A citation-based method for searching scientific literature

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.
Umut Güçlü, Marcel A J van Gerven. J Neurosci 2015
Times Cited: 283






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



Times Cited
  Times     Co-cited
Similarity


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
521
59
59

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
391
59
59

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
201
36
36

Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
1201
34
34

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
385
34
34

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
200
28
28

Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.
Nikolaus Kriegeskorte. Annu Rev Vis Sci 2015
266
26
26

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
81
25
30

Seeing it all: Convolutional network layers map the function of the human visual system.
Michael Eickenberg, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion. Neuroimage 2017
78
23
29

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
8279
21
21

Generic decoding of seen and imagined objects using hierarchical visual features.
Tomoyasu Horikawa, Yukiyasu Kamitani. Nat Commun 2017
88
20
22

A deep learning framework for neuroscience.
Blake A Richards, Timothy P Lillicrap, Philippe Beaudoin, Yoshua Bengio, Rafal Bogacz, Amelia Christensen, Claudia Clopath, Rui Ponte Costa, Archy de Berker, Surya Ganguli,[...]. Nat Neurosci 2019
155
19
19

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
86
18
20

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
83
18
21

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
57
18
31

A Task-Optimized Neural Network Replicates Human Auditory Behavior, Predicts Brain Responses, and Reveals a Cortical Processing Hierarchy.
Alexander J E Kell, Daniel L K Yamins, Erica N Shook, Sam V Norman-Haignere, Josh H McDermott. Neuron 2018
104
16
16

Deep Neural Networks as a Computational Model for Human Shape Sensitivity.
Jonas Kubilius, Stefania Bracci, Hans P Op de Beeck. PLoS Comput Biol 2016
92
16
17

Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision.
Haiguang Wen, Junxing Shi, Yizhen Zhang, Kun-Han Lu, Jiayue Cao, Zhongming Liu. Cereb Cortex 2018
59
16
27

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
587
16
16

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.
Courtney J Spoerer, Patrick McClure, Nikolaus Kriegeskorte. Front Psychol 2017
52
14
26

Identifying natural images from human brain activity.
Kendrick N Kay, Thomas Naselaris, Ryan J Prenger, Jack L Gallant. Nature 2008
544
13
13

Encoding and decoding in fMRI.
Thomas Naselaris, Kendrick N Kay, Shinji Nishimoto, Jack L Gallant. Neuroimage 2011
331
13
13

Deep Neural Networks as Scientific Models.
Radoslaw M Cichy, Daniel Kaiser. Trends Cogn Sci 2019
71
12
16

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
676
12
12

A cortical representation of the local visual environment.
R Epstein, N Kanwisher. Nature 1998
1810
11
11

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
88
11
12

Neocognitron: a self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position.
K Fukushima. Biol Cybern 1980
661
11
11

Deep convolutional networks do not classify based on global object shape.
Nicholas Baker, Hongjing Lu, Gennady Erlikhman, Philip J Kellman. PLoS Comput Biol 2018
46
11
23

A toolbox for representational similarity analysis.
Hamed Nili, Cai Wingfield, Alexander Walther, Li Su, William Marslen-Wilson, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
328
11
11

Resolving human object recognition in space and time.
Radoslaw Martin Cichy, Dimitrios Pantazis, Aude Oliva. Nat Neurosci 2014
295
11
11

Increasingly complex representations of natural movies across the dorsal stream are shared between subjects.
Umut Güçlü, Marcel A J van Gerven. Neuroimage 2017
46
11
23

A continuous semantic space describes the representation of thousands of object and action categories across the human brain.
Alexander G Huth, Shinji Nishimoto, An T Vu, Jack L Gallant. Neuron 2012
342
10
10

The fusiform face area: a module in human extrastriate cortex specialized for face perception.
N Kanwisher, J McDermott, M M Chun. J Neurosci 1997
4265
10
10

Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.
D H HUBEL, T N WIESEL. J Physiol 1962
6626
10
10

The functional architecture of the ventral temporal cortex and its role in categorization.
Kalanit Grill-Spector, Kevin S Weiner. Nat Rev Neurosci 2014
332
10
10

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
289
9
9

Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
979
9
9

Emergence of simple-cell receptive field properties by learning a sparse code for natural images.
B A Olshausen, D J Field. Nature 1996
1349
9
9

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
66
9
13

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
126
9
9

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
55
9
16

A multi-modal parcellation of human cerebral cortex.
Matthew F Glasser, Timothy S Coalson, Emma C Robinson, Carl D Hacker, John Harwell, Essa Yacoub, Kamil Ugurbil, Jesper Andersson, Christian F Beckmann, Mark Jenkinson,[...]. Nature 2016
1555
9
9

Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.
R P Rao, D H Ballard. Nat Neurosci 1999
1990
9
9

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
398
8
8

Mid-level visual features underlie the high-level categorical organization of the ventral stream.
Bria Long, Chen-Ping Yu, Talia Konkle. Proc Natl Acad Sci U S A 2018
58
8
13

Distributed hierarchical processing in the primate cerebral cortex.
D J Felleman, D C Van Essen. Cereb Cortex 1991
4280
8
8

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
2093
8
8

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
376
8
8

Building machines that learn and think like people.
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman. Behav Brain Sci 2017
192
8
8

Representational geometry: integrating cognition, computation, and the brain.
Nikolaus Kriegeskorte, Rogier A Kievit. Trends Cogn Sci 2013
313
8
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.

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