A citation-based method for searching scientific literature

Kendrick N Kay. Neuroimage 2018
Times Cited: 19







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



Times Cited
  Times     Co-cited
Similarity


Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
314
63

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
42


Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
328
42


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
31

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
26

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
26

Encoding and decoding in fMRI.
Thomas Naselaris, Kendrick N Kay, Shinji Nishimoto, Jack L Gallant. Neuroimage 2011
296
26

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
26

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
26


Deep Learning: The Good, the Bad, and the Ugly.
Thomas Serre. Annu Rev Vis Sci 2019
28
26

Spatiotemporal energy models for the perception of motion.
E H Adelson, J R Bergen. J Opt Soc Am A 1985
21

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
21

Identifying natural images from human brain activity.
Kendrick N Kay, Thomas Naselaris, Ryan J Prenger, Jack L Gallant. Nature 2008
520
21


Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
767
15

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
523
15

Predict, then simplify.
Jonas Kubilius. Neuroimage 2018
3
100

Representational geometry: integrating cognition, computation, and the brain.
Nikolaus Kriegeskorte, Rogier A Kievit. Trends Cogn Sci 2013
280
15

Hierarchical models of object recognition in cortex.
M Riesenhuber, T Poggio. Nat Neurosci 1999
15

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
339
15


Fantastic DNimals and where to find them.
H Steven Scholte. Neuroimage 2018
7
42

Convolutional neural network-based encoding and decoding of visual object recognition in space and time.
K Seeliger, M Fritsche, U Güçlü, S Schoenmakers, J-M Schoffelen, S E Bosch, M A J van Gerven. Neuroimage 2018
27
15

Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
162
15

Cognitive computational neuroscience.
Nikolaus Kriegeskorte, Pamela K Douglas. Nat Neurosci 2018
53
15

Bayesian reconstruction of natural images from human brain activity.
Thomas Naselaris, Ryan J Prenger, Kendrick N Kay, Michael Oliver, Jack L Gallant. Neuron 2009
219
15


Task representations in neural networks trained to perform many cognitive tasks.
Guangyu Robert Yang, Madhura R Joglekar, H Francis Song, William T Newsome, Xiao-Jing Wang. Nat Neurosci 2019
54
15

Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.
Junxing Shi, Haiguang Wen, Yizhen Zhang, Kuan Han, Zhongming Liu. Hum Brain Mapp 2018
14
21

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
15

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
90
15


Compressive spatial summation in human visual cortex.
Kendrick N Kay, Jonathan Winawer, Aviv Mezer, Brian A Wandell. J Neurophysiol 2013
107
10

Computational neuroimaging and population receptive fields.
Brian A Wandell, Jonathan Winawer. Trends Cogn Sci 2015
70
10

Population receptive field estimates in human visual cortex.
Serge O Dumoulin, Brian A Wandell. Neuroimage 2008
552
10


Slow cortical dynamics and the accumulation of information over long timescales.
Christopher J Honey, Thomas Thesen, Tobias H Donner, Lauren J Silbert, Chad E Carlson, Orrin Devinsky, Werner K Doyle, Nava Rubin, David J Heeger, Uri Hasson. Neuron 2012
195
10

Theory of cortical function.
David J Heeger. Proc Natl Acad Sci U S A 2017
62
10



The Psychophysics Toolbox.
D H Brainard. Spat Vis 1997
10

A hierarchy of intrinsic timescales across primate cortex.
John D Murray, Alberto Bernacchia, David J Freedman, Ranulfo Romo, Jonathan D Wallis, Xinying Cai, Camillo Padoa-Schioppa, Tatiana Pasternak, Hyojung Seo, Daeyeol Lee,[...]. Nat Neurosci 2014
305
10

A model of neuronal responses in visual area MT.
E P Simoncelli, D J Heeger. Vision Res 1998
468
10


Object perception as Bayesian inference.
Daniel Kersten, Pascal Mamassian, Alan Yuille. Annu Rev Psychol 2004
565
10


A toolbox for representational similarity analysis.
Hamed Nili, Cai Wingfield, Alexander Walther, Li Su, William Marslen-Wilson, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
285
10


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.