- Bilinearity, rules, and prefrontal cortex Peter Dayan
- In CL Giles, SJ Hanson, and JD Cowan, editors, Advances in Neural Information Processing Systems 5 (NIPS*92), Morgan Kaufmann, San Mateo, CA
- An Hierarchical Model of Visual Rivalry Peter Dayan
- Behavioral and Brain Functions This Provisional PDF corresponds to the article as it appeared upon acceptance. The fully-formatted
- Appeared in Wilson, RA & Keil, F, editors. The MIT Encyclopedia of the Cognitive Sciences. Unsupervised Learning
- *Albert Einstein College of Medicine, Jack and Pearl
- NECO_a_00051-Moazzezi NECO.cls September 8, 2010 14:53 UncorrectedProof
- Spatial Representations in Related Environments in a Recurrent Model of Area CA3 of the Rat
- To appear in: M. S. Kearns, S. A. Solla, & D. A. Cohn, eds., Advances in Neural Information Processing Systems 11, MIT Press, Cambridge, MA, 1999.
- Modelling the Manifolds of Images of Handwritten Geo rey E. Hinton (hinton@cs.toronto.edu)
- Opponency Revisited: Competition and Cooperation Between Dopamine and Serotonin
- A familiaritybased learning procedure for the establishment of place fields in area CA3
- Serotonin, Inhibition, and Negative Mood Peter Dayan1
- Pavlovian-Instrumental Interaction in `Observing Ulrik R. Beierholm*, Peter Dayan
- Annu. Rev. Neurosci. 2003. 26:381410 doi: 10.1146/annurev.neuro.26.041002.131112
- Submitted to Handbook of Brain Theory and Neural Networks, 2. Helmholtz Machines
- Submitted to NIPS 2000. Hippocampally-Dependent Consolidation
- Statistical Models of Conditioning Peter Dayan
- *Department of Brain and Cognitive Sciences,
- Neuron, Vol. 46, 681692, May 19, 2005, Copyright 2005 by Elsevier Inc. DOI 10.1016/j.neuron.2005.04.026 Uncertainty, Neuromodulation, and Attention
- Dynamics of Attentional Selection Under Conflict: Toward a Rational Bayesian Account
- Network: Computation in Neural Systems December 2006; 17(4): 335350
- Expected and Unexpected Uncertainty: ACh and NE in the Neocortex
- Uncertainty and Learning Peter Dayan Angela J Yu
- 2002 Special issue Acetylcholine in cortical inference
- ACh, Uncertainty, and Cortical Inference Peter Dayan Angela Yu
- An unsupervised learning model of neural plasticity: Orientation selectivity in goggle-reared kittens
- Communicated by Steve Nowlan Competition and Multiple Cause Models
- To appear in: M. S. Kearns, S. A. Solla, & D. A. Cohn, eds., Advances in Neural Information Processing Systems 11, MIT Press, Cambridge, MA, 1999.
- We greatly regret that there are errors in the article "The Role of Background Statistics in Face Adaptation" by Jianhua Wu, Hong Xu, Peter Dayan, and Ning Qian, Journal of Neuroscience,
- Feudal Reinforcement Learning Peter Dayan
- Selective Bayes: Attentional load and crowding Peter Dayan a,*, Joshua A. Solomon b
- Physica D 239 (2010) 477484 Contents lists available at ScienceDirect
- Neural Networks 22 (2009) 213219 Contents lists available at ScienceDirect
- Prospective and Retrospective Temporal Difference Learning Peter Dayan
- Flexible shaping: How learning in small steps helps Kai A. Krueger *, Peter Dayan
- A Bayesian model predicts the response of axons to molecular gradients
- Frontiers in Neuroscience www.frontiersin.org December 2008 | Volume 2 | Issue 2 | 255 FOCUSED REVIEW
- ORIGINAL ARTICLE A novel method for automated classification of epileptiform
- Psychiatry: insights into depression through normative decision-making models
- Bayesian Model of Behaviour in Economic Games Debajyoti Ray
- ORIGINAL ARTICLE A novel method for automated classification of epileptiform
- Uncertainty, phase and oscillatory hippocampal recall Mate Lengyel and Peter Dayan
- Neural Networks 19 (2006) 14371439 www.elsevier.com/locate/neunet
- Dopamine, Learning, and Impulsivity: A Biological Account of Attention-
- duplicates were deleted to obtain predictions on the dispensability of the underlying enzymatic reaction.
