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Rossi KL, Budzinski RC, Medeiros ES, Boaretto BRR, Muller L, Feudel U. Dynamical properties and mechanisms of metastability: A perspective in neuroscience. Phys Rev E 2025; 111:021001. [PMID: 40103058 DOI: 10.1103/physreve.111.021001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2024] [Indexed: 03/20/2025]
Abstract
Metastability, characterized by a variability of regimes in time, is a ubiquitous type of neural dynamics. It has been formulated in many different ways in the neuroscience literature, however, which may cause some confusion. In this Perspective, we discuss metastability from the point of view of dynamical systems theory. We extract from the literature a very simple but general definition through the concept of metastable regimes as long-lived but transient epochs of activity with unique dynamical properties. This definition serves as an umbrella term that encompasses formulations from other works, and readily connects to concepts from dynamical systems theory. This allows us to examine general dynamical properties of metastable regimes, propose in a didactic manner several dynamics-based mechanisms that generate them, and discuss a theoretical tool to characterize them quantitatively. This Perspective leads to insights that help to address issues debated in the literature and also suggests pathways for future research.
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Affiliation(s)
- Kalel L Rossi
- Carl von Ossietzky University Oldenburg, Theoretical Physics/Complex Systems, ICBM, 26129 Oldenburg, Lower Saxony, Germany
| | - Roberto C Budzinski
- Western University, Department of Mathematics and Western Institute for Neuroscience, N6A 3K7 London, Ontario, Canada
- Fields Institute, Fields Lab for Network Science, M5T 3J1 Toronto, Ontario, Canada
| | - Everton S Medeiros
- São Paulo State University (UNESP), Institute of Geosciences and Exact Sciences, Avenida 24A 1515, 13506-900 Rio Claro, São Paulo, Brazil
| | - Bruno R R Boaretto
- Universidade Federal de São Paulo, Institute of Science and Technology, 12247-014 São José dos Campos, São Paulo, Brazil
- Universitat Politecnica de Catalunya, Department of Physics, 08222 Terrassa, Barcelona, Spain
| | - Lyle Muller
- Western University, Department of Mathematics and Western Institute for Neuroscience, N6A 3K7 London, Ontario, Canada
- Fields Institute, Fields Lab for Network Science, M5T 3J1 Toronto, Ontario, Canada
| | - Ulrike Feudel
- Carl von Ossietzky University Oldenburg, Theoretical Physics/Complex Systems, ICBM, 26129 Oldenburg, Lower Saxony, Germany
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Fatoyinbo HO, Brown RG, Simpson DJW, van Brunt B. Pattern Formation in a Spatially Extended Model of Pacemaker Dynamics in Smooth Muscle Cells. Bull Math Biol 2022; 84:86. [PMID: 35804271 PMCID: PMC9270316 DOI: 10.1007/s11538-022-01043-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 06/16/2022] [Indexed: 11/30/2022]
Abstract
Spatiotemporal patterns are common in biological systems. For electrically coupled cells, previous studies of pattern formation have mainly used applied current as the primary bifurcation parameter. The purpose of this paper is to show that applied current is not needed to generate spatiotemporal patterns for smooth muscle cells. The patterns can be generated solely by external mechanical stimulation (transmural pressure). To do this we study a reaction-diffusion system involving the Morris-Lecar equations and observe a wide range of spatiotemporal patterns for different values of the model parameters. Some aspects of these patterns are explained via a bifurcation analysis of the system without coupling - in particular Type I and Type II excitability both occur. We show the patterns are not due to a Turing instability and that the spatially extended model exhibits spatiotemporal chaos. We also use travelling wave coordinates to analyse travelling waves.
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Affiliation(s)
- H. O. Fatoyinbo
- School of Mathematical and Computational Sciences, Massey University, Palmerston North, New Zealand
| | - R. G. Brown
- School of Mathematical and Computational Sciences, Massey University, Palmerston North, New Zealand
| | - D. J. W. Simpson
- School of Mathematical and Computational Sciences, Massey University, Palmerston North, New Zealand
| | - B. van Brunt
- School of Mathematical and Computational Sciences, Massey University, Palmerston North, New Zealand
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Edwards V, deZonia P, Hsieh MA, Hindes J, Triandaf I, Schwartz IB. Delay induced swarm pattern bifurcations in mixed reality experiments. CHAOS (WOODBURY, N.Y.) 2020; 30:073126. [PMID: 32752651 DOI: 10.1063/1.5142849] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 07/02/2020] [Indexed: 06/11/2023]
Abstract
Swarms of coupled mobile agents subject to inter-agent wireless communication delays are known to exhibit multiple dynamic patterns in space that depend on the strength of the interactions and the magnitude of the communication delays. We experimentally demonstrate communication delay-induced bifurcations in the spatiotemporal patterns of robot swarms using two distinct hardware platforms in a mixed reality framework. Additionally, we make steps toward experimentally validating theoretically predicted parameter regions where transitions between swarm patterns occur. We show that multiple rotation patterns persist even when collision avoidance strategies are incorporated, and we show the existence of multi-stable, co-existing rotational patterns not predicted by usual mean field dynamics. Our experiments are the first significant steps toward validating existing theory and the existence and robustness of the delay-induced patterns in real robotic swarms.
