-
2
-
-
35248866865
-
Simulation of networks of spiking neurons: A review of tools and strategies
-
Brette, R., Rudolph, M., Carnevale, T., Hines, M., Beeman, D., et al. (2007). Simulation of networks of spiking neurons: A review of tools and strategies. Journal of Computational Neuroscience, 23, 349-398.
-
(2007)
Journal of Computational Neuroscience
, vol.23
, pp. 349-398
-
-
Brette, R.1
Rudolph, M.2
Carnevale, T.3
Hines, M.4
Beeman, D.5
-
3
-
-
34147171012
-
Interoperability of neuroscience modeling software: Current status and future directions
-
Cannon, R. C, Gewaltig, M., Gleeson, P., Bhalla, U. S., Cornelis, N. H., et al. (2007). Interoperability of neuroscience modeling software: Current status and future directions. Neuroinformatics, 5(2), 127-138.
-
(2007)
Neuroinformatics
, vol.5
, Issue.2
, pp. 127-138
-
-
Cannon, R.C.1
Gewaltig, M.2
Gleeson, P.3
Bhalla, U.S.4
Cornelis, N.H.5
-
5
-
-
84887302917
-
PyNN: A common interface for neuronal network simulators
-
Davison, A. P., Briderle, D., Eppler, J., Kremkow, J., Muller, E., et al. (2008). PyNN: A common interface for neuronal network simulators. Frontiers in Neuroinformatics, 2, 11.
-
(2008)
Frontiers in Neuroinformatics
, vol.2
, pp. 11
-
-
Davison, A.P.1
Briderle, D.2
Eppler, J.3
Kremkow, J.4
Muller, E.5
-
6
-
-
37749042762
-
Bayesian spiking neurons I: Inference
-
Deneve, S. (2008). Bayesian spiking neurons I: Inference. Neural Computation, 20(1), 91-117.
-
(2008)
Neural Computation
, vol.20
, Issue.1
, pp. 91-117
-
-
Deneve, S.1
-
7
-
-
0002236344
-
An efficient method for computing synaptic conductances based on a kinetic model of receptor binding
-
Destexhe, A., Mainen, Z., & Sejnowski, T. (1994a). An efficient method for computing synaptic conductances based on a kinetic model of receptor binding. Neural Computation, 6(1), 14-18.
-
(1994)
Neural Computation
, vol.6
, Issue.1
, pp. 14-18
-
-
Destexhe, A.1
Mainen, Z.2
Sejnowski, T.3
-
8
-
-
0028490340
-
Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism
-
Destexhe, A., Mainen, Z. F., & Sejnowski, T. J. (1994b). Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism. Journal of Computational Neuroscience, 1(3), 195-230.
-
(1994)
Journal of Computational Neuroscience
, vol.1
, Issue.3
, pp. 195-230
-
-
Destexhe, A.1
Mainen, Z.F.2
Sejnowski, T.J.3
-
9
-
-
77953494546
-
Fast and exact simulation methods applied on a broad range of neuron models
-
D'Haene, M., & Schrauwen, B. (2010). Fast and exact simulation methods applied on a broad range of neuron models. Neural Computation, 22(6), 1468-1472.
-
(2010)
Neural Computation
, vol.22
, Issue.6
, pp. 1468-1472
-
-
D'haene, M.1
Schrauwen, B.2
-
11
-
-
84890861283
-
PyNEST: A convenient interface to the NEST simulator
-
Eppler, J. M., Helias, M., Muller, E., Diesmann, M., & Gewaltig, M. (2008). PyNEST: A convenient interface to the NEST simulator. Frontiers in Neuroinformatics, 2,12.
-
(2008)
Frontiers in Neuroinformatics
, vol.2
, pp. 12
-
-
Eppler, J.M.1
Helias, M.2
Muller, E.3
Diesmann, M.4
Gewaltig, M.5
-
12
-
-
48349089965
-
CellML and associated tools and techniques
-
Garny, A., Nickerson, D. P., Cooper, J., dos Santos, R. W., Miller, A. K., et al. (2008). CellML and associated tools and techniques. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 366(1878), 3017-3043.
-
(2008)
Philosophical Transactions. Series A, Mathematical, Physical and Engineering Sciences
, vol.366
, Issue.1878
, pp. 3017-3043
-
-
Garny, A.1
Nickerson, D.P.2
Cooper, J.3
dos Santos, R.W.4
Miller, A.K.5
-
14
-
-
43949092150
-
NEST (NEural Simulation Tool)
-
Gewaltig, O., & Diesmann, M. (2007). NEST (NEural Simulation Tool). Scholarpe-dia, 2(4), 1430.
