A citation-based method for searching scientific literature

Blake A Richards, Timothy P Lillicrap, Philippe Beaudoin, Yoshua Bengio, Rafal Bogacz, Amelia Christensen, Claudia Clopath, Rui Ponte Costa, Archy de Berker, Surya Ganguli, Colleen J Gillon, Danijar Hafner, Adam Kepecs, Nikolaus Kriegeskorte, Peter Latham, Grace W Lindsay, Kenneth D Miller, Richard Naud, Christopher C Pack, Panayiota Poirazi, Pieter Roelfsema, João Sacramento, Andrew Saxe, Benjamin Scellier, Anna C Schapiro, Walter Senn, Greg Wayne, Daniel Yamins, Friedemann Zenke, Joel Zylberberg, Denis Therien, Konrad P Kording. Nat Neurosci 2019
Times Cited: 160







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



Times Cited
  Times     Co-cited
Similarity


Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
31

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
392
29

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
530
22

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
396
18


Backpropagation and the brain.
Timothy P Lillicrap, Adam Santoro, Luke Marris, Colin J Akerman, Geoffrey Hinton. Nat Rev Neurosci 2020
90
16


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
106
13

Toward an Integration of Deep Learning and Neuroscience.
Adam H Marblestone, Greg Wayne, Konrad P Kording. Front Comput Neurosci 2016
160
13

Deep Neural Networks as Scientific Models.
Radoslaw M Cichy, Daniel Kaiser. Trends Cogn Sci 2019
75
16


Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
10

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
85
11

Theories of Error Back-Propagation in the Brain.
James C R Whittington, Rafal Bogacz. Trends Cogn Sci 2019
61
16

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
593
10

Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
218
9

Random synaptic feedback weights support error backpropagation for deep learning.
Timothy P Lillicrap, Daniel Cownden, Douglas B Tweed, Colin J Akerman. Nat Commun 2016
132
8

Towards deep learning with segregated dendrites.
Jordan Guerguiev, Timothy P Lillicrap, Blake A Richards. Elife 2017
103
8


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
59
11

Overcoming catastrophic forgetting in neural networks.
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska,[...]. Proc Natl Acad Sci U S A 2017
162
7


Vector-based navigation using grid-like representations in artificial agents.
Andrea Banino, Caswell Barry, Benigno Uria, Charles Blundell, Timothy Lillicrap, Piotr Mirowski, Alexander Pritzel, Martin J Chadwick, Thomas Degris, Joseph Modayil,[...]. Nature 2018
114
7

Deep neural network models of sensory systems: windows onto the role of task constraints.
Alexander Je Kell, Josh H McDermott. Curr Opin Neurobiol 2019
22
31

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
8

Context-dependent computation by recurrent dynamics in prefrontal cortex.
Valerio Mante, David Sussillo, Krishna V Shenoy, William T Newsome. Nature 2013
609
7

Dendritic action potentials and computation in human layer 2/3 cortical neurons.
Albert Gidon, Timothy Adam Zolnik, Pawel Fidzinski, Felix Bolduan, Athanasia Papoutsi, Panayiota Poirazi, Martin Holtkamp, Imre Vida, Matthew Evan Larkum. Science 2020
83
8

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
380
6


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
90
6

Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
984
6

Canonical microcircuits for predictive coding.
Andre M Bastos, W Martin Usrey, Rick A Adams, George R Mangun, Pascal Fries, Karl J Friston. Neuron 2012
981
6

Highly nonrandom features of synaptic connectivity in local cortical circuits.
Sen Song, Per Jesper Sjöström, Markus Reigl, Sacha Nelson, Dmitri B Chklovskii. PLoS Biol 2005
815
6

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
57
10

Engineering a Less Artificial Intelligence.
Fabian H Sinz, Xaq Pitkow, Jacob Reimer, Matthias Bethge, Andreas S Tolias. Neuron 2019
38
15

Artificial Neural Networks for Neuroscientists: A Primer.
Guangyu Robert Yang, Xiao-Jing Wang. Neuron 2020
21
28

A solution to the learning dilemma for recurrent networks of spiking neurons.
Guillaume Bellec, Franz Scherr, Anand Subramoney, Elias Hajek, Darjan Salaj, Robert Legenstein, Wolfgang Maass. Nat Commun 2020
39
15

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
90
5

Building machines that learn and think like people.
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman. Behav Brain Sci 2017
200
5

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
206
5

Predictive Processing: A Canonical Cortical Computation.
Georg B Keller, Thomas D Mrsic-Flogel. Neuron 2018
158
5

Synaptic integration in tuft dendrites of layer 5 pyramidal neurons: a new unifying principle.
Matthew E Larkum, Thomas Nevian, Maya Sandler, Alon Polsky, Jackie Schiller. Science 2009
389
5

Mastering the game of Go with deep neural networks and tree search.
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot,[...]. Nature 2016
5


Towards the neural population doctrine.
Shreya Saxena, John P Cunningham. Curr Opin Neurobiol 2019
56
8


Flexible Sensorimotor Computations through Rapid Reconfiguration of Cortical Dynamics.
Evan D Remington, Devika Narain, Eghbal A Hosseini, Mehrdad Jazayeri. Neuron 2018
84
5


Long short-term memory.
S Hochreiter, J Schmidhuber. Neural Comput 1997
5

A neural network that finds a naturalistic solution for the production of muscle activity.
David Sussillo, Mark M Churchland, Matthew T Kaufman, Krishna V Shenoy. Nat Neurosci 2015
162
5


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.