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Traveling chimera states by weak temporal couplings
Wenbin Mao1, Guoshen Liang1, Zonghua Liu1
1East China Normal University, School of Physics and Electronic Science, Shanghai 200241, People's Republic of China.
Physical Review. E
|June 19, 2025
Summary
A neural model reveals how pacemaker loops influence brain rhythms during rest. It demonstrates sensitive switching between chimera states, offering insights into rapid brain state transitions.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Complex Systems
Background:
- Self-sustained oscillations in brain rhythms are crucial, with pacemaker loops playing a key role.
- The precise function of pacemaker loops in the resting state, characterized by multi-scaled slow-wave activity and dynamic state switching, remains unclear.
Purpose of the Study:
- To investigate the role of pacemaker loops in generating complex dynamics within the resting state of the brain.
- To explore how network coupling influences brain rhythm dynamics and state transitions.
Main Methods:
- Development of a neural model simulating a pacemaker loop-like network with weak temporal electrical coupling.
- Analysis of emergent dynamics, including disorder, traveling chimera states, chimera states, and synchronization.
- Introduction and application of an index Q to quantify local order parameter fluctuations.
Main Results:
- The model generates diverse dynamic patterns: disorder, traveling chimera, chimera, and synchronization.
- A sensitive switching phenomenon between traveling chimera and chimera states was observed.
- Index Q confirmed a new regularity related to local order parameter fluctuations, dependent on parameter matching.
- The traveling chimera state demonstrated robustness against variations in temporal coupling.
Conclusions:
- Pacemaker loop networks can exhibit complex dynamics relevant to brain resting states.
- The observed sensitive switching may explain rapid transitions between brain rhythms.
- The index Q provides a novel measure for understanding network fluctuations and underlying regularities.
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