标题
Channel-noise-induced stochastic facilitation in an auditory brainstem neuron model
作者
关键词
-
出版物
PHYSICAL REVIEW E
Volume 88, Issue 5, Pages -
出版商
American Physical Society (APS)
发表日期
2013-11-27
DOI
10.1103/physreve.88.052722
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Channel-based Langevin approach for the stochastic Hodgkin-Huxley neuron
- (2013) Yandong Huang et al. PHYSICAL REVIEW E
- A point process framework for modeling electrical stimulation of the auditory nerve
- (2012) Joshua H. Goldwyn et al. JOURNAL OF NEUROPHYSIOLOGY
- Analysis of inverse stochastic resonance and the long-term firing of Hodgkin–Huxley neurons with Gaussian white noise
- (2012) Henry C. Tuckwell et al. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
- Modeling ion channel dynamics through reflected stochastic differential equations
- (2012) Ciara E. Dangerfield et al. PHYSICAL REVIEW E
- Stochastic-Shielding Approximation of Markov Chains and its Application to Efficiently Simulate Random Ion-Channel Gating
- (2012) Nicolaus T. Schmandt et al. PHYSICAL REVIEW LETTERS
- Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States
- (2012) Patricio Orio et al. PLoS One
- The benefits of noise in neural systems: bridging theory and experiment
- (2011) Mark D. McDonnell et al. NATURE REVIEWS NEUROSCIENCE
- Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons
- (2011) Joshua H. Goldwyn et al. PHYSICAL REVIEW E
- Accurate and Fast Simulation of Channel Noise in Conductance-Based Model Neurons by Diffusion Approximation
- (2011) Daniele Linaro et al. PLoS Computational Biology
- The What and Where of Adding Channel Noise to the Hodgkin-Huxley Equations
- (2011) Joshua H. Goldwyn et al. PLoS Computational Biology
- Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons
- (2011) Lars Buesing et al. PLoS Computational Biology
- Fluid limit theorems for stochastic hybrid systems with application to neuron models
- (2010) K. Pakdaman et al. ADVANCES IN APPLIED PROBABILITY
- Comparison of Langevin and Markov channel noise models for neuronal signal generation
- (2010) B. Sengupta et al. PHYSICAL REVIEW E
- Slope-Based Stochastic Resonance: How Noise Enables Phasic Neurons to Encode Slow Signals
- (2010) Yan Gai et al. PLoS Computational Biology
- Weak Noise in Neurons May Powerfully Inhibit the Generation of Repetitive Spiking but Not Its Propagation
- (2010) Henry C. Tuckwell et al. PLoS Computational Biology
- Evaluation of Stochastic Differential Equation Approximation of Ion Channel Gating Models
- (2009) Ian C. Bruce ANNALS OF BIOMEDICAL ENGINEERING
- Stochastic Population Model for Electrical Stimulation of the Auditory Nerve
- (2009) N.S. Imennov et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Noise-Gated Encoding of Slow Inputs by Auditory Brain Stem Neurons With a Low-Threshold K+ Current
- (2009) Yan Gai et al. JOURNAL OF NEUROPHYSIOLOGY
- Broadband Coding with Dynamic Synapses
- (2009) B. Lindner et al. JOURNAL OF NEUROSCIENCE
- Inhibition of rhythmic neural spiking by noise: the occurrence of a minimum in activity with increasing noise
- (2009) Boris S. Gutkin et al. NATURWISSENSCHAFTEN
- Suprathreshold stochastic resonance induced by ion channel fluctuation
- (2009) Go Ashida et al. PHYSICA D-NONLINEAR PHENOMENA
- Inhibition and modulation of rhythmic neuronal spiking by noise
- (2009) Henry C. Tuckwell et al. PHYSICAL REVIEW E
- What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology
- (2009) Mark D. McDonnell et al. PLoS Computational Biology
- Noise in the nervous system
- (2008) A. Aldo Faisal et al. NATURE REVIEWS NEUROSCIENCE
- Reliability, synchrony and noise
- (2008) G. Bard Ermentrout et al. TRENDS IN NEUROSCIENCES
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started