-
2
-
-
55749088942
-
-
Available online at
-
Barrowes, B. (2007). Multiple precision toolbox for Matlab. Available online at http://www.mathworks.com/matlabcentral/fileexchange/ loadFile.do?objectId=6446&objectType=File.
-
(2007)
Multiple precision toolbox for Matlab
-
-
Barrowes, B.1
-
3
-
-
40749088917
-
Lapicque's 1907 paper: From frogs to integrate-and-fire
-
Brunel, N., & van Rossum, M. C. W. (2007). Lapicque's 1907 paper: From frogs to integrate-and-fire. Biol. Cybern., 97, 337-339.
-
(2007)
Biol. Cybern
, vol.97
, pp. 337-339
-
-
Brunel, N.1
van Rossum, M.C.W.2
-
4
-
-
33745712258
-
A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input
-
Burkitt, A. N. (2006). A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input. Biol. Cybern., 95, 1-19.
-
(2006)
Biol. Cybern
, vol.95
, pp. 1-19
-
-
Burkitt, A.N.1
-
5
-
-
0034625175
-
Noise in neurons is message-dependent
-
Cecchi, G. A., Sigman, M., Alonso, J. M., Martinez, L., Chialvo, D. R., & Magnasco, M. (2000). Noise in neurons is message-dependent. Proceedings of the National Academy of Sciences, 97, 5557-5561.
-
(2000)
Proceedings of the National Academy of Sciences
, vol.97
, pp. 5557-5561
-
-
Cecchi, G.A.1
Sigman, M.2
Alonso, J.M.3
Martinez, L.4
Chialvo, D.R.5
Magnasco, M.6
-
6
-
-
34247491502
-
Predicting neuronal activity with simple models of the threshold type: Adaptive exponential integrate-and-fire model with two compartments
-
Clopath, C., Jolivet, R., Rauch, A., Lüscher, H.-R., & Gerstner, W. (2007). Predicting neuronal activity with simple models of the threshold type: Adaptive exponential integrate-and-fire model with two compartments. Neurocomput., 70, 1668-1673.
-
(2007)
Neurocomput
, vol.70
, pp. 1668-1673
-
-
Clopath, C.1
Jolivet, R.2
Rauch, A.3
Lüscher, H.-R.4
Gerstner, W.5
-
9
-
-
0003597030
-
-
New York: Oxford University Press
-
Diggle, P. J., Heagerty, P., Liang, K. Y., & Zeger, S. L. (2002). Analysis of longitudinal data. New York: Oxford University Press.
-
(2002)
Analysis of longitudinal data
-
-
Diggle, P.J.1
Heagerty, P.2
Liang, K.Y.3
Zeger, S.L.4
-
10
-
-
45749127284
-
Mixed effects in stochastic differential equations models
-
Ditlevsen, S., & De Gaetano, A. (2005). Mixed effects in stochastic differential equations models. REVSTAT - Statistical Journal, 3(2), 137-153.
-
(2005)
REVSTAT - Statistical Journal
, vol.3
, Issue.2
, pp. 137-153
-
-
Ditlevsen, S.1
De Gaetano, A.2
-
11
-
-
41549100101
-
Parameter estimation from observations of first-passage times of the Ornstein-Uhlenbeck process and the Feller process
-
Ditlevsen, S., & Ditlevsen, O. (2008). Parameter estimation from observations of first-passage times of the Ornstein-Uhlenbeck process and the Feller process. Prob. Eng. Mech., 23, 170-179.
-
(2008)
Prob. Eng. Mech
, vol.23
, pp. 170-179
-
-
Ditlevsen, S.1
Ditlevsen, O.2
-
12
-
-
37649030460
-
Estimation of the input parameters in the Ornstein-Uhlenbeck neuronal model
-
Ditlevsen, S., & Lansky, P. (2005). Estimation of the input parameters in the Ornstein-Uhlenbeck neuronal model. Phys. Rev. E, 71, 011907.
-
(2005)
Phys. Rev. E
, vol.71
, pp. 011907
-
-
Ditlevsen, S.1
Lansky, P.2
-
13
-
-
33745189627
-
Estimation of the input parameters in the Feller neuronal model
-
Ditlevsen, S., & Lansky, P. (2006). Estimation of the input parameters in the Feller neuronal model. Phys. Rev. E, 73, 061910.