- Inference, Attention, and Decision in a Bayesian Neural Architecture
- Probabilistic computation in spiking populations Richard S. Zemel
- NIPS 2002, in press Replay, Repair and Consolidation
- Encyclopedia of Cognitive Science, in press Reinforcement Learning
- LETTER Communicated by Lawrence Saul Recurrent Sampling Models for the Helmholtz Machine
- Communicated by Terrence Sanger Probabilistic Interpretation of Population Codes
- Communicated by Robert Jacobs Factor Analysis Using Delta-Rule Wake-Sleep Learning
- Improving Policies without Measuring Peter Dayan
- Communicatedby Richard Durbin and Graeme Mitchison Arbitrary Elastic Topologies and Ocular Dominance
- Communicated by TerrenceJ. Sejnowski Optimal Plasticity from Matrix Memories
- Dopamine modulation in basal ganglia-cortical network implements
- Neuron, Vol. 36, 285298, October 10, 2002, Copyright 2002 by Cell Press ReviewReward, Motivation,
- Acquisition and Extinction in Autoshaping Sham Kakade and Peter Dayan
- Submitted to NIPS 2000. Competition and Arbors in Ocular Dominance
- Position Variance, Recurrence and Perceptual Zhaoping Li Peter Dayan
- LEARNING TO EVALUATE GO POSITIONS VIA TEMPORAL DIFFERENCE METHODS
- Network: Comput. Neural Syst. 10 (1999) 5977. Printed in the UK PII: S0954-898X(99)96892-6 Computational differences between asymmetrical and
- Neurobiological modeling: squeezing top down to meet P Read Montague
- IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 9, NO. 4, JULY 1998 705 Bayesian Retrieval in Associative
- Analytical Mean Squared Error Curves in Temporal Di erence Learning
- To appear in: International Joint Conference on Arti cial Intelligence 1997. Denver, CO: Morgan Kaufmann. Combining Probabilistic Population Codes
- Machine Learning, 25:522 Peter Dayan and Terrence Sejnowski.
- The Journal of Neuroscience, March 1, 1996, 76(5):1936-1947 A Framework for Mesencephalic Dopamine Systems Based on
- Appeared in Current Opinion in Neurobiology, 4:212-217. Computational Modelling
- Perturbing Hebbian Rules Peter Dayan
- Machine Learning, 8, 279-292 (1992) 1992 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- To appear in: Neural Computation, 10(2): 403-430 (1998). Probabilistic Interpretation of Population Codes
- Appeared in Wilson, RA & Keil, F, editors. The MIT Encyclopedia of the Cognitive Sciences. Unsupervised Learning
- Full text provided by www.sciencedirect.com A normative perspective on motivation
- The wake-sleep algorithm for unsupervised neural networks
- INSTITUTE OF PHYSICS PUBLISHING NETWORK: COMPUTATION IN NEURAL SYSTEMS Network: Comput. Neural Syst. 14 (2003) 233247 PII: S0954-898X(03)58143-X
- 01-07-436 NECO.cls March 29, 2008 2:27 UncorrectedProof
- LETTER Communicated by Alexandre Pouget Fast Population Coding
- Statistical Models of Conditioning Peter Dayan
- In NIPS 11. Computational Differences between
- Machine Learning, 25:5--22 Peter Dayan and Terrence Sejnowski.
- NOTE Communicated by David Willshaw The Variance of Covariance Rules for Associative Matrix
- Assignment of Multiplicative Mixtures in Natural Images
- 1 Curved Gaussian Models with Application to the Modeling of Foreign Exchange Rates
- Dopamine Bonuses Sham Kakade Peter Dayan
- Available online at www.sciencedirect.com Reinforcement learning: The Good, The Bad and The Ugly
- Temporal Difference Learning of Position Evaluation in the Game of Go \Lambda
- Statistical Models and Sensory Attention Peter Dayan Richard S Zemel
- Semi-rational Models of Conditioning: The Case of Trial
- A familiarity-based learning procedure for the establishment of place fields in area CA3
- LEARNING TO EVALUATE GO POSITIONS VIA TEMPORAL DIFFERENCE METHODS
- Position Variance, Recurrence and Perceptual Zhaoping Li Peter Dayan
- Competition and Arbors in Ocular Dominance Peter Dayan
- 1 Curved Gaussian Models with Application to the Modeling of Foreign Exchange Rates
- Load and Attentional Bayes Peter Dayan
- Hippocampal Contributions to Control: The Third Way
- LETTER Communicated by Pawan Sinha Images, Frames, and Connectionist Hierarchies
- The Involvement of Recurrent Connections in Area CA3 in Establishing the Properties of Place Fields: a Model
- Communicated by Michael Jordan The Helmholtz Machine
- A Bayesian formulation of behavioral control Quentin J.M. Huys a,b,*, Peter Dayan a
- LETTER Communicated by Michael Shadlen The Effect of Correlated Variability on the Accuracy of a
- TD( ) Converges with Probability 1 Peter Dayan Terrence J Sejnowski
- Does the Wake-sleep Algorithm Produce Good Density Estimators?
