Peter Dayan

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Increased decision thresholds enhance information gathering performance in juvenile Obsessive-Compulsive Disorder (OCD)

Raymond J. Dolan, Tobias U. Hauser, Michael Moutoussis, 2017, PLoS Comput. Biol..

Soft Mixer Assignment in a Hierarchical Generative Model of Natural Scene Statistics

Terrence J. Sejnowski, Peter Dayan, Odelia Schwartz, 2006, Neural Computation.

A Hierarchical Model of Visual Rivalry

Peter Dayan, P. Dayan, 1996, NIPS.

Statistical Models of Conditioning

Peter Dayan, Theresa Long, P. Dayan, 1997, NIPS.

Improving Generalization for Temporal Difference Learning: The Successor Representation

Peter Dayan, P. Dayan, 1993, Neural Computation.

Formalizing Neurath’s Ship: Approximate Algorithms for Online Causal Learning

Thomas L. Griffiths, Peter Dayan, David A. Lagnado, 2016, Psychological review.

Networks, circuits and computation

Peter Dayan, Dan Feldman, Marla Feller, 2011, Current Opinion in Neurobiology.

Disentangled behavioral representations

Richard Nock, Peter Dayan, Cheng Soon Ong, 2019, bioRxiv.

Recurrent Sampling Models for the Helmholtz Machine

Peter Dayan, P. Dayan, 1999, Neural Computation.

Factor Analysis Using Delta-Rule Wake-Sleep Learning

Peter Dayan, Radford M. Neal, P. Dayan, 1997, Neural Computation.

Psychiatry: Insights into depression through normative decision-making models

Peter Dayan, Joshua T. Vogelstein, Quentin J. M. Huys, 2008, NIPS.

Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange

Peter Dayan, P. Read Montague, Andreas Hula, 2015, PLoS Comput. Biol..

Structure in the Space of Value Functions

Peter Dayan, David J. Foster, David J. Foster, 2002, Machine Learning.

Retrospective model-based inference guides model-free credit assignment

Peter Dayan, Mehdi Keramati, Rani Moran, 2019, Nature Communications.

Computational Differences between Asymmetrical and Symmetrical Networks

Peter Dayan, Zhaoping Li, P. Dayan, 1998, NIPS.

Pre-attentive visual selection

Peter Dayan, Zhaoping Li, P. Dayan, 2006, Neural Networks.

Bayes-Optimal Chemotaxis

Peter Dayan, Kevin Burrage, Geoffrey J. Goodhill, 2011, Neural Computation.

Optimal Plasticity from Matrix Memories: What Goes Up Must Come Down

Peter Dayan, David J. Willshaw, P. Dayan, 1990, Neural Computation.

Disentangling the Roles of Approach, Activation and Valence in Instrumental and Pavlovian Responding

Raymond J. Dolan, Peter Dayan, Roshan Cools, 2011, PLoS Comput. Biol..

The Dopaminergic Midbrain Mediates an Effect of Average Reward on Pavlovian Vigor

Raymond J. Dolan, Peter Dayan, Francesco Rigoli, 2015, Journal of Cognitive Neuroscience.

Anticipation and Choice Heuristics in the Dynamic Consumption of Pain Relief

Raymond J. Dolan, Peter Dayan, Ara Darzi, 2015, PLoS Comput. Biol..

Volume Learning: Signaling Covariance Through Neural Tissue

Terrence J. Sejnowski, Peter Dayan, Pr Montague, 1993 .

Editorial overview: Computational modeling: After the Middle Ages of computational neuroscience

Peter Dayan, Daniel Durstewitz, 2016, Current Opinion in Behavioral Sciences.

Dynamic population codes for sensorimotor processing

Peter Dayan, Richard S. Zemel, Rama Natarajan, 2006 .

Motivated Reinforcement Learning

Peter Dayan, P. Dayan, 2001, NIPS.

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search

Peter Dayan, David Silver, Arthur Guez, 2012, NIPS.

