A citation-based method for searching scientific literature

Michael C-K Wu, Stephen V David, Jack L Gallant. Annu Rev Neurosci 2006
Times Cited: 162







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



Times Cited
  Times     Co-cited
Similarity


Encoding and decoding in fMRI.
Thomas Naselaris, Kendrick N Kay, Shinji Nishimoto, Jack L Gallant. Neuroimage 2011
290
24

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
22

Identifying natural images from human brain activity.
Kendrick N Kay, Thomas Naselaris, Ryan J Prenger, Jack L Gallant. Nature 2008
514
22


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
214
17

Reconstructing visual experiences from brain activity evoked by natural movies.
Shinji Nishimoto, An T Vu, Thomas Naselaris, Yuval Benjamini, Bin Yu, Jack L Gallant. Curr Biol 2011
254
17

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
17

Predicting neuronal responses during natural vision.
Stephen V David, Jack L Gallant. Network 2005
86
18

Natural stimulus statistics alter the receptive field structure of v1 neurons.
Stephen V David, William E Vinje, Jack L Gallant. J Neurosci 2004
196
16



Spike-triggered neural characterization.
Odelia Schwartz, Jonathan W Pillow, Nicole C Rust, Eero P Simoncelli. J Vis 2006
238
14

Bayesian reconstruction of natural images from human brain activity.
Thomas Naselaris, Ryan J Prenger, Kendrick N Kay, Michael Oliver, Jack L Gallant. Neuron 2009
217
14

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

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
296
14

Natural speech reveals the semantic maps that tile human cerebral cortex.
Alexander G Huth, Wendy A de Heer, Thomas L Griffiths, Frédéric E Theunissen, Jack L Gallant. Nature 2016
319
14

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

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


Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
309
13


Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
918
12

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
12

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
512
12


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
17


Optimizing sound features for cortical neurons.
R C deCharms, D T Blake, M M Merzenich. Science 1998
306
11

Statistical models for neural encoding, decoding, and optimal stimulus design.
Liam Paninski, Jonathan Pillow, Jeremy Lewi. Prog Brain Res 2007
122
11

Estimating sparse spectro-temporal receptive fields with natural stimuli.
Stephen V David, Nima Mesgarani, Shihab A Shamma. Network 2007
71
15



Population receptive field estimates in human visual cortex.
Serge O Dumoulin, Brian A Wandell. Neuroimage 2008
533
10

A natural approach to studying vision.
Gidon Felsen, Yang Dan. Nat Neurosci 2005
155
10

Inverse retinotopy: inferring the visual content of images from brain activation patterns.
Bertrand Thirion, Edouard Duchesnay, Edward Hubbard, Jessica Dubois, Jean-Baptiste Poline, Denis Lebihan, Stanislas Dehaene. Neuroimage 2006
145
10

Rapid task-related plasticity of spectrotemporal receptive fields in primary auditory cortex.
Jonathan Fritz, Shihab Shamma, Mounya Elhilali, David Klein. Nat Neurosci 2003
487
10



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
484
9


Distributed and overlapping representations of faces and objects in ventral temporal cortex.
J V Haxby, M I Gobbini, M L Furey, A Ishai, J L Schouten, P Pietrini. Science 2001
9

Intersubject synchronization of cortical activity during natural vision.
Uri Hasson, Yuval Nir, Ifat Levy, Galit Fuhrmann, Rafael Malach. Science 2004
673
9

Influence of context and behavior on stimulus reconstruction from neural activity in primary auditory cortex.
Nima Mesgarani, Stephen V David, Jonathan B Fritz, Shihab A Shamma. J Neurophysiol 2009
78
11

Multiresolution spectrotemporal analysis of complex sounds.
Taishih Chi, Powen Ru, Shihab A Shamma. J Acoust Soc Am 2005
188
9

Reconstructing speech from human auditory cortex.
Brian N Pasley, Stephen V David, Nima Mesgarani, Adeen Flinker, Shihab A Shamma, Nathan E Crone, Robert T Knight, Edward F Chang. PLoS Biol 2012
258
9

Integration over multiple timescales in primary auditory cortex.
Stephen V David, Shihab A Shamma. J Neurosci 2013
40
22

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
9


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