Neural processing as causal inference

[1]  S. Laughlin,et al.  Predictive coding: a fresh view of inhibition in the retina , 1982, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[2]  J. Movshon,et al.  The statistical reliability of signals in single neurons in cat and monkey visual cortex , 1983, Vision Research.

[3]  Joseph J. Atick,et al.  What Does the Retina Know about Natural Scenes? , 1992, Neural Computation.

[4]  Michael I. Jordan,et al.  An internal model for sensorimotor integration. , 1995, Science.

[5]  David J. Field,et al.  Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.

[6]  Geoffrey E. Hinton,et al.  Generative models for discovering sparse distributed representations. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[7]  Brendan J. Frey,et al.  Graphical Models for Machine Learning and Digital Communication , 1998 .

[8]  R. Shapley,et al.  Contrast's effect on spatial summation by macaque V1 neurons , 1999, Nature Neuroscience.

[9]  M. Ernst,et al.  Humans integrate visual and haptic information in a statistically optimal fashion , 2002, Nature.

[10]  R. Shapley,et al.  Area (mt) Spatial Summation, End Inhibition and Side Inhibition in the Middle Temporal Visual Adaptation Complex Cells Increase Their Phase Sensitivity at Low Contrasts and following Dependence of Response Properties on Sparse Connectivity in a Spiking Neuron Model Of , 2022 .

[11]  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.

[12]  J. Movshon,et al.  Adaptive Temporal Integration of Motion in Direction-Selective Neurons in Macaque Visual Cortex , 2004, The Journal of Neuroscience.

[13]  Rajesh P. N. Rao Bayesian Computation in Recurrent Neural Circuits , 2004, Neural Computation.

[14]  Nicole C. Rust,et al.  Do We Know What the Early Visual System Does? , 2005, The Journal of Neuroscience.

[15]  Wei Ji Ma,et al.  Bayesian inference with probabilistic population codes , 2006, Nature Neuroscience.

[16]  P. Dayan,et al.  Cortical substrates for exploratory decisions in humans , 2006, Nature.

[17]  Michael S. Lewicki,et al.  Efficient auditory coding , 2006, Nature.

[18]  Barry B. Lee,et al.  Suppressive Surrounds and Contrast Gain in Magnocellular-Pathway Retinal Ganglion Cells of Macaque , 2006, The Journal of Neuroscience.

[19]  Konrad Paul Kording,et al.  Causal Inference in Multisensory Perception , 2007, PloS one.

[20]  Alexandre Pouget,et al.  Exact Inferences in a Neural Implementation of a Hidden Markov Model , 2007, Neural Computation.

[21]  Chun-I Yeh,et al.  Temporal precision in the neural code and the timescales of natural vision , 2007, Nature.

[22]  Peter Dayan,et al.  Fast Population Coding , 2007, Neural Computation.

[23]  Konrad Paul Kording,et al.  Decision Theory: What "Should" the Nervous System Do? , 2007, Science.

[24]  W. Richards,et al.  Perception as Bayesian Inference , 2008 .

[25]  S. Denéve,et al.  Information transmission with spiking Bayesian neurons , 2008 .

[26]  Sophie Denève,et al.  Bayesian Spiking Neurons I: Inference , 2008, Neural Computation.

[27]  Jörg Lücke,et al.  Maximal Causes for Non-linear Component Extraction , 2008, J. Mach. Learn. Res..

[28]  Timothy D. Hanks,et al.  Probabilistic Population Codes for Bayesian Decision Making , 2008, Neuron.

[29]  Sophie Denève,et al.  Bayesian Spiking Neurons II: Learning , 2008, Neural Computation.

[30]  Karl J. Friston,et al.  Predictive coding under the free-energy principle , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.

[31]  P. Dayan,et al.  Perceptual organization in the tilt illusion. , 2009, Journal of vision.

[32]  Shimon Ullman,et al.  Cortical Circuitry Implementing Graphical Models , 2009, Neural Computation.

[33]  Wolfgang Maass,et al.  Belief Propagation in Networks of Spiking Neurons , 2009, Neural Computation.

[34]  Yonina C. Eldar,et al.  Bayesian Filtering in Spiking Neural Networks: Noise, Adaptation, and Multisensory Integration , 2009, Neural Computation.

[35]  Dileep George,et al.  Towards a Mathematical Theory of Cortical Micro-circuits , 2009, PLoS Comput. Biol..

[36]  A. Fairhall,et al.  Timescales of Inference in Visual Adaptation , 2009, Neuron.

[37]  Jacques Droulez,et al.  The Probabilistic Cell: Implementation of a Probabilistic Inference by the Biochemical Mechanisms of Phototransduction , 2010, Acta biotheoretica.

[38]  P. Dayan,et al.  Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials , 2010, Nature Neuroscience.

[39]  Andrew M. Clark,et al.  Stimulus onset quenches neural variability: a widespread cortical phenomenon , 2010, Nature Neuroscience.

[40]  Michael W. Spratling Predictive Coding as a Model of Response Properties in Cortical Area V1 , 2010, The Journal of Neuroscience.

[41]  J. Tenenbaum,et al.  A probabilistic model of theory formation , 2010, Cognition.

[42]  Konrad P. Kording,et al.  Sensory Adaptation and Short Term Plasticity as Bayesian Correction for a Changing Brain , 2010, PloS one.

[43]  W Pieter Medendorp,et al.  Multisensory Processing in Spatial Orientation: An Inverse Probabilistic Approach , 2011, The Journal of Neuroscience.

[44]  Arnulf B. A. Graf,et al.  Decoding the activity of neuronal populations in macaque primary visual cortex , 2011, Nature Neuroscience.

[45]  P. Fletcher,et al.  Glutamatergic Model Psychoses: Prediction Error, Learning, and Inference , 2011, Neuropsychopharmacology.

[46]  József Fiser,et al.  Spontaneous Cortical Activity Reveals Hallmarks of an Optimal Internal Model of the Environment , 2011, Science.

[47]  Sophie Denève,et al.  Spike-Based Population Coding and Working Memory , 2011, PLoS Comput. Biol..