A citation-based method for searching scientific literature

Emmanouil Froudarakis, Paul G Fahey, Jacob Reimer, Stelios M Smirnakis, Edward J Tehovnik, Andreas S Tolias. Annu Rev Vis Sci 2019
Times Cited: 3







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



Times Cited
  Times     Co-cited
Similarity


Arousal and locomotion make distinct contributions to cortical activity patterns and visual encoding.
Martin Vinck, Renata Batista-Brito, Ulf Knoblich, Jessica A Cardin. Neuron 2015
218
66

Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences.
Carlos R Ponce, Will Xiao, Peter F Schade, Till S Hartmann, Gabriel Kreiman, Margaret S Livingstone. Cell 2019
24
66

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
27
66

Spontaneous behaviors drive multidimensional, brainwide activity.
Carsen Stringer, Marius Pachitariu, Nicholas Steinmetz, Charu Bai Reddy, Matteo Carandini, Kenneth D Harris. Science 2019
99
66

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
106
33


Diverse suppressive influences in area MT and selectivity to complex motion features.
Yuwei Cui, Liu D Liu, Farhan A Khawaja, Christopher C Pack, Daniel A Butts. J. Neurosci. 2013
22
33

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
441
33

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
32
33

Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
866
33

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
241
33

The nonlinear pathway of Y ganglion cells in the cat retina.
J D Victor, R M Shapley. J. Gen. Physiol. 1979
113
33

Disparity processing in primary visual cortex.
Sid Henriksen, Seiji Tanabe, Bruce Cumming. Philos. Trans. R. Soc. Lond., B, Biol. Sci. 2016
12
33

Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model.
Liam Paninski, Jonathan W Pillow, Eero P Simoncelli. Neural Comput 2004
142
33

Spatiotemporal elements of macaque v1 receptive fields.
Nicole C Rust, Odelia Schwartz, J Anthony Movshon, Eero P Simoncelli. Neuron 2005
239
33

How close are we to understanding v1?
Bruno A Olshausen, David J Field. Neural Comput 2005
158
33

The physiology of stereopsis.
B G Cumming, G C DeAngelis. Annu. Rev. Neurosci. 2001
200
33

Estimating linear-nonlinear models using Renyi divergences.
Minjoon Kouh, Tatyana O Sharpee. Network 2009
21
33

Inferring nonlinear neuronal computation based on physiologically plausible inputs.
James M McFarland, Yuwei Cui, Daniel A Butts. PLoS Comput. Biol. 2013
64
33

Functional characterization of retinal ganglion cells using tailored nonlinear modeling.
Qing Shi, Pranjal Gupta, Alexandra K Boukhvalova, Joshua H Singer, Daniel A Butts. Sci Rep 2019
3
33

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
107
33

Bayesian reconstruction of natural images from human brain activity.
Thomas Naselaris, Ryan J Prenger, Kendrick N Kay, Michael Oliver, Jack L Gallant. Neuron 2009
190
33

Fully integrated silicon probes for high-density recording of neural activity.
James J Jun, Nicholas A Steinmetz, Joshua H Siegle, Daniel J Denman, Marius Bauza, Brian Barbarits, Albert K Lee, Costas A Anastassiou, Alexandru Andrei, Çağatay Aydın,[...]. Nature 2017
275
33

Receptive field organization of complex cells in the cat's striate cortex.
J A Movshon, I D Thompson, D J Tolhurst. J. Physiol. (Lond.) 1978
352
33

Modern Machine Learning as a Benchmark for Fitting Neural Responses.
Ari S Benjamin, Hugo L Fernandes, Tucker Tomlinson, Pavan Ramkumar, Chris VerSteeg, Raeed H Chowdhury, Lee E Miller, Konrad P Kording.  2018
8
33

Predicting every spike: a model for the responses of visual neurons.
J Keat, P Reinagel, R C Reid, M Meister. Neuron 2001
190
33

Learning and attention reveal a general relationship between population activity and behavior.
A M Ni, D A Ruff, J J Alberts, J Symmonds, M R Cohen. Science 2018
33
33



Learning quadratic receptive fields from neural responses to natural stimuli.
Kanaka Rajan, Olivier Marre, Gašper Tkačik. Neural Comput 2013
14
33

Inferring Cortical Variability from Local Field Potentials.
Yuwei Cui, Liu D Liu, James M McFarland, Christopher C Pack, Daniel A Butts. J. Neurosci. 2016
20
33

Convolutional neural network models of V1 responses to complex patterns.
Yimeng Zhang, Tai Sing Lee, Ming Li, Fang Liu, Shiming Tang. J Comput Neurosci 2019
4
33




Feedback determines the structure of correlated variability in primary visual cortex.
Adrian G Bondy, Ralf M Haefner, Bruce G Cumming. Nat Neurosci 2018
28
33

How advances in neural recording affect data analysis.
Ian H Stevenson, Konrad P Kording. Nat. Neurosci. 2011
180
33


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
39
33

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
539
33

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
35
33

Complete functional characterization of sensory neurons by system identification.
Michael C-K Wu, Stephen V David, Jack L Gallant. Annu. Rev. Neurosci. 2006
134
33


Computational subunits of visual cortical neurons revealed by artificial neural networks.
Brian Lau, Garrett B Stanley, Yang Dan. Proc. Natl. Acad. Sci. U.S.A. 2002
32
33

Explicit information for category-orthogonal object properties increases along the ventral stream.
Ha Hong, Daniel L K Yamins, Najib J Majaj, James J DiCarlo. Nat. Neurosci. 2016
73
33

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
63
33

Adaptation of the simple or complex nature of V1 receptive fields to visual statistics.
Julien Fournier, Cyril Monier, Marc Pananceau, Yves Frégnac. Nat. Neurosci. 2011
27
33


The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction.
Ross S Williamson, Maneesh Sahani, Jonathan W Pillow. PLoS Comput. Biol. 2015
16
33

Spatial summation in the receptive fields of simple cells in the cat's striate cortex.
J A Movshon, I D Thompson, D J Tolhurst. J. Physiol. (Lond.) 1978
535
33


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.