Related references
Note: Only part of the references are listed.Unsupervised neural network models of the ventral visual stream
Chengxu Zhuang et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)
Lapses in perceptual decisions reflect exploration
Sashank Pisupati et al.
ELIFE (2021)
Unsupervised experience with temporal continuity of the visual environment is causally involved in the development of V1 complex cells
Giulio Matteucci et al.
SCIENCE ADVANCES (2020)
Backpropagation and the brain
Timothy P. Lillicrap et al.
NATURE REVIEWS NEUROSCIENCE (2020)
An investigation of the effect of temporal contiguity training on size -tolerant representations in object -selective cortex
Chayenne Van Meel et al.
NEUROIMAGE (2020)
Reversible Inactivation of Different Millimeter-Scale Regions of Primate IT Results in Different Patterns of Core Object Recognition Deficits
Rishi Rajalingham et al.
NEURON (2019)
Perceptual straightening of natural videos
Olivier J. Henaff et al.
NATURE NEUROSCIENCE (2019)
Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior
Kohitij Kar et al.
NATURE NEUROSCIENCE (2019)
Unsupervised Temporal Contiguity Experience Does Not Break the Invariance of Orientation Selectivity Across Spatial Frequency
Els Crijns et al.
FRONTIERS IN SYSTEMS NEUROSCIENCE (2019)
Psychophysics with children: Investigating the effects of attentional lapses on threshold estimates
Catherine Manning et al.
ATTENTION PERCEPTION & PSYCHOPHYSICS (2018)
Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks
Rishi Rajalingham et al.
JOURNAL OF NEUROSCIENCE (2018)
The Code for Facial Identity in the Primate Brain
Le Chang et al.
CELL (2017)
ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky et al.
COMMUNICATIONS OF THE ACM (2017)
Bio-inspired unsupervised learning of visual features leads to robust invariant object recognition
Saeed Reza Kheradpisheh et al.
NEUROCOMPUTING (2016)
Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance
Najib J. Majaj et al.
JOURNAL OF NEUROSCIENCE (2015)
Comparison of Object Recognition Behavior in Human and Monkey
Rishi Rajalingham et al.
JOURNAL OF NEUROSCIENCE (2015)
Optogenetic and pharmacological suppression of spatial clusters of face neurons reveal their causal role in face gender discrimination
Arash Afraz et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2015)
Performance-optimized hierarchical models predict neural responses in higher visual cortex
Daniel L. K. Yamins et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2014)
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition
Charles F. Cadieu et al.
PLOS COMPUTATIONAL BIOLOGY (2014)
Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation
Seyed-Mahdi Khaligh-Razavi et al.
PLOS COMPUTATIONAL BIOLOGY (2014)
How mechanisms of perceptual decision-making affect the psychometric function
Joshua I. Gold et al.
PROGRESS IN NEUROBIOLOGY (2013)
Neuronal Learning of Invariant Object Representation in the Ventral Visual Stream Is Not Dependent on Reward
Nuo Li et al.
JOURNAL OF NEUROSCIENCE (2012)
The psychometric function: The lapse rate revisited
Nicolaas Prins
JOURNAL OF VISION (2012)
How Does the Brain Solve Visual Object Recognition?
James J. DiCarlo et al.
NEURON (2012)
Learning and disrupting invariance in visual recognition with a temporal association rule
Leyla Isik et al.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE (2012)
Selectivity and Tolerance (Invariance) Both Increase as Visual Information Propagates from Cortical Area V4 to IT
Nicole C. Rust et al.
JOURNAL OF NEUROSCIENCE (2010)
Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex
Nuo Li et al.
NEURON (2010)
The neural basis of visual object learning
Hans P. Op de Beeck et al.
TRENDS IN COGNITIVE SCIENCES (2010)
What Response Properties Do Individual Neurons Need to Underlie Position and Clutter Invariant Object Recognition?
Nuo Li et al.
JOURNAL OF NEUROPHYSIOLOGY (2009)
Learning illumination- and orientation-invariant representations of objects through temporal association
Guy Wallis et al.
JOURNAL OF VISION (2009)
Spike timing-dependent plasticity: A Hebbian learning rule
Natalia Caporale et al.
ANNUAL REVIEW OF NEUROSCIENCE (2008)
Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey
Nikolaus Kriegeskorte et al.
NEURON (2008)
Observing object motion induces increased generalization and sensitivity
Benjamin Balas et al.
PERCEPTION (2008)
Unsupervised natural experience rapidly alters invariant object representation in visual cortex
Nuo Li et al.
SCIENCE (2008)
Untangling invariant object recognition
James J. DiCarlo et al.
TRENDS IN COGNITIVE SCIENCES (2007)
Slowness: An objective for spike-timing-dependent plasticity?
Henning Sprekeler et al.
PLOS COMPUTATIONAL BIOLOGY (2007)
Invariant visual object recognition: A model, with lighting invariance
Edmund T. Rolls et al.
JOURNAL OF PHYSIOLOGY-PARIS (2006)
Fast readout of object identity from macaque inferior temporal cortex
CP Hung et al.
SCIENCE (2005)
'Breaking' position-invariant object recognition
DD Cox et al.
NATURE NEUROSCIENCE (2005)
Learning viewpoint invariant object representations using a temporal coherence principle
W Einhäuser et al.
BIOLOGICAL CYBERNETICS (2005)
Generalized Bienenstock-Cooper-Munro rule for spiking neurons that maximizes information transmission
T Toyoizumi et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2005)
Slow feature analysis yields a rich repertoire of complex cell properties
P Berkes et al.
JOURNAL OF VISION (2005)
Homeostatic plasticity in the developing nervous system
GG Turrigiano et al.
NATURE REVIEWS NEUROSCIENCE (2004)
How are complex cell properties adapted to the statistics of natural stimuli?
KP Kording et al.
JOURNAL OF NEUROPHYSIOLOGY (2004)
Faces and objects in macaque cerebral cortex
DY Tsao et al.
NATURE NEUROSCIENCE (2003)
Impact of learning on representation of parts and wholes in monkey inferotemporal cortex
CI Baker et al.
NATURE NEUROSCIENCE (2002)
Slow feature analysis: Unsupervised learning of invariances
L Wiskott et al.
NEURAL COMPUTATION (2002)
The psychometric function: I. Fitting, sampling, and goodness of fit
FA Wichmann et al.
PERCEPTION & PSYCHOPHYSICS (2001)
Neuronal representations of stimulus associations develop in the temporal lobe during learning
A Messinger et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2001)
Spike-timing-dependent Hebbian plasticity as temporal difference learning
RPN Rao et al.
NEURAL COMPUTATION (2001)
Effects of temporal association on recognition memory
G Wallis et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2001)
Natural patterns of activity and long-term synaptic plasticity
O Paulsen et al.
CURRENT OPINION IN NEUROBIOLOGY (2000)
Share Paper
