Publikationen:
Abteilung für Computational Neuroscience

Zeitschriftenartikel (15)

  1. 1.
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    Lloyd, K.; Sanborn, A.; Leslie, D.; Lewandowsky, S.: Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation. Cognitive Science 43 (12), S. 1 - 43 (2019)
  2. 2.
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    Schad, D.; Rapp, M.; Garbusow, M.; Nebe, S.; Sebold, M.; Obst, E.; Sommer, C.; Deserno, L.; Rabovsky, M.; Friedel, E. et al.; Romanczuk-Seiferth , N.; Wittchen, H.-U.; Zimmermann, U.; Walter, H.; Sterzer, P.; Smolka, M.; Schlagenhauf, F.; Heinz, A.; Dayan, P.; Huys, Q.: Dissociating neural learning signals in human sign- and goal-trackers. Nature Human Behaviour Epub ahead (2019)
  3. 3.
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    Wise, T.; Michely, J.; Dayan, P.; Dolan, R.: A computational account of threat-related attentional bias. PLoS Computational Biology 15 (10) (2019)
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    Zhao, S.; Chait, M.; Dick, F.; Dayan, P.; Furukawa, S.; Liao, H.: Pupil-linked phasic arousal evoked by violation but not emergence of regularity within rapid sound sequences. Nature Communications 10 (2019)
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    Javadi, A.; Patai, E.; Marin-Garcia, E.; Margolis, A.; Tan, H.-R.; Kumaran, D.; Nardini, M.; Duzel, E.; Dayan, P.; Spiers, H.: Prefrontal Dynamics Associated with Efficient Detours and Shortcuts: A Combined Functional Magnetic Resonance Imaging and Magnetoencenphalography Study. Journal of Cognitive Neuroscience 31 (8), S. 1227 - 1247 (2019)
  6. 6.
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    Na, S.; Chung, D.; Jung, J.; Hula, A.; Fiore, V.; Dayan, P.; Gu, X.: Humans Use Forward Thinking to Exert Social Control. Neuron (angenommen)
  7. 7.
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    Javadi, A.-H.; Patai, E.; Marin-Garcia, E.; Margois, A.; Tan, H.-R.; Kumaran, D.; Nardini, M.; Penny, W.; Duzel, E.; Dayan, P. et al.; Spiers, H.: Backtracking during navigation is correlated with enhanced anterior cingulate activity and suppression of alpha oscillations and the "default-mode" network. Proceedings of the Royal Society B: Biological Sciences 286 (1908) (2019)
  8. 8.
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    Ahilan, S.; Solomon, R.; Breton, A.-Y.; Conover, K.; Niyogi, R.; Shizgal, P.; Dayan, P.: Learning to use past evidence in a sophisticated world model. PLoS Computational Biology 15 (6) (2019)
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    Dezfouli , A.; Griffiths, K.; Ramos, F.; Dayan, P.; Balleine, B.: Models that learn how humans learn: The case of decision-making and its disorders. PLoS Computational Biology 16 (6) (2019)
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    Stojic, H.; Orquin, J.; Dayan, P.; Dolan, R.; Speekenbrink, M.: Uncertainty in learning, choice and visual fixation. (eingereicht)
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    Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dayan, P.; Dolan, R.: Hippocampal-midbrain circuit enhances the pleasure of anticipation in the prefrontal cortex. (eingereicht)
  12. 12.
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    Rouault, M.; Dayan, P.; Fleming, S.: Forming global estimates of self-performance from local confidence. Nature Communications 10 (1) (2019)
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    Moran, R.; Keramati, M.; Dayan, P.; Dolan, R.: Retrospective model-based inference guides model-free credit assignment. Nature Communications 10 (2019)
  14. 14.
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    Moutoussis, M.; Bullmore, E.; Goodyer, I.; Fonagy, P.; Jones, P.; Dolan, R.; Dayan, P.: Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood. PLoS Computational Biology 14 (12) (2018)
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    Zhao, S.; Chait, M.; Dick, F.; Dayan, P.; Furukawa, S.; Liao, H.-I.: Phasic norepinephrine is a neural interrupt signal for unexpected events in rapidly unfolding sensory sequences: evidence from pupillometry. - (2018)

