Vibrational resonance in a randomly connected neural network

Yingmei Qin, Chunxiao Han, Yanqiu Che, Jia Zhao

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

A randomly connected network is constructed with similar characteristics (e.g., the ratio of excitatory and inhibitory neurons, the connection probability between neurons, and the axonal conduction delays) as that in the mammalian neocortex and the effects of high-frequency electrical field on the response of the network to a subthreshold low-frequency electrical field are studied in detail. It is found that both the amplitude and frequency of the high-frequency electrical field can modulate the response of the network to the low-frequency electric field. Moreover, vibrational resonance (VR) phenomenon induced by the two types of electrical fields can also be influenced by the network parameters, such as the neuron population, the connection probability between neurons and the synaptic strength. It is interesting that VR is found to be related with the ratio of excitatory neurons that are under high-frequency electrical stimuli. In summary, it is suggested that the interaction of excitatory and inhibitory currents is also an important factor that can influence the performance of VR in neural networks.

Original languageEnglish (US)
Pages (from-to)509-518
Number of pages10
JournalCognitive Neurodynamics
Volume12
Issue number5
DOIs
StatePublished - Oct 1 2018

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience

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