Inference, Attention, and Decision in a Bayesian Neural Architecture

Peter Dayan, Angela J. Yu, P. Dayan, 2004, NIPS.

Staying afloat on Neurath's boat - Heuristics for sequential causal learning

Peter Dayan, David A. Lagnado, Neil Bramley, 2015, CogSci.

Encoding and Decoding Spikes for Dynamic Stimuli

Peter Dayan, Richard S. Zemel, Quentin J. M. Huys, 2008, Neural Computation.

Assignment of Multiplicative Mixtures in Natural Images

Terrence J. Sejnowski, Peter Dayan, Odelia Schwartz, 2004, NIPS.

Expected and Unexpected Uncertainty: ACh and NE in the Neocortex

Peter Dayan, Angela J. Yu, P. Dayan, 2002, NIPS.

Arbitrary Elastic Topologies and Ocular Dominance

Peter Dayan, P. Dayan, 1993, Neural Computation.

When Money Is Not Enough: Awareness, Success, and Variability in Motor Learning

Peter Dayan, Jörn Diedrichsen, Harry Manley, 2014, PloS one.

Optimal helplessness: a normative framework for depression

Peter Dayan, Q Huys, P. Dayan, 2006 .

Combining Probabilistic Population Codes

Peter Dayan, Richard S. Zemel, R. Zemel, 1997, IJCAI.

Doubly Distributional Population Codes: Simultaneous Representation of Uncertainty and Multiplicity

Peter Dayan, Maneesh Sahani, P. Dayan, 2003, Neural Computation.

Probabilistic Interpretation of Population Codes

Alexandre Pouget, Peter Dayan, Richard S. Zemel, 1996, Neural Computation.

Hippocampal Model of Rat Spatial Abilities Using Temporal Difference Learning

Peter Dayan, David J. Foster, Richard G. M. Morris, 1997, NIPS.

Forget-me-some: General versus special purpose models in a hierarchical probabilistic task

Peter Dayan, Sven Bestmann, Louise Marshall, 2018, PloS one.

Know Thy Neighbour: A Normative Theory of Synaptic Depression

Jean-Pascal Pfister, Peter Dayan, Máté Lengyel, 2009, NIPS.

Varieties of Helmholtz Machine

Geoffrey E. Hinton, Peter Dayan, P. Dayan, 1996, Neural Networks.

Fast Parametric Learning with Activation Memorization

Peter Dayan, Chris Dyer, Timothy P. Lillicrap, 2018, ICML.

The influence of contextual reward statistics on risk preference

Raymond J. Dolan, Peter Dayan, Francesco Rigoli, 2016, NeuroImage.

Rate- and Phase-coded Autoassociative Memory

Peter Dayan, Máté Lengyel, P. Dayan, 2004, NIPS.

The Role of Background Statistics in Face Adaptation

Peter Dayan, Hong Xu, Ning Qian, 2009, The Journal of Neuroscience.

Goal-directed control and its antipodes

Peter Dayan, P. Dayan, 2009, Neural Networks.

Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood

Michael Moutoussis, Peter Dayan, Peter Fonagy, 2018, PLoS Comput. Biol..

Bilinearity, Rules, and Prefrontal Cortex

Peter Dayan, P. Dayan, 2007, Frontiers Comput. Neurosci..

Multiple value signals in dopaminergic midbrain and their role in avoidance contexts

Raymond J. Dolan, Peter Dayan, Francesco Rigoli, 2016, NeuroImage.

Semi-rational models of conditioning: The case of trial order

Peter Dayan, Aaron C. Courville, Nathaniel D. Daw, 2012 .

Using Expectation-Maximization for Reinforcement Learning

Geoffrey E. Hinton, Peter Dayan, P. Dayan, 1997, Neural Computation.

Better Optimism By Bayes: Adaptive Planning with Rich Models pdf

Peter Dayan, David Silver, Arthur Guez, 2014, ArXiv.

