Pages that link to "Item:Q1899175"

The following pages link to On the parameter estimation for diffusion models of single neuron's activities. I: Application to spontaneous activities of mesencephalic reticular formation cells in sleep and waking states (Q1899175):

Displaying 30 items.

• On the classification of experimental data modeled via a stochastic leaky integrate and fire model through boundary values (Q263681) (← links)
• The gamma renewal process as an output of the diffusion leaky integrate-and-fire neuronal model (Q309609) (← links)
• Reconstruction of the input signal of the leaky integrate-and-fire neuronal model from its interspike intervals (Q310131) (← links)
• Modeling neural activity with cumulative damage distributions (Q310175) (← links)
• Fluctuation scaling in neural spike trains (Q335086) (← links)
• A new firing paradigm for integrate and fire stochastic neuronal models (Q335094) (← links)
• Estimating nonstationary inputs from a single spike train based on a neuron model with adaptation (Q395708) (← links)
• The parameters of the stochastic leaky integrate-and-fire neuronal model (Q849517) (← links)
• A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models (Q999378) (← links)
• On the asymptotic behavior of the parameter estimators for some diffusion processes: application to neuronal models (Q1042620) (← links)
• Are the input parameters of white noise driven integrate and fire neurons uniquely determined by rate and CV? (Q1617507) (← links)
• Two-compartment stochastic model of a neuron (Q1809404) (← links)
• On the comparison of Feller and Ornstein-Uhlenbeck models for neural activity (Q1902608) (← links)
• Computing the survival probability density function in jump-diffusion models: a new approach based on radial basis functions (Q1944574) (← links)
• Maximum likelihood estimation for an Ornstein-Uhlenbeck model for neural activity (Q2241467) (← links)
• Fokker-Planck and Fortet equation-based parameter estimation for a leaky integrate-and-fire model with sinusoidal and stochastic forcing (Q2251600) (← links)
• A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input (Q2373188) (← links)
• Stochastic modeling of the neuronal activity in the subthalamic nucleus and model parameter identification from Parkinson patient data (Q2376510) (← links)
• Estimation of the input parameters in the Feller neuronal model (Q2903689) (← links)
• A Recursion Formula for the Moments of the First Passage Time of the Ornstein-Uhlenbeck Process (Q2949857) (← links)
• On a Stochastic Leaky Integrate-and-Fire Neuronal Model (Q3057209) (← links)
• Discrimination with Spike Times and ISI Distributions (Q3503719) (← links)
• Parameters of the Diffusion Leaky Integrate-and-Fire Neuronal Model for a Slowly Fluctuating Signal (Q3536230) (← links)
• The Jacobi diffusion process as a neuronal model (Q4556543) (← links)
• On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties (Q4565969) (← links)
• Stochastic Integrate and Fire Models: A Review on Mathematical Methods and Their Applications (Q4567932) (← links)
• (Q5134772) (← links)
• The Ornstein-Uhlenbeck neuronal model with signal-dependent noise (Q5936291) (← links)
• Applications of an extended geometric Brownian motion degradation model (Q6587714) (← links)
• A review of stochastic models of neuronal dynamics: from a single neuron to networks (Q6606789) (← links)