Living systems exhibit complex yet organized behavior on multiple spatiotemporal scales. To investigate the nature of multiscale coordination in living systems, one needs a meaningful and systematic way to quantify the complex dynamics, a challenge in both theoretical and empirical realms. The present work shows how integrating approaches from computational algebraic topology and dynamical systems may help us meet this challenge. In particular, we focus on the application of multiscale topological analysis to coordinated rhythmic processes. First, theoretical arguments are introduced as to why certain topological features and their scale-dependency are highly relevant to understanding complex collective dynamics. Second, we propose a method to capture such dynamically relevant topological information using persistent homology, which allows us to effectively construct a multiscale topological portrait of rhythmic coordination. Finally, the method is put to test in detecting transitions in real data from an experiment of rhythmic coordination in ensembles of interacting humans. The recurrence plots of topological portraits highlight collective transitions in coordination patterns that were elusive to more traditional methods. This sensitivity to collective transitions would be lost if the behavioral dynamics of individuals were treated as separate degrees of freedom instead of constituents of the topology that they collectively forge. Such multiscale topological portraits highlight collective aspects of coordination patterns that are irreducible to properties of individual parts. The present work demonstrates how the analysis of multiscale coordination dynamics can benefit from topological methods, thereby paving the way for further systematic quantification of complex, high-dimensional dynamics in living systems.
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http://dx.doi.org/10.1016/j.jneumeth.2020.108672 | DOI Listing |
Heliyon
May 2024
Department of Mechanical Engineering, Sejong University, Seoul 05006, South Korea.
This research focuses on the interaction between the grape borer and grapevine using a discrete-time plant-herbivore model with Allee's effect. We specifically investigate a model that incorporates a strong predator functional response to better understand the system's qualitative behavior at positive equilibrium points. In the present study, we explore the topological classifications at fixed points, stability analysis, Neimark-Sacker, Transcritical bifurcation and State feedback control in the two-dimensional discrete-time plant-herbivore model.
View Article and Find Full Text PDFChaos
January 2021
School of Artificial Intelligence and Automation and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan 430074, China.
This paper aims to propose a novel no-equilibrium Hindmarsh-Rose (HR) neuron model with memristive electromagnetic radiation effect. Compared with other memristor-based HR neuron models, the uniqueness of this memristive HR neuron model is that it can generate multi-scroll hidden attractors with sophisticated topological structures and the parity of the scrolls can be controlled conveniently with changing the internal parameters of the memristor. In particular, the number of scrolls of the multi-scroll hidden attractors is also associated with the intensity of external electromagnetic radiation stimuli.
View Article and Find Full Text PDFPLoS Comput Biol
February 2021
Department of Mathematics, Rutgers, The State University of New Jersey, Piscataway, New Jersey, United States of America.
J Neurosci Methods
June 2020
Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL, USA.
Living systems exhibit complex yet organized behavior on multiple spatiotemporal scales. To investigate the nature of multiscale coordination in living systems, one needs a meaningful and systematic way to quantify the complex dynamics, a challenge in both theoretical and empirical realms. The present work shows how integrating approaches from computational algebraic topology and dynamical systems may help us meet this challenge.
View Article and Find Full Text PDFGenetics
November 2018
Genetics Society of America, Rockville, Maryland 20852
The Genetics Society of America's (GSA) Edward Novitski Prize is awarded to researchers who have solved challenging problems in genetics through experiments that demonstrate exceptional creativity and ingenuity. Job Dekker of the University of Massachusetts Medical School has been selected for the 2018 award in recognition of his innovative approach to understanding chromosome interactions and nuclear organization. Among Dekker's contributions are the development of the now-ubiquitous approach of chromosome conformation capture and the discovery of topologically associating domains.
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