- This article was downloaded by:[University College London] On: 1 July 2008
- Neurobiological modeling: squeezing top down to meet P Read Montague 1 and Peter Dayan 2
- The wakesleep algorithm for unsupervised neural networks
- TRENDS in Cognitive Sciences Vol.6 No.3 March 2002 http://tics.trends.com 1364-6613/02/$ see front matter 2002 Elsevier Science Ltd. All rights reserved. PII: S1364-6613(00)01851-9
- LETTER Communicated by Michael Lewicki Soft Mixer Assignment in a Hierarchical Generative Model of
- Temporal Difference Learning of Position Evaluation in the Game of Go
- In NIPS 11. Computational Differences between
- A simple algorithm that discovers efficient perceptual codes
- Acquisition in Autoshaping Sham Kakade Peter Dayan
- Behavioral/Systems/Cognitive Human PavlovianInstrumental Transfer
- The Role of Value Systems in Decision Making
- Neuron, Vol. 28, 329337, April 24, 2003, Copyright 2003 by Cell Press Temporal Difference Models and
- LETTER Communicated by Sidney Lehky A Hierarchical Model of Binocular Rivalry
- Rate-and Phase-coded Autoassociative Memory Mt Lengyel Peter Dayan
- Behavioral/Systems/Cognitive Adaptation across the Cortical Hierarchy: Low-Level Curve
- Recognition in Hierarchical Models Peter Dayan
- UNCORRECTEDPROOF 2 Pattern formation and cortical maps
- Behavioral/Systems/Cognitive How Humans Integrate the Prospects of Pain and Reward
- SUPPORTING ON-LINE MATERIAL MATERIALS AND METHODS
- A simple algorithm that discovers e cient perceptual codes
- Machine Learning, 49, 325346, 2002 c 2002 Kluwer Academic Publishers. Manufactured in The Netherlands.
- An Hierarchical Model of Visual Rivalry Peter Dayan
- In CL Giles, SJ Hanson, and JD Cowan, editors, Advances in Neural Information Processing Systems 5 (NIPS*92), Morgan Kaufmann, San Mateo, CA
- To appear in: International Joint Conference on Artificial Intelligence 1997. Denver, CO: Morgan Kaufmann. Combining Probabilistic Population Codes
- Communicated by Andrew Barto Improving Generalization for Temporal Difference
- Submitted to Encyclopedia of Cognitive Science Levels of analysis in neural modeling
- nature neurOSCIenCe VOLUME 13 | NUMBER 10 | OCTOBER 2010 1271 a r t I C l e S
- 2002 Special issue Dopamine: generalization and bonuses
- Network: Comput. Neural Syst. 10 (1999) 59--77. Printed in the UK PII: S0954898X(99)968926 Computational differences between asymmetrical and
- Recognition in Hierarchical Models Peter Dayan
- Perturbing Hebbian Rules Peter Dayan
- To appear in: Neural Computation, 10(2): 403430 (1998). Probabilistic Interpretation of Population Codes
- Accepted for NIPS 2001 Motivated Reinforcement Learning
- Dopamine Bonuses 1 Dopamine Bonuses
- Adaptation and Unsupervised Learning Peter Dayan Maneesh Sahani Gregoire Deback
- NOTE Communicated by Andrew Barto and Michael Jordan Using Expectation-Maximization for Reinforcement Learning
- , , 138 () c Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- The involvement of recurrent connections in area CA3 in establishing the properties of place elds
- Explaining Away in Weight Space Peter Dayan Sham Kakade
- Neural Models for PartWhole Hierarchies Maximilian Riesenhuber Peter Dayan
- Does the Wakesleep Algorithm Produce Good Density Estimators?
- Appeared in Current Opinion in Neurobiology, 4:212217. Computational Modelling
- Persecutory delusions and the conditioned avoidance paradigm: Towards an integration of the psychology and
- Acquisition in Autoshaping Sham Kakade Peter Dayan
- J Comput Neurosci (2006) 20:153166 DOI 10.1007/s10827-005-5705-x
- *Department Cognitive Sciences,
- 1218 nature neuroscience supplement volume 3 november 2000 Attention is a complex neural and psychological phenomenon,
- Neural Models for Part-Whole Hierarchies Maximilian Riesenhuber Peter Dayan
- Behavioral/Systems/Cognitive Action Dominates Valence in Anticipatory Representations
- Using Aperiodic Reinforcement for Directed Self-Organization During Development
- Submitted to NIPS 2000. Explaining Away in Weight Space
- Recognizing Handwritten Digits Using Mixtures of Linear Models Geoffrey E Hinton Michael Revow Peter Dayan
- Modelling the Manifolds of Images of Handwritten Geoffrey E. Hinton (hinton@cs.toronto.edu)
- Recognizing Handwritten Digits Using Mixtures of Linear Models Geoffrey E Hinton Michael Revow Peter Dayan
- Opponent Interactions between Serotonin and Dopamine Nathaniel D Daw Sham Kakade Peter Dayan
- Spatial Representations in Related Environments in a Recurrent Model of Area CA3 of the Rat
- Behavioral/Systems/Cognitive The Role of Background Statistics in Face Adaptation
- Submitted to Handbook of Brain Theory and Neural Networks, 2. Helmholtz Machines
- This article was downloaded by: [University College London] On: 09 July 2011, At: 15:37
- ARTICLE Communicated by Florian Luisier Bayes-Optimal Chemotaxis
- Model-Based Influences on Humans' Choices and Striatal Prediction Errors
- Vigor in the Face of Fluctuating Rates of Reward: An Experimental Examination
- Know Thy Neighbour: A Normative Theory of Synaptic Depression
- Behavioral/Systems/Cognitive Neural Prediction Errors Reveal a Risk-Sensitive
