An Empirical Model for Reliable Spiking Activity

DOI10.1162/NECO_a_00754zbMath1414.92124OpenAlexW2193238454WikidataQ40288928 ScholiaQ40288928MaRDI QIDQ5380296

Nathaniel N. Urban, Robert E. Kass, Wanjie Wang, Krishnan Padmanabhan, Shreejoy J. Tripathy

Publication date: 4 June 2019

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

Full work available at URL: https://doi.org/10.1162/neco_a_00754

zbMATH Keywords

neuron's transfer functionreliable spiking activity

Mathematics Subject Classification ID

Neural biology (92C20)

Uses Software

• ElemStatLearn

Cites Work

• Extracting nonlinear integrate-and-fire models from experimental data using dynamic \(I-V\) curves
• Analysis of neural data
• A Spike-Train Probability Model
• Hidden Markov Models for the Stimulus-Response Relationships of Multistate Neural Systems
• Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model
• Computation in a Single Neuron: Hodgkin and Huxley Revisited
• What Causes a Neuron to Spike?
• The elements of statistical learning. Data mining, inference, and prediction
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