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Coupling parameter in synchronization of diluted neural networks
Qi Li1, Yong Chen, Ying Hai Wang
1Department of Physics, Lanzhou University, Gansu 730000, China.
Summary
This study explores neural network synchronization, revealing critical coupling parameters. Findings show specific coupling intensities are essential for synchronization in complex neural systems.
Area of Science:
- Computational neuroscience
- Complex systems analysis
- Network dynamics
Background:
- Neural networks exhibit complex dynamics crucial for brain function.
- Understanding synchronization is key to deciphering information processing in neural systems.
- Diluted synapses introduce heterogeneity, impacting network synchronization.
Purpose of the Study:
- To investigate the critical features of coupling parameters in neural network synchronization.
- To determine the influence of coupling intensity and fraction on synchronization.
- To analyze synchronization in spatially extended neural networks with diluted synapses.
Main Methods:
- Numerical simulations of neural network models.
- Analysis of synchronization phenomena under varying coupling conditions.
- Examination of critical coupling intensity and fraction thresholds.
Main Results:
- An exponential decay form characterizes critical coupling in globally coupled subsystems.
- A maximum and minimum critical coupling intensity for synchronization was identified.
- The critical coupling fraction was determined for partial coupling across different network linking degrees.
Conclusions:
- Coupling parameters critically influence neural network synchronization.
- Spatially extended systems exhibit distinct synchronization behaviors based on coupling.
- Results provide insights into the role of synaptic dilution in network dynamics.