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      Modeling dynamics on the dance floor with directional swarmalators

      methods-article

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          Abstract

          Understanding collective behavior in both biological and social contexts, such as human interactions on dance floors, is a growing field of interest. Spatiotemporal dynamics of collective behavior have previously been modeled, for instance, with swarmalators, which are dynamical units that exhibit both swarming behavior and synchronization, combining spatial movement and entrainment. In our current study, we have expanded the swarmalator concept to encompass gaze direction as a representation of visual attention. We employ the newly developed directional swarmalator model for simulating the complex spatiotemporal dynamics observed on dance floors. Our model aims to reflect the complex dynamics of collective movement, as well as rhythmic synchronization and gaze alignment. It establishes a quantitative framework to dissect how individuals on dance floors self-organize and generate emergent patterns in response to both musical stimuli and visual perception of other dancers. The inclusion of gaze direction allows for the simulation of realistic scenarios on dance floors, mirroring the dynamic interplay of human movement in rhythm-driven environments. The model is initially tested against motion capture recordings of two groups dancing in a silent disco, however, it is theoretically adaptable to a variety of scenarios, including varying group sizes, adjustable degrees of auditory and visual coupling, as well as modifiable interaction ranges, making it a generic tool for exploring collective behavior in musical settings. The development of the directional swarmalator model contributes to understanding social dynamics in shared music and dance experiences.

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          There is a deep and useful connection between statistical mechanics (the behavior of systems with many degrees of freedom in thermal equilibrium at a finite temperature) and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters). A detailed analogy with annealing in solids provides a framework for optimization of the properties of very large and complex systems. This connection to statistical mechanics exposes new information and provides an unfamiliar perspective on traditional optimization problems and methods.
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              Embodied Meter: Hierarchical Eigenmodes in Music-Induced Movement

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                Author and article information

                Contributors
                URI : http://loop.frontiersin.org/people/87251/overviewRole: Role: Role: Role: Role: Role:
                URI : http://loop.frontiersin.org/people/394180/overviewRole: Role: Role:
                URI : http://loop.frontiersin.org/people/87380/overviewRole: Role: Role: Role:
                Journal
                Front Behav Neurosci
                Front Behav Neurosci
                Front. Behav. Neurosci.
                Frontiers in Behavioral Neuroscience
                Frontiers Media S.A.
                1662-5153
                05 February 2025
                2025
                : 19
                : 1534371
                Affiliations
                [1] 1Centre of Excellence in Music, Mind, Body and Brain, University of Jyväskylä , Jyväskylä, Finland
                [2] 2Department of Music, Art and Culture Studies, University of Jyväskylä , Jyväskylä, Finland
                [3] 3Social Body Lab, Centre for the Study of Social Cohesion, School of Anthropology and Museum Ethnography, University of Oxford , Oxford, United Kingdom
                Author notes

                Edited by: Viktor Müller, Max Planck Institute for Human Development, Germany

                Reviewed by: Bettina E. Bläsing, Bielefeld University, Germany

                Benjamin De Bari, DeSales University, United States

                *Correspondence: Petri Toiviainen, petri.toiviainen@ 123456jyu.fi
                Article
                10.3389/fnbeh.2025.1534371
                11835799
                39974292
                d7ed8a74-351e-40a8-967a-15890cff7ae2
                Copyright © 2025 Toiviainen, Bamford and Thompson.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 09 December 2024
                : 20 January 2025
                Page count
                Figures: 5, Tables: 1, Equations: 21, References: 27, Pages: 10, Words: 6522
                Funding
                Funded by: Research Council of Finland, doi 10.13039/501100002341;
                Award ID: 346210
                Award ID: 332331
                The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Research Council of Finland’s Centre of Excellence Programme (project numbers 332331 and 346210).
                Categories
                Neuroscience
                Methods
                Custom metadata
                Individual and Social Behaviors

                Neurosciences
                dance and movement,interaction,complex dynamics,swarmalators,entrainment
                Neurosciences
                dance and movement, interaction, complex dynamics, swarmalators, entrainment

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