Spike-triggered covariance: geometric proof, symmetry properties, and extension beyond Gaussian stimuli

DOI10.1007/s10827-012-0411-yzbMath1387.92023DBLPjournals/jcns/SamengoG13OpenAlexW2155443738WikidataQ43068576 ScholiaQ43068576MaRDI QIDQ1746818

Inés Samengo, Tim Gollisch

Publication date: 26 April 2018

Published in: Journal of Computational Neuroscience (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10827-012-0411-y

zbMATH Keywords

covariance analysisreceptive fieldlinear-nonlinear modelspike-triggered average

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural biology (92C20)

Related Items (5)

Linking dynamical and functional properties of intrinsically bursting neurons ⋮ Identifying Functional Bases for Multidimensional Neural Computations ⋮ Time- and frequency-resolved covariance analysis for detection and characterization of seizures from intracraneal EEG recordings ⋮ Effects of spike-triggered negative feedback on receptive-field properties ⋮ Nonlinear Modeling of Neural Interaction for Spike Prediction Using the Staged Point-Process Model

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