A citation-based method for searching scientific literature

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
Times Cited: 45







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



Times Cited
  Times     Co-cited
Similarity


The role of visual area V4 in the discrimination of partially occluded shapes.
Yoshito Kosai, Yasmine El-Shamayleh, Amber M Fyall, Anitha Pasupathy. J Neurosci 2014
26
11

Visual properties of neurons in inferotemporal cortex of the Macaque.
C G Gross, C E Rocha-Miranda, D B Bender. J Neurophysiol 1972
953
6

Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
174
6

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
914
6

Toward an Integration of Deep Learning and Neuroscience.
Adam H Marblestone, Greg Wayne, Konrad P Kording. Front Comput Neurosci 2016
144
6

Towards deep learning with segregated dendrites.
Jordan Guerguiev, Timothy P Lillicrap, Blake A Richards. Elife 2017
83
6


Why is real-world visual object recognition hard?
Nicolas Pinto, David D Cox, James J DiCarlo. PLoS Comput Biol 2008
117
6

Top-down signal from prefrontal cortex in executive control of memory retrieval.
H Tomita, M Ohbayashi, K Nakahara, I Hasegawa, Y Miyashita. Nature 1999
410
6


Dynamic representation of partially occluded objects in primate prefrontal and visual cortex.
Amber M Fyall, Yasmine El-Shamayleh, Hannah Choi, Eric Shea-Brown, Anitha Pasupathy. Elife 2017
13
23

Masking interrupts figure-ground signals in V1.
Victor A F Lamme, Karl Zipser, Henk Spekreijse. J Cogn Neurosci 2002
180
6


Recurrent Processing during Object Recognition.
Randall C O'Reilly, Dean Wyatte, Seth Herd, Brian Mingus, David J Jilk. Front Psychol 2013
49
6


Robust object recognition with cortex-like mechanisms.
Thomas Serre, Lior Wolf, Stanley Bileschi, Maximilian Riesenhuber, Tomaso Poggio. IEEE Trans Pattern Anal Mach Intell 2007
308
6


Neural mechanisms of selective visual attention.
R Desimone, J Duncan. Annu Rev Neurosci 1995
6


Theories of Error Back-Propagation in the Brain.
James C R Whittington, Rafal Bogacz. Trends Cogn Sci 2019
45
6

A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs.
Dileep George, Wolfgang Lehrach, Ken Kansky, Miguel Lázaro-Gredilla, Christopher Laan, Bhaskara Marthi, Xinghua Lou, Zhaoshi Meng, Yi Liu, Huayan Wang,[...]. Science 2017
23
13

Long short-term memory.
S Hochreiter, J Schmidhuber. Neural Comput 1997
6

Neural scene representation and rendering.
S M Ali Eslami, Danilo Jimenez Rezende, Frederic Besse, Fabio Viola, Ari S Morcos, Marta Garnelo, Avraham Ruderman, Andrei A Rusu, Ivo Danihelka, Karol Gregor,[...]. Science 2018
34
8

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
45
6

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
41
7


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
638
6

What crowding can tell us about object representations.
Mauro Manassi, Sophie Lonchampt, Aaron Clarke, Michael H Herzog. J Vis 2016
16
18

Grouping, pooling, and when bigger is better in visual crowding.
Mauro Manassi, Bilge Sayim, Michael H Herzog. J Vis 2012
95
6


Imprinting and recalling cortical ensembles.
Luis Carrillo-Reid, Weijian Yang, Yuki Bando, Darcy S Peterka, Rafael Yuste. Science 2016
103
6

A quantitative theory of immediate visual recognition.
Thomas Serre, Gabriel Kreiman, Minjoon Kouh, Charles Cadieu, Ulf Knoblich, Tomaso Poggio. Prog Brain Res 2007
74
6

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
108
6

Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
947
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
899
6

Distributed circuits, not circumscribed centers, mediate visual recognition.
Marlene Behrmann, David C Plaut. Trends Cogn Sci 2013
164
6

A basis for generating expectancies for verbs from nouns.
Ken McRae, Mary Hare, Jeffrey L Elman, Todd Ferretti. Mem Cognit 2005
73
6



Patterns of Verb Impairment in Aphasia: An Analysis of Four Cases.
Sarah D Breedin, Randi C Martin. Cogn Neuropsychol 1996
42
7

A distributed, developmental model of word recognition and naming.
M S Seidenberg, J L McClelland. Psychol Rev 1989
6

Category specific semantic impairments.
E K Warrington, T Shallice. Brain 1984
6

Statistical learning of parts and wholes: A neural network approach.
David C Plaut, Anna K Vande Velde. J Exp Psychol Gen 2017
6
50

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.
Dharshan Kumaran, Demis Hassabis, James L McClelland. Trends Cogn Sci 2016
118
6

Neuronal tuning: To sharpen or broaden?
K Zhang, T J Sejnowski. Neural Comput 1999
152
6


Understanding normal and impaired word reading: computational principles in quasi-regular domains.
D C Plaut, J L McClelland, M S Seidenberg, K Patterson. Psychol Rev 1996
6



Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
786
6


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.