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  • Open Access

Emergent bifurcation and robust decision-making in neurodynamic swarms

Peng Ren1,2, Jiang Zhao3, Pei Chi1,*, and Yingxun Wang1

  • 1Institute of Unmanned System, Beihang University, Beijing, China
  • 2Zhongguancun Academy, Beijing, China
  • 3School of Automation Science and Electrical Engineering, Beihang University, Beijing, China

  • *Contact author: peichi@buaa.edu.cn
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Phys. Rev. Research 8, 013003 – Published 5 January, 2026

DOI: https://doi.org/10.1103/xwdd-hjhn

Abstract

Collective motion is typically modeled by local velocity-alignment rules. However, these models do not fully capture recent evidence for complex decision-making in biological swarms and are fragile to structured, adversarial perturbations. Here, we introduce a neurodynamic swarm model where collective behavior emerges not from alignment, but from nonlinear competition within Hopfield-type ring attractors. We show that this mechanism naturally gives rise to emergent decision bifurcations that reproduce sophisticated animal behaviors. Crucially, the inherent stability of the attractors provides the swarm with remarkable resilience, allowing it to maintain coherence against adversarial perturbations that shatter alignment-based models.

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Phys. Rev. Research 8, 013003– Published 5 January, 2026
  • Received 30 September 2025
  • Accepted 7 December 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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