A citation-based method for searching scientific literature

Courtney J Spoerer, Patrick McClure, Nikolaus Kriegeskorte. Front Psychol 2017
Times Cited: 35







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



Times Cited
  Times     Co-cited
Similarity


Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
328
51

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
45

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
314
42


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
37

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
523
34

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
31

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
28

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
28


Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior.
Kohitij Kar, Jonas Kubilius, Kailyn Schmidt, Elias B Issa, James J DiCarlo. Nat Neurosci 2019
62
28

Recurrence is required to capture the representational dynamics of the human visual system.
Tim C Kietzmann, Courtney J Spoerer, Lynn K A Sörensen, Radoslaw M Cichy, Olaf Hauk, Nikolaus Kriegeskorte. Proc Natl Acad Sci U S A 2019
44
28


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
22

Hierarchical models of object recognition in cortex.
M Riesenhuber, T Poggio. Nat Neurosci 1999
20

Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
20

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
20


A toolbox for representational similarity analysis.
Hamed Nili, Cai Wingfield, Alexander Walther, Li Su, William Marslen-Wilson, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
285
17

Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
930
17


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
109
14

Speed of processing in the human visual system.
S Thorpe, D Fize, C Marlot. Nature 1996
14

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
344
14

Early recurrent feedback facilitates visual object recognition under challenging conditions.
Dean Wyatte, David J Jilk, Randall C O'Reilly. Front Psychol 2014
37
14

Toward an Integration of Deep Learning and Neuroscience.
Adam H Marblestone, Greg Wayne, Konrad P Kording. Front Comput Neurosci 2016
141
14

Distributed hierarchical processing in the primate cerebral cortex.
D J Felleman, D C Van Essen. Cereb Cortex 1991
14



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
37
14

Top-down influences on visual processing.
Charles D Gilbert, Wu Li. Nat Rev Neurosci 2013
406
14

Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition.
Saeed Reza Kheradpisheh, Masoud Ghodrati, Mohammad Ganjtabesh, Timothée Masquelier. Sci Rep 2016
46
14

Deep convolutional networks do not classify based on global object shape.
Nicholas Baker, Hongjing Lu, Gennady Erlikhman, Philip J Kellman. PLoS Comput Biol 2018
30
16

Atoms of recognition in human and computer vision.
Shimon Ullman, Liav Assif, Ethan Fetaya, Daniel Harari. Proc Natl Acad Sci U S A 2016
32
12

Recurrent Processing during Object Recognition.
Randall C O'Reilly, Dean Wyatte, Seth Herd, Brian Mingus, David J Jilk. Front Psychol 2013
48
11

Masking disrupts reentrant processing in human visual cortex.
J J Fahrenfort, H S Scholte, V A F Lamme. J Cogn Neurosci 2007
196
11

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
11

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
11



Cortical feedback improves discrimination between figure and background by V1, V2 and V3 neurons.
J M Hupé, A C James, B R Payne, S G Lomber, P Girard, J Bullier. Nature 1998
532
8

Feedforward object-vision models only tolerate small image variations compared to human.
Masoud Ghodrati, Amirhossein Farzmahdi, Karim Rajaei, Reza Ebrahimpour, Seyed-Mahdi Khaligh-Razavi. Front Comput Neurosci 2014
13
23

Representational dynamics of object recognition: Feedforward and feedback information flows.
Erin Goddard, Thomas A Carlson, Nadene Dermody, Alexandra Woolgar. Neuroimage 2016
28
10

The Psychophysics Toolbox.
D H Brainard. Spat Vis 1997
8

Comparing machines and humans on a visual categorization test.
François Fleuret, Ting Li, Charles Dubout, Emma K Wampler, Steven Yantis, Donald Geman. Proc Natl Acad Sci U S A 2011
21
14


Nonparametric statistical testing of EEG- and MEG-data.
Eric Maris, Robert Oostenveld. J Neurosci Methods 2007
8

Feedforward, horizontal, and feedback processing in the visual cortex.
V A Lamme, H Supèr, H Spekreijse. Curr Opin Neurobiol 1998
339
8

Resolving human object recognition in space and time.
Radoslaw Martin Cichy, Dimitrios Pantazis, Aude Oliva. Nat Neurosci 2014
264
8

Brain Mechanisms Underlying the Brief Maintenance of Seen and Unseen Sensory Information.
Jean-Rémi King, Niccolo Pescetelli, Stanislas Dehaene. Neuron 2016
73
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.