P Dayan

Summary

Affiliation: University College London
Country: UK

Publications

  1. pmc Mapping anhedonia onto reinforcement learning: a behavioural meta-analysis
    Quentin Jm Huys
    Gatsby Computational Neuroscience Unit, UCL, London, UK
    Biol Mood Anxiety Disord 3:12. 2013
  2. doi request reprint How to set the switches on this thing
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, 17 Queen Square, London WC1N 3AR, United Kingdom
    Curr Opin Neurobiol 22:1068-74. 2012
  3. doi request reprint Twenty-five lessons from computational neuromodulation
    Peter Dayan
    Gatsby Computational Neuroscience Unit, 17 Queen Square, London, UK
    Neuron 76:240-56. 2012
  4. doi request reprint Instrumental vigour in punishment and reward
    Peter Dayan
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London WC1N 3AR, UK
    Eur J Neurosci 35:1152-68. 2012
  5. doi request reprint Reinforcement learning: the good, the bad and the ugly
    Peter Dayan
    UCL, UK
    Curr Opin Neurobiol 18:185-96. 2008
  6. ncbi request reprint Images, frames, and connectionist hierarchies
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London
    Neural Comput 18:2293-319. 2006
  7. ncbi request reprint The misbehavior of value and the discipline of the will
    Peter Dayan
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London, UK
    Neural Netw 19:1153-60. 2006
  8. doi request reprint Serotonin in affective control
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London WC1N3AR, UK
    Annu Rev Neurosci 32:95-126. 2009
  9. doi request reprint Decision theory, reinforcement learning, and the brain
    Peter Dayan
    University College London, London, England
    Cogn Affect Behav Neurosci 8:429-53. 2008
  10. doi request reprint Prospective and retrospective temporal difference learning
    Peter Dayan
    Gatsby Computational Neuroscience Unit, UCL, London, WC1N 3AR, UK
    Network 20:32-46. 2009

Detail Information

Publications56

  1. pmc Mapping anhedonia onto reinforcement learning: a behavioural meta-analysis
    Quentin Jm Huys
    Gatsby Computational Neuroscience Unit, UCL, London, UK
    Biol Mood Anxiety Disord 3:12. 2013
    ..We attempted to disentangle these factors with respect to anhedonia in the context of stress, Major Depressive Disorder (MDD), Bipolar Disorder (BPD) and a dopaminergic challenge...
  2. doi request reprint How to set the switches on this thing
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, 17 Queen Square, London WC1N 3AR, United Kingdom
    Curr Opin Neurobiol 22:1068-74. 2012
    ..We review recent work in this area, focusing on cognitive control...
  3. doi request reprint Twenty-five lessons from computational neuromodulation
    Peter Dayan
    Gatsby Computational Neuroscience Unit, 17 Queen Square, London, UK
    Neuron 76:240-56. 2012
    ..Here, I offer a computationally focused review of algorithmic and implementational motifs associated with neuromodulators, using decision making in the face of uncertainty as a running example...
  4. doi request reprint Instrumental vigour in punishment and reward
    Peter Dayan
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London WC1N 3AR, UK
    Eur J Neurosci 35:1152-68. 2012
    ..Finally, we study how to fit these ideas into nascent treatments that extend concepts of opponency between dopamine and serotonin from valence to invigoration...
  5. doi request reprint Reinforcement learning: the good, the bad and the ugly
    Peter Dayan
    UCL, UK
    Curr Opin Neurobiol 18:185-96. 2008
    ..Here we review the latest dispatches from the forefront of this field, and map out some of the territories where lie monsters...
  6. ncbi request reprint Images, frames, and connectionist hierarchies
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London
    Neural Comput 18:2293-319. 2006
    ..We meld unsupervised learning notions formulated for multilinear models with tensor product ideas for representing rich information. We apply the model to images of faces...
