Learning what to expect

[1]  Iain Murray,et al.  Attention as Reward-Driven Optimization of Sensory Processing , 2013, Neural Computation.

[2]  Peggy Seriès,et al.  Charles Bonnet Syndrome: Evidence for a Generative Model in the Cortex? , 2013, PLoS Comput. Biol..

[3]  Jonathan Tong,et al.  Prediction, Postdiction, and Perceptual Length Contraction: A Bayesian Low-Speed Prior Captures the Cutaneous Rabbit and Related Illusions , 2013, Front. Psychol..

[4]  Isabelle Mareschal,et al.  Humans Have an Expectation That Gaze Is Directed Toward Them , 2013, Current Biology.

[5]  Wendy J. Adams,et al.  Learning different light prior distributions for different contexts , 2013, Cognition.

[6]  Aaron R. Seitz,et al.  Complexity and specificity of experimentally induced expectations in motion perception , 2013, BMC Neuroscience.

[7]  Luigi Acerbi,et al.  Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing , 2012, PLoS Comput. Biol..

[8]  M. Ahissar,et al.  How Recent History Affects Perception: The Normative Approach and Its Heuristic Approximation , 2012, PLoS Comput. Biol..

[9]  W. Ma Organizing probabilistic models of perception , 2012, Trends in Cognitive Sciences.

[10]  Xue-Xin Wei,et al.  Bayesian Inference with Efficient Neural Population Codes , 2012, ICANN.

[11]  Matteo Colombo,et al.  Bayes in the Brain—On Bayesian Modelling in Neuroscience , 2012, The British Journal for the Philosophy of Science.

[12]  Karl J. Friston The history of the future of the Bayesian brain , 2012, NeuroImage.

[13]  Janneke F. M. Jehee,et al.  Less Is More: Expectation Sharpens Representations in the Primary Visual Cortex , 2012, Neuron.

[14]  J. Bowers,et al.  Bayesian just-so stories in psychology and neuroscience. , 2012, Psychological bulletin.

[15]  A. Pouget,et al.  Not Noisy, Just Wrong: The Role of Suboptimal Inference in Behavioral Variability , 2012, Neuron.

[16]  P. Mamassian,et al.  Predictive Properties of Visual Adaptation , 2012, Current Biology.

[17]  S. Jbabdi,et al.  How can a Bayesian approach inform neuroscience? , 2012, The European journal of neuroscience.

[18]  Peggy Seriès,et al.  Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability , 2011, NIPS.

[19]  Aaron R. Seitz,et al.  Changing expectations about speed alters perceived motion direction , 2011, Current Biology.

[20]  R. Vogels,et al.  Practicing Coarse Orientation Discrimination Improves Orientation Signals in Macaque Cortical Area V4 , 2011, Current Biology.

[21]  Richard F Murray,et al.  The human visual system's assumption that light comes from above is weak , 2011, Proceedings of the National Academy of Sciences.

[22]  Rufin Vogels,et al.  Stimulus repetition probability does not affect repetition suppression in macaque inferior temporal cortex. , 2011, Cerebral cortex.

[23]  D. Sagi Perceptual learning in Vision Research , 2011, Vision Research.

[24]  M. Carrasco Visual attention: The past 25 years , 2011, Vision Research.

[25]  Hoon Choi,et al.  Perceptual learning solely induced by feedback , 2011, Vision Research.

[26]  Brian J. Fischer,et al.  Owl's behavior and neural representation predicted by Bayesian inference , 2011, Nature Neuroscience.

[27]  Eero P. Simoncelli,et al.  Cardinal rules: Visual orientation perception reflects knowledge of environmental statistics , 2011, Nature Neuroscience.

[28]  Peggy Seriès,et al.  Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model , 2010, NIPS.

[29]  Eero P. Simoncelli,et al.  Implicit encoding of prior probabilities in optimal neural populations , 2010, NIPS.

[30]  Erich W Graf,et al.  Efficient Visual Recalibration from Either Visual or Haptic Feedback: The Importance of Being Wrong , 2010, The Journal of Neuroscience.

[31]  Adam N Sanborn,et al.  Rational approximations to rational models: alternative algorithms for category learning. , 2010, Psychological review.

[32]  S. Klein,et al.  Rule-Based Learning Explains Visual Perceptual Learning and Its Specificity and Transfer , 2010, The Journal of Neuroscience.

