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Updated: Jul 18, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Effects of degree distribution in mutual synchronization of neural networks
Sheng-Jun Wang1, Xin-Jian Xu, Zhi-Xi Wu
1Institute of Theoretical Physics, Lanzhou University, Lanzhou Gansu 730000, China.
Abstract:
We study the effects of the degree distribution in mutual synchronization of two-layer neural networks. We carry out three coupling strategies: large-large coupling, random coupling, and small-small coupling. By computer simulations and analytical methods, we find that couplings between nodes with large degree play an important role in the synchronization. For large-large coupling, less couplings are needed for inducing synchronization for both random and scale-free networks. For random coupling, cutting couplings between nodes with large degree is very efficient for preventing neural systems from synchronization, especially when subnetworks are scale free.
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