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Affiliation(s)
- Victoria Edwards
- Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Washington, DC 20375, USA
| | - Philip deZonia
- Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - M Ani Hsieh
- Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Jason Hindes
- Nonlinear Dynamical Systems, Naval Research Laboratory, Washington, DC 20375, USA
| | - Ioana Triandaf
- Nonlinear Dynamical Systems, Naval Research Laboratory, Washington, DC 20375, USA
| | - Ira B Schwartz
- Nonlinear Dynamical Systems, Naval Research Laboratory, Washington, DC 20375, USA
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Hindes J, Edwards V, Kamimoto S, Triandaf I, Schwartz IB. Unstable modes and bistability in delay-coupled swarms. Phys Rev E 2020; 101:042202. [PMID: 32422704 DOI: 10.1103/physreve.101.042202] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 03/12/2020] [Indexed: 06/11/2023]
Abstract
It is known that introducing time delays into the communication network of mobile-agent swarms produces coherent rotational patterns, from both theory and experiments. Often such spatiotemporal rotations can be bistable with other swarming patterns, such as milling and flocking. Yet, most known bifurcation results related to delay-coupled swarms rely on inaccurate mean-field techniques. As a consequence, the utility of applying macroscopic theory as a guide for predicting and controlling swarms of mobile robots has been limited. To overcome this limitation, we perform an exact stability analysis of two primary swarming patterns in a general model with time-delayed interactions. By correctly identifying the relevant spatiotemporal modes, we are able to accurately predict unstable oscillations beyond the mean-field dynamics and bistability in large swarms-laying the groundwork for comparisons to robotics experiments.
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Affiliation(s)
- Jason Hindes
- U.S. Naval Research Laboratory, Code 6792, Plasma Physics Division, Washington, DC 20375, USA
| | - Victoria Edwards
- U.S. Naval Research Laboratory, Code 5514, Navy Center for Applied Research in Artificial Intelligence, Washington, DC 20375, USA
| | - Sayomi Kamimoto
- Department of Mathematics, George Mason University, Fairfax, Virginia 22030, USA
| | - Ioana Triandaf
- U.S. Naval Research Laboratory, Code 6792, Plasma Physics Division, Washington, DC 20375, USA
| | - Ira B Schwartz
- U.S. Naval Research Laboratory, Code 6792, Plasma Physics Division, Washington, DC 20375, USA
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Kaminker V, Wackerbauer R. Alternating activity patterns and a chimeralike state in a network of globally coupled excitable Morris-Lecar neurons. CHAOS (WOODBURY, N.Y.) 2019; 29:053121. [PMID: 31154794 DOI: 10.1063/1.5093483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Accepted: 04/30/2019] [Indexed: 06/09/2023]
Abstract
Spatiotemporal chaos collapses to either a rest state or a propagating pulse in a ring network of diffusively coupled, excitable Morris-Lecar neurons. Adding global varying synaptic coupling to the ring network reveals complex transient behavior. Spatiotemporal chaos collapses into a transient pulse that reinitiates spatiotemporal chaos to allow sequential pattern switching until a collapse to the rest state. A domain of irregular neuron activity coexists with a domain of inactive neurons forming a transient chimeralike state. Transient spatial localization of the chimeralike state is observed for stronger synapses.
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Affiliation(s)
- Vitaliy Kaminker
- Department of Physics, University of Alaska, Fairbanks, Alaska 99775-5920, USA
| | - Renate Wackerbauer
- Department of Physics, University of Alaska, Fairbanks, Alaska 99775-5920, USA
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Gambino G, Lombardo MC, Sammartino M. Cross-diffusion-induced subharmonic spatial resonances in a predator-prey system. Phys Rev E 2018; 97:012220. [PMID: 29448421 DOI: 10.1103/physreve.97.012220] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2017] [Indexed: 06/08/2023]
Abstract
In this paper we investigate the complex dynamics originated by a cross-diffusion-induced subharmonic destabilization of the fundamental subcritical Turing mode in a predator-prey reaction-diffusion system. The model we consider consists of a two-species Lotka-Volterra system with linear diffusion and a nonlinear cross-diffusion term in the predator equation. The taxis term in the search strategy of the predator is responsible for the onset of complex dynamics. In fact, our model does not exhibit any Hopf or wave instability, and on the basis of the linear analysis one should only expect stationary patterns; nevertheless, the presence of the nonlinear cross-diffusion term is able to induce a secondary instability: due to a subharmonic spatial resonance, the stationary primary branch bifurcates to an out-of-phase oscillating solution. Noticeably, the strong resonance between the harmonic and the subharmonic is able to generate the oscillating pattern albeit the subharmonic is below criticality. We show that, as the control parameter is varied, the oscillating solution (subT mode) can undergo a sequence of secondary instabilities, generating a transition toward chaotic dynamics. Finally, we investigate the emergence of subT-mode solutions on two-dimensional domains: when the fundamental mode describes a square pattern, subharmonic resonance originates oscillating square patterns. In the case of subcritical Turing hexagon solutions, the internal interactions with a subharmonic mode are able to generate the so-called "twinkling-eyes" pattern.
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Affiliation(s)
- G Gambino
- Department of Mathematics, University of Palermo, via Archirafi 34, 90123 Palermo, Italy
| | - M C Lombardo
- Department of Mathematics, University of Palermo, via Archirafi 34, 90123 Palermo, Italy
| | - M Sammartino
- DIID, University of Palermo, Viale delle Scienze, Ed. 8, 90128 Palermo, Italy
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