A citation-based method for searching scientific literature

James M McFarland, Yuwei Cui, Daniel A Butts. PLoS Comput Biol 2013
Times Cited: 75







List of co-cited articles
760 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
587
45


Spike-triggered neural characterization.
Odelia Schwartz, Jonathan W Pillow, Nicole C Rust, Eero P Simoncelli. J Vis 2006
238
34


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
485
33

Analyzing neural responses to natural signals: maximally informative dimensions.
Tatyana Sharpee, Nicole C Rust, William Bialek. Neural Comput 2004
179
30

Spatiotemporal elements of macaque v1 receptive fields.
Nicole C Rust, Odelia Schwartz, J Anthony Movshon, Eero P Simoncelli. Neuron 2005
263
30

Temporal precision in the visual pathway through the interplay of excitation and stimulus-driven suppression.
Daniel A Butts, Chong Weng, Jianzhong Jin, Jose-Manuel Alonso, Liam Paninski. J Neurosci 2011
44
43

Spatiotemporal energy models for the perception of motion.
E H Adelson, J R Bergen. J Opt Soc Am A 1985
24

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
273
24


A Convolutional Subunit Model for Neuronal Responses in Macaque V1.
Brett Vintch, J Anthony Movshon, Eero P Simoncelli. J Neurosci 2015
35
45

Inferring input nonlinearities in neural encoding models.
Misha B Ahrens, Liam Paninski, Maneesh Sahani. Network 2008
50
30

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
20


Partitioning neuronal variability.
Robbe L T Goris, J Anthony Movshon, Eero P Simoncelli. Nat Neurosci 2014
224
17

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
40
32



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
119
14

Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
756
14

The consequences of response nonlinearities for interpretation of spectrotemporal receptive fields.
G Björn Christianson, Maneesh Sahani, Jennifer F Linden. J Neurosci 2008
82
13

Fast and slow contrast adaptation in retinal circuitry.
Stephen A Baccus, Markus Meister. Neuron 2002
318
13



Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
13

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
41
24


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
23

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
24

Selectivity for multiple stimulus features in retinal ganglion cells.
Adrienne L Fairhall, C Andrew Burlingame, Ramesh Narasimhan, Robert A Harris, Jason L Puchalla, Michael J Berry. J Neurophysiol 2006
109
12

Efficient and direct estimation of a neural subunit model for sensory coding.
Brett Vintch, Andrew D Zaharia, J Anthony Movshon, Eero P Simoncelli. Adv Neural Inf Process Syst 2012
32
28

Predicting every spike: a model for the responses of visual neurons.
J Keat, P Reinagel, R C Reid, M Meister. Neuron 2001
202
12

Identifying functional bases for multidimensional neural computations.
Joel Kaardal, Jeffrey D Fitzgerald, Michael J Berry, Tatyana O Sharpee. Neural Comput 2013
17
52

Predicting neuronal responses during natural vision.
Stephen V David, Jack L Gallant. Network 2005
87
12

Measuring and interpreting neuronal correlations.
Marlene R Cohen, Adam Kohn. Nat Neurosci 2011
498
12

Complete functional characterization of sensory neurons by system identification.
Michael C-K Wu, Stephen V David, Jack L Gallant. Annu Rev Neurosci 2006
163
10

Learning quadratic receptive fields from neural responses to natural stimuli.
Kanaka Rajan, Olivier Marre, Gašper Tkačik. Neural Comput 2013
14
57

A generalized linear model for estimating spectrotemporal receptive fields from responses to natural sounds.
Ana Calabrese, Joseph W Schumacher, David M Schneider, Liam Paninski, Sarah M N Woolley. PLoS One 2011
68
11

Rapid task-related plasticity of spectrotemporal receptive fields in primary auditory cortex.
Jonathan Fritz, Shihab Shamma, Mounya Elhilali, David Klein. Nat Neurosci 2003
493
10

Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli.
F E Theunissen, S V David, N C Singh, A Hsu, W E Vinje, J L Gallant. Network 2001
215
10




Retinal ganglion cells can rapidly change polarity from Off to On.
Maria Neimark Geffen, Saskia E J de Vries, Markus Meister. PLoS Biol 2007
69
11

Receptive field inference with localized priors.
Mijung Park, Jonathan W Pillow. PLoS Comput Biol 2011
36
22


Beyond GLMs: a generative mixture modeling approach to neural system identification.
Lucas Theis, Andrè Maia Chagas, Daniel Arnstein, Cornelius Schwarz, Matthias Bethge. PLoS Comput Biol 2013
20
40




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.