Konferenzbeitrag (5)

  1. 16.
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    Dezfouli , A.; Ashtiani , H.; Ghattas, O.; Nock, R.; Dayan, P.; Ong, C.: Disentangled behavioural representations. In: Advances in Neural Information Processing Systems 32 (Hg. Wallach, H.; Larochelle, H.; Beygelzimer , A.; d'Alché-Buc, F.; Fox, E. et al.). Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 09. Dezember 2019 - 13. Dezember 2019. (2019)
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    Jain, Y.; Gupta, S.; Rakesh, V.; Dayan, P.; Callaway, F.; Lieder, F.: How do people learn how to plan? In: Conference on Cognitive Computational Neuroscience (CCN 2019). Conference on Cognitive Computational Neuroscience (CCN 2019), Berlin, Germany, 13. September 2019 - 16. September 2019. (2019)
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    Browning, M.; Carter, C.; Chatham, C.; Den Ouden, H.; Gillan, C.; Baker, J.; Chekroud, A.; Cools, R.; Dayan, P.; Gold, J. et al.; Goldstein, R.; Hartley, C.; Kepecs, A.; Lawson, R.; Mourao-Miranda, J.; Phillips, M.; Pizzagalli, D.; Powers, A.; Rindskopf, D.; Roiser, J.; Schmack, K.; Schiller, D.; Sebold, M.; Stephan, K.; Frank, M.; Huys, Q.; Paulus, M.: Realizing the Clinical Potential of Computational Psychiatry: Report from the Banbury Center Meeting, February 2019. In: Banbury Center Meeting. Banbury Center Meeting, Huntington, NY, USA, 2019-02. (2019)
  4. 19.
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    Ahilan, S.; Dayan, P.: Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. In: Annual Conference of the American Library Association (ALA 2019). Annual Conference of the American Library Association (ALA 2019) , Washington, DC, USA, 20. Juni 2019 - 25. Juni 2019. (2019)
  5. 20.
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    Ahilan, S.; Dayan, P.: Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. In: Workshop on Structure & Priors in Reinforcement Learning (SPiRL 2019) at ICLR 2019. Workshop on Structure & Priors in Reinforcement Learning (SPiRL 2019) at ICLR 2019, New Orleans, LA, USA, 06. Mai 2019. (2019)

Meeting Abstract (5)

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    Dayan, P.; Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dolan, R.: Anticipation, imagination and information seeking via mid-brain, hippocampal, and prefrontal interactions. In 49th Annual Meeting of the Society for Neuroscience (Neuroscience 2019), 018.12. 49th Annual Meeting of the Society for Neuroscience (Neuroscience 2019), Chicago, IL, USA, 19. Oktober 2019 - 23. Oktober 2019. (2019)
  2. 22.
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    Mendl, M.; Jones, S.; Neville, V.; Higgs, L.; Robinson, E.; Dayan, P.; Paul, E.: An automated and self-initiated judgement bias task based on natural investigative behaviour. In Applied Ethology 2019: Animal lives worth living: 53rd Congress of the International Society of Applied Ethology (ISAE 2019), S. 126 (Hg. Newberry, R.; Braastad, B.). 53rd Congress of the International Society of Applied Ethology (ISAE 2019), Bergen, Norway, 05. August 2019 - 09. August 2019. Wageningen Academic Publishers, Wageningen, The Netherlands (2019)
  3. 23.
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    Neville, V.; Paul, L.; Dayan, P.; Gilchrist, I.; Mendl, M.: Investigating animal affect and welfare using computational modelling. In Applied Ethology 2019: Animal lives worth living: 53rd Congress of the International Society of Applied Ethology (ISAE 2019), S. 127 (Hg. Newberry, R.; Braastad, B.). 53rd Congress of the International Society of Applied Ethology (ISAE 2019), Bergen, Norway, 05. August 2019 - 09. August 2019. Wageningen Academic Publishers, Wageningen, The Netherlands (2019)
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    Rouault, C.; Dayan, P.; Fleming, S.: Forming global estimates of self-performance from local confidence. In Tagung Experimentell Arbeitender Psychologen (TEAP 2019). Tagung Experimentell Arbeitender Psychologen (TEAP 2019), London, UK, 15. April 2019 - 17. April 2019. (2019)
  5. 25.
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    Vilares, I.; Nolte, T.; Hula, A.; Cui, Z.; Fonagy, P.; Zhu, L.; Chiu, P.; King-Casas, B.; Lohrenz, T.; Dayan, P. et al.; Montague, R.: Computational Phenotyping in Borderline Personality Using a Role-Based Social Hierarchy Probe. In Biological Psychiatry, 85 (10 Supplement), O8. 74th Annual Meeting of the Society of Biological Psychiatry, Chicago, IL, USA, 16. Mai 2019 - 18. Mai 2019. Elsevier, New York (2019)

