A citation-based method for searching scientific literature

Brett Vintch, J Anthony Movshon, Eero P Simoncelli. J Neurosci 2015
Times Cited: 34







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



Times Cited
  Times     Co-cited
Similarity


Spatiotemporal elements of macaque v1 receptive fields.
Nicole C Rust, Odelia Schwartz, J Anthony Movshon, Eero P Simoncelli. Neuron 2005
260
55

Spatiotemporal energy models for the perception of motion.
E H Adelson, J R Bergen. J Opt Soc Am A 1985
50

Spike-triggered neural characterization.
Odelia Schwartz, Jonathan W Pillow, Nicole C Rust, Eero P Simoncelli. J Vis 2006
238
47

Inferring nonlinear neuronal computation based on physiologically plausible inputs.
James M McFarland, Yuwei Cui, Daniel A Butts. PLoS Comput Biol 2013
73
44


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
585
32


Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
751
32

Do we know what the early visual system does?
Matteo Carandini, Jonathan B Demb, Valerio Mante, David J Tolhurst, Yang Dan, Bruno A Olshausen, Jack L Gallant, Nicole C Rust. J Neurosci 2005
272
29




Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
296
26

Deep Learning Models of the Retinal Response to Natural Scenes.
Lane T McIntosh, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, Stephen A Baccus. Adv Neural Inf Process Syst 2016
38
26


Mapping nonlinear receptive field structure in primate retina at single cone resolution.
Jeremy Freeman, Greg D Field, Peter H Li, Martin Greschner, Deborah E Gunning, Keith Mathieson, Alexander Sher, Alan M Litke, Liam Paninski, Eero P Simoncelli,[...]. Elife 2015
39
23

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
414
23

Predicting neuronal responses during natural vision.
Stephen V David, Jack L Gallant. Network 2005
86
23

Analyzing neural responses to natural signals: maximally informative dimensions.
Tatyana Sharpee, Nicole C Rust, William Bialek. Neural Comput 2004
178
20

Nonlinear V1 responses to natural scenes revealed by neural network analysis.
Ryan Prenger, Michael C-K Wu, Stephen V David, Jack L Gallant. Neural Netw 2004
39
20

Neural representation of natural images in visual area V2.
Ben D B Willmore, Ryan J Prenger, Jack L Gallant. J Neurosci 2010
69
20


Identifying functional bases for multidimensional neural computations.
Joel Kaardal, Jeffrey D Fitzgerald, Michael J Berry, Tatyana O Sharpee. Neural Comput 2013
17
41

Complete functional characterization of sensory neurons by system identification.
Michael C-K Wu, Stephen V David, Jack L Gallant. Annu Rev Neurosci 2006
162
20


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
190
17



Receptive field inference with localized priors.
Mijung Park, Jonathan W Pillow. PLoS Comput Biol 2011
36
17

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
17

Second order dimensionality reduction using minimum and maximum mutual information models.
Jeffrey D Fitzgerald, Ryan J Rowekamp, Lawrence C Sincich, Tatyana O Sharpee. PLoS Comput Biol 2011
37
17

Adaptive filtering enhances information transmission in visual cortex.
Tatyana O Sharpee, Hiroki Sugihara, Andrei V Kurgansky, Sergei P Rebrik, Michael P Stryker, Kenneth D Miller. Nature 2006
198
17

Characterizing responses of translation-invariant neurons to natural stimuli: maximally informative invariant dimensions.
Michael Eickenberg, Ryan J Rowekamp, Minjoon Kouh, Tatyana O Sharpee. Neural Comput 2012
13
46

Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
918
17

Model Constrained by Visual Hierarchy Improves Prediction of Neural Responses to Natural Scenes.
Ján Antolík, Sonja B Hofer, James A Bednar, Thomas D Mrsic-Flogel. PLoS Comput Biol 2016
15
40



Computational identification of receptive fields.
Tatyana O Sharpee. Annu Rev Neurosci 2013
43
14

Linearity of cortical receptive fields measured with natural sounds.
Christian K Machens, Michael S Wehr, Anthony M Zador. J Neurosci 2004
192
14




The spatial structure of a nonlinear receptive field.
Gregory W Schwartz, Haruhisa Okawa, Felice A Dunn, Josh L Morgan, Daniel Kerschensteiner, Rachel O Wong, Fred Rieke. Nat Neurosci 2012
118
14

The receptive-field organization of simple cells in primary visual cortex of ferrets under natural scene stimulation.
Darragh Smyth, Ben Willmore, Gary E Baker, Ian D Thompson, David J Tolhurst. J Neurosci 2003
89
14

Hierarchical models of object recognition in cortex.
M Riesenhuber, T Poggio. Nat Neurosci 1999
14

Triggered correlation.
R de Boer, P Kuyper. IEEE Trans Biomed Eng 1968
291
14

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
309
14

Deep neural networks rival the representation of primate IT cortex for core visual object recognition.
Charles F Cadieu, Ha Hong, Daniel L K Yamins, Nicolas Pinto, Diego Ardila, Ethan A Solomon, Najib J Majaj, James J DiCarlo. PLoS Comput Biol 2014
173
14




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.