A citation-based method for searching scientific literature

Shreya Saxena, John P Cunningham. Curr Opin Neurobiol 2019
Times Cited: 33







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



Times Cited
  Times     Co-cited
Similarity


Context-dependent computation by recurrent dynamics in prefrontal cortex.
Valerio Mante, David Sussillo, Krishna V Shenoy, William T Newsome. Nature 2013
522
39

Dimensionality reduction for large-scale neural recordings.
John P Cunningham, Byron M Yu. Nat Neurosci 2014
315
33

Navigating the Neural Space in Search of the Neural Code.
Mehrdad Jazayeri, Arash Afraz. Neuron 2017
81
30

Spontaneous behaviors drive multidimensional, brainwide activity.
Carsen Stringer, Marius Pachitariu, Nicholas Steinmetz, Charu Bai Reddy, Matteo Carandini, Kenneth D Harris. Science 2019
204
27

Flexible timing by temporal scaling of cortical responses.
Jing Wang, Devika Narain, Eghbal A Hosseini, Mehrdad Jazayeri. Nat Neurosci 2018
107
24

High-dimensional geometry of population responses in visual cortex.
Carsen Stringer, Marius Pachitariu, Nicholas Steinmetz, Matteo Carandini, Kenneth D Harris. Nature 2019
62
24

Fully integrated silicon probes for high-density recording of neural activity.
James J Jun, Nicholas A Steinmetz, Joshua H Siegle, Daniel J Denman, Marius Bauza, Brian Barbarits, Albert K Lee, Costas A Anastassiou, Alexandru Andrei, Çağatay Aydın,[...]. Nature 2017
451
24

Neural Manifolds for the Control of Movement.
Juan A Gallego, Matthew G Perich, Lee E Miller, Sara A Solla. Neuron 2017
81
24

Flexible Sensorimotor Computations through Rapid Reconfiguration of Cortical Dynamics.
Evan D Remington, Devika Narain, Eghbal A Hosseini, Mehrdad Jazayeri. Neuron 2018
60
24

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
516
24

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
57
24

Neural population dynamics during reaching.
Mark M Churchland, John P Cunningham, Matthew T Kaufman, Justin D Foster, Paul Nuyujukian, Stephen I Ryu, Krishna V Shenoy. Nature 2012
497
21

Why neurons mix: high dimensionality for higher cognition.
Stefano Fusi, Earl K Miller, Mattia Rigotti. Curr Opin Neurobiol 2016
159
21

A Dynamical Systems Perspective on Flexible Motor Timing.
Evan D Remington, Seth W Egger, Devika Narain, Jing Wang, Mehrdad Jazayeri. Trends Cogn Sci 2018
30
23

Cortical Areas Interact through a Communication Subspace.
João D Semedo, Amin Zandvakili, Christian K Machens, Byron M Yu, Adam Kohn. Neuron 2019
45
18

Inferring single-trial neural population dynamics using sequential auto-encoders.
Chethan Pandarinath, Daniel J O'Shea, Jasmine Collins, Rafal Jozefowicz, Sergey D Stavisky, Jonathan C Kao, Eric M Trautmann, Matthew T Kaufman, Stephen I Ryu, Leigh R Hochberg,[...]. Nat Methods 2018
88
18

Demixed principal component analysis of neural population data.
Dmitry Kobak, Wieland Brendel, Christos Constantinidis, Claudia E Feierstein, Adam Kepecs, Zachary F Mainen, Xue-Lian Qi, Ranulfo Romo, Naoshige Uchida, Christian K Machens. Elife 2016
134
18

Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions.
Warasinee Chaisangmongkon, Sruthi K Swaminathan, David J Freedman, Xiao-Jing Wang. Neuron 2017
44
18

Cortical control of arm movements: a dynamical systems perspective.
Krishna V Shenoy, Maneesh Sahani, Mark M Churchland. Annu Rev Neurosci 2013
283
18

