Statistical assessment of time-varying dependency between two neurons.
about
A Granger causality measure for point process models of ensemble neural spiking activityConditional modeling and the jitter method of spike resampling.Algorithms for the analysis of ensemble neural spiking activity using simultaneous-event multivariate point-process modelsTesting a neural coding hypothesis using surrogate dataData-driven significance estimation for precise spike correlationHierarchical Bayesian modeling and Markov chain Monte Carlo sampling for tuning-curve analysis.Cooperative and competitive interactions facilitate stereo computations in macaque primary visual cortex.Influence of retinal image shifts and extra-retinal eye movement signals on binocular rivalry alternations.A rate and history-preserving resampling algorithm for neural spike trainsASSESSMENT OF SYNCHRONY IN MULTIPLE NEURAL SPIKE TRAINS USING LOGLINEAR POINT PROCESS MODELS.Functional two-way analysis of variance and bootstrap methods for neural synchrony analysis.A semiparametric Bayesian model for detecting synchrony among multiple neurons.Spatiotemporal conditional inference and hypothesis tests for neural ensemble spiking precisionEffects of spatiotemporal stimulus properties on spike timing correlations in owl monkey primary somatosensory cortexWidespread spatial integration in primary somatosensory cortexRelating functional connectivity in V1 neural circuits and 3D natural scenes using Boltzmann machines.A framework for evaluating pairwise and multiway synchrony among stimulus-driven neurons.Surrogate spike train generation through dithering in operational time.Trial-to-trial variability and its effect on time-varying dependency between two neurons.Dynamics of stimulus-evoked spike timing correlations in the cat lateral geniculate nucleus.Accelerated spike resampling for accurate multiple testing controls.Impact of spike train autostructure on probability distribution of joint spike events.Generating spike trains with specified correlation coefficients.Identification of excitatory-inhibitory links and network topology in large-scale neuronal assemblies from multi-electrode recordings
P2860
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P2860
Statistical assessment of time-varying dependency between two neurons.
description
2005 nî lūn-bûn
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2005年の論文
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2005年学术文章
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2005年学术文章
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2005年学术文章
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2005年学术文章
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2005年学术文章
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2005年学术文章
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2005年學術文章
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name
Statistical assessment of time-varying dependency between two neurons.
@en
Statistical assessment of time-varying dependency between two neurons.
@nl
type
label
Statistical assessment of time-varying dependency between two neurons.
@en
Statistical assessment of time-varying dependency between two neurons.
@nl
prefLabel
Statistical assessment of time-varying dependency between two neurons.
@en
Statistical assessment of time-varying dependency between two neurons.
@nl
P2860
P356
P1476
Statistical assessment of time-varying dependency between two neurons.
@en
P2093
Robert E Kass
P2860
P304
P356
10.1152/JN.00645.2004
P407
P577
2005-10-01T00:00:00Z