-
(2006)
Phys. Rev. E
, vol.73
, pp. 061910
-
-
Ditlevsen, S.1
Lansky, P.2
-
14
-
-
35248883957
-
Parameters of stochastic diffusion processes estimated from observations of first hitting-times: Application to the leaky integrate-and-fire neuronal model
-
Ditlevsen, S., & Lansky, P. (2007). Parameters of stochastic diffusion processes estimated from observations of first hitting-times: Application to the leaky integrate-and-fire neuronal model. Phys. Rev. E, 76, 041906.
-
(2007)
Phys. Rev. E
, vol.76
, pp. 041906
-
-
Ditlevsen, S.1
Lansky, P.2
-
15
-
-
55749092754
-
Parametric inference for mixed models defined by stochastic differential equations
-
Donnet, S., & Samson, A. (2008). Parametric inference for mixed models defined by stochastic differential equations. ESAIM: Probability and Statistics, 12, 196-218.
-
(2008)
ESAIM: Probability and Statistics
, vol.12
, pp. 196-218
-
-
Donnet, S.1
Samson, A.2
-
16
-
-
0010964703
-
-
Upper Saddle River, NJ: Benjamin/Cummings
-
Fröberg, C. E. (1985). Numerical mathematics. Upper Saddle River, NJ: Benjamin/Cummings.
-
(1985)
Numerical mathematics
-
-
Fröberg, C.E.1
-
18
-
-
0010394749
-
Inference for stochastic neuronal models
-
Habib, M. K., & Thavaneswaran, A. (1990). Inference for stochastic neuronal models. Applied Math. Comput., 38, 51-73.
-
(1990)
Applied Math. Comput
, vol.38
, pp. 51-73
-
-
Habib, M.K.1
Thavaneswaran, A.2
-
19
-
-
34248523849
-
On a set of data for the membrane potential in a neuron
-
Höpfner, R. (2007). On a set of data for the membrane potential in a neuron. Math. Biosci., 207, 275-301.
-
(2007)
Math. Biosci
, vol.207
, pp. 275-301
-
-
Höpfner, R.1
-
20
-
-
33746752672
-
Efficient estimation of detailed single-neuron models
-
Huys, Q. J. M., Ahrens, M. B., & Paninski, L. (2006). Efficient estimation of detailed single-neuron models. J. Neurophysiol., 96, 872-890.
-
(2006)
J. Neurophysiol
, vol.96
, pp. 872-890
-
-
Huys, Q.J.M.1
Ahrens, M.B.2
Paninski, L.3
-
21
-
-
0029355301
-
On the parameter estimation for diffusion models of single neurons' activity
-
Inoue, J., Sato, S., & Ricciardi, L. M. (1995). On the parameter estimation for diffusion models of single neurons' activity. Biol. Cybern., 73, 209-221.
-
(1995)
Biol. Cybern
, vol.73
, pp. 209-221
-
-
Inoue, J.1
Sato, S.2
Ricciardi, L.M.3
-
22
-
-
3142666109
-
Generalized integrate-and-fire models of neuronal activity approximate spike trains of a detailed model to a high degree of accuracy
-
Jolivet, R., Lewis, T. J., & Gerstner, W. (2004). Generalized integrate-and-fire models of neuronal activity approximate spike trains of a detailed model to a high degree of accuracy. J. Neurophysiol., 92, 959-976.
-
(2004)
J. Neurophysiol
, vol.92
, pp. 959-976
-
-
Jolivet, R.1
Lewis, T.J.2
Gerstner, W.3
-
23
-
-
33745833056
-
Predicting spike timing of neocortical pyramidal neurons by simple threshold models
-
Jolivet, R., Rauch, A., Lüscher, H.-R., & Gerstner, W. (2006). Predicting spike timing of neocortical pyramidal neurons by simple threshold models. J. Comput. Neurosci., 21, 35-49.
-
(2006)
J. Comput. Neurosci
, vol.21
, pp. 35-49
-
-
Jolivet, R.1
Rauch, A.2
Lüscher, H.-R.3
Gerstner, W.4
-
26
-
-
4344670177
-
Minimal models of adapted neuronal response to in vivo-like input currents
-
La Camera, G., Rauch, A., Lüscher, H.-R., Senn, W., & Fusi, S. (2004). Minimal models of adapted neuronal response to in vivo-like input currents. Neural Comput., 16, 2101-2124.
-
(2004)
Neural Comput
, vol.16
, pp. 2101-2124
-
-
La Camera, G.1
Rauch, A.2
Lüscher, H.-R.3
Senn, W.4
Fusi, S.5
-
27
-
-
0032212528
-
Input parameters in a one-dimensional neuronal model with reversal potentials
-
Lanska, V., & Lansky, P. (1998). Input parameters in a one-dimensional neuronal model with reversal potentials. Biosystems, 48, 123-129.
