Cargando…

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

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 cogn...

Descripción completa

Detalles Bibliográficos
Autores principales:	Liu, Jing, Yang, Xu, Zhu, Yimeng, Lei, Yunlin, Cai, Jian, Wang, Miao, Huan, Ziyi, Lin, Xialv
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7911228/ https://www.ncbi.nlm.nih.gov/pubmed/33503833 http://dx.doi.org/10.3390/brainsci11020153

Ejemplares similares

Evaluation of the Effect of the Dynamic Behavior and Topology Co-Learning of Neurons and Synapses on the Small-Sample Learning Ability of Spiking Neural Network
por: Yang, Xu, et al.
Publicado: (2022)

Adaptive Neural Network Structure Optimization Algorithm Based on Dynamic Nodes
por: Wang, Miao, et al.
Publicado: (2022)

Shifting Spike Times or Adding and Deleting Spikes—How Different Types of Noise Shape Signal Transmission in Neural Populations
por: Voronenko, Sergej O, et al.
Publicado: (2015)

Constructing an Associative Memory System Using Spiking Neural Network
por: He, Hu, et al.
Publicado: (2019)

The Effect of Neural Noise on Spike Time Precision in a Detailed CA3 Neuron Model
por: Kuriscak, Eduard, et al.
Publicado: (2012)

Neuronal spike-train responses in the presence of threshold noise
por: Coombes, S., et al.
Publicado: (2012)

Noise-enhanced coding in phasic neuron spike trains
por: Ly, Cheng, et al.
Publicado: (2017)

Noise suppression ability and its mechanism analysis of scale-free spiking neural network under white Gaussian noise
por: Guo, Lei, et al.
Publicado: (2020)

Inhibition of rhythmic neural spiking by noise: the occurrence of a minimum in activity with increasing noise
por: Gutkin, Boris S., et al.
Publicado: (2009)

A Low Noise Amplifier for Neural Spike Recording Interfaces
por: Ruiz-Amaya, Jesus, et al.
Publicado: (2015)

Optimal spike pattern v.s. noise separation by neurons equipped with STDP
por: Masquelier, Timothée, et al.
Publicado: (2013)

Coherent noise enables probabilistic sequence replay in spiking neuronal networks
por: Bouhadjar, Younes, et al.
Publicado: (2023)

Signal-to-noise ratio of binned spike-counts and the timescales of neural coding
por: Zacksenhouse, Miriam, et al.
Publicado: (2010)

Exploiting noise as a resource for computation and learning in spiking neural networks
por: Ma, Gehua, et al.
Publicado: (2023)

Implementing Signature Neural Networks with Spiking Neurons
por: Carrillo-Medina, José Luis, et al.
Publicado: (2016)

Noise Enhancement of Neural Information Processing
por: Destexhe, Alain
Publicado: (2022)

Lateral Information Processing by Spiking Neurons: A Theoretical Model of the Neural Correlate of Consciousness
por: Ebner, Marc, et al.
Publicado: (2011)

Decision-making in a population of spiking neurons shaped by dynamics of intrinsic noise
por: Richardson, Lydia, et al.
Publicado: (2014)

Impacts of clustering on noise-induced spiking regularity in the excitatory neuronal networks of subnetworks
por: Li, Huiyan, et al.
Publicado: (2015)

Structured chaos shapes spike-response noise entropy in balanced neural networks
por: Lajoie, Guillaume, et al.
Publicado: (2014)

Anti-Disturbance of Scale-Free Spiking Neural Network against Impulse Noise
por: Guo, Lei, et al.
Publicado: (2023)

Signal Processing for Neural Spike Trains
por: Berger, Theodore W., et al.
Publicado: (2010)

Spike Timing and Reliability in Cortical Pyramidal Neurons: Effects of EPSC Kinetics, Input Synchronization and Background Noise on Spike Timing
por: Rodriguez-Molina, Victor M., et al.
Publicado: (2007)

A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains
por: Sidhu, Robin S., et al.
Publicado: (2022)

Neural Code—Neural Self-information Theory on How Cell-Assembly Code Rises from Spike Time and Neuronal Variability
por: Li, Meng, et al.
Publicado: (2017)

Spiking Neural P Systems with Neuron Division and Dissolution
por: Zhao, Yuzhen, et al.
Publicado: (2016)

Weak Noise in Neurons May Powerfully Inhibit the Generation of Repetitive Spiking but Not Its Propagation
por: Tuckwell, Henry C., et al.
Publicado: (2010)

Self-organized noise resistance of oscillatory neural networks with spike timing-dependent plasticity
por: Popovych, Oleksandr V., et al.
Publicado: (2013)

Does noise shift or delete spikes?
por: Voronenko, Sergej, et al.
Publicado: (2013)

Noise-induced speed up in repetitively firing neurons occurs far from spike threshold
por: Troyer, Todd W, et al.
Publicado: (2014)

Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment
por: Legenstein, Robert, et al.
Publicado: (2014)

Optimal noise level for coding with tightly balanced networks of spiking neurons in the presence of transmission delays
por: Timcheck, Jonathan, et al.
Publicado: (2022)

A Functional Spiking Neural Network of Ultra Compact Neurons
por: Stoliar, Pablo, et al.
Publicado: (2021)

Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons
por: Yang, Geunbo, et al.
Publicado: (2023)

An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens
por: Ge, Hui, et al.
Publicado: (2021)

SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron
por: Mozafari, Milad, et al.
Publicado: (2019)

The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields
por: Deco, Gustavo, et al.
Publicado: (2008)

Neural pathway prediction based on multi-neuron spike train data
por: Zeng, Yi, et al.
Publicado: (2014)

Estimating the Parameters of Fitzhugh–Nagumo Neurons from Neural Spiking Data
por: Doruk, Resat Ozgur, et al.
Publicado: (2019)

Neuronal-Plasticity and Reward-Propagation Improved Recurrent Spiking Neural Networks
por: Jia, Shuncheng, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_nr18ei2jdfd9c2kbun30m1umbo