  7. ncbi request reprint The misbehavior of value and the discipline of the will
    Peter Dayan
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London, UK
    Neural Netw 19:1153-60. 2006
    ..The misbehavior created by Pavlovian values can be quite debilitating; we discuss how it may be disciplined...
  8. doi request reprint Serotonin in affective control
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London WC1N3AR, UK
    Annu Rev Neurosci 32:95-126. 2009
    ..Finally, we suggest that it is only a partial reflection of dopamine because of essential asymmetries between the natural statistics of rewards and punishments...
  9. doi request reprint Decision theory, reinforcement learning, and the brain
    Peter Dayan
    University College London, London, England
    Cogn Affect Behav Neurosci 8:429-53. 2008
    ....
  10. doi request reprint Prospective and retrospective temporal difference learning
    Peter Dayan
    Gatsby Computational Neuroscience Unit, UCL, London, WC1N 3AR, UK
    Network 20:32-46. 2009
    ..At the heart of the model is the average reward per step, which acts as a baseline for measuring immediate rewards. Relatively subtle changes to this baseline occasioned by the past can markedly influence predictions and thus behavior...
  11. doi request reprint Goal-directed control and its antipodes
    Peter Dayan
    UCL, 17 Queen Square, London WC1N 3AR, UK
    Neural Netw 22:213-9. 2009
    ..Our overall aim is to reconnect some presently far-flung relations...
  12. doi request reprint Dopamine, reinforcement learning, and addiction
    P Dayan
    Gatsby Computational Neuroscience Unit, UCL, London, UK
    Pharmacopsychiatry 42:S56-65. 2009
    ..We then use this as a framework to sketch various notions of the neuromodulator's possible participation in initiation and compulsion. We end with some pointers towards future theoretical developments...
  13. doi request reprint Selective Bayes: attentional load and crowding
    Peter Dayan
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London WC1N 3AR, United Kingdom
    Vision Res 50:2248-60. 2010
    ..We show how these seeming anomalies can arise from normative Bayesian inference in the face of spatially confounded input...
  14. ncbi request reprint Putting the computation back into computational modeling
    P Dayan
    Gatsby Computational Neuroscience Unit, University College, London, UK
    Pharmacopsychiatry 39:S50-1. 2006
    ..Many different varieties of modeling coexist in theoretical neuroscience. Here, we consider the positive and negative implications, for theories of schizophrenia, of a crucial distinction between computational and mathematical modeling...
  15. ncbi request reprint Pattern formation and cortical maps
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, Alexandra House, 17 Queen Square, London WCIN 3AR, UK
    J Physiol Paris 97:475-89. 2003
    ..Here, we describe and analyse a paradigmatic algorithm for activity-dependent development of the refinement and generation of neuronal selectivities, and relate it to some of the wealth of suggestions in the literature...
  16. ncbi request reprint Reward, motivation, and reinforcement learning
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, 17 Queen Square, WC1N 3AR, London, United Kingdom
    Neuron 36:285-98. 2002
    ..We review the data and consider the involvement of a rich collection of different neural systems in various aspects of these forms of conditioning. Dopamine plays a pivotal, but complicated, role...
  17. ncbi request reprint Learning and selective attention
    P Dayan
    Gatsby Computational Neuroscience Unit, University College London, UK
    Nat Neurosci 3:1218-23. 2000
    ..Neuromodulatory systems and limbic structures are known to underlie attentional effects in such tasks...
  18. ncbi request reprint Neuroscience. Matchmaking
    Nathaniel D Daw
    Gatsby Computational Neuroscience Unit, University College London, London WC1N 3AR, UK
    Science 304:1753-4. 2004
  19. ncbi request reprint Phasic norepinephrine: a neural interrupt signal for unexpected events
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London, UK
    Network 17:335-50. 2006
    ..We quantify this idea in a Bayesian model of a well-studied visual discrimination task, demonstrating that the model captures a rich repertoire of noradrenergic responses at the sub-second temporal resolution...
