A citation-based method for searching scientific literature

Gergő Orbán, Pietro Berkes, József Fiser, Máté Lengyel. Neuron 2016
Times Cited: 62







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



Times Cited
  Times     Co-cited
Similarity


Bayesian inference with probabilistic population codes.
Wei Ji Ma, Jeffrey M Beck, Peter E Latham, Alexandre Pouget. Nat Neurosci 2006
664
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
45

Statistically optimal perception and learning: from behavior to neural representations.
József Fiser, Pietro Berkes, Gergo Orbán, Máté Lengyel. Trends Cogn Sci 2010
291
43

Perceptual Decision-Making as Probabilistic Inference by Neural Sampling.
Ralf M Haefner, Pietro Berkes, József Fiser. Neuron 2016
68
29

Stimulus onset quenches neural variability: a widespread cortical phenomenon.
Mark M Churchland, Byron M Yu, John P Cunningham, Leo P Sugrue, Marlene R Cohen, Greg S Corrado, William T Newsome, Andrew M Clark, Paymon Hosseini, Benjamin B Scott,[...]. Nat Neurosci 2010
518
24

Probabilistic brains: knowns and unknowns.
Alexandre Pouget, Jeffrey M Beck, Wei Ji Ma, Peter E Latham. Nat Neurosci 2013
213
20

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
20

Information-limiting correlations.
Rubén Moreno-Bote, Jeffrey Beck, Ingmar Kanitscheider, Xaq Pitkow, Peter Latham, Alexandre Pouget. Nat Neurosci 2014
228
20

Partitioning neuronal variability.
Robbe L T Goris, J Anthony Movshon, Eero P Simoncelli. Nat Neurosci 2014
226
20

Probabilistic population codes for Bayesian decision making.
Jeffrey M Beck, Wei Ji Ma, Roozbeh Kiani, Tim Hanks, Anne K Churchland, Jamie Roitman, Michael N Shadlen, Peter E Latham, Alexandre Pouget. Neuron 2008
329
19


Hierarchical Bayesian inference in the visual cortex.
Tai Sing Lee, David Mumford. J Opt Soc Am A Opt Image Sci Vis 2003
518
17

State dependence of noise correlations in macaque primary visual cortex.
Alexander S Ecker, Philipp Berens, R James Cotton, Manivannan Subramaniyan, George H Denfield, Cathryn R Cadwell, Stelios M Smirnakis, Matthias Bethge, Andreas S Tolias. Neuron 2014
179
17

Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
767
17


The Bayesian brain: the role of uncertainty in neural coding and computation.
David C Knill, Alexandre Pouget. Trends Neurosci 2004
839
16



Not noisy, just wrong: the role of suboptimal inference in behavioral variability.
Jeffrey M Beck, Wei Ji Ma, Xaq Pitkow, Peter E Latham, Alexandre Pouget. Neuron 2012
133
12


Natural signal statistics and sensory gain control.
O Schwartz, E P Simoncelli. Nat Neurosci 2001
416
12

Bayesian integration in sensorimotor learning.
Konrad P Körding, Daniel M Wolpert. Nature 2004
853
12


Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
12

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

Reliability of spike timing in neocortical neurons.
Z F Mainen, T J Sejnowski. Science 1995
12

Decorrelated neuronal firing in cortical microcircuits.
Alexander S Ecker, Philipp Berens, Georgios A Keliris, Matthias Bethge, Nikos K Logothetis, Andreas S Tolias. Science 2010
361
12

Neural correlations, population coding and computation.
Bruno B Averbeck, Peter E Latham, Alexandre Pouget. Nat Rev Neurosci 2006
823
12

Flexible gating of contextual influences in natural vision.
Ruben Coen-Cagli, Adam Kohn, Odelia Schwartz. Nat Neurosci 2015
67
12


Measuring and interpreting neuronal correlations.
Marlene R Cohen, Adam Kohn. Nat Neurosci 2011
505
11

The Nature of Shared Cortical Variability.
I-Chun Lin, Michael Okun, Matteo Carandini, Kenneth D Harris. Neuron 2015
109
11

Attention stabilizes the shared gain of V4 populations.
Neil C Rabinowitz, Robbe L Goris, Marlene Cohen, Eero P Simoncelli. Elife 2015
83
11

Neural coding of uncertainty and probability.
Wei Ji Ma, Mehrdad Jazayeri. Annu Rev Neurosci 2014
106
11


Motion illusions as optimal percepts.
Yair Weiss, Eero P Simoncelli, Edward H Adelson. Nat Neurosci 2002
512
11

Stimulus-dependent variability and noise correlations in cortical MT neurons.
Adrián Ponce-Alvarez, Alexander Thiele, Thomas D Albright, Gene R Stoner, Gustavo Deco. Proc Natl Acad Sci U S A 2013
62
11

Bayesian sampling in visual perception.
Rubén Moreno-Bote, David C Knill, Alexandre Pouget. Proc Natl Acad Sci U S A 2011
71
9

Marginalization in neural circuits with divisive normalization.
Jeffrey M Beck, Peter E Latham, Alexandre Pouget. J Neurosci 2011
72
9


Performance-optimized hierarchical models predict neural responses in higher visual cortex.
Daniel L K Yamins, Ha Hong, Charles F Cadieu, Ethan A Solomon, Darren Seibert, James J DiCarlo. Proc Natl Acad Sci U S A 2014
436
9


On the Structure of Neuronal Population Activity under Fluctuations in Attentional State.
Alexander S Ecker, George H Denfield, Matthias Bethge, Andreas S Tolias. J Neurosci 2016
39
15

Optimal representation of sensory information by neural populations.
Mehrdad Jazayeri, J Anthony Movshon. Nat Neurosci 2006
302
9

Origin of information-limiting noise correlations.
Ingmar Kanitscheider, Ruben Coen-Cagli, Alexandre Pouget. Proc Natl Acad Sci U S A 2015
49
12

Correlations and Neuronal Population Information.
Adam Kohn, Ruben Coen-Cagli, Ingmar Kanitscheider, Alexandre Pouget. Annu Rev Neurosci 2016
121
9


With or without you: predictive coding and Bayesian inference in the brain.
Laurence Aitchison, Máté Lengyel. Curr Opin Neurobiol 2017
57
10

The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability.
Guillaume Hennequin, Yashar Ahmadian, Daniel B Rubin, Máté Lengyel, Kenneth D Miller. Neuron 2018
30
20

Vision as Bayesian inference: analysis by synthesis?
Alan Yuille, Daniel Kersten. Trends Cogn Sci 2006
275
8


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.