A citation-based method for searching scientific literature

Lane T McIntosh, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, Stephen A Baccus. Adv Neural Inf Process Syst 2016
Times Cited: 38







List of co-cited articles
356 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
585
36

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
296
31


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
28

Spike-triggered neural characterization.
Odelia Schwartz, Jonathan W Pillow, Nicole C Rust, Eero P Simoncelli. J Vis 2006
238
26

A Convolutional Subunit Model for Neuronal Responses in Macaque V1.
Brett Vintch, J Anthony Movshon, Eero P Simoncelli. J Neurosci 2015
34
26

Inferring nonlinear neuronal computation based on physiologically plausible inputs.
James M McFarland, Yuwei Cui, Daniel A Butts. PLoS Comput Biol 2013
73
23

Inferring hidden structure in multilayered neural circuits.
Niru Maheswaranathan, David B Kastner, Stephen A Baccus, Surya Ganguli. PLoS Comput Biol 2018
22
40


Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
918
23

The functional diversity of retinal ganglion cells in the mouse.
Tom Baden, Philipp Berens, Katrin Franke, Miroslav Román Rosón, Matthias Bethge, Thomas Euler. Nature 2016
359
21

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
21



Spatiotemporal elements of macaque v1 receptive fields.
Nicole C Rust, Odelia Schwartz, J Anthony Movshon, Eero P Simoncelli. Neuron 2005
260
18

Neural Circuit Inference from Function to Structure.
Esteban Real, Hiroki Asari, Tim Gollisch, Markus Meister. Curr Biol 2017
16
43

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
18

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
18

Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization.
Jian K Liu, Helene M Schreyer, Arno Onken, Fernando Rozenblit, Mohammad H Khani, Vidhyasankar Krishnamoorthy, Stefano Panzeri, Tim Gollisch. Nat Commun 2017
22
31

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
18

Deep convolutional models improve predictions of macaque V1 responses to natural images.
Santiago A Cadena, George H Denfield, Edgar Y Walker, Leon A Gatys, Andreas S Tolias, Matthias Bethge, Alexander S Ecker. PLoS Comput Biol 2019
31
22



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
15

Decorrelation and efficient coding by retinal ganglion cells.
Xaq Pitkow, Markus Meister. Nat Neurosci 2012
88
15




Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
309
15

Spatiotemporal energy models for the perception of motion.
E H Adelson, J R Bergen. J Opt Soc Am A 1985
13

Approach sensitivity in the retina processed by a multifunctional neural circuit.
Thomas A Münch, Rava Azeredo da Silveira, Sandra Siegert, Tim James Viney, Gautam B Awatramani, Botond Roska. Nat Neurosci 2009
183
13

The contrast sensitivity of retinal ganglion cells of the cat.
C Enroth-Cugell, J G Robson. J Physiol 1966
13



The challenges natural images pose for visual adaptation.
Fred Rieke, Michael E Rudd. Neuron 2009
110
13

Diverse coupling of neurons to populations in sensory cortex.
Michael Okun, Nicholas Steinmetz, Lee Cossell, M Florencia Iacaruso, Ho Ko, Péter Barthó, Tirin Moore, Sonja B Hofer, Thomas D Mrsic-Flogel, Matteo Carandini,[...]. Nature 2015
176
13


Hierarchical models of object recognition in cortex.
M Riesenhuber, T Poggio. Nat Neurosci 1999
13



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
13

Analyzing neural responses to natural signals: maximally informative dimensions.
Tatyana Sharpee, Nicole C Rust, William Bialek. Neural Comput 2004
178
13

Measuring the Performance of Neural Models.
Oliver Schoppe, Nicol S Harper, Ben D B Willmore, Andrew J King, Jan W H Schnupp. Front Comput Neurosci 2016
32
15

Inhibition decorrelates visual feature representations in the inner retina.
Katrin Franke, Philipp Berens, Timm Schubert, Matthias Bethge, Thomas Euler, Tom Baden. Nature 2017
74
13

Weak pairwise correlations imply strongly correlated network states in a neural population.
Elad Schneidman, Michael J Berry, Ronen Segev, William Bialek. Nature 2006
710
13


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
33

Inferring single-trial neural population dynamics using sequential auto-encoders.
Chethan Pandarinath, Daniel J O'Shea, Jasmine Collins, Rafal Jozefowicz, Sergey D Stavisky, Jonathan C Kao, Eric M Trautmann, Matthew T Kaufman, Stephen I Ryu, Leigh R Hochberg,[...]. Nat Methods 2018
84
13

Identifying functional bases for multidimensional neural computations.
Joel Kaardal, Jeffrey D Fitzgerald, Michael J Berry, Tatyana O Sharpee. Neural Comput 2013
17
23



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.