Legends: | Link to a Model | Reference cited by multiple papers |
References and models cited by this paper | References and models that cite this paper | |||||||
Agüera y Arcas B, Fairhall AL (2003) What causes a neuron to spike? Neural Comput 15:1789-807 [Journal] [PubMed] Badel L, Richardson M, Gerstner W (2006) Dependence of the spike-triggered average voltage on membrane response properties Neurocomputing 69:1062-1065 Berry MJ, Meister M (1998) Refractoriness and neural precision. J Neurosci 18:2200-11 [PubMed] Brunel N, Hakim V (1999) Fast global oscillations in networks of integrate-and-fire neurons with low firing rates. Neural Comput 11:1621-71 [PubMed]
Brunel N, Latham PE (2003) Firing rate of the noisy quadratic integrate-and-fire neuron. Neural Comput 15:2281-306 [Journal] [PubMed] Bryant HL, Segundo JP (1976) Spike initiation by transmembrane current: a white-noise analysis. J Physiol 260:279-314 [PubMed] Burkitt AN, Clark GM (1999) Analysis of integrate-and-fire neurons: synchronization of synaptic input and spike output. Neural Comput 11:871-901 [PubMed] Bussgang JJ (1952) Crosscorrelation functions of amplitude distorted gaussian signals Mit Res Lab Elec Tech Rep 216:1-14 Chichilnisky EJ (2001) A simple white noise analysis of neuronal light responses. Network 12:199-213 [PubMed] Daniels H (1982) Sequential tests constructed from images Ann Stat 10:394-400 Dayan P, Abbott LF (2001) Theoretical Neuroscience. Computational and Mathematical Modeling of Neural Systems de Boer R, Kuyper P (1968) Triggered correlation. IEEE Trans Biomed Eng 15:169-79 [PubMed] de Ruyter van Steveninck RR, Bialek W (1988) Real-time performance of a movement sensitive in the blowfly visual system: Information transfer in short spike sequences Proc Roy Soc Lond 234:379-414 Freidlin M, Wentzell A (1998) Random Perturbations of Dynamical Systems Gerstner W (2001) Coding properties of spiking neurons: reverse and cross-correlations. Neural Netw 14:599-610 [PubMed] Gerstner W, Kistler WM (2002) Spiking neuron models Harvey A (1991) Forecasting: Structural time series models and the Kalman filter Haskell E, Nykamp DQ, Tranchina D (2001) Population density methods for large-scale modelling of neuronal networks with realistic synaptic kinetics: cutting the dimension down to size. Network 12:141-74 Hida T (1980) Brownian Motion Kanev J, Wenning G, Obermayer K (2004) Approximating the response stimulus correlation for the integrate-and-fire neuron Neurocomputing 58:47-52 Karatzas I, Shreve S (1997) Brownian Motion and Stochastic Calculus Karlin S, Taylor HM (1982) Asecond course in stochasticprocesses. Kautz RL (1988) Thermally induced escape: The principle of minimum available noise energy. Phys Rev A Gen Phys 38:2066-2080 [PubMed] Koch C (1999) Biophysics Of Computation: Information Processing in Single Neurons Paninski L (2003) Convergence properties of three spike-triggered analysis techniques. Network 14:437-64 [PubMed] Paninski L (2004) Maximum likelihood estimation of cascade point-process neural encoding models. Network 15:243-62 [PubMed] Paninski L (2006) The most likely voltage path and large deviations approximations for integrate-and-fire neurons. J Comput Neurosci 21:71-87 [Journal] [PubMed] Paninski L, Haith A, Pillow J, Williams C (2005) Improved numerical methods for computing likelihoods in the stochastic integrate-and-fire model Comp Sys Neur Paninski L, Lau B, Reyes A (2003) Noise-driven adaptation: in vitro and mathematical analysis Neurocomputing 52:877-883 Paninski L, Pillow JW, Simoncelli EP (2004) Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model. Neural Comput 16:2533-61 [Journal] [PubMed] Pillow J, Simoncelli E (2003) Biases in white noise analysis due to non-Poisson spike generation Neurocomputing 52:109-155 Pillow JW, Paninski L, Uzzell VJ, Simoncelli EP, Chichilnisky EJ (2005) Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model. J Neurosci 25:11003-13 [Journal] [PubMed] Plesser HE, Tanaka S (1997) Stochastic resonance in a model neuron with reset. Phys Lett A 225:228-234 Press WH, Teukolsky SA, Vellerling WT, Flannery BP (1992) Numerical Recipes In C: The Art Of Scientific Computing Rabiner L (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc IEEE 77:257-286 Rieke F, Warland D, de Ruyter van Steveninck, R, Bialek B (1997) Spikes: Exploring The Neural Code Risken H (1996) The Fokker Planck Equation: Methods of Solution and Applications Rudd ME, Brown LG (1997) Noise adaptation in integrate-and fire neurons. Neural Comput 9:1047-69 [PubMed] Seshadri V (1993) The inverse gaussian distribution Simoncelli EP, Paninski L, Pillow J, Schwartz O (2004) Characterization of neural responses with stochastic stimuli The New Cognitive Neurosciences (3rd ed), Gazzaniga M, ed. Tuckwell HC (1988) Introduction to Theoretical Neurobiology. Volume 2: Nonlinear and Stochastic Theories Yu Y, Lee TS (2003) Dynamical mechanisms underlying contrast gain control in single neurons. Phys Rev E Stat Nonlin Soft Matter Phys 68:011901 [Journal] [PubMed] | Köndgen H, Geisler C, Fusi S, Wang XJ, Lüscher HR, Giugliano M (2008) The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro. Cereb Cortex 18:2086-97 [Journal] [PubMed]
Paninski L (2006) The most likely voltage path and large deviations approximations for integrate-and-fire neurons. J Comput Neurosci 21:71-87 [Journal] [PubMed] Pospischil M, Piwkowska Z, Rudolph M, Bal T, Destexhe A (2007) Calculating event-triggered average synaptic conductances from the membrane potential. J Neurophysiol 97:2544-52 [Journal] [PubMed]
|