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[1]  A. Burkitt,et al.  Shot noise in the leaky integrate-and-fire neuron. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Fredric M. Wolf,et al.  Action Potential Onset Dynamics and the Response Speed of Neuronal Populations , 2004, Journal of Computational Neuroscience.

[3]  Stefan Rotter,et al.  Exact digital simulation of time-invariant linear systems with applications to neuronal modeling , 1999, Biological Cybernetics.

[4]  Wulfram Gerstner,et al.  Population Dynamics of Spiking Neurons: Fast Transients, Asynchronous States, and Locking , 2000, Neural Computation.

[5]  Derek Abbott,et al.  What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology , 2009, PLoS Comput. Biol..

[6]  Martin Jacobsen,et al.  Exit times for a class of piecewise exponential Markov processes with two-sided jumps , 2007 .

[7]  H. Sompolinsky,et al.  Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity , 1996, Science.

[8]  Frank Moss,et al.  Noise enhancement of information transfer in crayfish mechanoreceptors by stochastic resonance , 1993, Nature.

[9]  Virginia Giorno,et al.  AN OUTLINE OF THEORETICAL AND ALGORITHMIC APPROACHES TO FIRST PASSAGE TIME PROBLEMS WITH APPLICATIONS TO BIOLOGICAL MODELING , 1999 .

[10]  J. Poulet,et al.  Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice , 2008, Nature.

[11]  R. Kempter,et al.  Hebbian learning and spiking neurons , 1999 .

[12]  P. Johannesma,et al.  Diffusion Models for the Stochastic Activity of Neurons , 1968 .

[13]  Stefan Rotter,et al.  Higher-Order Statistics of Input Ensembles and the Response of Simple Model Neurons , 2003, Neural Computation.

[14]  W. Senn,et al.  Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents. , 2003, Journal of neurophysiology.

[15]  D. Hansel,et al.  How Spike Generation Mechanisms Determine the Neuronal Response to Fluctuating Inputs , 2003, The Journal of Neuroscience.

[16]  Lawrence Sirovich,et al.  On the Simulation of Large Populations of Neurons , 2004, Journal of Computational Neuroscience.

[17]  Markus Diesmann,et al.  Exact Subthreshold Integration with Continuous Spike Times in Discrete-Time Neural Network Simulations , 2007, Neural Computation.

[18]  M. DeWeese,et al.  Non-Gaussian Membrane Potential Dynamics Imply Sparse, Synchronous Activity in Auditory Cortex , 2006, The Journal of Neuroscience.

[19]  Jaime de la Rocha,et al.  Supplementary Information for the article ‘ Correlation between neural spike trains increases with firing rate ’ , 2007 .

[20]  Eugene M. Izhikevich,et al.  Which model to use for cortical spiking neurons? , 2004, IEEE Transactions on Neural Networks.

[21]  R E Poppele,et al.  Correlation analysis of stimulus-evoked changes in excitability of spontaneously firing neurons. , 1977, Journal of neurophysiology.

[22]  Walter Senn,et al.  Minimal Models of Adapted Neuronal Response to In VivoLike Input Currents , 2004, Neural Computation.

[23]  Tim Gollisch,et al.  Modeling Single-Neuron Dynamics and Computations: A Balance of Detail and Abstraction , 2006, Science.

[24]  Magnus J. E. Richardson,et al.  Spike-train spectra and network response functions for non-linear integrate-and-fire neurons , 2008, Biological Cybernetics.

[25]  Nicolas Brunel,et al.  Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons , 2000, Journal of Computational Neuroscience.

[26]  L Schimansky-Geier,et al.  Transmission of noise coded versus additive signals through a neuronal ensemble. , 2001, Physical review letters.

[27]  Moritz Helias,et al.  Structural Plasticity Controlled by Calcium Based Correlation Detection , 2008, Frontiers Comput. Neurosci..

[28]  Moritz Helias,et al.  Equilibrium and response properties of the integrate-and-fi re neuron in discrete time , 2022 .

[29]  Lawrence Sirovich,et al.  Dynamics of Neuronal Populations: The Equilibrium Solution , 2000, SIAM J. Appl. Math..