-
(1998)
Biosystems
, vol.48
, pp. 123-129
-
-
Lanska, V.1
Lansky, P.2
-
28
-
-
0021076773
-
Inference for diffusion models of neuronal activity
-
Lansky, P. (1983). Inference for diffusion models of neuronal activity. Math. Biosci., 67, 247-260.
-
(1983)
Math. Biosci
, vol.67
, pp. 247-260
-
-
Lansky, P.1
-
29
-
-
0035796609
-
The Ornstein-Uhlenbeck neuronal model with signal-dependent noise
-
Lansky, P., & Sacerdote, L. (2001). The Ornstein-Uhlenbeck neuronal model with signal-dependent noise. Physics Letters A, 285, 132-140.
-
(2001)
Physics Letters A
, vol.285
, pp. 132-140
-
-
Lansky, P.1
Sacerdote, L.2
-
30
-
-
33747272940
-
The parameters of the stochastic leaky integrate-and-fire neuronal model
-
Lansky, P., Sanda, P., & He, J. (2006). The parameters of the stochastic leaky integrate-and-fire neuronal model. J. Comput. Neurosci., 21, 211-223.
-
(2006)
J. Comput. Neurosci
, vol.21
, pp. 211-223
-
-
Lansky, P.1
Sanda, P.2
He, J.3
-
33
-
-
34748913632
-
A Matlab framework for estimation of NLME models using stochastic differential equations: Applications for estimation of insulin secretion rates
-
Mortensen, S. B., Klim, S., Dammann, B., Kristensen, N. R., Madsen, H., & Overgaard, R. (2007). A Matlab framework for estimation of NLME models using stochastic differential equations: Applications for estimation of insulin secretion rates. J. Pharmacokinet. Pharmacodyn., 34(5), 623-642.
-
(2007)
J. Pharmacokinet. Pharmacodyn
, vol.34
, Issue.5
, pp. 623-642
-
-
Mortensen, S.B.1
Klim, S.2
Dammann, B.3
Kristensen, N.R.4
Madsen, H.5
Overgaard, R.6
-
34
-
-
23844551829
-
Non-linear mixed effects models with stochastic differential equations: Implementation of an estimation algorithm
-
Overgaard, R. V., Jonsson, N., Tornøe, C. W., & Madsen, H. (2005). Non-linear mixed effects models with stochastic differential equations: Implementation of an estimation algorithm. J. Pharmacokinet. Pharmacodyn., 32, 85-107.
-
(2005)
J. Pharmacokinet. Pharmacodyn
, vol.32
, pp. 85-107
-
-
Overgaard, R.V.1
Jonsson, N.2
Tornøe, C.W.3
Madsen, H.4
-
35
-
-
9744239998
-
Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model
-
Paninski, L., Pillow, J. W., & Simoncelli, E. P. (2004). Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model. Neural Comput., 16, 2533-2561.
-
(2004)
Neural Comput
, vol.16
, pp. 2533-2561
-
-
Paninski, L.1
Pillow, J.W.2
Simoncelli, E.P.3
-
36
-
-
18144381247
-
Comparing integrate-and-fire-models estimated using intracellular and extracellular data
-
Paninski, L., Pillow, J., & Simoncelli, E. (2005). Comparing integrate-and-fire-models estimated using intracellular and extracellular data. Neurocomputing, 65-66, 379-385.
-
(2005)
Neurocomputing
, vol.65-66
, pp. 379-385
-
-
Paninski, L.1
Pillow, J.2
Simoncelli, E.3
-
37
-
-
55749092589
-
Parameter estimation in stochastic differential mixed-effects models
-
06/12, Copenhagen: Department of Biostatistics, University of Copenhagen
-
Picchini, U., De Gaetano, A., & Ditlevsen, S. (2006). Parameter estimation in stochastic differential mixed-effects models (Tech. Rep. 06/12). Copenhagen: Department of Biostatistics, University of Copenhagen.
-
(2006)
Tech. Rep
-
-
Picchini, U.1
De Gaetano, A.2
Ditlevsen, S.3
-
39
-
-
55749099307
-
-
Pinheiro, J. C, Bates, D. M, DebRoy, S, Sarkar, D, & R Core Team, 2007, nlme: Linear and nonlinear mixed effects models. The R Foundation for Statistical Computing. R package version 3.1-86 available online at
-
Pinheiro, J. C., Bates, D. M., DebRoy, S., Sarkar, D., & R Core Team. (2007). nlme: Linear and nonlinear mixed effects models. The R Foundation for Statistical Computing. R package version 3.1-86 available online at http://www.r-project.org/.
