A citation-based method for searching scientific literature

Wilson Truccolo, Uri T Eden, Matthew R Fellows, John P Donoghue, Emery N Brown. J Neurophysiol 2005
Times Cited: 529







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



Times Cited
  Times     Co-cited
Similarity


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
642
39

The time-rescaling theorem and its application to neural spike train data analysis.
Emery N Brown, Riccardo Barbieri, Valérie Ventura, Robert E Kass, Loren M Frank. Neural Comput 2002
270
19

Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model.
Jonathan W Pillow, Liam Paninski, Valerie J Uzzell, Eero P Simoncelli, E J Chichilnisky. J Neurosci 2005
203
17


Dynamic analysis of neural encoding by point process adaptive filtering.
Uri T Eden, Loren M Frank, Riccardo Barbieri, Victor Solo, Emery N Brown. Neural Comput 2004
184
16

Collective dynamics in human and monkey sensorimotor cortex: predicting single neuron spikes.
Wilson Truccolo, Leigh R Hochberg, John P Donoghue. Nat Neurosci 2010
135
16

Dimensionality reduction for large-scale neural recordings.
John P Cunningham, Byron M Yu. Nat Neurosci 2014
415
15

Estimating a state-space model from point process observations.
Anne C Smith, Emery N Brown. Neural Comput 2003
173
12

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
144
12

Inferring nonlinear neuronal computation based on physiologically plausible inputs.
James M McFarland, Yuwei Cui, Daniel A Butts. PLoS Comput Biol 2013
84
13

A spike-train probability model.
R E Kass, V Ventura. Neural Comput 2001
122
11

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
286
11

Mood variations decoded from multi-site intracranial human brain activity.
Omid G Sani, Yuxiao Yang, Morgan B Lee, Heather E Dawes, Edward F Chang, Maryam M Shanechi. Nat Biotechnol 2018
75
14

Encoding and decoding in parietal cortex during sensorimotor decision-making.
Il Memming Park, Miriam L R Meister, Alexander C Huk, Jonathan W Pillow. Nat Neurosci 2014
126
11

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
603
11

Statistical models for neural encoding, decoding, and optimal stimulus design.
Liam Paninski, Jonathan Pillow, Jeremy Lewi. Prog Brain Res 2007
131
11




Rapid control and feedback rates enhance neuroprosthetic control.
Maryam M Shanechi, Amy L Orsborn, Helene G Moorman, Suraj Gowda, Siddharth Dangi, Jose M Carmena. Nat Commun 2017
44
22


The origin of extracellular fields and currents--EEG, ECoG, LFP and spikes.
György Buzsáki, Costas A Anastassiou, Christof Koch. Nat Rev Neurosci 2012
9

Likelihood methods for point processes with refractoriness.
Luca Citi, Demba Ba, Emery N Brown, Riccardo Barbieri. Neural Comput 2014
20
45


Optimizing the learning rate for adaptive estimation of neural encoding models.
Han-Lin Hsieh, Maryam M Shanechi. PLoS Comput Biol 2018
13
69


Single-trial dynamics of motor cortex and their applications to brain-machine interfaces.
Jonathan C Kao, Paul Nuyujukian, Stephen I Ryu, Mark M Churchland, John P Cunningham, Krishna V Shenoy. Nat Commun 2015
90
10

A high performing brain-machine interface driven by low-frequency local field potentials alone and together with spikes.
Sergey D Stavisky, Jonathan C Kao, Paul Nuyujukian, Stephen I Ryu, Krishna V Shenoy. J Neural Eng 2015
67
11

Brain-Machine Interface Control Algorithms.
Maryam M Shanechi. IEEE Trans Neural Syst Rehabil Eng 2017
26
30



How advances in neural recording affect data analysis.
Ian H Stevenson, Konrad P Kording. Nat Neurosci 2011
235
8

Modern Machine Learning as a Benchmark for Fitting Neural Responses.
Ari S Benjamin, Hugo L Fernandes, Tucker Tomlinson, Pavan Ramkumar, Chris VerSteeg, Raeed H Chowdhury, Lee E Miller, Konrad P Kording. Front Comput Neurosci 2018
21
38

