about
A Spike-Train Probability ModelStatistical smoothing of neuronal data.Statistical issues in the analysis of neuronal data.The time-rescaling theorem and its application to neural spike train data analysis.Automatic scan test for detection of functional connectivity between cortex and muscles.Automated acoustic detection of mouse scratching.Accurately estimating neuronal correlation requires a new spike-sorting paradigmSeparating Spike Count Correlation from Firing Rate Correlation.Traditional waveform based spike sorting yields biased rate code estimates.A computationally efficient method for incorporating spike waveform information into decoding algorithms.Automatic spike sorting using tuning information.Trial-to-trial variability and its effect on time-varying dependency between two neurons.Spike train decoding without spike sortingNeural Decoding: A Predictive Viewpoint.Statistical analysis of temporal evolution in single-neuron firing rates.Spike count correlation increases with length of time interval in the presence of trial-to-trial variation.Spline-based non-parametric regression for periodic functions and its application to directional tuning of neurons.Single-snippet analysis for detection of postspike effects.Statistical assessment of time-varying dependency between two neurons.Testing for and estimating latency effects for poisson and non-poisson spike trains.Chronic recruitment of primary afferent neurons by microstimulation in the feline dorsal root ganglia.Controlling the Proportion of Falsely Rejected Hypotheses when Conducting Multiple Tests with Climatological DataMultiple Indices of Northern Hemisphere Cyclone Activity, Winters 1949–99
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P50
name
Valérie Ventura
@ast
Valérie Ventura
@en
Valérie Ventura
@nl
type
label
Valérie Ventura
@ast
Valérie Ventura
@en
Valérie Ventura
@nl
prefLabel
Valérie Ventura
@ast
Valérie Ventura
@en
Valérie Ventura
@nl