-
-
-
-
40
-
-
0030051231
-
Experimental evaluation of input-output models of motoneuron discharge
-
Powers, R. K., & Binder, M. D. (1996). Experimental evaluation of input-output models of motoneuron discharge. J. Neurophysiol., 75, 367-379.
-
(1996)
J. Neurophysiol
, vol.75
, pp. 367-379
-
-
Powers, R.K.1
Binder, M.D.2
-
41
-
-
0141565240
-
Neocortical pyramidal cells respond as integrate-and fire neurons in vivo-like input currents
-
Rauch, A., La Camera, G., Lüscher, H.-R., Senn, W., & Fusi, S. (2003). Neocortical pyramidal cells respond as integrate-and fire neurons in vivo-like input currents. J. Neurophysiol., 90, 1598-1612.
-
(2003)
J. Neurophysiol
, vol.90
, pp. 1598-1612
-
-
Rauch, A.1
La Camera, G.2
Lüscher, H.-R.3
Senn, W.4
Fusi, S.5
-
43
-
-
0003126612
-
Table of the zeros and weight factors of the first twenty Hermite polynomials
-
Available online at
-
Salzer, H. E., Zucker, R., & Capuano, R. (1952). Table of the zeros and weight factors of the first twenty Hermite polynomials. Journal of Research of the National Bureau of Standards, 48, 111-116. Available online at http://nvl.nist.gov/pub/nistpubs/jres/048/2/V48.N02.A04.pdf.
-
(1952)
Journal of Research of the National Bureau of Standards
, vol.48
, pp. 111-116
-
-
Salzer, H.E.1
Zucker, R.2
Capuano, R.3
-
44
-
-
0033561846
-
The Ornstein-Uhlenbeck process does not reproduce spiking statistics of neurons in prefrontal cortex
-
Shinomoto, S., Sakai, Y., & Funahashi, S. (1999). The Ornstein-Uhlenbeck process does not reproduce spiking statistics of neurons in prefrontal cortex. Neural Comput., 11, 935-951.
-
(1999)
Neural Comput
, vol.11
, pp. 935-951
-
-
Shinomoto, S.1
Sakai, Y.2
Funahashi, S.3
-
45
-
-
23844485993
-
Stochastic differential equations in NONMEM: Implementation, application, and comparison with ordinary differential equations
-
Tornøe, C. W., Overgaard, R. V., Agersø, H., Nielsen, H. A., Madsen, H., & Jonsson, E. N. (2005). Stochastic differential equations in NONMEM: Implementation, application, and comparison with ordinary differential equations. Pharmaceutical Research, 22(8), 1247-1258.
-
(2005)
Pharmaceutical Research
, vol.22
, Issue.8
, pp. 1247-1258
-
-
Tornøe, C.W.1
Overgaard, R.V.2
Agersø, H.3
Nielsen, H.A.4
Madsen, H.5
Jonsson, E.N.6
-
46
-
-
0842277469
-
Introduction to theoretical neurobiology
-
Cambridge: Cambridge University Press
-
Tuckwell, H. C. (1988). Introduction to theoretical neurobiology, Vol. 2: Nonlinear and stochastic theories. Cambridge: Cambridge University Press.
-
(1988)
Nonlinear and stochastic theories
, vol.2
-
-
Tuckwell, H.C.1
-
47
-
-
0017799081
-
Neuronal interspike time distributions and the estimation of neurophysiological and neuroanatomical parameters
-
Tuckwell, H. C., & Richter, W. (1978). Neuronal interspike time distributions and the estimation of neurophysiological and neuroanatomical parameters. J. Theor. Biol., 71, 167-180.
-
(1978)
J. Theor. Biol
, vol.71
, pp. 167-180
-
-
Tuckwell, H.C.1
Richter, W.2
-
48
-
-
1642546600
-
Corticofugal gating of auditory information in the thalamus: An in vivo intracellular recording study
-
Yu, Y. Q., Xiong, Y., Chan, Y. S., & He, J. F. (2004). Corticofugal gating of auditory information in the thalamus: An in vivo intracellular recording study. J. Neurosci., 24, 3060-3069.
-
(2004)
J. Neurosci
, vol.24
, pp. 3060-3069
-
-
Yu, Y.Q.1
Xiong, Y.2
Chan, Y.S.3
He, J.F.4
|