Spatial Representations in Related Environments in a Recurrent Model of Area CA3 of the Rat

Peter Dayan, S Kali, P. Dayan, 1999 .

Change-Based Inference in Attractor Nets: Linear Analysis

Peter Dayan, Reza Moazzezi, P. Dayan, 2010, Neural Computation.

The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning

Terrence J. Sejnowski, Peter Dayan, P. Dayan, 1993, Neural Computation.

Using Aperiodic Reinforcement for Directed Self-Organization During Development

Terrence J. Sejnowski, Peter Dayan, Steven J. Nowlan, 1992, NIPS.

Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing

Peter Dayan, Odelia Schwartz, Ruben Coen Cagli, 2009, NIPS.

Structured cognitive representations and complex inference in neural systems

Alexandre Pouget, Peter Dayan, Joshua B. Tenenbaum, 2013, CogSci.

A Hierarchical Model of Binocular Rivalry

Peter Dayan, P. Dayan, 1998, Neural Computation.

Pavlovian-Instrumental Interaction in ‘Observing Behavior’

Peter Dayan, Ulrik R. Beierholm, Ulrik R Beierholm, 2010, PLoS Comput. Biol..

Serotonin, Inhibition, and Negative Mood

Peter Dayan, Quentin J. M. Huys, P. Dayan, 2007, PLoS Comput. Biol..

The role of value systems in decision making.

Peter Dayan, P. Dayan, 2008 .

Fast Population Coding

Peter Dayan, Richard S. Zemel, Quentin J. M. Huys, 2007, Neural Computation.

Taming the shrewdness of neural function: methodological challenges in computational psychiatry

Karl J. Friston, Peter Dayan, Karl J Friston, 2015, Current Opinion in Behavioral Sciences.

Probabilistic Meta-Representations Of Neural Networks pdf

Peter Dayan, Zoubin Ghahramani, Theofanis Karaletsos, 2018, ArXiv.

Plasticity Kernels and Temporal Statistics

Peter Dayan, Michael Häusser, P. Dayan, 2003, NIPS.

Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories

Peter Dayan, Máté Lengyel, Cristina Savin, 2011, NIPS.

Values and Actions in Aversion

Peter Dayan, Ben Seymour, P. Dayan, 2009 .

Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3

Peter Dayan, Máté Lengyel, Cristina Savin, 2014, PLoS Comput. Biol..

Bayesian Model of Behaviour in Economic Games

Peter Dayan, P. Read Montague, Debajyoti Ray, 2008, NIPS.

How fast to work: Response vigor, motivation and tonic dopamine

Peter Dayan, Nathaniel D. Daw, Yael Niv, 2005, NIPS.

Optimal indolence: a normative microscopic approach to work and leisure

Peter Dayan, Peter Shizgal, Ritwik K Niyogi, 2014, Journal of The Royal Society Interface.

Dopamine modulation in the basal ganglia locks the gate to working memory

Boris S. Gutkin, Peter Dayan, Aaron J. Gruber, 2006, Journal of Computational Neuroscience.

TD(λ) Converges with Probability 1

Terrence J. Sejnowski, Peter Dayan, P. Dayan, 1994, Machine Learning.

A Bayesian Framework for Tilt Perception and Confidence

Terrence J. Sejnowski, Peter Dayan, Odelia Schwartz, 2005, NIPS.

Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics

Peter Dayan, Odelia Schwartz, Ruben Coen Cagli, 2012, PLoS Comput. Biol..

Models of value and choice.

Peter Dayan, P. Dayan, 2012 .

The Classification of Spikes in EEG Recordings using Features Derived from ICA

Peter Dayan, David S. Holder, J. Fritschy, 2006 .

Hippocampal Contributions to Control: The Third Way

Peter Dayan, Máté Lengyel, P. Dayan, 2007, NIPS.

Models that learn how humans learn: The case of decision-making and its disorders

Peter Dayan, Amir Dezfouli, Bernard W Balleine, 2019, PLoS Comput. Biol..

