Kastner, D.; Gillespie, A.; Dayan, P.; Frank, L.: Memory Alone Does Not Account for the Way Rats Learn a Simple Spatial Alternation Task. The Journal of Neuroscience 40 (38), S. 7311 - 7317 (2020)

Neville, V.; King, J.; Gilchrist, I.; Dayan, P.; Paul, E.; Mendl, M.: Reward and punisher experience alter rodent decision-making in a judgement bias task. Scientific Reports 10 (1), 11839, S. 1 - 14 (2020)

Bellucci, G.; Camilleri, J.; Iyengar, V.; Eickhoff, S.; Krueger, F.: The Emerging Neuroscience of Social Punishment: Meta-Analytic Evidence. Neuroscience and Biobehavioral Reviews 113, S. 426 - 439 (2020)

Bellucci, G.; Münte, T.; Park , S.: Effects of a dopamine agonist on trusting behaviors in females. Psychopharmacology 237 (6), S. 1671 - 1680 (2020)

Dayan, P.: Representation, abstraction, and simple-minded sophisticates. Behavioral and Brain Sciences 43, e126 (2020)

Eldar, E.; Lièvre, G.; Dayan, P.; Dolan, R.: The roles of online and offline replay in planning. eLife 9, e56911, S. 1 - 23 (2020)

Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dayan, P.; Dolan , R.: The Value of What's to Come: Neural Mechanisms Coupling Prediction Error and the Utility of Anticipation. Science Advances 6 (25), eaba3828 (2020)

Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dayan, P.; Dolan, R.: The value of what’s to come: Neural mechanisms coupling prediction error and the utility of anticipation. Science Advances 6, 25 (2020)

Krueger, F.; Bellucci, G.; Xu, P.; Feng, C.: The Critical Role of the Right Dorsal and Ventral Anterior Insula in Reciprocity: Evidence From the Trust and Ultimatum Games. Frontiers in Human Neuroscience 14, 176, S. 1 - 6 (2020)

Mobbs, D.; Headley, D.; Ding, W.; Dayan, P.: Space, Time, and Fear: Survival Computations along Defensive Circuits. Trends in Cognitive Sciences 24 (3), S. 228 - 241 (2020)

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 4 (2), S. 201 - 214 (2020)

Stojić, H.; Orquin, J.; Dayan, P.; Dolan, R.; Speekenbrink, M.: Uncertainty in learning, choice and visual fixation. Proceedings of the National Academy of Sciences of the United States of America 117 (6), S. 3291 - 3300 (2020)

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), e12805 (2019)

Wise, T.; Michely, J.; Dayan, P.; Dolan, R.: A computational account of threat-related attentional bias. PLoS Computational Biology 15 (10), S. 1 - 21 (2019)

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, 4030, S. 1 - 16 (2019)

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)

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), 20191016, S. 1 - 9 (2019)

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), S. 1 - 20 (2019)

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), S. 1 - 33 (2019)

Rouault, M.; Dayan, P.; Fleming, S.: Forming global estimates of self-performance from local confidence. Nature Communications 10 (1), 1141, S. 1 - 11 (2019)

Moran, R.; Keramati, M.; Dayan, P.; Dolan, R.: Retrospective model-based inference guides model-free credit assignment. Nature Communications 10, 750, S. 1 - 14 (2019)

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), S. 1 - 26 (2018)

Brielmann, A.; Dayan, P.: Aesthetic boredom. In: The Routledge International Handbook of Boredom (Hg. Bieleke, M.; Wolff, W.; Martarelli, C.). Routledge, London, UK (2024)

Brielmann, A.: Top-down processes in art experience. In: The Routledge International Handbook of Neuroaesthetics, 25, S. 461 - 474 (Hg. Skov, M.; Nadal, M.). Routledge, London, UK (2022)

Bellucci, G.; Dreher, J.-C.: Trust and Learning. In: The Neurobiology of Trust, 8, S. 185 - 220 (Hg. Krueger, F.). Cambridge University Press, Cambridge, UK (2022)

Brielmann, A.: Empirical Aesthetics. In: Internet Encyclopedia of Philosophy (Hg. Fieser, J.; Dowden, B.) (2021)

Dayan, P.; Roiser, J.; Viding, E.: The first steps on long marches: The costs of active observation. In: Psychiatry Reborn: Biopsychosocial psychiatry in modern medicine, 14, S. 213 - 228 (Hg. Davies, W.; Savulescu, J.; Roache, R.; Loebel, J.). Oxford University Press, Oxford, UK (2020)

