Publication | Closed Access
Vibrational resonance in feedforward network
49
Citations
21
References
2011
Year
EngineeringNeural Networks (Machine Learning)Neural RecodingSocial SciencesVibrationsNeurodynamicsHigh-frequency StimuliPhysicsVibrational ResonanceFfn NetworkNeural Networks (Computational Neuroscience)Stochastic ResonanceComputational NeuroscienceMechanical SystemsNeuronal NetworkDouble ResonanceNeuroscienceBrain-like ComputingNonlinear ResonanceVibration Control
This paper investigates vibrational resonance in multi-layer feedforward network (FFN) based on FitzHugh-Nagumo (FHN) neuron model. High-frequency stimuli can improve the input-output linearity of firing rates, especially for the inputs with low firing rate. For FFN network, it is found that high-frequency disturbances play important roles in enhancing the propagation of weak signal through layers. Synfire-enhanced phenomenon of signal propagation is also observed in multi-layers network, when the signal transmission is affected by high-frequency disturbances. Network connections are found to be important for the propagation of weak signal. Besides that, the characteristics of high-frequency stimuli such as heterogeneity and frequency can also modulate the propagation of neural code through layers.
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