Coupling resonance of signal responses induced by heterogeneously mixed positive and negative couplings in cognitive subnetworks

Liyuan Deng, Siyu Huo, Aihua Chen and Zonghua Liu

Chaos, Solitons & Fractals, 2024, vol. 180, issue C

Abstract: How weak external signals are detected in cognitive subnetworks is one of the key problems to understand how brain functions work. So far, most studies on signal responses are focused on artificial complex networks and it is found that a topological resonance can be induced by the feature of scale-free networks, but little attention has been paid to real brain networks, especially the cognitive subnetworks responsible for signal responses. Herein we address this problem in real brain networks but do not find such a topological resonance, indicating that scale-free is not the key feature of brain networks. Surprisingly, we find a novel resonance effect of signal response induced by heterogeneously mixed positive and negative couplings and thus name it as coupling resonance of signal responses, which explains the mechanism of how brain networks, especially the cognitive subnetworks, detects weak signals. We investigate this coupling resonance in the cases of both heterogeneous couplings and heterogeneous oscillators and find that there is an optimal phenomenon on both the average and standard deviation of coupling strengths. Further, we confirm this coupling resonance in real cognitive subnetworks with weighted links. Finally, we provide a theoretical analysis to show that this coupling resonant comes from the coexistence of the two different local states of neighboring nodes.

Keywords: Signal responses; Brain networks; Cognitive subnetworks; Coupling resonance; Weighted connections; Subthreshold signals (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:180:y:2024:i:c:s0960077924000560

DOI: 10.1016/j.chaos.2024.114505

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