Unsupervised learning

Peter Dayan, Maneesh Sahani, Gregoire Deback, 1999 .

Scalable and Efficient Bayes-Adaptive Reinforcement Learning Based on Monte-Carlo Tree Search

Peter Dayan, David Silver, Arthur Guez, 2013, J. Artif. Intell. Res..

Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex

Szabolcs Káli, Peter Dayan, P. Dayan, 2000, NIPS.

Simple Plans or Sophisticated Habits? State, Transition and Learning Interactions in the Two-Step Task

Peter Dayan, Rui Costa, Thomas E. Akam, 2015, bioRxiv.

Acquisition in Autoshaping

Peter Dayan, Sham M. Kakade, S. Kakade, 1999, NIPS.

The convergence of TD(λ) for general λ

Peter Dayan, P. Dayan, 1992, Machine Learning.

Neural Models for Part-Whole Hierarchies

Peter Dayan, Maximilian Riesenhuber, P. Dayan, 1996, NIPS.

Much Ado About Not a LoT

Peter Dayan, P. Dayan, 1992 .

Tamping Ramping: Algorithmic, Implementational, and Computational Explanations of Phasic Dopamine Signals in the Accumbens

Peter Dayan, Kevin Lloyd, P. Dayan, 2015, PLoS Comput. Biol..

Temporal Difference Learning of Position Evaluation in the Game of Go

Terrence J. Sejnowski, Peter Dayan, Nicol N. Schraudolph, 1993, NIPS.

Semiconductor Waveguides: Analysis Of Coupling Between Rib Waveguides And Optical Fibres

Peter Dayan, M. J. Robertson, S. Ritchie, 1985, Other Conferences.

Interplay of approximate planning strategies

Peter Dayan, Erich Seifritz, Samuel J Gershman, 2015, Proceedings of the National Academy of Sciences.

Exploration from Generalization Mediated by Multiple Controllers

Peter Dayan, P. Dayan, 2013, Intrinsically Motivated Learning in Natural and Artificial Systems.

Replay, Repair and Consolidation

Szabolcs Káli, Peter Dayan, P. Dayan, 2002, NIPS.

Acetylcholine in cortical inference

Peter Dayan, Angela J. Yu, P. Dayan, 2002, Neural Networks.

Explaining Away in Weight Space

Peter Dayan, Sham M. Kakade, S. Kakade, 2000, NIPS.

Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning pdf

Peter Dayan, Sanjeevan Ahilan, S. Ahilan, 2019, ICLR 2019.

Dynamic decision making: neuronal, computational, and cognitive underpinnings

Peter Dayan, Nigel Harvey, Maarten Speekenbrink, 2012, CogSci.

A model of risk and mental state shifts during social interaction

Peter Dayan, P. Read Montague, Iris Vilares, 2017, PLoS Comput. Biol..

Some Work and Some Play: Microscopic and Macroscopic Approaches to Labor and Leisure

Peter Dayan, Peter Shizgal, Ritwik K. Niyogi, 2014, PLoS Comput. Biol..

Neural Reinforcement Learning 2: Choice

Peter Dayan, P. Dayan, 2018 .

Bonsai Trees in Your Head: How the Pavlovian System Sculpts Goal-Directed Choices by Pruning Decision Trees

Peter Dayan, Quentin J. M. Huys, Jonathan P. Roiser, 2012, PLoS Comput. Biol..

A Probabilistic Palimpsest Model of Visual Short-term Memory

Peter Dayan, Loic Matthey, Paul M. Bays, 2015, PLoS Comput. Biol..

Learning to use past evidence in a sophisticated world model

Peter Dayan, Peter Shizgal, Ritwik K Niyogi, 2019, PLoS Comput. Biol..

Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131)

Peter Dayan, Ales Leonardis, Jan Peters, 2011, Dagstuhl Reports.

Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm

Peter Dayan, Nathaniel D. Daw, Ben Seymour, 2022 .

Using EM for Reinforcement Learning

Geoffrey E. Hinton, Peter Dayan, P. Dayan, 2000 .

