A citation-based method for searching scientific literature

Shared spatiotemporal category representations in biological and artificial deep neural networks.
Michelle R Greene, Bruce C Hansen. PLoS Comput Biol 2018
Times Cited: 12






Login to export Results
Don't have an account? Register here

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
10
83

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
328
8
66

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
239
7
58

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
5
41

Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
1042
5
41

Resolving human object recognition in space and time.
Radoslaw Martin Cichy, Dimitrios Pantazis, Aude Oliva. Nat Neurosci 2014
264
5
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
4
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
4
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
4
40

Speed of processing in the human visual system.
S Thorpe, D Fize, C Marlot. Nature 1996
1620
4
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
4
33

Visual objects in context.
Moshe Bar. Nat Rev Neurosci 2004
717
3
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
3
25

The Psychophysics Toolbox.
D H Brainard. Spat Vis 1997
9849
3
25

Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.
Nikolaus Kriegeskorte. Annu Rev Vis Sci 2015
225
3
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
3
25

Computational mechanisms underlying cortical responses to the affordance properties of visual scenes.
Michael F Bonner, Russell A Epstein. PLoS Comput Biol 2018
26
3
25

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
314
3
25

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
523
3
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
3
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
3
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
3
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
3
25

Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features.
Tomoyasu Horikawa, Yukiyasu Kamitani. Front Comput Neurosci 2017
15
2
16

Computational modelling of visual attention.
L Itti, C Koch. Nat Rev Neurosci 2001
1344
2
16

Increasingly complex representations of natural movies across the dorsal stream are shared between subjects.
Umut Güçlü, Marcel A J van Gerven. Neuroimage 2017
38
2
16

State-of-the-art in visual attention modeling.
Ali Borji, Laurent Itti. IEEE Trans Pattern Anal Mach Intell 2013
238
2
16

The fusiform face area: a module in human extrastriate cortex specialized for face perception.
N Kanwisher, J McDermott, M M Chun. J Neurosci 1997
4165
2
16

Generic decoding of seen and imagined objects using hierarchical visual features.
Tomoyasu Horikawa, Yukiyasu Kamitani. Nat Commun 2017
64
2
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
2
16

Components of bottom-up gaze allocation in natural images.
Robert J Peters, Asha Iyer, Laurent Itti, Christof Koch. Vision Res 2005
176
2
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
2
16

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
6549
2
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
2
16

Deep learning-Using machine learning to study biological vision.
Najib J Majaj, Denis G Pelli. J Vis 2018
8
2
25

Cognition does not affect perception: Evaluating the evidence for "top-down" effects.
Chaz Firestone, Brian J Scholl. Behav Brain Sci 2016
260
2
16

Relations between the statistics of natural images and the response properties of cortical cells.
D J Field. J Opt Soc Am A 1987
1066
2
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
2
16

A horizontal bias in human visual processing of orientation and its correspondence to the structural components of natural scenes.
Bruce C Hansen, Edward A Essock. J Vis 2004
90
2
16

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
315
2
16

Different spatial frequency bands selectively signal for natural image statistics in the early visual system.
Bruce C Hansen, Aaron P Johnson, Dave Ellemberg. J Neurophysiol 2012
25
2
16

Spatiotemporal energy models for the perception of motion.
E H Adelson, J R Bergen. J Opt Soc Am A 1985
1671
2
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
2
16

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
57
2
16

The time course of visual processing: from early perception to decision-making.
R VanRullen, S J Thorpe. J Cogn Neurosci 2001
396
2
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
2
16

The briefest of glances: the time course of natural scene understanding.
Michelle R Greene, Aude Oliva. Psychol Sci 2009
203
2
16

Statistics of natural image categories.
Antonio Torralba, Aude Oliva. Network 2003
287
2
16

Finding decodable information that can be read out in behaviour.
Tijl Grootswagers, Radoslaw M Cichy, Thomas A Carlson. Neuroimage 2018
22
2
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
2
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.

Longstocking, LLC. © 2021
Home | About Us | FAQs | Terms & Privacy