-
(2007)
Scholarpedia
, vol.2
, Issue.4
, pp. 1430
-
-
Gewaltig, O.1
Diesmann, M.2
-
15
-
-
0034166633
-
Synthesis of generalized algorithms for the fast computation of synaptic conductances with Markov kinetic models in large network simulations
-
Giugliano, M. (2000). Synthesis of generalized algorithms for the fast computation of synaptic conductances with Markov kinetic models in large network simulations. Neural Computation, 12(4), 903-931.
-
(2000)
Neural Computation
, vol.12
, Issue.4
, pp. 903-931
-
-
Giugliano, M.1
-
16
-
-
0033566452
-
Fast calculation of short-term depressing synaptic conductances
-
Giugliano, M., Bove, M., & Grattarola, M. (1999). Fast calculation of short-term depressing synaptic conductances. Neural Computation, 11(6), 1413-1426.
-
(1999)
Neural Computation
, vol.11
, Issue.6
, pp. 1413-1426
-
-
Giugliano, M.1
Bove, M.2
Grattarola, M.3
-
17
-
-
0035968419
-
Towards NeuroML: Model description methods for collaborative modelling in neuroscience
-
Goddard, N. H., Hucka, M., Howell, F., Cornelis, H., Shankar, K., et al. (2001). Towards NeuroML: Model description methods for collaborative modelling in neuroscience. Philosophical Transactions of the Royal Society of London. Series B, Biolomcal Sciences, 356,1209-1228.
-
(2001)
Philosophical Transactions of the Royal Society of London. Series B, Biolomcal Sciences
, vol.356
, pp. 1209-1228
-
-
Goddard, N.H.1
Hucka, M.2
Howell, F.3
Cornelis, H.4
Shankar, K.5
-
18
-
-
84885847922
-
Brian: A simulator for spiking neural networks in Python
-
Goodman, D., & Brette, R. (2008). Brian: A simulator for spiking neural networks in Python. Frontiers in Neuroinformatics, 2, 5.
-
(2008)
Frontiers in Neuroinformatics
, vol.2
, pp. 5
-
-
Goodman, D.1
Brette, R.2
-
19
-
-
84892640984
-
The Brian simulator
-
Goodman, D. F. M., & Brette, R. (2009). The Brian simulator. Frontiers in Neuroscience, 3(2), 192-197.
-
(2009)
Frontiers in Neuroscience
, vol.3
, Issue.2
, pp. 192-197
-
-
Goodman, D.F.M.1
Brette, R.2
-
20
-
-
79958294115
-
A general and efficient method for incorporating precise spike times in globally time-driven simulations
-
Hanuschkin, A., Kunkel, S., Helias, M., Morrison, A., & Diesmann, M. (2010). A general and efficient method for incorporating precise spike times in globally time-driven simulations. Frontiers in Neuroinformatics, 4(0), 12.
-
(2010)
Frontiers in Neuroinformatics
, vol.4
, Issue.0
, pp. 12
-
-
Hanuschkin, A.1
Kunkel, S.2
Helias, M.3
Morrison, A.4
Diesmann, M.5
-
21
-
-
0021322056
-
Efficient computation of branched nerve equations
-
Hines, M. (1984). Efficient computation of branched nerve equations. International Journal of Bio-Medical Computing, 15(1), 69-76.
-
(1984)
International Journal of Bio-Medical Computing
, vol.15
, Issue.1
, pp. 69-76
-
-
Hines, M.1
-
22
-
-
0034180688
-
Expanding NEURON's repertoire of mechanisms with NMODL
-
Hines, M. L., & Carnevale, N. T. (2000). Expanding NEURON's repertoire of mechanisms with NMODL. Neural Computation, 12(5), 995-1007.
-
(2000)
Neural Computation
, vol.12
, Issue.5
, pp. 995-1007
-
-
Hines, M.L.1
Carnevale, N.T.2
-
23
-
-
77955504196
-
NEURON and Python
-
Hines, M. L., Davison, A. P., & Muller, E. (2009). NEURON and Python. Frontiers in Neuroinformatics 3,1.
-
(2009)
Frontiers in Neuroinformatics
, vol.3
, pp. 1
-
-
Hines, M.L.1
Davison, A.P.2
Muller, E.3
-
24
-
-
0003779190
-
-
Orlando, FL: Academic Press
-
Hirsch, M., & Smale, S. (1974). Differential equations, dynamical systems, and linear algebra. Orlando, FL: Academic Press.
-
(1974)
Differential equations, dynamical systems, and linear algebra
-
-
Hirsch, M.1
Smale, S.2
-
25
-
-
33644898137
-
Polychronization: Computation with spikes
-
Izhikevich, E. M. (2006). Polychronization: Computation with spikes. Neural Computation, 18(2), 245-282.
