E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
Times Cited: 976
Times Cited: 976
Times Cited
Times Co-cited
Similarity
Emergence of simple-cell receptive field properties by learning a sparse code for natural images.
B A Olshausen, D J Field. Nature 1996
B A Olshausen, D J Field. Nature 1996
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Relations between the statistics of natural images and the response properties of cortical cells.
D J Field. J Opt Soc Am A 1987
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Visual perception and the statistical properties of natural scenes.
Wilson S Geisler. Annu Rev Psychol 2008
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Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
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Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.
R P Rao, D H Ballard. Nat Neurosci 1999
R P Rao, D H Ballard. Nat Neurosci 1999
13
The "independent components" of natural scenes are edge filters.
A J Bell, T J Sejnowski. Vision Res 1997
A J Bell, T J Sejnowski. Vision Res 1997
12
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
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
10
Sparse coding with an overcomplete basis set: a strategy employed by V1?
B A Olshausen, D J Field. Vision Res 1997
B A Olshausen, D J Field. Vision Res 1997
10
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Independent component filters of natural images compared with simple cells in primary visual cortex.
J H van Hateren, A van der Schaaf. Proc Biol Sci 1998
J H van Hateren, A van der Schaaf. Proc Biol Sci 1998
10
Sparse coding and decorrelation in primary visual cortex during natural vision.
W E Vinje, J L Gallant. Science 2000
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10
Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
9
Vision and the statistics of the visual environment.
Eero P Simoncelli. Curr Opin Neurobiol 2003
Eero P Simoncelli. Curr Opin Neurobiol 2003
9
Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.
Umut Güçlü, Marcel A J van Gerven. J Neurosci 2015
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8
Receptive fields of single neurones in the cat's striate cortex.
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Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
8
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.
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8
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
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8
Visual discomfort and natural image statistics.
Igor Juricevic, Leah Land, Arnold Wilkins, Michael A Webster. Perception 2010
Igor Juricevic, Leah Land, Arnold Wilkins, Michael A Webster. Perception 2010
11
Eye smarter than scientists believed: neural computations in circuits of the retina.
Tim Gollisch, Markus Meister. Neuron 2010
Tim Gollisch, Markus Meister. Neuron 2010
7
The functional diversity of retinal ganglion cells in the mouse.
Tom Baden, Philipp Berens, Katrin Franke, Miroslav Román Rosón, Matthias Bethge, Thomas Euler. Nature 2016
Tom Baden, Philipp Berens, Katrin Franke, Miroslav Román Rosón, Matthias Bethge, Thomas Euler. Nature 2016
7
Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.
Nikolaus Kriegeskorte. Annu Rev Vis Sci 2015
Nikolaus Kriegeskorte. Annu Rev Vis Sci 2015
7
Could information theory provide an ecological theory of sensory processing?
Joseph J Atick. Network 2011
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7
The human visual system is optimised for processing the spatial information in natural visual images.
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9
Adaptation-induced plasticity of orientation tuning in adult visual cortex.
V Dragoi, J Sharma, M Sur. Neuron 2000
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6
Benefits of pathway splitting in sensory coding.
Julijana Gjorgjieva, Haim Sompolinsky, Markus Meister. J Neurosci 2014
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9
Stimulus- and goal-oriented frameworks for understanding natural vision.
Maxwell H Turner, Luis Gonzalo Sanchez Giraldo, Odelia Schwartz, Fred Rieke. Nat Neurosci 2019
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Modelling the power spectra of natural images: statistics and information.
A van der Schaaf, J H van Hateren. Vision Res 1996
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6
How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
6
6
Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.
Courtney J Spoerer, Patrick McClure, Nikolaus Kriegeskorte. Front Psychol 2017
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11
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
Santiago A Cadena, George H Denfield, Edgar Y Walker, Leon A Gatys, Andreas S Tolias, Matthias Bethge, Alexander S Ecker. PLoS Comput Biol 2019
10
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
Jonathan W Pillow, Jonathon Shlens, Liam Paninski, Alexander Sher, Alan M Litke, E J Chichilnisky, Eero P Simoncelli. Nature 2008
6
6
Visual discomfort and the spatial distribution of Fourier energy.
Olivier Penacchio, Arnold J Wilkins. Vision Res 2015
Olivier Penacchio, Arnold J Wilkins. Vision Res 2015
16
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
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6
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
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7
Image quality assessment: from error visibility to structural similarity.
Zhou Wang, Alan Conrad Bovik, Hamid Rahim Sheikh, Eero P Simoncelli. IEEE Trans Image Process 2004
Zhou Wang, Alan Conrad Bovik, Hamid Rahim Sheikh, Eero P Simoncelli. IEEE Trans Image Process 2004
6
Zebrafish Differentially Process Color across Visual Space to Match Natural Scenes.
Maxime J Y Zimmermann, Noora E Nevala, Takeshi Yoshimatsu, Daniel Osorio, Dan-Eric Nilsson, Philipp Berens, Tom Baden. Curr Biol 2018
Maxime J Y Zimmermann, Noora E Nevala, Takeshi Yoshimatsu, Daniel Osorio, Dan-Eric Nilsson, Philipp Berens, Tom Baden. Curr Biol 2018
7
12
Trichromacy, opponent colours coding and optimum colour information transmission in the retina.
G Buchsbaum, A Gottschalk. Proc R Soc Lond B Biol Sci 1983
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5
Deep Learning Models of the Retinal Response to Natural Scenes.
Lane T McIntosh, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, Stephen A Baccus. Adv Neural Inf Process Syst 2016
Lane T McIntosh, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, Stephen A Baccus. Adv Neural Inf Process Syst 2016
10
A tale of two retinal domains: near-optimal sampling of achromatic contrasts in natural scenes through asymmetric photoreceptor distribution.
Tom Baden, Timm Schubert, Le Chang, Tao Wei, Mariana Zaichuk, Bernd Wissinger, Thomas Euler. Neuron 2013
Tom Baden, Timm Schubert, Le Chang, Tao Wei, Mariana Zaichuk, Bernd Wissinger, Thomas Euler. Neuron 2013
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.