A citation-based method for searching scientific literature

Christopher DiMattina, Kechen Zhang. Neural Comput 2011
Times Cited: 20







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



Times Cited
  Times     Co-cited
Similarity


Adaptive design optimization: a mutual information-based approach to model discrimination in cognitive science.
Daniel R Cavagnaro, Jay I Myung, Mark A Pitt, Janne V Kujala. Neural Comput 2010
41
60

Sequential optimal design of neurophysiology experiments.
Jeremy Lewi, Robert Butera, Liam Paninski. Neural Comput 2009
54
60

Adaptive stimulus optimization for sensory systems neuroscience.
Christopher DiMattina, Kechen Zhang. Front Neural Circuits 2013
16
62

From response to stimulus: adaptive sampling in sensory physiology.
Jan Benda, Tim Gollisch, Christian K Machens, Andreas Vm Herz. Curr Opin Neurobiol 2007
35
40

Complete functional characterization of sensory neurons by system identification.
Michael C-K Wu, Stephen V David, Jack L Gallant. Annu Rev Neurosci 2006
166
35

Statistical models for neural encoding, decoding, and optimal stimulus design.
Liam Paninski, Jonathan Pillow, Jeremy Lewi. Prog Brain Res 2007
123
35

Bayesian adaptive estimation of the contrast sensitivity function: the quick CSF method.
Luis Andres Lesmes, Zhong-Lin Lu, Jongsoo Baek, Thomas D Albright. J Vis 2010
149
35



QUEST: a Bayesian adaptive psychometric method.
A B Watson, D G Pelli. Percept Psychophys 1983
30

Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach.
Daniel R Cavagnaro, Richard Gonzalez, Jay I Myung, Mark A Pitt. Manage Sci 2013
12
50



Bayesian adaptive estimation of threshold versus contrast external noise functions: the quick TvC method.
Luis Andres Lesmes, Seong-Taek Jeon, Zhong-Lin Lu, Barbara Anne Dosher. Vision Res 2006
57
25

A hierarchical adaptive approach to optimal experimental design.
Woojae Kim, Mark A Pitt, Zhong-Lin Lu, Mark Steyvers, Jay I Myung. Neural Comput 2014
29
25

Model discrimination through adaptive experimentation.
Daniel R Cavagnaro, Mark A Pitt, Jay I Myung. Psychon Bull Rev 2011
18
27

Automating the design of informative sequences of sensory stimuli.
Jeremy Lewi, David M Schneider, Sarah M N Woolley, Liam Paninski. J Comput Neurosci 2011
10
40

How optimal stimuli for sensory neurons are constrained by network architecture.
Christopher DiMattina, Kechen Zhang. Neural Comput 2008
7
57



A Tutorial on Adaptive Design Optimization.
Jay I Myung, Daniel R Cavagnaro, Mark A Pitt. J Math Psychol 2013
24
20

Optimal experimental design for model discrimination.
Jay I Myung, Mark A Pitt. Psychol Rev 2009
45
20



A neural code for three-dimensional object shape in macaque inferotemporal cortex.
Yukako Yamane, Eric T Carlson, Katherine C Bowman, Zhihong Wang, Charles E Connor. Nat Neurosci 2008
156
15

Adaptive stimulus optimization for auditory cortical neurons.
Kevin N O'Connor, Christopher I Petkov, Mitchell L Sutter. J Neurophysiol 2005
31
15

Optimizing sound features for cortical neurons.
R C deCharms, D T Blake, M M Merzenich. Science 1998
306
15

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
15

Using genetic algorithms to find the most effective stimulus for sensory neurons.
S Bleeck, R D Patterson, I M Winter. J Neurosci Methods 2003
13
23

Analyzing neural responses to natural signals: maximally informative dimensions.
Tatyana Sharpee, Nicole C Rust, William Bialek. Neural Comput 2004
179
15


Testing the efficiency of sensory coding with optimal stimulus ensembles.
Christian K Machens, Tim Gollisch, Olga Kolesnikova, Andreas V M Herz. Neuron 2005
66
15

Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization.
Daniel R Cavagnaro, Mark A Pitt, Richard Gonzalez, Jay I Myung. J Risk Uncertain 2013
10
30

A batch ensemble approach to active learning with model selection.
Masashi Sugiyama, Neil Rubens. Neural Netw 2008
5
60


Classification images: A review.
Richard F Murray. J Vis 2011
76
15

The psychometric function: I. Fitting, sampling, and goodness of fit.
F A Wichmann, N J Hill. Percept Psychophys 2001
15

A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects.
Wilson Truccolo, Uri T Eden, Matthew R Fellows, John P Donoghue, Emery N Brown. J Neurophysiol 2005
487
15



Noise, neural codes and cortical organization.
M N Shadlen, W T Newsome. Curr Opin Neurobiol 1994
683
15

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
251
15

A hierarchical Bayesian approach to adaptive vision testing: A case study with the contrast sensitivity function.
Hairong Gu, Woojae Kim, Fang Hou, Luis Andres Lesmes, Mark A Pitt, Zhong-Lin Lu, Jay I Myung. J Vis 2016
15
20

Nonlinear V1 responses to natural scenes revealed by neural network analysis.
Ryan Prenger, Michael C-K Wu, Stephen V David, Jack L Gallant. Neural Netw 2004
39
10

Medial axis shape coding in macaque inferotemporal cortex.
Chia-Chun Hung, Eric T Carlson, Charles E Connor. Neuron 2012
59
10

The staircrase-method in psychophysics.
T N CORNSWEET. Am J Psychol 1962
740
10


How close are we to understanding v1?
Bruno A Olshausen, David J Field. Neural Comput 2005
186
10


Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regime.
Jonathan Hunter Huggins, Liam Paninski. J Comput Neurosci 2012
6
33


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.