Nonlinear Modeling of Neural Interaction for Spike Prediction Using the Staged Point-Process Model

DOI10.1162/neco_a_01137zbMath1472.92039OpenAlexW2897103715WikidataQ57472001 ScholiaQ57472001MaRDI QIDQ5157274

Xiao-Xiang Zheng, Gang Pan, Hong-Bao Li, Xuyun Sun, Shaomin Zhang, Cunle Qian, Dong Xing, Yi Wen Wang

Publication date: 12 October 2021

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

Full work available at URL: https://doi.org/10.1162/neco_a_01137

zbMATH Keywords

point processesgeneralized linear modelneuronal communicationspike prediction

Mathematics Subject Classification ID

Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (1)

Binless Kernel Machine: Modeling Spike Train Transformation for Cognitive Neural Prostheses

Uses Software

• ElemStatLearn
• PRMLT

Cites Work

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• The Time-Rescaling Theorem and Its Application to Neural Spike Train Data Analysis
• Generalized linear models
• Maximum likelihood analysis of spike trains of interacting nerve cells
• PRMLT
• Spike-triggered covariance: geometric proof, symmetry properties, and extension beyond Gaussian stimuli
• Robustness of neuroprosthetic decoding algorithms
• A simple white noise analysis of neuronal light responses
• Discrete Time Rescaling Theorem: Determining Goodness of Fit for Discrete Time Statistical Models of Neural Spiking
• Sequential Monte Carlo Point-Process Estimation of Kinematics from Neural Spiking Activity for Brain-Machine Interfaces
• Identifying Functional Connectivity in Large-Scale Neural Ensemble Recordings: A Multiscale Data Mining Approach
• An Algorithm for Least-Squares Estimation of Nonlinear Parameters
• Robust regression using iteratively reweighted least-squares
• Spiking Neuron Models
• Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions
• Mechanism-Based and Input-Output Modeling of the Key Neuronal Connections and Signal Transformations in the CA3-CA1 Regions of the Hippocampus
• Sufficiency and Exponential Families for Discrete Sample Spaces
• Analyzing Functional Connectivity Using a Network Likelihood Model of Ensemble Neural Spiking Activity
• A method for the solution of certain non-linear problems in least squares
• Approximation by superpositions of a sigmoidal function
• The elements of statistical learning. Data mining, inference, and prediction

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