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
641
8

Context-dependent computation by recurrent dynamics in prefrontal cortex.
Valerio Mante, David Sussillo, Krishna V Shenoy, William T Newsome. Nature 2013
633
8

A generalized linear model for estimating spectrotemporal receptive fields from responses to natural sounds.
Ana Calabrese, Joseph W Schumacher, David M Schneider, Liam Paninski, Sarah M N Woolley. PLoS One 2011
72
9

Predicting every spike: a model for the responses of visual neurons.
J Keat, P Reinagel, R C Reid, M Meister. Neuron 2001
210
7


Neural population partitioning and a concurrent brain-machine interface for sequential motor function.
Maryam M Shanechi, Rollin C Hu, Marissa Powers, Gregory W Wornell, Emery N Brown, Ziv M Williams. Nat Neurosci 2012
48
14

Learning to control a brain-machine interface for reaching and grasping by primates.
Jose M Carmena, Mikhail A Lebedev, Roy E Crist, Joseph E O'Doherty, David M Santucci, Dragan F Dimitrov, Parag G Patil, Craig S Henriquez, Miguel A L Nicolelis. PLoS Biol 2003
881
7

A high-performance neural prosthesis enabled by control algorithm design.
Vikash Gilja, Paul Nuyujukian, Cindy A Chestek, John P Cunningham, Byron M Yu, Joline M Fan, Mark M Churchland, Matthew T Kaufman, Jonathan C Kao, Stephen I Ryu,[...]. Nat Neurosci 2012
263
7

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.
Leigh R Hochberg, Daniel Bacher, Beata Jarosiewicz, Nicolas Y Masse, John D Simeral, Joern Vogel, Sami Haddadin, Jie Liu, Sydney S Cash, Patrick van der Smagt,[...]. Nature 2012
7

Modelling and analysis of local field potentials for studying the function of cortical circuits.
Gaute T Einevoll, Christoph Kayser, Nikos K Logothetis, Stefano Panzeri. Nat Rev Neurosci 2013
387
7

High-performance neuroprosthetic control by an individual with tetraplegia.
Jennifer L Collinger, Brian Wodlinger, John E Downey, Wei Wang, Elizabeth C Tyler-Kabara, Douglas J Weber, Angus J C McMorland, Meel Velliste, Michael L Boninger, Andrew B Schwartz. Lancet 2013
780
7

Generalized leaky integrate-and-fire models classify multiple neuron types.
Corinne Teeter, Ramakrishnan Iyer, Vilas Menon, Nathan Gouwens, David Feng, Jim Berg, Aaron Szafer, Nicholas Cain, Hongkui Zeng, Michael Hawrylycz,[...]. Nat Commun 2018
47
14

Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity.
Byron M Yu, John P Cunningham, Gopal Santhanam, Stephen I Ryu, Krishna V Shenoy, Maneesh Sahani. J Neurophysiol 2009
247
7

Inference and Decoding of Motor Cortex Low-Dimensional Dynamics via Latent State-Space Models.
Mehdi Aghagolzadeh, Wilson Truccolo. IEEE Trans Neural Syst Rehabil Eng 2016
24
29

Functional dissection of signal and noise in MT and LIP during decision-making.
Jacob L Yates, Il Memming Park, Leor N Katz, Jonathan W Pillow, Alexander C Huk. Nat Neurosci 2017
50
14

Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models.
Christian Pozzorini, Skander Mensi, Olivier Hagens, Richard Naud, Christof Koch, Wulfram Gerstner. PLoS Comput Biol 2015
34
20

Nonlinear Modeling of Neural Interaction for Spike Prediction Using the Staged Point-Process Model.
Cunle Qian, Xuyun Sun, Shaomin Zhang, Dong Xing, Hongbao Li, Xiaoxiang Zheng, Gang Pan, Yiwen Wang. Neural Comput 2018
8
87


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.