Abbott LF, Dayan P. (2001). Theoretical Neuroscience. Computational and Mathematical Modeling of Neural Systems.
Agüera y Arcas B, Fairhall AL. (2003). What causes a neuron to spike? Neural computation. 15 [PubMed]
Berry MJ, Meister M. (1998). Refractoriness and neural precision. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]
Bogachev V. (1998). Gaussian measures.
Brillinger DR. (1992). Nerve cell spike train data analysis: A progression of technique J Am Stat Assoc. 87
Brown E, Fellows M, Donoghue J, Truccolo W, Eden U. (2003). Multivariate conditional intensity models for motor cortex Soc Neurosci Abstr 607.11.
Brown EN, Barbieri R, Ventura V, Kass RE, Frank LM. (2002). The time-rescaling theorem and its application to neural spike train data analysis. Neural computation. 14 [PubMed]
Brunel N, Latham PE. (2003). Firing rate of the noisy quadratic integrate-and-fire neuron. Neural computation. 15 [PubMed]
Burkitt AN, Clark GM. (1999). Analysis of integrate-and-fire neurons: synchronization of synaptic input and spike output. Neural computation. 11 [PubMed]
Chichilnisky EJ. (2001). A simple white noise analysis of neuronal light responses. Network (Bristol, England). 12 [PubMed]
Dodd T, Harris C. (2002). Identification of nonlinear time series via kernels International Journal Of Systems Science. 33
Donoho DL, Elad M. (2003). Optimally sparse representation in general (nonorthogonal) dictionaries via l minimization. Proceedings of the National Academy of Sciences of the United States of America. 100 [PubMed]
Donoho DL, Johnstone IM, Kerkyacharian G, Picard D. (1995). Wavelet shrinkage: Asymptopia J R Statist Soc B. 57
Duda RO, Hart PE. (1973). Pattern Classification and Scene Analysis.
Efron B, Stein C. (1981). The jackknife estimate of variance Ann Stat. 9
Fourcaud N, Brunel N. (2002). Dynamics of the firing probability of noisy integrate-and-fire neurons. Neural computation. 14 [PubMed]
Genz A. (1992). Numerical computation of multivariate normal probabilities J Comput Graph Stat. 1
Gerstner W, Lewis T, Jolivet R. (2003). The spike response model: A framework to predict neuronal spike trains Proc Joint Intl Conf .
Girosi F. (1998). An Equivalence Between Sparse Approximation and Support Vector Machines. Neural computation. 10 [PubMed]
Harris KD, Csicsvari J, Hirase H, Dragoi G, Buzsáki G. (2003). Organization of cell assemblies in the hippocampus. Nature. 424 [PubMed]
Hatsopoulos N, Paninski L, Fellows M, Donoghue J, Shoham S. (2003). Nonlinear population models for the encoding of dynamic hand position signals in primary motor cortex Poster session presented at the annual computational neuroscience meeting Alicante, Spain.
Iyengar S, Liao Q. (1997). Modeling neural activity using the generalized inverse Gaussian distribution. Biological cybernetics. 77 [PubMed]
Izhikevich EM. (1998). Phase models with explicit time delays Phys Rev E. 58
James W, Stein C. (1961). Estimation with quadratic loss Proc Fourth Berkeley Symposium Mathematical Statistics And Probability. 1
Joeken S, Schwegler H, Richter CP. (1997). Modeling stochastic spike train responses of neurons: an extended Wiener series analysis of pigeon auditory nerve fibers. Biological cybernetics. 76 [PubMed]
Karlin S, Taylor HM. (1982). Asecond course in stochasticprocesses..
Keat J, Reinagel P, Reid RC, Meister M. (2001). Predicting every spike: a model for the responses of visual neurons. Neuron. 30 [PubMed]
Kistler WM, Gerstner W. (2002). Spiking neuron models.
Knight BW, Omurtag A, Sirovich L. (2000). The approach of a neuron population firing rate to a new equilibrium: an exact theoretical result. Neural computation. 12 [PubMed]
Koberle R, de Ruyter van Steveninck R, Bialek W, Stong S. (1998). Entropy and information in neural spike trains Physical Review Lett. 80
Koch C. (1999). Biophysics Of Computation: Information Processing in Single Neurons.
Levin JE, Miller JP. (1996). Broadband neural encoding in the cricket cercal sensory system enhanced by stochastic resonance. Nature. 380 [PubMed]
Miller KD, Troyer TW. (2002). Neural noise can explain expansive, power-law nonlinearities in neural response functions. Journal of neurophysiology. 87 [PubMed]
Miller MI, Mark KE. (1992). A statistical study of cochlear nerve discharge patterns in response to complex speech stimuli. The Journal of the Acoustical Society of America. 92 [PubMed]
Moreno R, de la Rocha J, Renart A, Parga N. (2002). Response of spiking neurons to correlated inputs. Physical review letters. 89 [PubMed]
Paninski L. (2003). Convergence properties of three spike-triggered analysis techniques. Network (Bristol, England). 14 [PubMed]
Pillow J, Simoncelli E. (2003). Biases in white noise analysis due to non-Poisson spike generation Neurocomputing. 52
Plesser HE, Gerstner W. (2000). Noise in integrate-and-fire neurons: from stochastic input to escape rates. Neural computation. 12 [PubMed]
Press WH, Teukolsky SA, Flannery BP, Vellerling WT. (1992). Numerical Recipes In C: The Art Of Scientific Computing.
