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Enhancement of gamma oscillations in E/I neural networks by increase of difference between external inputs

  • Received: 01 December 2020 Revised: 01 March 2021 Published: 15 April 2021
  • Primary: 92B20, 92C20; Secondary: 92-10

  • Experimental observations suggest that gamma oscillations are enhanced by the increase of the difference between the components of external stimuli. To explain these experimental observations, we firstly construct a small excitatory/inhibitory (E/I) neural network of IAF neurons with external current input to E-neuron population differing from that to I-neuron population. Simulation results show that the greater the difference between the external inputs to excitatory and inhibitory neurons, the stronger gamma oscillations in the small E/I neural network. Furthermore, we construct a large-scale complicated neural network with multi-layer columns to explore gamma oscillations regulated by external stimuli which are simulated by using a novel CUDA-based algorithm. It is further found that gamma oscillations can be caused and enhanced by the difference between the external inputs in a large-scale neural network with a complicated structure. These results are consistent with the existing experimental findings well.

    Citation: Xiaochun Gu, Fang Han, Zhijie Wang, Kaleem Kashif, Wenlian Lu. Enhancement of gamma oscillations in E/I neural networks by increase of difference between external inputs[J]. Electronic Research Archive, 2021, 29(5): 3227-3241. doi: 10.3934/era.2021035

    Related Papers:

  • Experimental observations suggest that gamma oscillations are enhanced by the increase of the difference between the components of external stimuli. To explain these experimental observations, we firstly construct a small excitatory/inhibitory (E/I) neural network of IAF neurons with external current input to E-neuron population differing from that to I-neuron population. Simulation results show that the greater the difference between the external inputs to excitatory and inhibitory neurons, the stronger gamma oscillations in the small E/I neural network. Furthermore, we construct a large-scale complicated neural network with multi-layer columns to explore gamma oscillations regulated by external stimuli which are simulated by using a novel CUDA-based algorithm. It is further found that gamma oscillations can be caused and enhanced by the difference between the external inputs in a large-scale neural network with a complicated structure. These results are consistent with the existing experimental findings well.



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