Foraging in an Uncertain Environment Using Predictive Hebbian Learning

Terrence J. Sejnowski, Peter Dayan, P. Read Montague, 1993, NIPS.

A familiarity-based learning procedure for the establishment of place fields in area CA3 of the rat hippocampus

Szabolcs Káli, Peter Dayan, 2001, Neurocomputing.

Computational psychiatry (vol 16, pg 72, 2012)

Karl J. Friston, Peter Dayan, R. J. Dolan, 2012 .

Position Variance, Recurrence and Perceptual Learning

Peter Dayan, Zhaoping Li, P. Dayan, 2000, NIPS.

Comparison of Maximum Likelihood and GAN-based training of Real NVPs pdf

Peter Dayan, Daan Wierstra, Benigno Uria, 2017, ArXiv.

Recurrent sampling models

Peter Dayan, 1998 .

Recognizing Handwritten Digits Using Mixtures of Linear Models

Geoffrey E. Hinton, Peter Dayan, Michael Revow, 1994, NIPS.

Learning to evaluate Go positions via temporal difference methods

Terrence J. Sejnowski, Peter Dayan, Nicol N. Schraudolph, 2001 .

Perturbing Hebbian Rules

Peter Dayan, Geoffrey J. Goodhill, 1991, NIPS.

Probabilistic Computation in Spiking Populations

Peter Dayan, Richard S. Zemel, Quentin J. M. Huys, 2004, NIPS.

How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences

Raymond J. Dolan, Michael Moutoussis, Peter Dayan, 2016, PLoS Comput. Biol..

The Helmholtz Machine

Geoffrey E. Hinton, Peter Dayan, Richard S. Zemel, 1995, Neural Computation.

Computational, Cognitive, and Neural Models of Decision-making Biases

Nick Chater, Peter Dayan, Joshua B. Tenenbaum, 2012, CogSci.

Computational Phenotyping of Two-Person Interactions Reveals Differential Neural Response to Depth-of-Thought

Peter Dayan, Ting Xiang, P. Read Montague, 2012, PLoS Comput. Biol..

The Effect of Correlated Variability on the Accuracy of a Population Code

Peter Dayan, L. F. Abbott, P. Dayan, 1999, Neural Computation.

Load and Attentional Bayes

Peter Dayan, P. Dayan, 2008, NIPS.

Feudal Reinforcement Learning

Geoffrey E. Hinton, Peter Dayan, P. Dayan, 1992, NIPS.

Dopamine Modulation in a Basal Ganglio-cortical Network Implements Saliency-based Gating of Working Memory

Boris S. Gutkin, Peter Dayan, Aaron J. Gruber, 2003, NIPS.

Improving Policies without Measuring Merits

Peter Dayan, Satinder P. Singh, Satinder Singh, 1995, NIPS.

Simple Substrates for Complex Cognition

Peter Dayan, P. Dayan, 2008, Front. Neurosci..

Competition and Arbors in Ocular Dominance

Peter Dayan, 2000, NIPS.

Uncertainty, phase and oscillatory hippocampal recall

Peter Dayan, Máté Lengyel, P. Dayan, 2006, NIPS.

Distributional Population Codes and Multiple Motion Models

Peter Dayan, Richard S. Zemel, R. Zemel, 1998, NIPS.

Correlational-Based Development of Disparity Sensitivity

Terrence J. Sejnowski, Peter Dayan, Gregory S. Berns, 1993 .

Predictive Hebbian learning

Terrence J. Sejnowski, Peter Dayan, P. Read Montague, 1995, COLT '95.

Rationalizable Irrationalities of Choice

Peter Dayan, P. Dayan, 2014, Top. Cogn. Sci..

Exploration Bonuses and Dual Control

Terrence J. Sejnowski, Peter Dayan, P. Dayan, 1996, Machine Learning.

Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models

Peter Dayan, Fabio Tozeto Ramos, Bernard W. Balleine, 2018, bioRxiv.

Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems

Peter Dayan, L. F. Abbott, P. Dayan, 2001 .

Images, Frames, and Connectionist Hierarchies

Peter Dayan, P. Dayan, 2006, Neural Computation.

Bayesian retrieval in associative memories with storage errors

Peter Dayan, Friedrich T. Sommer, P. Dayan, 1998, IEEE Trans. Neural Networks.

Models and Methods for Reinforcement Learning

Peter Dayan, Hiroyuki Nakahara, P. Dayan, 2018 .

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis

Peter Dayan, David S. Holder, Marzia De Lucia, 2008, Medical & Biological Engineering & Computing.

Norepinephrine and Neural Interrupts

Peter Dayan, Angela J. Yu, 2005, NIPS.

Navigating Through Temporal Difference

Peter Dayan, P. Dayan, 1990, NIPS.

Technical Note: Q-Learning

Peter Dayan, Christopher J.C.H. Watkins, P. Dayan, 2004, Machine Learning.

Correlations strike back (again): the case of associative memory retrieval

Peter Dayan, Máté Lengyel, Cristina Savin, 2013, NIPS.

Differential Priors for Elastic Nets

Miguel Á. Carreira-Perpiñán, Peter Dayan, Geoffrey J. Goodhill, 2005, IDEAL.

ACh, Uncertainty, and Cortical Inference

Peter Dayan, Angela J. Yu, P. Dayan, 2001, NIPS.

Optimal learning: a route to depression?

Peter Dayan, Quentin J. M. Huys, 2006 .

Dopamine: generalization and bonuses

Peter Dayan, Sham M. Kakade, S. Kakade, 2002, Neural Networks.

Bayes-Adaptive Simulation-based Search with Value Function Approximation

Peter Dayan, David Silver, Nicolas Heess, 2014, NIPS.

Analytical Mean Squared Error Curves for Temporal Difference Learning

Peter Dayan, Satinder P. Singh, Satinder Singh, 1996, Machine Learning.

Sparse Coding Can Predict Primary Visual Cortex Receptive Field Changes Induced by Abnormal Visual Input

Peter Dayan, Jonathan J. Hunt, Geoffrey J. Goodhill, 2013, PLoS Comput. Biol..

THEORETICAL ANALYSIS OF SEMICONDUCTOR RIB WAVEGUIDES.

Peter Dayan, M. J. Robertson, Michael J. Adams, 1985 .

Go and no-go learning in reward and punishment: Interactions between affect and effect

Raymond J. Dolan, Peter Dayan, Quentin J. M. Huys, 2012, NeuroImage.

Does the Wake-sleep Algorithm Produce Good Density Estimators?

Brendan J. Frey, Geoffrey E. Hinton, Peter Dayan, 1995, NIPS.

Levels of analysis in neural modelling

Peter Dayan, P. Dayan, 2006 .

Control of neurite growth and guidance by an inhibitory cell-body signal

Peter Dayan, Geoffrey J. Goodhill, Zac Pujic, 2018, PLoS Comput. Biol..

Interrupting behaviour: Minimizing decision costs via temporal commitment and low-level interrupts

Peter Dayan, Kevin Lloyd, P. Dayan, 2018, PLoS Comput. Biol..

A model of structure learning, inference, and generation for scene understanding

Peter Dayan, Demis Hassabis, Peter W. Battaglia, 2017, CogSci.

The three R's of trust

Peter Dayan, Terry Lohrenz, P Read Montague, 2015, Current Opinion in Behavioral Sciences.

Dopamine Bonuses

Peter Dayan, Sham M. Kakade, S. Kakade, 2000, NIPS.

Recognition in hierarchical models

Peter Dayan, P. Dayan, 1997 .

Modeling the manifolds of images of handwritten digits

Geoffrey E. Hinton, Peter Dayan, Michael Revow, 1997, IEEE Trans. Neural Networks.

Control over patch encounters changes foraging behavior

Peter Dayan, Nicolas W. Schuck, Sam Hall-McMaster, 2021, iScience.

