System identification based on point processes and correlation densities. I: The nonrefractory neuron model

DOI10.1016/0025-5564(86)90042-8zbMath0613.92013OpenAlexW2108298694MaRDI QIDQ1820087

Gerard H. F. M. Hesselmans, Henk F. P. van den Boogaard, Peter I. M. Johannesma

Publication date: 1986

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0025-5564(86)90042-8

zbMATH Keywords

computer simulationslinear filtersoutput point processinput point processesinput-output crosscorrelationnonrefractory neuron modeloutput autocorrelation

Mathematics Subject Classification ID

Signal detection and filtering (aspects of stochastic processes) (60G35) Identification in stochastic control theory (93E12) Physiological, cellular and medical topics (92Cxx)

Related Items (8)

Maximum likelihood estimations in a nonlinear self-exciting point process model ⋮ Sensory interpretation of neural activity patterns ⋮ Maximum likelihood analysis of spike trains of interacting nerve cells ⋮ System identification based on point processes and correlation densities. II. The refractory neuron model ⋮ Spectro-temporal interpretation of activity patterns of auditory neurons ⋮ On the significance of correlations among neuronal spike trains ⋮ Minimum mean square error estimation of connectivity in biological neural networks ⋮ The characteristic functional of the peri-event stimulus ensemble

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