Vortrag (30)

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    Dayan, P.: All Models Are Wronged. Gordon Research Conference: Functions of the Basal Ganglia from Thought to Action , Ventura, CA, USA (2020)
  2. 27.
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    Dayan, P.; Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dolan, R.: Savouring and its Modulation by Prediction Errors. Departmental Colloquium Max Planck for Biological Cybernetics, Tübingen, Germany (2019)
  3. 28.
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    Dayan, P.: Replay and Preplay in Human Planning. Seminars of the Department of Neuroscience: Université de Genève, Genève, Switzerland (2019)
  4. 29.
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    Dayan, P.: Neural Reinforcement Learning. Humboldt Lecture Series at Tübingen University , Tübingen, Germany (2019)
  5. 30.
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    Dayan, P.; Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dolan, R.: Savouring and its Modulation by Prediction Errors. Colloquium Cognitive Systems: Universität Ulm , Ulm, Germany (2019)
  6. 31.
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    Dayan, P.: Savouring and its Modulation by Prediction Errors. 17th Annual Meeting of the Society for NeuroEconomics (SNE 2019), Dublin, Ireland (2019)
  7. 32.
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    Dayan, P.: Theoretical Neuroscience: Decision Making and its Discontents. 49th Annual Meeting of the Society for Neuroscience (Neuroscience 2019) , Chicago, IL, USA (2019)
  8. 33.
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    Sharan, M.; Dinkel, H.: Building Blocks of Python Programming. EMBL Course: Computing Skills For Reproducible Research: Software Carpentry, Heidelberg, Germany (2019)
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    Sharan, M.; Dinkel, H.; Alves, R.: Building programs with Python I. EMBL Course: Computing Skills For Reproducible Research: Software Carpentry, Heidelberg, Germany (2019)
  10. 35.
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    Sharan, M.; Dinkel, H.; Alves, R.: Building programs with Python II. EMBL Course: Computing Skills For Reproducible Research: Software Carpentry, Heidelberg, Germany (2019)
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    Sharan, M.; Dinkel, H.; Alves, R.: Using commandline git for version control. EMBL Course: Computing Skills For Reproducible Research: Software Carpentry, Heidelberg, Germany (2019)
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    Dayan, P.: The cortical dynamics of integrative decision making. 6th ESI Systems Neuroscience Conference 2019: The recurrent cortex: feedback, dynamics, and dimensionality , Frankfurt a.M., Germany (2019)
  13. 38.
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    Dayan, P.: Unsupervised Yearning. David Marr, 50 years on (Marr 2019) at Artificial & Biological Cognition 2019, Cambridge, UK (2019)
  14. 39.
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    Dayan, P.: Dysfunctional decision-making. Tübingen International Summer School (TISS 2019), Kloster Heiligkreuztal (2019)
  15. 40.
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    Dayan, P.: Functional decision-making. Tübingen International Summer School (TISS 2019), Kloster Heiligkreuztal (2019)
  16. 41.
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    Dayan, P.: Reinforcement learning. 2019 Computational Psychiatry Summer Course, New York, NY, USA (2019)
  17. 42.
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    Dayan, P.: Theoretical approaches to function and dysfunction. 2019 Computational Psychiatry Summer Course, New York, NY, USA (2019)
  18. 43.
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    Dayan, P.: Slothful serial: perilous parallel processing. Workshop Heuristics, Hacks and Habits: 41st Annual Meeting of the Cognitive Science Society (COGSCI 2019), Montréal, Canada (2019)
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    Dayan, P.: Decision-making and some of its Discontents. 9th IMPRS NeuroCom Summer School in Cognitive Neuroscience , Leipzig, Germany (2019)
  20. 45.
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    Dayan, P.: Savouring and its Modulation by Prediction Errors. NEUREX Workshop: Neuroeconomics: Studying Decision Making in an Economic Context, Strasbourg, France (2019)
  21. 46.
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    Dayan, P.: Pavlovian-Instrumental Interactions in Active Avoidance: The Bark of Neutral Trials. Modulation of Neural Circuits and Behavior Gordon Research Conference: Neuromodulatory Mechanisms Underlying Flexible Brain Functions and Behavior , Les Diablerets, Switzerland (2019)
  22. 47.
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    Dayan, P.: The Cortical Dynamics of Integrative Decision Making. University of Freiburg: Bernstein Seminar, Freiburg i.Br., Germany (2019)
  23. 48.
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    Dayan, P.: Learning in Natural Neural Systems. Eberhard-Karls-Universität Tübingen: Studium Generale: Maschinelles Lernen, Tübingen, Germany (2019)
  24. 49.
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    Dayan, P.: The long and the short of serotonergic stimulation: The learning rate for rewards. NeuroRetreat 2019: Max Planck Institute of Psychiatry, München, Germany (2019)
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    Dayan, P.: The Good, The Bad, and Something Inbetween: Dopamine in Active Avoidance. Centro Champalimaud, Lisboa, Portugal (2019)
  26. 51.
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    Dayan, P.: The long and the short of 5-HT stimulation: optogenetic activation of dorsal raphe serotonergic neurons changes the learning rate for rewards. COSYNE 2019 Workshop: Advances and convergences in 5-HT research , Cascais, Portugal (2019)
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    Dayan, P.: Neural Reinforcement Learning 3: The Self and the Other. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)
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    Dayan, P.: Neural Reinforcement Learning 2: Choice. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)
  29. 54.
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    Dayan, P.: Neural Reinforcement Learning 1: Prediction. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)
  30. 55.
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    Dayan, P.: The long and the short of serotonergic stimulation: Selective effects on the learning rate of rewards. InstitutsSeminar Neurobiologie: Institute of Neurobiology, Eberhard-Karls Universität Tübingen, Tübingen, Germany (2018)

