On a framework of data assimilation for hyperparameter estimation of spiking neuronal networks

DOI10.1016/J.NEUNET.2023.11.016arXiv2206.02986OpenAlexW4388598934MaRDI QIDQ6193255

Wenyong Zhang, Boyu Chen, Wenlian Lu, Jian-Feng Feng

Publication date: 13 February 2024

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

Full work available at URL: https://arxiv.org/abs/2206.02986

zbMATH Keywords

data assimilationhierarchical Bayesian estimationblood oxygen level dependent signalshierarchical data assimilationLeaky integral-fired Neuron model

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Medical applications (general) (92C50) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Computational aspects of data analysis and big data (68T09)

Cites Work

• Predicting the future. Completing models of observed complex systems
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• A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input
• Particle filters and Bayesian inference in financial econometrics
• Emergence of Scaling in Random Networks
• Data Assimilation
• Collective dynamics of ‘small-world’ networks
• Non-linear filtering by approximation of the a posteriori density
• A logical calculus of the ideas immanent in nervous activity

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