Two steps to risk sensitivity pdf

Peter Dayan, Chris Gagne, P. Dayan, 2021, NeurIPS.

Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach

Peter Dayan, Iain D. Gilchrist, Michael Mendl, 2021, PLoS Comput. Biol..

Correcting Experience Replay for Multi-Agent Communication pdf

Peter Dayan, Sanjeevan Ahilan, S. Ahilan, 2020, ICLR.

Catastrophe, Compounding & Consistency in Choice pdf

Peter Dayan, Chris Gagne, P. Dayan, 2021, ArXiv.

When unsupervised training benefits category learning

Bradley C. Love, Peter Dayan, Franziska Bröker, 2021, Cognition.

Internality and the internalisation of failure: Evidence from a novel task

Peter Dayan, Jonathan P. Roiser, Federico Mancinelli, 2021, PLoS Comput. Biol..

The Anterior Cingulate Cortex Predicts Future States to Mediate Model-Based Action Selection

Peter Dayan, Michael Pereira, Thomas Akam, 2020, Neuron.

Using Primary Reinforcement to Enhance Translatability of a Human Affect and Decision-Making Judgment Bias Task

Peter Dayan, Iain D Gilchrist, Michael Mendl, 2021, Journal of Cognitive Neuroscience.

Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference

Peter Dayan, Rani Moran, Lorenz Deserno, 2021, Biological Psychiatry.

Temporal difference learning model accounts for responses in human ventral striatum

Karl J. Friston, Peter Dayan, Hugo D. Critchley, 2002 .

Uncertainty and Learning

Peter Dayan, P. Dayan, Angela Jyu, 2003 .

Touché: the feeling of choice

Peter Dayan, Peter E Latham, P. Dayan, 2005, Nature Neuroscience.

Pattern formation and cortical maps

Peter Dayan, P. Dayan, 2003, Journal of Physiology-Paris.

Association of Neural and Emotional Impacts of Reward Prediction Errors With Major Depression

Jenifer Z. Siegel, Michael Moutoussis, Peter Dayan, 2017, JAMA psychiatry.

Decodability of Reward Learning Signals Predicts Mood Fluctuations

Peter Dayan, Eran Eldar, Raymond J. Dolan, 2018, Current Biology.

Locus coeruleus integrity in old age is selectively related to memories linked with salient negative events

Peter Dayan, Nikolaus Weiskopf, Emrah Düzel, 2018, Proceedings of the National Academy of Sciences.

Persecutory delusions and the conditioned avoidance paradigm: Towards an integration of the psychology and biology of paranoia

Michael Moutoussis, Peter Dayan, P. Dayan, 2007, Cognitive neuropsychiatry.

Some work and some play: a normative, microscopic approach to allocating time between work and leisure

Peter Dayan, Peter Shizgal, Kent Conover, 2013 .

A Bayesian View of Sensory Conflicts in Decision-Making March 3 , 2006 1 Introduction

Peter Dayan, Angela J. Yu, P. Dayan, 2006 .

Are you sure about that? On the origins of confidence in concept learning

Peter Dayan, Hrvoje Stojic, Eran Eldar, 2018 .

The modulation of savouring by prediction error and its effects on choice

Zeb Kurth-Nelson, Peter Dayan, Giles W. Story, 2016, eLife.

Necessary, Yet Dissociable Contributions of the Insular and Ventromedial Prefrontal Cortices to Norm Adaptation: Computational and Lesion Evidence in Humans

Peter Dayan, Xiaosi Gu, Robert T Knight, 2015, The Journal of Neuroscience.

The Protective Action Encoding of Serotonin Transients in the Human Brain

Peter Dayan, Terry Lohrenz, Thomas L Ellis, 2018, Neuropsychopharmacology.

Nonpolitical Images Evoke Neural Predictors of Political Ideology

Peter Dayan, Gideon Yaffe, Xiaosi Gu, 2014, Current Biology.