The most likely voltage path and large deviations approximations for integrate-and-fire neurons.
about
Stress-induced impairment of a working memory task: role of spiking rate and spiking history predicted dischargeThe accuracy of membrane potential reconstruction based on spiking receptive fields.Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods.Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentialsDesigning optimal stimuli to control neuronal spike timing.Value encoding in single neurons in the human amygdala during decision makingDendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.An electromechanical model of neuronal dynamics using Hamilton's principle.State-space algorithms for estimating spike rate functions.Inferring synaptic inputs given a noisy voltage trace via sequential Monte Carlo methods.Efficient estimation of phase-response curves via compressive sensing.Inferring interactions in assemblies of stochastic integrate-and-fire neurons from spike recordings: method, applications and software.Fast inference of interactions in assemblies of stochastic integrate-and-fire neurons from spike recordings.Bessel-like functional distributions in brain average evoked potentials.Spike-triggered averages for passive and resonant neurons receiving filtered excitatory and inhibitory synaptic drive.Calculating event-triggered average synaptic conductances from the membrane potential.Mechanisms that modulate the transfer of spiking correlations.Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.Feature selection in simple neurons: how coding depends on spiking dynamics.Subthreshold dynamics of a single neuron from a Hamiltonian perspective.Relating neural dynamics to neural coding.Estimation in Discretely Observed Diffusions Killed at a ThresholdInverse statistical problems: from the inverse Ising problem to data science
P2860
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P2860
The most likely voltage path and large deviations approximations for integrate-and-fire neurons.
description
2006 nî lūn-bûn
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2006年の論文
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2006年学术文章
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2006年学术文章
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name
The most likely voltage path a ...... or integrate-and-fire neurons.
@en
The most likely voltage path a ...... or integrate-and-fire neurons.
@nl
type
label
The most likely voltage path a ...... or integrate-and-fire neurons.
@en
The most likely voltage path a ...... or integrate-and-fire neurons.
@nl
prefLabel
The most likely voltage path a ...... or integrate-and-fire neurons.
@en
The most likely voltage path a ...... or integrate-and-fire neurons.
@nl
P1476
The most likely voltage path a ...... or integrate-and-fire neurons.
@en
P2888
P356
10.1007/S10827-006-7200-4
P577
2006-04-22T00:00:00Z