Stochastic resonance in the small-world networks with higher order neural motifs interactions

• Published in: The European physical journal. ST, Special topics Special topics, 2024, Vol.233 (4), p.797-806
• Main Authors: Li, Tianyu, Yu, Dong, Wu, Yong, Ding, Qianming, Jia, Ya
• Format: Article
• Language: English
• Subjects: Atomic; Classical and Continuum Physics; Condensed Matter Physics; Coupling; Materials Science; Measurement Science and Instrumentation; Molecular; Network topologies; Neural networks; Neurons; Optical and Plasma Physics; Physics; Physics and Astronomy; Regular Article; Routes to Synchronization and Collective Behavior in Higher-Order Networks; Stochastic resonance
• ISSN: 1951-6355; 1951-6401
• DOI: 10.1140/epjs/s11734-024-01139-w

Transmission of weak signals in neural networks is crucial for understanding the functionality of brain. In this work, stochastic resonance (SR) in the three neuron FitzHugh–Nagumo (FHN) motifs and its small-world network with higher order motif interactions are studied. Simulation results show that a single motif induces SR and responds better to high-frequency weak signal. Stronger coupling strength within the motif increases the firing rate of the output neurons, resulting in a more pronounced resonance. Considering only the connections within the motif, a higher in-degree of the output neuron or a shorter minimum path length between input and output neurons will lead to a better response to weak signals. SR phenomena can also be observed in small-world networks composed of these motif. Increasing whether the motif coupling or node coupling strength enhances the firing rate of output neurons, amplifying the response. There is a very strong correlation between firing rate of output neurons and response. Our results may provide insights into the propagation of weak signals in higher order networks and the selection of appropriate network topology.