_{Publikationen:
Abteilung für Computational Neuroscience}

Zeitschriftenartikel (11)

1. 1.
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   Zeitschriftenartikel

   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)
2. 2.
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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)
3. 3.
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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)
4. 4.
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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)
5. 5.
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   Stojic, H.; Orquin, J.; Dayan, P.; Dolan, R.: Uncertainty in learning, choice and visual fixation. (eingereicht)
6. 6.
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   Stojic, H.; Orquin, J.; Dayan, P.; Dolan, R.; Speekenbrink, M.: Uncertainty in learning, choice and visual fixation. (eingereicht)
7. 7.
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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)
8. 8.
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   Rouault, M.; Dayan, P.; Fleming, S.: Forming global estimates of self-performance from local confidence. Nature Communications 10 (1) (2019)
9. 9.
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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)
10. 10.
    MPG.PuRe

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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)
11. 11.
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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 (1)

1. 12.
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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 (2)

1. 13.
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   Meeting Abstract

   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)
2. 14.
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   Meeting Abstract

   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 (17)

1. 15.
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   Dayan, P.: Savouring and its Modulation by Prediction Errors. 2019 Annual Meeting of the Society for NeuroEconomics: The Fred Kavli Plenary Lecture, Dublin, Ireland (2019)
2. 16.
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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)
3. 17.
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   Vortrag

   Dayan, P.: Unsupervised Yearning. David Marr, 50 years on (Marr 2019) at Artificial & Biological Cognition 2019, Cambridge, UK (2019)
4. 18.
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   Vortrag

   Dayan, P.: Reinforcement learning. 2019 Computational Psychiatry Summer Course, New York, NY, USA (2019)
5. 19.
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   Dayan, P.: Theoretical approaches to function and dysfunction. 2019 Computational Psychiatry Summer Course, New York, NY, USA (2019)
6. 20.
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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)
7. 21.
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   Dayan, P.: Decision-making and some of its Discontents. 9th IMPRS NeuroCom Summer School in Cognitive Neuroscience , Leipzig, Germany (2019)
8. 22.
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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)
9. 23.
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   Dayan, P.: The Cortical Dynamics of Integrative Decision Making. University of Freiburg: Bernstein Seminar, Freiburg i.Br., Germany (2019)
10. 24.
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    Dayan, P.: Learning in Natural Neural Systems. Eberhard-Karls-Universität Tübingen: Studium Generale: Maschinelles Lernen, Tübingen, Germany (2019)
11. 25.
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    Vortrag

    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)
12. 26.
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    Dayan, P.: The Good, The Bad, and Something Inbetween: Dopamine in Active Avoidance. Centro Champalimaud, Lisboa, Portugal (2019)
13. 27.
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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)
14. 28.
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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)
15. 29.
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    Dayan, P.: Neural Reinforcement Learning 2: Choice. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)
16. 30.
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    Vortrag

    Dayan, P.: Neural Reinforcement Learning 1: Prediction. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)
17. 31.
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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 (2)

1. 32.
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   Poster

   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)
2. 33.
   MPG.PuRe

   Abstr
   Poster

   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)