Parameter Estimation in Multiple Dynamic Synaptic Coupling Model Using Bayesian Point Process State-Space Modeling Framework

DOI10.1162/neco_a_01375zbMath1469.92030OpenAlexW3132350608MaRDI QIDQ5004352

Behzad Nazari, Yalda Amidi, Saeid Sadri, Ali Yousefi

Publication date: 30 July 2021

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

Full work available at URL: https://doi.org/10.1162/neco_a_01375

Mathematics Subject Classification ID

Neural biology (92C20)

Uses Software

• bayesreg

Cites Work

• The Time-Rescaling Theorem and Its Application to Neural Spike Train Data Analysis
• Synaptic dynamics: linear model and adaptation algorithm
• Shrinkage priors for Bayesian penalized regression
• The Bayesian elastic net
• NONLINEAR DYNAMICAL SYSTEM IDENTIFICATION FROM UNCERTAIN AND INDIRECT MEASUREMENTS
• Estimating a State-Space Model from Point Process Observations
• Dynamic Analysis of Neural Encoding by Point Process Adaptive Filtering
• Fisher information and stochastic complexity
• A combined method to estimate parameters of neuron from a heavily noise-corrupted time series of active potential
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