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
141
18

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
18

From the neuron doctrine to neural networks.
Rafael Yuste. Nat Rev Neurosci 2015
217
18

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
523
18


Cortical population activity within a preserved neural manifold underlies multiple motor behaviors.
Juan A Gallego, Matthew G Perich, Stephanie N Naufel, Christian Ethier, Sara A Solla, Lee E Miller. Nat Commun 2018
40
15

A Neural Population Mechanism for Rapid Learning.
Matthew G Perich, Juan A Gallego, Lee E Miller. Neuron 2018
40
15


Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
314
15

Cortical activity in the null space: permitting preparation without movement.
Matthew T Kaufman, Mark M Churchland, Stephen I Ryu, Krishna V Shenoy. Nat Neurosci 2014
229
15


Learning by neural reassociation.
Matthew D Golub, Patrick T Sadtler, Emily R Oby, Kristin M Quick, Stephen I Ryu, Elizabeth C Tyler-Kabara, Aaron P Batista, Steven M Chase, Byron M Yu. Nat Neurosci 2018
56
15

Neural constraints on learning.
Patrick T Sadtler, Kristin M Quick, Matthew D Golub, Steven M Chase, Stephen I Ryu, Elizabeth C Tyler-Kabara, Byron M Yu, Aaron P Batista. Nature 2014
228
15

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
15

Accurate Estimation of Neural Population Dynamics without Spike Sorting.
Eric M Trautmann, Sergey D Stavisky, Subhaneil Lahiri, Katherine C Ames, Matthew T Kaufman, Daniel J O'Shea, Saurabh Vyas, Xulu Sun, Stephen I Ryu, Surya Ganguli,[...]. Neuron 2019
43
15

Computation Through Neural Population Dynamics.
Saurabh Vyas, Matthew D Golub, David Sussillo, Krishna V Shenoy. Annu Rev Neurosci 2020
15
33

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
38
15

Toward an Integration of Deep Learning and Neuroscience.
Adam H Marblestone, Greg Wayne, Konrad P Kording. Front Comput Neurosci 2016
141
15

Bridging large-scale neuronal recordings and large-scale network models using dimensionality reduction.
Ryan C Williamson, Brent Doiron, Matthew A Smith, Byron M Yu. Curr Opin Neurobiol 2019
13
30

How advances in neural recording affect data analysis.
Ian H Stevenson, Konrad P Kording. Nat Neurosci 2011
202
12

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning.
Jonathan A Michaels, Benjamin Dann, Hansjörg Scherberger. PLoS Comput Biol 2016
41
12


Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1.
Jeffrey S Seely, Matthew T Kaufman, Stephen I Ryu, Krishna V Shenoy, John P Cunningham, Mark M Churchland. PLoS Comput Biol 2016
17
23

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
344
12

A category-free neural population supports evolving demands during decision-making.
David Raposo, Matthew T Kaufman, Anne K Churchland. Nat Neurosci 2014
201
12


Cortical preparatory activity: representation of movement or first cog in a dynamical machine?
Mark M Churchland, John P Cunningham, Matthew T Kaufman, Stephen I Ryu, Krishna V Shenoy. Neuron 2010
198
12


Structure in neural population recordings: an expected byproduct of simpler phenomena?
Gamaleldin F Elsayed, John P Cunningham. Nat Neurosci 2017
36
12

Thirst regulates motivated behavior through modulation of brainwide neural population dynamics.
William E Allen, Michael Z Chen, Nandini Pichamoorthy, Rebecca H Tien, Marius Pachitariu, Liqun Luo, Karl Deisseroth. Science 2019
69
12

Spatio-temporal correlations and visual signalling in a complete neuronal population.
Jonathan W Pillow, Jonathon Shlens, Liam Paninski, Alexander Sher, Alan M Litke, E J Chichilnisky, Eero P Simoncelli. Nature 2008
590
12


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.