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Recurrence-Based Synchronization Analysis of Weakly Coupled Bursting Neurons under External ELF Fields
Aissatou Mboussi Nkomidio1, Eulalie Ketchamen Ngamga2, Blaise Romeo Nana Nbendjo1
1Laboratory of Modelling and Simulation in Engineering, Biomimetics and Prototypes, Faculty of Sciences, University of Yaoundé I, Yaoundé 812, Cameroon.
Entropy (Basel, Switzerland)
|February 25, 2022
Summary
Neurons exposed to extremely low frequency (ELF) electric fields show varied spiking patterns. Recurrence analysis reveals that ELF fields enhance phase synchronization in weakly coupled neurons, even with a novel synchronization measure.
Area of Science:
- Computational Neuroscience
- Biophysics
- Nonlinear Dynamics
Background:
- Neurons exhibit complex spiking patterns influenced by external stimuli.
- Synchronization is crucial for neural function but challenging to analyze in chaotic systems.
- Extremely low frequency (ELF) electric fields are ubiquitous and can affect biological systems.
Purpose of the Study:
- To investigate neuron model responses to ELF electric fields.
- To analyze synchronization dynamics in weakly coupled neurons under ELF field influence.
- To introduce a novel recurrence plot-based measure for phase synchronization.
Main Methods:
- Numerical simulations of a 2D neuron model.
- Recurrence plot (RP) analysis to characterize spiking patterns.
- Recurrence-based synchronization analysis for coupled neurons.
Main Results:
- Neurons display diverse spiking patterns observable via RP structure.
- Phase synchronization is detected in weakly coupled neurons, even in chaotic regimes.
- ELF electric fields increase phase synchronization proportionally to field amplitude.
- A novel RP-based measure improves phase synchronization analysis.
Conclusions:
- RP analysis is a robust tool for phase detection in complex neural signals.
- ELF electric fields can modulate and enhance neural synchronization.
- The proposed RP-based measure offers a more sensitive approach to synchronization analysis.