[30]  Benjamin Lindner,et al.  Method to calculate the moments of the membrane voltage in a model neuron driven by multiplicative filtered shot noise. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[31]  Markus Diesmann,et al.  Spike-Timing-Dependent Plasticity in Balanced Random Networks , 2007, Neural Computation.

[32]  F. Attneave,et al.  The Organization of Behavior: A Neuropsychological Theory , 1949 .

[33]  Matthieu Gilson,et al.  Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks III: Partially connected neurons driven by spontaneous activity , 2009, Biological Cybernetics.

[34]  Bartlett W. Mel,et al.  Impact of Active Dendrites and Structural Plasticity on the Memory Capacity of Neural Tissue , 2001, Neuron.

[35]  John P. Miller,et al.  Broadband neural encoding in the cricket cereal sensory system enhanced by stochastic resonance , 1996, Nature.

[36]  Frances S. Chance,et al.  Effects of synaptic noise and filtering on the frequency response of spiking neurons. , 2001, Physical review letters.

[37]  P. Talkner,et al.  First-passage time problems for non-Markovian processes. , 1985, Physical review. A, General physics.

[38]  Markus Diesmann,et al.  The mechanism of synchronization in feed-forward neuronal networks , 2008 .

[39]  Nicolas Brunel,et al.  Dynamics of the Firing Probability of Noisy Integrate-and-Fire Neurons , 2002, Neural Computation.

[40]  Peter Hänggi,et al.  Activation rates for nonlinear stochastic flows driven by non-Gaussian noise , 1984 .

[41]  Nicolas Brunel,et al.  Fast Global Oscillations in Networks of Integrate-and-Fire Neurons with Low Firing Rates , 1999, Neural Computation.

[42]  Matthieu Gilson,et al.  Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks IV , 2009, Biological Cybernetics.

[43]  Moritz Helias,et al.  A General and Efficient Method for Incorporating Precise Spike Times in Globally Time-Driven Simulations , 2010, Front. Neuroinform..

[44]  M. J. Richardson,et al.  Firing-rate response of linear and nonlinear integrate-and-fire neurons to modulated current-based and conductance-based synaptic drive. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[45]  Wulfram Gerstner,et al.  Phenomenological models of synaptic plasticity based on spike timing , 2008, Biological Cybernetics.

[46]  Matthieu Gilson,et al.  Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. II. Input selectivity—symmetry breaking , 2009, Biological Cybernetics.

[47]  Markus Diesmann,et al.  The spread of rate and correlation in stationary cortical networks , 2003, Neurocomputing.

[48]  A. Siegert.  On the First Passage Time Probability Problem , 1951 .

[49]  G. Bi,et al.  Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.

[50]  Matthieu Gilson,et al.  Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity–strengthening correlated input pathways , 2009, Biological Cybernetics.

[51]  H Markram,et al.  Dynamics of population rate codes in ensembles of neocortical neurons. , 2004, Journal of neurophysiology.

[52]  Marc de Kamps,et al.  A Simple and Stable Numerical Solution for the Population Density Equation , 2003, Neural Computation.

[53]  Wulfram Gerstner,et al.  A benchmark test for a quantitative assessment of simple neuron models , 2008, Journal of Neuroscience Methods.

[54]  Carson C. Chow,et al.  Aperiodic stochastic resonance. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[55]  R. Stein.  A THEORETICAL ANALYSIS OF NEURONAL VARIABILITY. , 1965, Biophysical journal.

[56]  Néstor Parga,et al.  Auto- and crosscorrelograms for the spike response of leaky integrate-and-fire neurons with slow synapses. , 2006, Physical review letters.

[57]  Lyle J. Graham,et al.  Efficient evaluation of neuron populations receiving colored-noise current based on a refractory density method. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[58]  L. Ricciardi,et al.  The Ornstein-Uhlenbeck process as a model for neuronal activity , 1979, Biological Cybernetics.

[59]  Frank Moss,et al.  Noise in human muscle spindles , 1996, Nature.

[60]  Marc-Oliver Gewaltig,et al.  NEST (NEural Simulation Tool) , 2007, Scholarpedia.

[61]  H. Risken.  Fokker-Planck Equation , 1984 .