[33]  Konrad Paul Kording,et al.  Learning Priors for Bayesian Computations in the Nervous System , 2010, PloS one.

[34]  Aaron R. Seitz,et al.  Rapidly learned stimulus expectations alter perception of motion. , 2010, Journal of vision.

[35]  Alan A. Stocker,et al.  Is the Homunculus Aware of Sensory Adaptation? , 2009, Neural Computation.

[36]  Robyn Kim,et al.  Testing assumptions of statistical learning: Is it long-term and implicit? , 2009, Neuroscience Letters.

[37]  C. Summerfield,et al.  Expectation (and attention) in visual cognition , 2009, Trends in Cognitive Sciences.

[38]  Ladan Shams,et al.  Bayesian priors are encoded independently from likelihoods in human multisensory perception. , 2009, Journal of vision.

[39]  B. Scholl,et al.  Flexible visual statistical learning: transfer across space and time. , 2009, Journal of experimental psychology. Human perception and performance.

[40]  D. Heeger,et al.  The Normalization Model of Attention , 2009, Neuron.

[41]  L. Maloney,et al.  Bayesian decision theory as a model of human visual perception: Testing Bayesian transfer , 2009, Visual Neuroscience.

[42]  M. Peterson,et al.  Inhibitory competition in figure-ground perception: context and convexity. , 2008, Journal of vision.

[43]  Aaron R. Seitz,et al.  Interactions between contrast and spatial displacement in visual motion processing , 2008, Current Biology.

[44]  Jim M. Monti,et al.  Neural repetition suppression reflects fulfilled perceptual expectations , 2008, Nature Neuroscience.

[45]  P. Petrovic,et al.  Believing is seeing: expectations alter visual awareness , 2008, Current Biology.

[46]  A. Thiele,et al.  Comparison of spatial integration and surround suppression characteristics in spiking activity and the local field potential in macaque V1 , 2008, The European journal of neuroscience.

[47]  C. Law,et al.  Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area , 2008, Nature Neuroscience.

[48]  D. Norris,et al.  Shortlist B: a Bayesian model of continuous speech recognition. , 2008, Psychological review.

[49]  B. Scholl,et al.  Multidimensional visual statistical learning. , 2008, Journal of experimental psychology. Learning, memory, and cognition.

[50]  P. Dayan,et al.  Space and time in visual context , 2007, Nature Reviews Neuroscience.

[51]  D. Knill Learning Bayesian priors for depth perception. , 2007, Journal of vision.

[52]  Aaron R. Seitz,et al.  A common framework for perceptual learning , 2007, Current Opinion in Neurobiology.

[53]  Steven R. Holloway,et al.  Perceptual Learning of Motion Leads to Faster Flicker Perception , 2006, PloS one.

[54]  Bart Krekelberg,et al.  Interactions between Speed and Contrast Tuning in the Middle Temporal Area: Implications for the Neural Code for Speed , 2006, The Journal of Neuroscience.

[55]  G. Orban,et al.  Learning to See the Difference Specifically Alters the Most Informative V4 Neurons , 2006, The Journal of Neuroscience.

[56]  P. Perruchet,et al.  Implicit learning and statistical learning: one phenomenon, two approaches , 2006, Trends in Cognitive Sciences.

[57]  Eero P. Simoncelli,et al.  Noise characteristics and prior expectations in human visual speed perception , 2006, Nature Neuroscience.

[58]  J. Saunders,et al.  Demonstration of cue recruitment: change in visual appearance by means of Pavlovian conditioning. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[59]  W. Singer,et al.  Hemodynamic Signals Correlate Tightly with Synchronized Gamma Oscillations , 2005, Science.

[60]  Steven R. Holloway,et al.  Seeing what is not there shows the costs of perceptual learning. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[61]  W. Newsome,et al.  Correlation between Speed Perception and Neural Activity in the Middle Temporal Visual Area , 2005, The Journal of Neuroscience.

[62]  M. Eckstein,et al.  Perceptual learning through optimization of attentional weighting: human versus optimal Bayesian learner. , 2004, Journal of vision.

[63]  D. Knill,et al.  The Bayesian brain: the role of uncertainty in neural coding and computation , 2004, Trends in Neurosciences.

[64]  M. Bar Visual objects in context , 2004, Nature Reviews Neuroscience.