Gouw, M.; Alvarado-Valverde, J.; Čalyševa, J.; Diella, F.; Kumar, M.; Michael, S.; Van Roey, K.; Dinkel, H.; Gibson, T.: How to Annotate and Submit a Short Linear Motif to the Eukaryotic Linear Motif Resource. In: Intrinsically Disordered Proteins: Methods and Protocols, S. 73 - 102 (Hg. Kragelund, B.; Skriver, K.). Humana, New York, NY, USA (2020)

Dayan, P.; Nakahara, H.: Models and Methods for Reinforcement Learning. In: Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Bd. 5: Methodology, 4. Aufl., S. 507 - 546 (Hg. Wixted, J.; Wagenmakers, E.-J.). Wiley, Hoboken, NJ, USA (2018)

Whole brain dynamics: Modeling and applications. Satellite Workshops of the Bernstein Conference 2023: Whole brain dynamics: Modeling and applications, Berlin, Germany, 26. September 2023. (2023)

Multi-modal understanding of brain and behavior. Satellite Workshops of the Bernstein Conference 2023: Multi-modal understanding of brain and behavior, Berlin, Germany, 26. September 2023. (2023)

Bucher, S.; Dayan, P.: Algorithmic Choice Architecture for Boundedly Rational Consumers. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023). NeurIPS Workshop on Information-Theoretic Principles in Cognitive Systems (InfoCog @ NeurIPS 2023), New Orleans, LA, USA, 15. Dezember 2023. (2023)

Saanum, T.; Éltetö, N.; Dayan, P.; Binz, M.; Schulz, E.: Reinforcement Learning with Simple Sequence Priors. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, 10. Dezember 2023 - 16. Dezember 2023. (2023)

Safavi, S.: Methods for cross-scale analysis of neural data. In: Satellite Workshops of the Bernstein Conference 2023: Multi-modal understanding of brain and behavior. Satellite Workshops of the Bernstein Conference 2023: Multi-modal understanding of brain and behavior, Berlin, Germany, 26. September 2023 - 27. September 2023. (2023)

Bruijns, S.; Dayan, P.; The International Brain Laborartory: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.97, S. 770 - 772. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Ershadmanesh, S.; Gholamzadeh, A.; Desender, K.; Dayan, P.: Meta-cognitive Efficiency in Learned Value-based Choice. In: 2023 Conference on Cognitive Computational Neuroscience, P-1A.9, S. 29 - 32. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Hamidi, M.; Bányai, M.; Wu, C.: One bottleneck is not enough. In: 2023 Conference on Cognitive Computational Neuroscience, P-2B.44, S. 795 - 798. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Renz, F.; Grossman, S.; Schuck, N.; Dayan, P.; Doeller, C.: Learning and adapting cognitive maps for flexible decision-making. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.35, S. 999 - 1001. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Rubino, V.; Dayan, P.; Wu, C.: Biases towards compositionally simpler hypotheses are robust and unaffected by learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2B.50, S. 817 - 820. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Safavi, S.; Dayan, P.: A decision-theoretic model of perceptual multistability: perceptual switches as internal actions. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.41, S. 1022 - 1024. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Shen, T.; Dayan, P.: Risking your Tail: Curiosity, Danger & Exploration. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.67, S. 1113 - 1116. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Shen, T.; Dayan, P.; Bányai, M.: Meta-cognitive planning for learning representations. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.1, S. 425 - 428. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Xiong, Y.; Wu, C.; Moneta, N.; Banyai, M.: Selective memory for reward-relevant features is modulated by expertise during reward learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.87, S. 733 - 736. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Alon, N.; Schulz, L.; Dayan, P.; Barnby, J.: Between prudence and paranoia: Theory of Mind gone right, and wrong. In: ICML 2023: First Workshop on Theory of Mind in Communicating Agents (ToM 2023). ICML 2023: First Workshop on Theory of Mind in Communicating Agents (ToM 2023), Honolulu, HI,USA, 28. Juli 2023. (2023)

Éltetö, N.; Dayan, P.: Habits of Mind: Reusing Action Sequences for Efficient Planning. 45th Annual Meeting of the Cognitive Science Society (CogSci 2023), Sydney, Australia, 26. Juli 2023 - 29. Juli 2023. Proceedings of the Annual Meeting of the Cognitive Science Society 45, S. 195 - 201 (2023)

Kurtz-David, V.; Alladi, V.; Bucher, S.; Brandenburger, A.; Louie, K.; Glimcher, P.; Tymula, A.: Choosers Adapt Value Coding to the Environment, But Do Not Attain Efficiency. 45th Annual Meeting of the Cognitive Science Society (CogSci 2023), Sydney, Australia, 26. Juli 2023 - 29. Juli 2023. Proceedings of the Annual Meeting of the Cognitive Science Society 45, S. 2237 - 2244 (2023)

