Study on the anti-interference characteristics of neuronal networks : a comparative study of chemical synapses and electrical synapses

Xiang LiMai Lu^*

• Lanzhou Jiaotong University, Lanzhou, China

The synapses and network topology enhance neural synchronization and anti-interference, enabling bio-inspired brain model to mimic biological noise resilience effectively. This study numerically simulate the effects of synapses and network topology on the synchronous discharge and anti-interference of neuronal networks. The Hodgkin-Huxley neuron model, the electrical synapses (ES), Hansel chemical synapse (HS), and Rabinovich chemical synapse (RS) were used to construct the neural networks with the ring structure and the Newman-Watts (NW) small-world topology. The sine wave and the sine wave with superimposed Gaussian white noise interference were selected as the stimulation signals. The MATLAB & Simulink platform was employed to implement the numerical simulation. For the ring network with the sine wave stimulation, the correlation coefficients of one set of neuron pair (neuron 1 and neuron 25) were 0.292 (ES), 0.236 (HS), and 0.168 (RS), respectively. However, after superimposed interference, the correlation coefficients becomes 0.099, 0.086, and 0.379, respectively. For the NW small-world topology with sinusoidal stimulation, the correlation coefficients of the same neuron pair were 0.569 (ES), 0.563 (HS), and 0.969 (RS), respectively. The correlation coefficients after superposition interference becomes 0.569, 0.163 and 0.88, respectively. The HS coupled network exhibit severe signal latency (Ring network: Latency >200 ms, NW small-world network: Latency >150ms). While RS coupled network demonstrates dramatically reduced delays (<50 ms) across both topologies. The results suggest the synchronization of RS coupling network is much better than that by both ES and HS coupling networks. Ring network coupled via HS demonstrate performance metrics comparable to those of ES coupled ring networks, albeit with significant action potential propagation delays observed in both configurations. The NW small-world network can reduce the delay of signal transmission in the network by increasing the number of pathways. As network topological complexity increases, distal neurons demonstrate reduced spike timing variability and enhanced firing synchrony, collectively improving interference suppression efficacy.