A citation-based method for searching scientific literature

Renaud Jolivet, Alexander Rauch, Hans-Rudolf Lüscher, Wulfram Gerstner. J Comput Neurosci 2006
Times Cited: 114







List of co-cited articles
801 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Spatio-temporal correlations and visual signalling in a complete neuronal population.
Jonathan W Pillow, Jonathon Shlens, Liam Paninski, Alexander Sher, Alan M Litke, E J Chichilnisky, Eero P Simoncelli. Nature 2008
590
26


Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model.
Jonathan W Pillow, Liam Paninski, Valerie J Uzzell, Eero P Simoncelli, E J Chichilnisky. J Neurosci 2005
191
24


How spike generation mechanisms determine the neuronal response to fluctuating inputs.
Nicolas Fourcaud-Trocmé, David Hansel, Carl van Vreeswijk, Nicolas Brunel. J Neurosci 2003
269
20

Reliability of spike timing in neocortical neurons.
Z F Mainen, T J Sejnowski. Science 1995
20

Neuroscience. How good are neuron models?
Wulfram Gerstner, Richard Naud. Science 2009
103
20



Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms.
Skander Mensi, Richard Naud, Christian Pozzorini, Michael Avermann, Carl C H Petersen, Wulfram Gerstner. J Neurophysiol 2012
45
42

Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces.
Laurent Badel, Sandrine Lefort, Romain Brette, Carl C H Petersen, Wulfram Gerstner, Magnus J E Richardson. J Neurophysiol 2008
114
18

A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects.
Wilson Truccolo, Uri T Eden, Matthew R Fellows, John P Donoghue, Emery N Brown. J Neurophysiol 2005
487
18

Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents.
Alexander Rauch, Giancarlo La Camera, Hans-Rudolf Luscher, Walter Senn, Stefano Fusi. J Neurophysiol 2003
153
17

Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model.
Liam Paninski, Jonathan W Pillow, Eero P Simoncelli. Neural Comput 2004
153
16

Simple model of spiking neurons.
E M Izhikevich. IEEE Trans Neural Netw 2003
903
15

Predicting every spike: a model for the responses of visual neurons.
J Keat, P Reinagel, R C Reid, M Meister. Neuron 2001
202
14


Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons.
A Destexhe, M Rudolph, J M Fellous, T J Sejnowski. Neuroscience 2001
366
14

A benchmark test for a quantitative assessment of simple neuron models.
Renaud Jolivet, Ryota Kobayashi, Alexander Rauch, Richard Naud, Shigeru Shinomoto, Wulfram Gerstner. J Neurosci Methods 2008
71
19


Which model to use for cortical spiking neurons?
Eugene M Izhikevich. IEEE Trans Neural Netw 2004
487
13

Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold.
Ryota Kobayashi, Yasuhiro Tsubo, Shigeru Shinomoto. Front Comput Neurosci 2009
71
18

A universal model for spike-frequency adaptation.
Jan Benda, Andreas V M Herz. Neural Comput 2003
232
12

The high-conductance state of neocortical neurons in vivo.
Alain Destexhe, Michael Rudolph, Denis Paré. Nat Rev Neurosci 2003
648
12

Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning.
Jean-Pascal Pfister, Taro Toyoizumi, David Barber, Wulfram Gerstner. Neural Comput 2006
105
12

Noise in the nervous system.
A Aldo Faisal, Luc P J Selen, Daniel M Wolpert. Nat Rev Neurosci 2008
12


Neuronal circuits of the neocortex.
Rodney J Douglas, Kevan A C Martin. Annu Rev Neurosci 2004
926
12

Temporal whitening by power-law adaptation in neocortical neurons.
Christian Pozzorini, Richard Naud, Skander Mensi, Wulfram Gerstner. Nat Neurosci 2013
92
13

Gain modulation from background synaptic input.
Frances S Chance, L F Abbott, Alex D Reyes. Neuron 2002
655
11

The quantitative single-neuron modeling competition.
Renaud Jolivet, Felix Schürmann, Thomas K Berger, Richard Naud, Wulfram Gerstner, Arnd Roth. Biol Cybern 2008
59
18


Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity.
Bernhard Nessler, Michael Pfeiffer, Lars Buesing, Wolfgang Maass. PLoS Comput Biol 2013
88
12


Efficient estimation of detailed single-neuron models.
Quentin J M Huys, Misha B Ahrens, Liam Paninski. J Neurophysiol 2006
72
13




Rate, timing, and cooperativity jointly determine cortical synaptic plasticity.
P J Sjöström, G G Turrigiano, S B Nelson. Neuron 2001
619
10

Fractional differentiation by neocortical pyramidal neurons.
Brian N Lundstrom, Matthew H Higgs, William J Spain, Adrienne L Fairhall. Nat Neurosci 2008
140
10

Interneurons of the neocortical inhibitory system.
Henry Markram, Maria Toledo-Rodriguez, Yun Wang, Anirudh Gupta, Gilad Silberberg, Caizhi Wu. Nat Rev Neurosci 2004
10

Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons.
Lars Buesing, Johannes Bill, Bernhard Nessler, Wolfgang Maass. PLoS Comput Biol 2011
107
10


A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data.
Shaul Druckmann, Yoav Banitt, Albert Gidon, Felix Schürmann, Henry Markram, Idan Segev. Front Neurosci 2007
144
9


Improved similarity measures for small sets of spike trains.
Richard Naud, Felipe Gerhard, Skander Mensi, Wulfram Gerstner. Neural Comput 2011
18
50

Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment.
Pietro Berkes, Gergo Orbán, Máté Lengyel, József Fiser. Science 2011
310
9

From subthreshold to firing-rate resonance.
Magnus J E Richardson, Nicolas Brunel, Vincent Hakim. J Neurophysiol 2003
153
8

A stochastic model of the repetitive activity of neurons.
C D Geisler, J M Goldberg. Biophys J 1966
83
9

State space method for predicting the spike times of a neuron.
Ryota Kobayashi, Shigeru Shinomoto. Phys Rev E Stat Nonlin Soft Matter Phys 2007
13
61


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.