Spike-triggered covariance: geometric proof, symmetry properties, and extension beyond Gaussian stimuli
type: Item
instance of: scholarly article
title: Spike-triggered covariance: geometric proof, symmetry properties, and extension beyond Gaussian stimuli
zbMATH Open document ID: 1387.92023
author: Inés Samengo
author: Tim Gollisch
published in: Journal of Computational Neuroscience
publication date: 2018-04-26T00:00:00Z
Mathematics Subject Classification ID: 92C20
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 6864794
zbMATH Keywords: covariance analysis
zbMATH Keywords: spike-triggered average
zbMATH Keywords: receptive field
zbMATH Keywords: linear-nonlinear model
Wikidata QID: Q43068576
MaRDI profile type: Publication
full work available at URL: s10827-012-0411-y
OpenAlex ID: W2155443738
cites work: What Causes a Neuron to Spike?
cites work: Computation in a Single Neuron: Hodgkin and Huxley Revisited
cites work: A simple white noise analysis of neuronal light responses
cites work: Effects of stimulus transformations on estimates of sensory neuron selectivity
cites work: Modeling convergent ON and OFF pathways in the early visual system
cites work: Identification of nonlinear systems using random impulse train inputs
cites work: A family of quasi-white random signals and its optimal use in biological system identification. I: Theory
cites work: Type I and Type II Neuron Models Are Selectively Driven by Differential Stimulus Features
cites work: Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model
cites work: A theory of non-linear system identification
cites work: Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions
cites work: Q4532680
cites work: Q5569073
cites work: Nonlinear analysis with an arbitrary stimulus ensemble
cites work: Q3256710
cites work: Q5732117
DBLP publication ID: journals/jcns/SamengoG13
DOI: 10.1007/S10827-012-0411-Y
description: scientific article; zbMATH DE number 6864794