James J DiCarlo, David D Cox. Trends Cogn Sci 2007
Times Cited: 374
Times Cited: 374
Times Cited
Times Co-cited
Similarity
How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
38
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
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
30
Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
24
Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
19
Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
19
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
Nikolaus Kriegeskorte, Marieke Mur, Douglas A Ruff, Roozbeh Kiani, Jerzy Bodurka, Hossein Esteky, Keiji Tanaka, Peter A Bandettini. Neuron 2008
18
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
Ha Hong, Daniel L K Yamins, Najib J Majaj, James J DiCarlo. Nat Neurosci 2016
18
Selectivity and tolerance ("invariance") both increase as visual information propagates from cortical area V4 to IT.
Nicole C Rust, James J Dicarlo. J Neurosci 2010
Nicole C Rust, James J Dicarlo. J Neurosci 2010
16
16
Fast readout of object identity from macaque inferior temporal cortex.
Chou P Hung, Gabriel Kreiman, Tomaso Poggio, James J DiCarlo. Science 2005
Chou P Hung, Gabriel Kreiman, Tomaso Poggio, James J DiCarlo. Science 2005
14
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
Rishi Rajalingham, Elias B Issa, Pouya Bashivan, Kohitij Kar, Kailyn Schmidt, James J DiCarlo. J Neurosci 2018
15
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
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
14
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
Kohitij Kar, Jonas Kubilius, Kailyn Schmidt, Elias B Issa, James J DiCarlo. Nat Neurosci 2019
16
Resolving human object recognition in space and time.
Radoslaw Martin Cichy, Dimitrios Pantazis, Aude Oliva. Nat Neurosci 2014
Radoslaw Martin Cichy, Dimitrios Pantazis, Aude Oliva. Nat Neurosci 2014
13
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.
D H HUBEL, T N WIESEL. J Physiol 1962
D H HUBEL, T N WIESEL. J Physiol 1962
13
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
J V Haxby, M I Gobbini, M L Furey, A Ishai, J L Schouten, P Pietrini. Science 2001
13
The importance of mixed selectivity in complex cognitive tasks.
Mattia Rigotti, Omri Barak, Melissa R Warden, Xiao-Jing Wang, Nathaniel D Daw, Earl K Miller, Stefano Fusi. Nature 2013
Mattia Rigotti, Omri Barak, Melissa R Warden, Xiao-Jing Wang, Nathaniel D Daw, Earl K Miller, Stefano Fusi. Nature 2013
12
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
Umut Güçlü, Marcel A J van Gerven. J Neurosci 2015
12
Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.
Nikolaus Kriegeskorte. Annu Rev Vis Sci 2015
Nikolaus Kriegeskorte. Annu Rev Vis Sci 2015
12
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
Radoslaw Martin Cichy, Aditya Khosla, Dimitrios Pantazis, Antonio Torralba, Aude Oliva. Sci Rep 2016
11
Functional compartmentalization and viewpoint generalization within the macaque face-processing system.
Winrich A Freiwald, Doris Y Tsao. Science 2010
Winrich A Freiwald, Doris Y Tsao. Science 2010
11
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
R P Rao, D H Ballard. Nat Neurosci 1999
11
Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
11
Distributed hierarchical processing in the primate cerebral cortex.
D J Felleman, D C Van Essen. Cereb Cortex 1991
D J Felleman, D C Van Essen. Cereb Cortex 1991
11
Representational geometry: integrating cognition, computation, and the brain.
Nikolaus Kriegeskorte, Rogier A Kievit. Trends Cogn Sci 2013
Nikolaus Kriegeskorte, Rogier A Kievit. Trends Cogn Sci 2013
11
10
Neural correlations, population coding and computation.
Bruno B Averbeck, Peter E Latham, Alexandre Pouget. Nat Rev Neurosci 2006
Bruno B Averbeck, Peter E Latham, Alexandre Pouget. Nat Rev Neurosci 2006
10
Signals in inferotemporal and perirhinal cortex suggest an untangling of visual target information.