Poster (7)

  1. 56.
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    Bröker, F.; Love, B.; Dayan, P.: Semi-Supervised Categorisation: Input Representations Determine Necessity of Feedback. 20th Conference of Junior Neuroscientists (NeNa 2019) , Schramberg, Germany (2019)
  2. 57.
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    Bruijns, S.; Dayan, P.: Anticipating Every Turn: Learning About Learning in Mice. 20th Conference of Junior Neuroscientists (NeNa 2019) , Schramberg, Germany (2019)
  3. 58.
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    Ahilan, S.; Dayan, P.: Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2019), Montreal, Canada (2019)
  4. 59.
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    Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O’Doherty, J.; Dayan, P.; Dolan, R.: Hippocampal-midbrain circuit enhances the pleasure of anticipation in the prefrontal cortex. 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2019), Montreal, Canada (2019)
  5. 60.
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    Stojic, H.; Orquin, J.; Dayan, P.; Dolan, R.; Speekenbrink, M.: Rewards and uncertainty jointly drive the attention dynamics in reinforcement learning. Ninth International Symposium on Biology of Decision Making (SBDM 2019) , Oxford, UK (2019)
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    Zamfir, E.; Dayan, P.: The dynamical interaction between attribution and belief: Evidence from a novel task. Ninth International Symposium on Biology of Decision Making (SBDM 2019), Oxford, UK (2019)
  7. 62.
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    Zhao, S.; Dick, F.; Dayan, P.; Furukawa, S.; Hiao, L.-I.; Chait, M.: Phasic norepinephrine is a neural interrupt signal for unexpected events in rapidly unfolding sensory sequences: evidence from pupillometry. Ninth International Symposium on Biology of Decision Making (SBDM 2019), Oxford, UK (2019)
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