[65]  Roger W Li,et al.  Perceptual learning improves efficiency by re-tuning the decision 'template' for position discrimination , 2004, Nature Neuroscience.

[66]  Maneesh Sahani,et al.  A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning , 2003, NIPS.

[67]  Y. Frégnac,et al.  The “silent” surround of V1 receptive fields: theory and experiments , 2003, Journal of Physiology-Paris.

[68]  Tai Sing Lee,et al.  Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.

[69]  Pascal Mamassian,et al.  Neural correlates of shape from shading , 2003, Neuroreport.

[70]  R. Aslin,et al.  From the Cover: Statistical learning of new visual feature combinations by infants , 2002 .

[71]  Edward H. Adelson,et al.  Motion illusions as optimal percepts , 2002, Nature Neuroscience.

[72]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[73]  M. Chun,et al.  Temporal contextual cuing of visual attention. , 2001, Journal of experimental psychology. Learning, memory, and cognition.

[74]  G. Orban,et al.  Practising orientation identification improves orientation coding in V1 neurons , 2001, Nature.

[75]  P. Mamassian,et al.  Prior knowledge on the illumination position , 2001, Cognition.

[76]  A. B. Sekuler,et al.  Signal but not noise changes with perceptual learning , 1999, Nature.

[77]  Michael L. Platt,et al.  Neural correlates of decision variables in parietal cortex , 1999, Nature.

[78]  Z L Lu,et al.  Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[79]  M. Chun,et al.  Contextual Cueing: Implicit Learning and Memory of Visual Context Guides Spatial Attention , 1998, Cognitive Psychology.

[80]  Michele A. Basso,et al.  Modulation of neuronal activity by target uncertainty , 1997, Nature.

[81]  L. Bowns Evidence for a Feature Tracking Explanation of Why Type II Plaids Move in the Vector Sum Direction at Short Durations , 1996, Vision Research.

[82]  M. Shiffrar,et al.  Different motion sensitive units are involved in recovering the direction of moving lines , 1993, Vision Research.

[83]  P. Wenderoth,et al.  The effect of interactions between one-dimensional component gratings on two-dimensional motion perception , 1993, Vision Research.

[84]  P. Thompson,et al.  Human speed perception is contrast dependent , 1992, Vision Research.

[85]  Maggie Shiffrar,et al.  The influence of terminators on motion integration across space , 1992, Vision Research.

[86]  John R. Anderson,et al.  The Adaptive Nature of Human Categorization. , 1991 .

[87]  J. B. Mulligan,et al.  Effect of contrast on the perceived direction of a moving plaid , 1990, Vision Research.

[88]  C. J. Downing Expectancy and visual-spatial attention: effects on perceptual quality. , 1988, Journal of experimental psychology. Human perception and performance.

[89]  Ellen C. Hildreth,et al.  Measurement of Visual Motion , 1984 .

[90]  J B Pittenger,et al.  An illusion of auditory saltation similar to the cutaneous "rabbit". , 1977, The American journal of psychology.

[91]  R Sekuler,et al.  Mental set alters visibility of moving targets , 1977, Science.

[92]  W. Hershberger,et al.  Attached-shadow orientation perceived as depth by chickens reared in an environment illuminated from below. , 1970, Journal of comparative and physiological psychology.

[93]  P. Seriès,et al.  Explorer Perceptual learning in visual hyperacuity : A reweighting model , 2017 .

[94]  Hugo L. Fernandes,et al.  Supplemental Information Differential Representations of Prior and Likelihood Uncertainty in the Human Brain , 2012 .

[95]  B. Scholl,et al.  The Automaticity of Visual Statistical Learning Statistical Learning , 2005 .

[96]  R. Aslin,et al.  PSYCHOLOGICAL SCIENCE Research Article UNSUPERVISED STATISTICAL LEARNING OF HIGHER-ORDER SPATIAL STRUCTURES FROM VISUAL SCENES , 2022 .

[97]  Konrad Kording,et al.  Annals of the New York Academy of Sciences Bayesian Models: the Structure of the World, Uncertainty, Behavior, and the Brain , 2022 .

[98]  P. Berkes,et al.  Statistically Optimal Perception and Learning: from Behavior to Neural Representations , 2022 .

[99]  Michael I. Posner,et al.  Please Scroll down for Article the Quarterly Journal of Experimental Psychology Orienting of Attention Orienting of Attention* , 2022 .