-
(2006)
Neural Computation
, vol.18
, Issue.2
, pp. 245-282
-
-
Izhikevich, E.M.1
-
26
-
-
33750113770
-
Digital simulation of spiking neural networks
-
W. Maass & C. M. Bishop (Eds.), Cambridge, MA: MIT Press
-
Jahnke, A., Roth, U., & Schnauer, T. (1999). Digital simulation of spiking neural networks. In W. Maass & C. M. Bishop (Eds.), Pulsed neural networks (pp. 237-257). Cambridge, MA: MIT Press.
-
(1999)
Pulsed neural networks
, pp. 237-257
-
-
Jahnke, A.1
Roth, U.2
Schnauer, T.3
-
27
-
-
0032184981
-
Employing the Z-Transform to optimize the calculation of the synaptic conductance of NMDA and other synaptic channels in network simulations
-
Köhn, J., & Wörgötter, F. (1998). Employing the Z-Transform to optimize the calculation of the synaptic conductance of NMDA and other synaptic channels in network simulations. Neural Computation, 10(7), 1639-1651.
-
(1998)
Neural Computation
, vol.10
, Issue.7
, pp. 1639-1651
-
-
Köhn, J.1
Wörgötter, F.2
-
28
-
-
0036749743
-
Computation by ensemble synchronization in recurrent networks with synaptic depression
-
Loebel, A., & Tsodyks, M. (2002). Computation by ensemble synchronization in recurrent networks with synaptic depression. Journal of Computational Neuroscience, 13(2), 111-124.
-
(2002)
Journal of Computational Neuroscience
, vol.13
, Issue.2
, pp. 111-124
-
-
Loebel, A.1
Tsodyks, M.2
-
29
-
-
0030115144
-
Optimizing synaptic conductance calculation for network simulations
-
Lytton, W. W. (1996). Optimizing synaptic conductance calculation for network simulations. Neural Computation, 8(3), 501-509.
-
(1996)
Neural Computation
, vol.8
, Issue.3
, pp. 501-509
-
-
Lytton, W.W.1
-
30
-
-
0032574789
-
Differential signaling via the same axon of neocortical pyramidal neurons
-
Markram, H., Wang, Y, & Tsodyks, M. (1998). Differential signaling via the same axon of neocortical pyramidal neurons. Proceedings of the National Academy of Sciences of the United States of America, 95(9), 5323-5328.
-
(1998)
Proceedings of the National Academy of Sciences of the United States of America
, vol.95
, Issue.9
, pp. 5323-5328
-
-
Markram, H.1
Wang, Y.2
Tsodyks, M.3
-
31
-
-
40849102598
-
Synaptic theory of working memory
-
Mongillo, G., Barak, O, & Tsodyks, M. (2008). Synaptic theory of working memory. Science, 319(5869), 1543-1546.
-
(2008)
Science
, vol.319
, Issue.5869
, pp. 1543-1546
-
-
Mongillo, G.1
Barak, O.2
Tsodyks, M.3
-
32
-
-
34249703480
-
Spike-timing-dependent plasticity in balanced random networks
-
Morrison, A., Aertsen, A., & Diesmann, M. (2007). Spike-timing-dependent plasticity in balanced random networks. Neural Computation, 19(6), 1437-1467.
-
(2007)
Neural Computation
, vol.19
, Issue.6
, pp. 1437-1467
-
-
Morrison, A.1
Aertsen, A.2
Diesmann, M.3
-
33
-
-
43949102027
-
Phenomenological models of synaptic plasticity based on spike timing
-
Morrison, A., Diesmann, M., & Gerstner, W. (2008). Phenomenological models of synaptic plasticity based on spike timing. Biological Cybernetics, 98(6), 459-478.
-
(2008)
Biological Cybernetics
, vol.98
, Issue.6
, pp. 459-478
-
-
Morrison, A.1
Diesmann, M.2
Gerstner, W.3
-
34
-
-
20844460509
-
Advancing the boundaries of high connectivity network simulation with distributed computing
-
Morrison, A., Mehring, C, Geisel, T., Aertsen, A., & Diesmann, M. (2005). Advancing the boundaries of high connectivity network simulation with distributed computing. Neural Computation, 17,1776-1801.
-
(2005)
Neural Computation
, vol.17
, pp. 1776-1801
-
-
Morrison, A.1
Mehring, C.2
Geisel, T.3
Aertsen, A.4
Diesmann, M.5
-
35
-
-
33846013910
-
Exact subthreshold integration with continuous spike times in discrete-time neural network simulations
-
Morrison, A., Straube, S., Plesser, H. E., & Diesmann, M. (2007). Exact subthreshold integration with continuous spike times in discrete-time neural network simulations. Neural Computation, 19,47-79.