Reich DS, Victor JD, Knight BW. (1998). The power ratio and the interval map: spiking models and extracellular recordings. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]
Reyes A, Paninski L, Lau B. (2003). Noise-driven adaptation: in vitro and mathematical analysis Neurocomputing. 52
Rinott Y. (1976). On convexity of measures Ann Prob. 4
Rudd ME, Brown LG. (1997). Noise adaptation in integrate-and fire neurons. Neural computation. 9 [PubMed]
Sahani M. (2000). Kernel regression for neural systems identification Presented at NIPS00 workshop on Information and Statistical Structure in Spike Trains: Abstract available online at http:--www-users.med.cornell.edu-jdvicto-nips2000speakers.html.
Sahani M, Linden J. (2003). Evidence optimization techniques for estimating stimulus-response functions Advances in neural information processing systems. 15
Schwartz O, Simoncelli EP, Paninski L, Pillow J. (2004). Characterization of neural responses with stochastic stimuli The New Cognitive Neurosciences (3rd ed).
Seeger M. (2002). PAC-Bayesian generalisation error bounds for gaussian process classifiers J Mach Learn Res. 3
Seshardri V. (1993). The inverse gaussian distribution.
Shawe-taylor J, Cristianini N. (2000). An introduction to support vector machines.
Smyth D, Willmore B, Baker GE, Thompson ID, Tolhurst DJ. (2003). The receptive-field organization of simple cells in primary visual cortex of ferrets under natural scene stimulation. The Journal of neuroscience : the official journal of the Society for Neuroscience. 23 [PubMed]
Snyder DL, Miller MI. (1991). Random point processes in time and space..
Stevens CF, Zador AM. (1998). Novel integrate-and-fire-like model of repetitive firing in cortical neurons. Proceedings of the Fifth Joint Symposium on Neural Computation.
Tipping M. (2001). Sparse Bayesian learning and the relevance vector machine J Mach Learn Res. 1
Tranchina D, Nykamp DQ, Haskell E. (2001). Population density methods for large-scale modelling of neuronal networks with realistic synaptic kinetics: cutting the dimension down to size. Network. 12
Tsodyks M, Kenet T, Grinvald A, Arieli A. (1999). Linking spontaneous activity of single cortical neurons and the underlying functional architecture. Science (New York, N.Y.). 286 [PubMed]
Victor JD. (2000). How the brain uses time to represent and process visual information(1). Brain research. 886 [PubMed]
Warland DK, Reinagel P, Meister M. (1997). Decoding visual information from a population of retinal ganglion cells. Journal of neurophysiology. 78 [PubMed]
Williams CKI, Barber D. (1998). Bayesian classification with gaussian processes IEEE Trans Patt Anal Mach Intel. 20
Yu Y, Lee TS. (2003). Dynamical mechanisms underlying contrast gain control in single neurons. Physical review. E, Statistical, nonlinear, and soft matter physics. 68 [PubMed]
Zador A, Stevens C. (1996). When is an integrate-and-fire neuron like a Poisson neuron? NIPS. 8
Zador A, Wehr M, Machens C. (2003). Spectro-temporal receptive fields of subthreshold responses in auditory cortex Advances in neural information processing systems. 15
Zhang K, Ginzburg I, McNaughton BL, Sejnowski TJ. (1998). Interpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cells. Journal of neurophysiology. 79 [PubMed]
van_derVaart A. (1998). Asymptotic statistics.
Badel L et al. (2008). Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces. Journal of neurophysiology. 99 [PubMed]
Brette R, Gerstner W. (2005). Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. Journal of neurophysiology. 94 [PubMed]
Carver S, Roth E, Cowan NJ, Fortune ES. (2008). Synaptic plasticity can produce and enhance direction selectivity. PLoS computational biology. 4 [PubMed]
Goldwyn JH, Rubinstein JT, Shea-Brown E. (2012). A point process framework for modeling electrical stimulation of the auditory nerve. Journal of neurophysiology. 108 [PubMed]
Hong S, Agüera y Arcas B, Fairhall AL. (2007). Single neuron computation: from dynamical system to feature detector. Neural computation. 19 [PubMed]
Lansky P, Sanda P, He J. (2006). The parameters of the stochastic leaky integrate-and-fire neuronal model. Journal of computational neuroscience. 21 [PubMed]
Mensi S et al. (2012). Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. Journal of neurophysiology. 107 [PubMed]
Olshausen BA, Field DJ. (2005). How close are we to understanding v1? Neural computation. 17 [PubMed]
Paninski L. (2006). The most likely voltage path and large deviations approximations for integrate-and-fire neurons. Journal of computational neuroscience. 21 [PubMed]
Paninski L. (2006). The spike-triggered average of the integrate-and-fire cell driven by gaussian white noise. Neural computation. 18 [PubMed]
Pospischil M, Piwkowska Z, Rudolph M, Bal T, Destexhe A. (2007). Calculating event-triggered average synaptic conductances from the membrane potential. Journal of neurophysiology. 97 [PubMed]
Powers RK, Dai Y, Bell BM, Percival DB, Binder MD. (2005). Contributions of the input signal and prior activation history to the discharge behaviour of rat motoneurones. The Journal of physiology. 562 [PubMed]
Shao J, Lai D, Meyer U, Luksch H, Wessel R. (2009). Generating oscillatory bursts from a network of regular spiking neurons without inhibition. Journal of computational neuroscience. 27 [PubMed]
Shlens J, Kennel MB, Abarbanel HD, Chichilnisky EJ. (2007). Estimating information rates with confidence intervals in neural spike trains. Neural computation. 19 [PubMed]