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Updated: Mar 27, 2026
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Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
Published on: June 24, 2015
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Explosive synchronization in networks of type-I neurons with electrical synapses
1Department of Physics, BITS Pilani K K Birla Goa Campus, Zuarinagar, Goa 403726, India.
Chaos (Woodbury, N.Y.)
|March 25, 2026
Summary
Explosive synchronization (ES) is now observed in type-I neurons, a significant finding for neuronal network dynamics. This study reveals conditions for ES in Quadratic Integrate and Fire and Morris-Lecar neurons, expanding on the Kuramoto model.
Area of Science:
- Computational Neuroscience
- Complex Systems
- Theoretical Physics
Background:
- Explosive synchronization (ES) is a phenomenon observed in coupled oscillator systems.
- Previous studies of ES were primarily limited to the Kuramoto model and specific oscillator types.
- Investigating ES in neuronal networks is crucial for understanding brain function but remains underexplored.
Purpose of the Study:
- To investigate the occurrence of explosive synchronization (ES) in networks of type-I neurons.
- To determine if conditions inducing ES in the Kuramoto model are applicable to type-I neurons.
- To explore ES in specific neuronal models like Quadratic Integrate and Fire (QIF) and Morris-Lecar neurons.
Main Methods:
- Utilized a mapping between weakly heterogeneous type-I neurons and the Kuramoto model under weak coupling.
- Simulated networks of QIF neurons and type-I Morris-Lecar neurons with electrical synapses.
- Examined scale-free and star network topologies with complete and partial degree-frequency correlations.
Main Results:
- Demonstrated explosive synchronization (ES) in networks of QIF neurons under weak heterogeneity.
- Extended the observation of ES to networks of type-I Morris-Lecar neurons under similar conditions.
- Confirmed that ES can occur in type-I neurons near saddle-node on invariant circle (SNIC) bifurcation.
Conclusions:
- This work establishes conditions for explosive synchronization (ES) in type-I neurons, particularly those near SNIC bifurcation.
- The findings generalize ES phenomena from abstract oscillator models to more biologically relevant neuronal networks.
- Suggests potential mechanisms for rapid network state transitions in the brain.
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