  20. pmc Differential encoding of losses and gains in the human striatum
    Ben Seymour
    Wellcome Trust Centre for Neuroimaging, UCL, London, United Kingdom
    J Neurosci 27:4826-31. 2007
    ....
  21. ncbi request reprint Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control
    Nathaniel D Daw
    Gatsby Computational Neuroscience Unit, University College London, Alexandra House, 17 Queen Square, London WC1N 3AR, UK
    Nat Neurosci 8:1704-11. 2005
    ..This provides a unifying account of a wealth of experimental evidence about the factors favoring dominance by either system...
  22. pmc Human pavlovian-instrumental transfer
    Deborah Talmi
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, WC1N 3BG London, United Kingdom
    J Neurosci 28:360-8. 2008
    ..Our data dovetails well with the animal literature and sheds light on the neural control of vigor...
  23. doi request reprint Change-based inference for invariant discrimination
    Reza Moazzezi
    Gatsby Computational Neuroscience Unit, Alexandra House, 17 Queen Square, London, WC1N 3AR, UK
    Network 19:236-52. 2008
    ....
  24. doi request reprint Flexible shaping: how learning in small steps helps
    Kai A Krueger
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London WC1N 3AR, United Kingdom
    Cognition 110:380-94. 2009
    ..Further, it leads to internal representations that are more robust to task manipulations such as reversals. We use the model to investigate some of the elements of successful shaping...
  25. pmc A common mechanism for adaptive scaling of reward and novelty
    Nico Bunzeck
    Institute of Cognitive Neuroscience, University College London, London WC1N 3AR, United Kingdom
    Hum Brain Mapp 31:1380-94. 2010
    ..These findings demonstrate a new mechanism for adjusting gain and sensitivity in declarative memory in accordance with contextual probabilities and expectancies of future events...
  26. ncbi request reprint Acetylcholine in cortical inference
    Angela J Yu
    Gatsby Computational Neuroscience Unit, University College London, UK
    Neural Netw 15:719-30. 2002
    ..We illustrate our proposal by means of an hierarchical hidden Markov model, showing that cholinergic modulation of contextual information leads to appropriate perceptual inference...
  27. ncbi request reprint Dopamine: generalization and bonuses
    Sham Kakade
    Gatsby Computational Neuroscience Unit, University College London, UK
    Neural Netw 15:549-59. 2002
    ..We interpret this additional role for dopamine in terms of the mechanistic attentional and psychomotor effects of dopamine, having the computational role of guiding exploration...
  28. ncbi request reprint Acquisition and extinction in autoshaping
    Sham Kakade
    Gatsby Computational Neuroscience Unit, University College London, England
    Psychol Rev 109:533-44. 2002
    ....
  29. ncbi request reprint Pre-attentive visual selection
    Li Zhaoping
    University College London, Department of Psychology, United Kingdom
    Neural Netw 19:1437-9. 2006
  30. ncbi request reprint Temporal difference models and reward-related learning in the human brain
    JOHN P O'DOHERTY
    Wellcome Department of Imaging Neuroscience, Institute of Neurology, University College London, WC1N 3BG, London, United Kingdom
    Neuron 38:329-37. 2003
    ....
  31. pmc Cortical substrates for exploratory decisions in humans
    Nathaniel D Daw
    Gatsby Computational Neuroscience Unit, University College London UCL, Alexandra House, 17 Queen Square, London WC1N 3AR, UK
    Nature 441:876-9. 2006
    ....
  32. ncbi request reprint Matching storage and recall: hippocampal spike timing-dependent plasticity and phase response curves
    Máté Lengyel
    Gatsby Computational Neuroscience Unit, University College London, 17 Queen Square, London WC1N 3AR, UK
    Nat Neurosci 8:1677-83. 2005
    ..We show through simulation that such memories are competent analog autoassociators and demonstrate directly that the attributes of phase response curves of CA3 pyramidal cells recorded in vitro qualitatively conform with the theory...