Marino Pagan, Luke S Urban, Margot P Wohl, Nicole C Rust. Nat Neurosci 2013
Marino Pagan, Luke S Urban, Margot P Wohl, Nicole C Rust. Nat Neurosci 2013
14
Context-dependent computation by recurrent dynamics in prefrontal cortex.
Valerio Mante, David Sussillo, Krishna V Shenoy, William T Newsome. Nature 2013
Valerio Mante, David Sussillo, Krishna V Shenoy, William T Newsome. Nature 2013
10
Emergence of simple-cell receptive field properties by learning a sparse code for natural images.
B A Olshausen, D J Field. Nature 1996
B A Olshausen, D J Field. Nature 1996
10
A toolbox for representational similarity analysis.
Hamed Nili, Cai Wingfield, Alexander Walther, Li Su, William Marslen-Wilson, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
Hamed Nili, Cai Wingfield, Alexander Walther, Li Su, William Marslen-Wilson, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
10
A feedforward architecture accounts for rapid categorization.
Thomas Serre, Aude Oliva, Tomaso Poggio. Proc Natl Acad Sci U S A 2007
Thomas Serre, Aude Oliva, Tomaso Poggio. Proc Natl Acad Sci U S A 2007
8
The functional architecture of the ventral temporal cortex and its role in categorization.
Kalanit Grill-Spector, Kevin S Weiner. Nat Rev Neurosci 2014
Kalanit Grill-Spector, Kevin S Weiner. Nat Rev Neurosci 2014
8
Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.
Najib J Majaj, Ha Hong, Ethan A Solomon, James J DiCarlo. J Neurosci 2015
Najib J Majaj, Ha Hong, Ethan A Solomon, James J DiCarlo. J Neurosci 2015
17
Deep Neural Networks as a Computational Model for Human Shape Sensitivity.
Jonas Kubilius, Stefania Bracci, Hans P Op de Beeck. PLoS Comput Biol 2016
Jonas Kubilius, Stefania Bracci, Hans P Op de Beeck. PLoS Comput Biol 2016
8
The fusiform face area: a module in human extrastriate cortex specialized for face perception.
N Kanwisher, J McDermott, M M Chun. J Neurosci 1997
N Kanwisher, J McDermott, M M Chun. J Neurosci 1997
8
Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
9
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
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
10
7
Attention improves performance primarily by reducing interneuronal correlations.
Marlene R Cohen, John H R Maunsell. Nat Neurosci 2009
Marlene R Cohen, John H R Maunsell. Nat Neurosci 2009
7
Identifying natural images from human brain activity.
Kendrick N Kay, Thomas Naselaris, Ryan J Prenger, Jack L Gallant. Nature 2008
Kendrick N Kay, Thomas Naselaris, Ryan J Prenger, Jack L Gallant. Nature 2008
7
Decoding the visual and subjective contents of the human brain.
Yukiyasu Kamitani, Frank Tong. Nat Neurosci 2005
Yukiyasu Kamitani, Frank Tong. Nat Neurosci 2005
7
Beyond mind-reading: multi-voxel pattern analysis of fMRI data.
Kenneth A Norman, Sean M Polyn, Greg J Detre, James V Haxby. Trends Cogn Sci 2006
Kenneth A Norman, Sean M Polyn, Greg J Detre, James V Haxby. Trends Cogn Sci 2006
7
Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
7
Recognition-by-components: a theory of human image understanding.
Irving Biederman. Psychol Rev 1987
Irving Biederman. Psychol Rev 1987
7
Slow feature analysis: unsupervised learning of invariances.
Laurenz Wiskott, Terrence J Sejnowski. Neural Comput 2002
Laurenz Wiskott, Terrence J Sejnowski. Neural Comput 2002
7
Characterizing the dynamics of mental representations: the temporal generalization method.
J-R King, S Dehaene. Trends Cogn Sci 2014
J-R King, S Dehaene. Trends Cogn Sci 2014
7
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.