-
(2007)
Neural Computation
, vol.19
, pp. 47-79
-
-
Morrison, A.1
Straube, S.2
Plesser, H.E.3
Diesmann, M.4
-
36
-
-
76449115517
-
Model sharing in computational neuroscience
-
Morse, T. (2007). Model sharing in computational neuroscience. Scholarpedia, 2(4), 3036.
-
(2007)
Scholarpedia
, vol.2
, Issue.4
, pp. 3036
-
-
Morse, T.1
-
37
-
-
33947588048
-
A survey of general-purpose computation on graphics hardware
-
Owens, J. D., Luebke, D., Govindaraju, N., Harris, M., Krüger, J., et al. (2007). A survey of general-purpose computation on graphics hardware. Computer Graphics Forum, 26(1), 80-113.
-
(2007)
Computer Graphics Forum
, vol.26
, Issue.1
, pp. 80-113
-
-
Owens, J.D.1
Luebke, D.2
Govindaraju, N.3
Harris, M.4
Krüger, J.5
-
38
-
-
78049262157
-
A threshold equation for action potential initiation
-
Platkiewicz, J., & Brette, R. (2010). A threshold equation for action potential initiation. PLoS Comput. Biol, 6(7), e1000850.
-
(2010)
PLoS Comput. Biol
, vol.6
, Issue.7
-
-
Platkiewicz, J.1
Brette, R.2
-
39
-
-
67650317451
-
Simplicity and efficiency of integrate-and-fire neuron models
-
Plesser, H. E., & Diesmann, M. (2009). Simplicity and efficiency of integrate-and-fire neuron models. Neural Computation, 21(2), 353-359.
-
(2009)
Neural Computation
, vol.21
, Issue.2
, pp. 353-359
-
-
Plesser, H.E.1
Diesmann, M.2
-
40
-
-
0003378339
-
Simulating large networks of neurons
-
C. Koch & I. Segev (Eds.), (2nd ed.). Cambridge, MA: MIT Press
-
Protopapas, A., Vanier, M., & Bower, J. (1998). Simulating large networks of neurons. In C. Koch & I. Segev (Eds.), Methods in neuronal modeling: From ions to networks (2nd ed.). Cambridge, MA: MIT Press.
-
(1998)
Methods in neuronal modeling: From ions to networks
-
-
Protopapas, A.1
Vanier, M.2
Bower, J.3
-
41
-
-
84890866325
-
Automatic fitting of spiking neuron models to electrophysiological recordings
-
Rossant, C, Goodman, D. F. M., Platkiewicz, J., & Brette, R. (2010). Automatic fitting of spiking neuron models to electrophysiological recordings. Frontiers in Neuroinformatics, 4, 2.
-
(2010)
Frontiers in Neuroinformatics
, vol.4
, pp. 2
-
-
Rossant, C.1
Goodman, D.F.M.2
Platkiewicz, J.3
Brette, R.4
-
42
-
-
0033220632
-
Exact digital simulation of time-invariant linear systems with applications to neuronal modeling
-
Rotter, S., & Diesmann, M. (1999). Exact digital simulation of time-invariant linear systems with applications to neuronal modeling. Biolomcal Cybernetics, 81(5-6), 381-402.
-
(1999)
Biolomcal Cybernetics
, vol.81
, Issue.5-6
, pp. 381-402
-
-
Rotter, S.1
Diesmann, M.2
-
44
-
-
44949119436
-
Why are computational neuroscience and systems biology so separate?
-
Schutter, E. D. (2008). Why are computational neuroscience and systems biology so separate? PLoS Comput. Biol., 4(5), e1000078.
-
(2008)
PLoS Comput. Biol.
, vol.4
, Issue.5
-
-
Schutter, E.D.1
-
45
-
-
0033860923
-
Competitive Hebbian learning through spike-timing-dependent synaptic plasticity
-
Song, S., Miller, K. D., & Abbott, L. F. (2000). Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nature Neurosci., 3,919-926.
-
(2000)
Nature Neurosci.
, vol.3
, pp. 919-926
-
-
Song, S.1
Miller, K.D.2
Abbott, L.F.3
-
46
-
-
0031018015
-
The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability
-
Tsodyks, M. V., & Markram, H. (1997). The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. PNAS, 94(2), 719-723.
-
(1997)
PNAS
, vol.94
, Issue.2
, pp. 719-723
-
-
Tsodyks, M.V.1
Markram, H.2
-
47
-
-
0032523457
-
Neural networks with dynamic synapses
-
Tsodyks, M., Pawelzik, K., & Markram, H. (1998). Neural networks with dynamic synapses. Neural Computation, 10(4), 821-835.
-
(1998)
Neural Computation
, vol.10
, Issue.4
, pp. 821-835
-
-
Tsodyks, M.1
Pawelzik, K.2
Markram, H.3
|