The passive properties of dendrites modulate the propagation of slowly-varying firing rate in feedforward networks

DOI10.1016/J.NEUNET.2022.03.001zbMath1528.92009OpenAlexW4220855970MaRDI QIDQ6072586

Jixuan Wang, Tianshi Gao, Jiang Wang, Bin Deng, Guosheng Yi

Publication date: 13 October 2023

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2022.03.001

zbMATH Keywords

dendritefeedforward neural networktwo-compartment modelinformation propagationtime-varying spiking activity

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20)

Cites Work

• Local excitation-inhibition ratio for synfire chain propagation in feed-forward neuronal networks
• A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input
• Intrinsic excitability state of local neuronal population modulates signal propagation in feed-forward neural networks
• Passive Nonlinear Dendritic Interactions as a Computational Resource in Spiking Neural Networks
• Coding of Temporally Varying Signals in Networks of Spiking Neurons with Global Delayed Feedback
• Unnamed Item

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