Neuronal morphology and network topology modulate weak-signal responses in single neurons and small-world networks

Studying stochastic resonance (SR) and its associated energy consumption is essential for understanding the mechanisms underlying neural information processing and transmission. In this work, the two-compartment model was used to investigate the influence of neuronal morphology and network properties on the detection and transmission of weak signals and the corresponding energy consumption. Transmitting weak signals requires an appropriate noise intensity, and weak signals with higher intensity and lower frequency are more easily detected by neurons. It is shown that neurons with larger dendrites can respond more effectively to weak signals. In small-world networks, neural networks composed of neurons with large dendrites are more sensitive to weak signals. Under specific conditions, the regular connectivity of the networks weakens the response to weak signals. The results of this study may contribute to a better understanding of information processing in the nervous system and the energy regulation involved in this process.