ArticleScience advances2022
Modes of information flow in collective cohesion.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Collective surfing of single cells on a chemo-attractant wave using multiscale Eulerian velocity vector field.Scientific reports · 2026Article
- Can AI help with the hardest thing: pro health behavior change.NPJ cardiovascular health · 2026Review
- Detecting existence of a hidden mediator between a pair of individual time series.Scientific reports · 2025Article
- Layer-by-layer unsupervised clustering of statistically relevant fluctuations in noisy time-series data of complex dynamical systems.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Inferring the roles of individuals in collective systems using information-theoretic measures of influence.Biophysics and physicobiology · 2024Review
- Comparison of particle image velocimetry and the underlying agents dynamics in collectively moving self propelled particles.Scientific reports · 2023Article
- Inference in conditioned dynamics through causality restoration.Scientific reports · 2023Article
- Transfer entropy dependent on distance among agents in quantifying leader-follower relationships.Biophysics and physicobiology · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pairwise interactions are fundamental drivers of collective behavior-responsible for group cohesion. The abiding question is how each individual influences the collective. However, time-delayed mutual information and transfer entropy, commonly used to quantify mutual influence in aggregated individuals, can result in misleading interpretations. Here, we show that these information measures have substantial pitfalls in measuring information flow between agents from their trajectories. We decompose the information measures into three distinct modes of information flow to expose the role of individual and group memory in collective behavior. It is found that decomposed information modes between a single pair of agents reveal the nature of mutual influence involving many-body nonadditive interactions without conditioning on additional agents. The pairwise decomposed modes of information flow facilitate an improved diagnosis of mutual influence in collectives.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.