  33. ncbi request reprint A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis
    Marzia De Lucia
    Medical Physics and Clinical Neurophysiology, University College London, London, UK
    Med Biol Eng Comput 46:263-72. 2008
    ..Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG...
  34. ncbi request reprint Uncertainty, neuromodulation, and attention
    Angela J Yu
    Gatsby Computational Neuroscience Unit, London, United Kingdom
    Neuron 46:681-92. 2005
    ..Moreover, the model suggests a class of attentional cueing tasks that involve both neuromodulators and shows how their interactions may be part-antagonistic, part-synergistic...
  35. ncbi request reprint Temporal difference models describe higher-order learning in humans
    Ben Seymour
    Wellcome Department of Imaging Neuroscience, 12 Queen Square, London WC1N 3BG, UK
    Nature 429:664-7. 2004
    ..Taken with existing data on reward learning, our results suggest a critical role for the ventral striatum in integrating complex appetitive and aversive predictions to coordinate behaviour...
  36. ncbi request reprint Dissociable roles of ventral and dorsal striatum in instrumental conditioning
    John O'Doherty
    Wellcome Department of Imaging Neuroscience, Institute of Neurology, University College London, London WC1N 3BG, UK
    Science 304:452-4. 2004
    ..Our results suggest partly dissociable contributions of the ventral and dorsal striatum, with the former corresponding to the critic and the latter corresponding to the actor...
  37. pmc Serotonin, inhibition, and negative mood
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
    PLoS Comput Biol 4:e4. 2008
    ....
  38. ncbi request reprint Fast population coding
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, University College London, London WC1N 3AR, UK
    Neural Comput 19:404-41. 2007
    ..We suggest this as an appropriate foundation for understanding time-varying population codes. Furthermore, we show how adaptation to temporal stimulus statistics emerges directly from the demands of simple decoding...
  39. ncbi request reprint Nonlinear ideal observation and recurrent preprocessing in perceptual learning
    L Zhaoping
    Department of Psychology, University College, London WC1E 6BT, UK
    Network 14:233-47. 2003
    ..Since, psychophysically, hyperacuity typically improves greatly over the course of perceptual learning, we discuss our model in the light of results on the speed and nature of learning...
  40. ncbi request reprint Dopamine, learning, and impulsivity: a biological account of attention-deficit/hyperactivity disorder
    Jonathan Williams
    Department of Child and Adolescent Psychiatry, Institute of Psychiatry, De Crespigny Park, Denmark Hill, London, UK
    J Child Adolesc Psychopharmacol 15:160-79; discussion 157-9. 2005
    ..In this study, we tested the theory that both the persistence and the variability of impulsivity could be the result of abnormalities in learning mechanisms and environment...
  41. doi request reprint A Bayesian formulation of behavioral control
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London WC1N3AR, UK
    Cognition 113:314-28. 2009
    ..These results are discussed with reference to depression and animal models thereof...
  42. ncbi request reprint Touché: the feeling of choice
    Peter E Latham
    Nat Neurosci 8:408-9. 2005
  43. ncbi request reprint Inference and computation with population codes
    Alexandre Pouget
    Department of Brain and Cognitive Sciences, Meliora Hall, University of Rochester, Rochester, NY 14627, USA
    Annu Rev Neurosci 26:381-410. 2003
    ..g., the probability density function over the orientation of a contour). This paper reviews both approaches, with a particular emphasis on the latter, which we see as a very promising framework for future modeling and experimental work...
  44. ncbi request reprint Tonic dopamine: opportunity costs and the control of response vigor
    Yael Niv
    Interdisciplinary Center for Neural Computation, The Hebrew University of Jerusalem, Jerusalem, 91904, Israel
    Psychopharmacology (Berl) 191:507-20. 2007
    ....
