TY - GEN
T1 - Effect of inhibitory firing patterns on the stochastic resonance in feed-forward-loop neuronal network motifs
AU - Liu, Shan
AU - Guo, Xinmeng
AU - Yi, Guosheng
AU - Song, Zhenxi
AU - Wang, Jiang
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Neurons express diverse firing patterns in terms of their morphological, biochemical and electrophysiological properties. Different firing patterns can switch the information transmission in neuron network. However, it is not clear how the firing patterns of the neurons affect information transmission. Here we investigate the effect of different firing patterns of inhibitory neuron on network information transmission of triple-neuron feed-forward-loop motif. Results show that the stochastic response behavior can be optimized by certain noise intensity, which indicates stochastic resonance (SR) occurs in the neuronal network motifs. Changing the inhibitory neuron from burst spiking neurons to fast spiking neurons does not affect the optimal noise intensity. In the case of the same noise intensity and coupling coefficient, the bursting neurons produce higher transmission efficiency than the fast firing neurons. Different firing patterns of neuron in the output of the network motif achieved a greater impact on the transmission efficiency of the motif than the neuron located in the middle position. This simulation directly quantifies the influence of firing patterns on information transmission, which has great significance for improving signal transmission efficiency and detecting signals at different operating points.
AB - Neurons express diverse firing patterns in terms of their morphological, biochemical and electrophysiological properties. Different firing patterns can switch the information transmission in neuron network. However, it is not clear how the firing patterns of the neurons affect information transmission. Here we investigate the effect of different firing patterns of inhibitory neuron on network information transmission of triple-neuron feed-forward-loop motif. Results show that the stochastic response behavior can be optimized by certain noise intensity, which indicates stochastic resonance (SR) occurs in the neuronal network motifs. Changing the inhibitory neuron from burst spiking neurons to fast spiking neurons does not affect the optimal noise intensity. In the case of the same noise intensity and coupling coefficient, the bursting neurons produce higher transmission efficiency than the fast firing neurons. Different firing patterns of neuron in the output of the network motif achieved a greater impact on the transmission efficiency of the motif than the neuron located in the middle position. This simulation directly quantifies the influence of firing patterns on information transmission, which has great significance for improving signal transmission efficiency and detecting signals at different operating points.
UR - https://www.scopus.com/pages/publications/85062488247
U2 - 10.1109/WCICA.2018.8630427
DO - 10.1109/WCICA.2018.8630427
M3 - 会议稿件
AN - SCOPUS:85062488247
T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
SP - 76
EP - 81
BT - Proceedings of the 2018 13th World Congress on Intelligent Control and Automation, WCICA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th World Congress on Intelligent Control and Automation, WCICA 2018
Y2 - 4 July 2018 through 8 July 2018
ER -