A citation-based method for searching scientific literature

Stefan Mihalaş, Ernst Niebur. Neural Comput 2009
Times Cited: 49







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



Times Cited
  Times     Co-cited
Similarity


Simple model of spiking neurons.
E M Izhikevich. IEEE Trans Neural Netw 2003
906
44


Which model to use for cortical spiking neurons?
Eugene M Izhikevich. IEEE Trans Neural Netw 2004
488
36


Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model.
Liam Paninski, Jonathan W Pillow, Eero P Simoncelli. Neural Comput 2004
153
22

Neuroscience. How good are neuron models?
Wulfram Gerstner, Richard Naud. Science 2009
103
22

Predicting spike timing of neocortical pyramidal neurons by simple threshold models.
Renaud Jolivet, Alexander Rauch, Hans-Rudolf Lüscher, Wulfram Gerstner. J Comput Neurosci 2006
115
20


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
73
18


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
115
14


Firing patterns in the adaptive exponential integrate-and-fire model.
Richard Naud, Nicolas Marcille, Claudia Clopath, Wulfram Gerstner. Biol Cybern 2008
107
14

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
12

Resonate-and-fire neurons.
E M Izhikevich. Neural Netw 2001
148
12


A silicon neuron.
M Mahowald, R Douglas. Nature 1991
124
12

A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity.
Giacomo Indiveri, Elisabetta Chicca, Rodney Douglas. IEEE Trans Neural Netw 2006
180
12

Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses.
R Jacob Vogelstein, Udayan Mallik, Joshua T Vogelstein, Gert Cauwenberghs. IEEE Trans Neural Netw 2007
53
12

Reliability of spike timing in neocortical neurons.
Z F Mainen, T J Sejnowski. Science 1995
10


The blue brain project.
Henry Markram. Nat Rev Neurosci 2006
380
10

Simulation of networks of spiking neurons: a review of tools and strategies.
Romain Brette, Michelle Rudolph, Ted Carnevale, Michael Hines, David Beeman, James M Bower, Markus Diesmann, Abigail Morrison, Philip H Goodman, Frederick C Harris,[...]. J Comput Neurosci 2007
257
10


The quantitative single-neuron modeling competition.
Renaud Jolivet, Felix Schürmann, Thomas K Berger, Richard Naud, Wulfram Gerstner, Arnd Roth. Biol Cybern 2008
61
10

Efficient estimation of detailed single-neuron models.
Quentin J M Huys, Misha B Ahrens, Liam Paninski. J Neurophysiol 2006
73
10

Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold.
Ryota Kobayashi, Yasuhiro Tsubo, Shigeru Shinomoto. Front Comput Neurosci 2009
72
10

A library of analog operators based on the hodgkin-huxley formalism for the design of tunable, real-time, silicon neurons.
S Saïghi, Y Bornat, J Tomas, G Le Masson, S Renaud. IEEE Trans Biomed Circuits Syst 2011
20
25

Synaptic dynamics in analog VLSI.
Chiara Bartolozzi, Giacomo Indiveri. Neural Comput 2007
72
10


Neuromorphic silicon neuron circuits.
Giacomo Indiveri, Bernabé Linares-Barranco, Tara Julia Hamilton, André van Schaik, Ralph Etienne-Cummings, Tobi Delbruck, Shih-Chii Liu, Piotr Dudek, Philipp Häfliger, Sylvie Renaud,[...]. Front Neurosci 2011
226
10

Estimating parameters of generalized integrate-and-fire neurons from the maximum likelihood of spike trains.
Yi Dong, Stefan Mihalas, Alexander Russell, Ralph Etienne-Cummings, Ernst Niebur. Neural Comput 2011
8
62

Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.
Paul A Merolla, John V Arthur, Rodrigo Alvarez-Icaza, Andrew S Cassidy, Jun Sawada, Filipp Akopyan, Bryan L Jackson, Nabil Imam, Chen Guo, Yutaka Nakamura,[...]. Science 2014
447
10

A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.
Ning Qiao, Hesham Mostafa, Federico Corradi, Marc Osswald, Fabio Stefanini, Dora Sumislawska, Giacomo Indiveri. Front Neurosci 2015
95
10

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
30


Large-scale model of mammalian thalamocortical systems.
Eugene M Izhikevich, Gerald M Edelman. Proc Natl Acad Sci U S A 2008
390
8



Conveying tactile feedback in sensorized hand neuroprostheses using a biofidelic model of mechanotransduction.
Sung Soo Kim, A P Sripati, R J Vogelstein, R S Armiger, A F Russell, S J Bensmaia. IEEE Trans Biomed Circuits Syst 2009
20
20

The neural coding of stimulus intensity: linking the population response of mechanoreceptive afferents with psychophysical behavior.
Michael A Muniak, Supratim Ray, Steven S Hsiao, J Frank Dammann, Sliman J Bensmaia. J Neurosci 2007
106
8


Synchrony in silicon: the gamma rhythm.
John V Arthur, Kwabena A Boahen. IEEE Trans Neural Netw 2007
20
20

Predicting the timing of spikes evoked by tactile stimulation of the hand.
Sung Soo Kim, Arun P Sripati, Sliman J Bensmaia. J Neurophysiol 2010
32
12

Compact silicon neuron circuit with spiking and bursting behaviour.
Jayawan H B Wijekoon, Piotr Dudek. Neural Netw 2008
42
9

A subthreshold aVLSI implementation of the Izhikevich simple neuron model.
Venkat Rangan, Abhishek Ghosh, Vladimir Aparin, Gert Cauwenberghs. Annu Int Conf IEEE Eng Med Biol Soc 2010
12
33


Optimization methods for spiking neurons and networks.
Alexander Russell, Garrick Orchard, Yi Dong, Stefan Mihalas, Ernst Niebur, Jonathan Tapson, Ralph Etienne-Cummings. IEEE Trans Neural Netw 2010
13
30




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.