Rubino, V.; Hamidi, M.; Dayan, P.; Wu, C.: Compositionality under time pressure. 45th Annual Meeting of the Cognitive Science Society (CogSci 2023), Sydney, Australia, 26. Juli 2023 - 29. Juli 2023. Proceedings of the Annual Meeting of the Cognitive Science Society 45, S. 678 - 685 (2023)

Nath, S.: Inside the Grid, yet Outside the Box: Computational Investigations of Human Creativity using Pixel Patterns. In: C&C '23: Proceedings of the 15th Conference on Creativity and Cognition, S. 28 - 34. 15th Conference on Creativity and Cognition (C&C 2023), 19. Juni 2023 - 21. Juni 2023. Association for Computing Machinery, New York, NY, USA (2023)

Schulz, L.; Alon, N.; Rosenschein, J.; Dayan, P.: Emergent deception and skepticism via theory of mind. In: ICML 2023: First Workshop on Theory of Mind in Communicating Agents (ToM 2023). ICML 2023: First Workshop on Theory of Mind in Communicating Agents (ToM 2023), Honolulu, HI,USA, 28. Juli 2023. (eingereicht)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Learning Structure from the Ground up: Hierarchical Representation Learning by Chunking. In: Advances in Neural Information Processing Systems 35: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), S. 36706 - 36721 (Hg. Koyejo, S.; Mohamed, S.). Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA, 28. November 2022 - 09. Dezember 2022. Curran, Red Hook, NY, USA (2023)

Khajehabdollahi, S.; Giannakakis, E.; Buendia, V.; Martius, G.; Levina, A.: Locally adaptive cellular automata for goal-oriented self-organization. In: ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference, S. 410 - 419 (Hg. Iizuka, H.; Suzuki, K.; Uno, R.; Damiano, L.; Spychala, N. et al.). ALIFE 2023: Ghost in the Machine: The 2021 Conference on Artificial Life, Sapporo, Japan, 24. Juli 2023 - 28. Juli 2023. MIT Press (2023)

Alon, N.; Schulz, L.; Rosenschein, J.; Dayan, P.: A (dis-)information theory of revealed and unrevealed preferences. In: Information-Theoretic Principles in Cognitive Systems: Workshop at the 36th Conference on Neural Information Processing Systems (NeurIPS 2022). NeurIPS 2022 Workshop on Information-Theoretic Principles in Cognitive Systems, New Orleans, LA, USA, 03. Dezember 2022. (2022)

Bruijns, S.; The International Brain Laboratory; Dayan, P.: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2022 Conference on Cognitive Computational Neuroscience, P-1.19, S. 64 - 66. Conference on Cognitive Computational Neuroscience (CCN 2022), San Francisco, CA, USA, 25. August 2022 - 28. August 2022. (2022)

Khajehnejad, M.; Habibollahi, F.; Nock, R.; Arabzadeh, E.; Dayan, P.; Dezfouli, A.: Neural Network Poisson Models for Behavioural and Neural Spike Train Data. In: International Conference on Machine Learning, 17-23 July 2022, Baltimore, Maryland, USA, S. 10974 - 10996 (Hg. Chaudhuri, K.; Jegelka, S.; Song, L.; Szepesvari, C.; Niu, G. et al.). Thirty-ninth International Conference on Machine Learning (ICML 2022), Baltimore, MD, USA, 17. Juli 2022 - 23. Juli 2022. (2022)

Renz, F.; Grossman, S.; Dayan, P.; Doeller, C.; Schuck, N.: Representation learning facilitates different levels of generalization. In: 2022 Conference on Cognitive Computational Neuroscience, P-2.66, S. 460 - 462. Conference on Cognitive Computational Neuroscience (CCN 2022), San Francisco, CA, USA, 25. August 2022 - 28. August 2022. (2022)

Bröker, F.; Roads, B.; Dayan, P.; Love, B.: Teaching categories to human semi-supervised learners. In: 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), 2.8, S. 122 - 125. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA, 08. Juni 2022 - 11. Juni 2022. (2022)

Dayan, P.; Gagne, C.: Two steps to risk sensitivity. In: Advances in Neural Information Processing Systems 34: 35th Conference on Neural Information Processing Systems (NeurIPS 2021), S. 22209 - 22220 (Hg. Ranzato, M.; Beygelzimer, A.; Liang, P.; Vaughan, J.; Dauphin, Y.). Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), 06. Dezember 2021 - 14. Dezember 2021. Curran, Red Hook, NY, USA (2022)