  45. ncbi request reprint Dopamine modulation in the basal ganglia locks the gate to working memory
    Aaron J Gruber
    Biomedical Engineering, Northwestern University, Chicago, IL, USA
    J Comput Neurosci 20:153-66. 2006
    ..Dopamine's involvement in affective processing endows this gating with specificity to motivational salience. We model a spatial working memory task and show that these combined effects of dopamine lead to superior performance...
  46. ncbi request reprint Opponent interactions between serotonin and dopamine
    Nathaniel D Daw
    Computer Science Department and Center for the Neural Basis of Cognition, School of Computer Science, Carnegie Mellon University, Pittsburgh PA 15213 3891, USA
    Neural Netw 15:603-16. 2002
    ....
  47. ncbi request reprint A normative perspective on motivation
    Yael Niv
    Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem, Israel
    Trends Cogn Sci 10:375-81. 2006
    ..However, in novel states, we propose that outcome-independent, global effects of the utilities can 'energize' habitual actions...
  48. ncbi request reprint Space and time in visual context
    Odelia Schwartz
    Albert Einstein College of Medicine, Jack and Pearl Resnick Campus, 1300 Morris Park Avenue, Bronx, New York 10461 718 430 2000, USA
    Nat Rev Neurosci 8:522-35. 2007
    ..We review the empirical literature and discuss the computational and statistical ideas that are battling to explain these conundrums, and thereby gain favour as more general accounts of cortical processing...
  49. ncbi request reprint Choice values
    Yael Niv
    Nat Neurosci 9:987-8. 2006
  50. doi request reprint Adaptation across the cortical hierarchy: low-level curve adaptation affects high-level facial-expression judgments
    Hong Xu
    Department of Neuroscience, Columbia University, New York, New York 10032, USA
    J Neurosci 28:3374-83. 2008
    ..By showing that adaptation can propagate up the cortical hierarchy, our findings also challenge existing functional accounts of adaptation...
  51. doi request reprint Encoding and decoding spikes for dynamic stimuli
    Rama Natarajan
    Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
    Neural Comput 20:2325-60. 2008
    ..We show that this network can be learned in a supervised manner by a simple local learning rule...
  52. ncbi request reprint Doubly distributional population codes: simultaneous representation of uncertainty and multiplicity
    Maneesh Sahani
    W M Keck Foundation Center for Integrative Neurosciences, Univ of Calif, San Francisco, CA 94143 0732, USA
    Neural Comput 15:2255-79. 2003
    ..We present and validate a more powerful proposal for the way that population activity may encode uncertainty, both distinctly from and simultaneously with multiplicity...
  53. ncbi request reprint Off-line replay maintains declarative memories in a model of hippocampal-neocortical interactions
    Szabolcs Káli
    Institute of Experimental Medicine, Hungarian Academy of Sciences, P O BOX 67, Budapest 1450, Hungary
    Nat Neurosci 7:286-94. 2004
    ..Hippocampal storage and replay also has a constructive role in the recall of structured, semantic information...
  54. doi request reprint A temporal difference account of avoidance learning
    Michael Moutoussis
    Tolworth Hospital, Surbiton, England
    Network 19:137-60. 2008
    ..These postulated roles of dopamine in aversive learning can thus account for many of the effects of dopaminergic modulation seen in laboratory models of psychopathological processes...
  55. ncbi request reprint Persecutory delusions and the conditioned avoidance paradigm: towards an integration of the psychology and biology of paranoia
    Michael Moutoussis
    Tolworth Hospital, Red Lion Road, Surbiton, UK
    Cogn Neuropsychiatry 12:495-510. 2007
    ..In this study, we reappraise the psychological significance of the CAR model of antipsychotic drug action; and we relate this to contemporary psychological theories of paranoia...
  56. pmc Soft mixer assignment in a hierarchical generative model of natural scene statistics
    Odelia Schwartz
    Howard Hughes Medical Institute, Computational Neurobiology Lab, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
    Neural Comput 18:2680-718. 2006
    ..We also show how our model helps interrelate a wide range of models of image statistics and cortical processing...