A citation-based method for searching scientific literature

Michelle R Greene, Bruce C Hansen. PLoS Comput Biol 2018
Times Cited: 12







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



Times Cited
  Times     Co-cited
Similarity


Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.
Radoslaw Martin Cichy, Aditya Khosla, Dimitrios Pantazis, Antonio Torralba, Aude Oliva. Sci Rep 2016
164
83

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
328
66


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
436
41

Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
41

Resolving human object recognition in space and time.
Radoslaw Martin Cichy, Dimitrios Pantazis, Aude Oliva. Nat Neurosci 2014
264
41

Places: A 10 Million Image Database for Scene Recognition.
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, Antonio Torralba. IEEE Trans Pattern Anal Mach Intell 2018
50
33

Deep Neural Networks as a Computational Model for Human Shape Sensitivity.
Jonas Kubilius, Stefania Bracci, Hans P Op de Beeck. PLoS Comput Biol 2016
75
33

Visual information representation and rapid-scene categorization are simultaneous across cortex: An MEG study.
Pavan Ramkumar, Bruce C Hansen, Sebastian Pannasch, Lester C Loschky. Neuroimage 2016
10
40

Speed of processing in the human visual system.
S Thorpe, D Fize, C Marlot. Nature 1996
33

A toolbox for representational similarity analysis.
Hamed Nili, Cai Wingfield, Alexander Walther, Li Su, William Marslen-Wilson, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
285
33

Visual objects in context.
Moshe Bar. Nat Rev Neurosci 2004
717
25

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks.
Radoslaw Martin Cichy, Aditya Khosla, Dimitrios Pantazis, Aude Oliva. Neuroimage 2017
59
25

The Psychophysics Toolbox.
D H Brainard. Spat Vis 1997
25


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
260
25


Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
314
25

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
523
25

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
182
25

Seeing it all: Convolutional network layers map the function of the human visual system.
Michael Eickenberg, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion. Neuroimage 2017
61
25

Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search.
Antonio Torralba, Aude Oliva, Monica S Castelhano, John M Henderson. Psychol Rev 2006
605
25

Matching categorical object representations in inferior temporal cortex of man and monkey.
Nikolaus Kriegeskorte, Marieke Mur, Douglas A Ruff, Roozbeh Kiani, Jerzy Bodurka, Hossein Esteky, Keiji Tanaka, Peter A Bandettini. Neuron 2008
626
25


Computational modelling of visual attention.
L Itti, C Koch. Nat Rev Neurosci 2001
16


State-of-the-art in visual attention modeling.
Ali Borji, Laurent Itti. IEEE Trans Pattern Anal Mach Intell 2013
238
16



Building machines that learn and think like people.
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman. Behav Brain Sci 2017
146
16

Components of bottom-up gaze allocation in natural images.
Robert J Peters, Asha Iyer, Laurent Itti, Christof Koch. Vision Res 2005
176
16

Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments.
Kamila M Jozwik, Nikolaus Kriegeskorte, Katherine R Storrs, Marieke Mur. Front Psychol 2017
31
16

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
16

Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks.
Rishi Rajalingham, Elias B Issa, Pouya Bashivan, Kohitij Kar, Kailyn Schmidt, James J DiCarlo. J Neurosci 2018
73
16




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
16




Spatiotemporal energy models for the perception of motion.
E H Adelson, J R Bergen. J Opt Soc Am A 1985
16

Recurrent computations for visual pattern completion.
Hanlin Tang, Martin Schrimpf, William Lotter, Charlotte Moerman, Ana Paredes, Josue Ortega Caro, Walter Hardesty, David Cox, Gabriel Kreiman. Proc Natl Acad Sci U S A 2018
42
16

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
57
16


The spatiotemporal dynamics of scene gist recognition.
Adam M Larson, Tyler E Freeman, Ryan V Ringer, Lester C Loschky. J Exp Psychol Hum Percept Perform 2014
23
16


Statistics of natural image categories.
Antonio Torralba, Aude Oliva. Network 2003
287
16

Finding decodable information that can be read out in behaviour.
Tijl Grootswagers, Radoslaw M Cichy, Thomas A Carlson. Neuroimage 2018
22
16

Spatially pooled contrast responses predict neural and perceptual similarity of naturalistic image categories.
Iris I A Groen, Sennay Ghebreab, Victor A F Lamme, H Steven Scholte. PLoS Comput Biol 2012
35
16


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.