoaling fish. https://app.cochat.ai/papers/10.1073/pnas.1109355108
- The paper
- Herbert-Read, J. E., Perna, A., Mann, R. P., Schaerf, T. M., Sumpter, D. J. T., & Ward, A. J. W. (2011). Inferring the rules of interaction of shoaling fish. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1109355108
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
