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Open AccessArticle

How Neuronal Noises Influence the Spiking Neural Networks’s Cognitive Learning Process: A Preliminary Study

School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
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Academic Editor: Yvonne Höller
Brain Sci. 2021, 11(2), 153; https://doi.org/10.3390/brainsci11020153
Received: 8 December 2020 / Revised: 19 January 2021 / Accepted: 22 January 2021 / Published: 25 January 2021
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
In neuroscience, the Default Mode Network (DMN), also known as the default network or the default-state network, is a large-scale brain network known to have highly correlated activities that are distinct from other networks in the brain. Many studies have revealed that DMNs can influence other cognitive functions to some extent. This paper is motivated by this idea and intends to further explore on how DMNs could help Spiking Neural Networks (SNNs) on image classification problems through an experimental study. The approach emphasizes the bionic meaning on model selection and parameters settings. For modeling, we select Leaky Integrate-and-Fire (LIF) as the neuron model, Additive White Gaussian Noise (AWGN) as the input DMN, and design the learning algorithm based on Spike-Timing-Dependent Plasticity (STDP). Then, we experiment on a two-layer SNN to evaluate the influence of DMN on classification accuracy, and on a three-layer SNN to examine the influence of DMN on structure evolution, where the results both appear positive. Finally, we discuss possible directions for future works. View Full-Text
Keywords: spiking neural network; neuronal noise; cognitive function spiking neural network; neuronal noise; cognitive function
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MDPI and ACS Style

Liu, J.; Yang, X.; Zhu, Y.; Lei, Y.; Cai, J.; Wang, M.; Huan, Z.; Lin, X. How Neuronal Noises Influence the Spiking Neural Networks’s Cognitive Learning Process: A Preliminary Study. Brain Sci. 2021, 11, 153. https://doi.org/10.3390/brainsci11020153

AMA Style

Liu J, Yang X, Zhu Y, Lei Y, Cai J, Wang M, Huan Z, Lin X. How Neuronal Noises Influence the Spiking Neural Networks’s Cognitive Learning Process: A Preliminary Study. Brain Sciences. 2021; 11(2):153. https://doi.org/10.3390/brainsci11020153

Chicago/Turabian Style

Liu, Jing; Yang, Xu; Zhu, Yimeng; Lei, Yunlin; Cai, Jian; Wang, Miao; Huan, Ziyi; Lin, Xialv. 2021. "How Neuronal Noises Influence the Spiking Neural Networks’s Cognitive Learning Process: A Preliminary Study" Brain Sci. 11, no. 2: 153. https://doi.org/10.3390/brainsci11020153

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