Wise, T.; Charpentier, C.; Dayan, P.; Mobbs, D.: Modeling the mind of a predator: Interactive cognitive maps enable avoidance of dynamic threats. In: 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), 1.49, S. 32 - 33. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA, 08. Juni 2022 - 11. Juni 2022. (2022)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Learning Structure from the Ground up: Hierarchical Representation Learning by Chunking. In: Tenth International Conference on Learning Representations (ICLR 2022). Tenth International Conference on Learning Representations (ICLR 2022), 25. April 2022 - 29. April 2022. (2022)

Gagne, C.; Dayan, P.: Catastrophe, Compounding & Consistency in Choice. In: Workshop on Human and Machine Decisions @ NeurIPS 2021 (WHMD 2021). Workshop on Human and Machine Decisions @ NeurIPS 2021 (WHMD 2021), 14. Dezember 2021. (2021)

Khajehabdollahi, S.; Giannakakis, E.; Prosi, J.; Levina, A.: Reservoir computing with self-organizing neural oscillators. In: Artificial Life Conference Proceedings, Bd. 2021, 78. ALIFE 2021: The 2021 Conference on Artificial Life, Praha, Czech Republic, 19. Juli 2021 - 23. Juli 2021. MIT Press (2021)

Prosi, J.; Khajehabdollahi, S.; Giannakakis, E.; Martius, G.; Levina, A.: The dynamical regime and its importance for evolvability, task performance and generalization. In: Artificial Life Conference Proceedings, Bd. 2021, 79. ALIFE 2021: The 2021 Conference on Artificial Life, Praha, Czech Republic, 19. Juli 2021 - 23. Juli 2021. MIT Press (2021)

Tano, P.; Dayan, P.; Pouget, A.: A local temporal difference code for distributional reinforcement learning. In: Advances in Neural Information Processing Systems 33, S. 13662 - 13673 (Hg. Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M.-F.; Lin, H.-T.). 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 06. Dezember 2020 - 12. Dezember 2020. Curran, Red Hook, NY, USA (2021)

Ahilan, S.; Dayan, P.: Correcting Experience Replay for Multi-Agent Communication. In: Ninth International Conference on Learning Representations (ICLR 2021). Ninth International Conference on Learning Representations (ICLR 2021), Vienna, Austria, 03. Mai 2021 - 07. Mai 2021. (2021)

Xia, L.; Master, S.; Eckstein, M.; Wilbrecht, L.; Collins, A.: Learning under uncertainty changes during adolescence. In: 42nd Annual Meeting of the Cognitive Science Society (CogSci 2020): 5Developing a Mind: Learning in Humans, Animals, and Machines, S. 716 - 722 (Hg. Denison, S.; Mack, M.; Xu, Y.; Armstrong, B.). 42nd Annual Virtual Meeting of the Cognitive Science Society (CogSci 2020), Toronto, Canada, 29. Juli 2020 - 01. August 2020. Curran, Red Hook, NY, USA (2020)

Sezener, E.; Dayan, P.: Static and Dynamic Values of Computation in MCTS. 36th Conference on Uncertainty in Artificial Intelligence (UAI 2020), 03. August 2020 - 06. August 2020. Proceedings of Machine Learning Research (PMLR) 124, 26, S. 31 - 40 (2020)

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. Banbury Center Meeting 2019, Huntington, NY, USA, 2019-02. Biological Psychiatry 88 (2), S. e5 - e10 (2020)

Dezfouli, A.; Ashtiani, H.; Ghattas, O.; Nock, R.; Dayan, P.; Ong, C.: Disentangled behavioural representations. In: Advances in Neural Information Processing Systems 32, S. 2243 - 2252 (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. Curran, Red Hook, NY, USA (2020)

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), PS-2A.70, S. 826 - 829. Conference on Cognitive Computational Neuroscience (CCN 2019), Berlin, Germany, 13. September 2019 - 16. September 2019. (2019)

Ahilan, S.; Dayan, P.: Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. In: Annual Conference of the American Library Association (ALA 2019), 5, S. 1 - 5. Annual Conference of the American Library Association (ALA 2019) , Washington, DC, USA, 20. Juni 2019 - 25. Juni 2019. (2019)

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, S. 1 - 11. Workshop on Structure & Priors in Reinforcement Learning (SPiRL 2019) at ICLR 2019, New Orleans, LA, USA, 06. Mai 2019. (2019)

Kastner, D.; Holobetz, C.; Yokotoa, N.; Williams, G.; Romano, J.; Dayan, P.: Slow progress of learning in rats haploinsufficient for a high-risk ASD gene. In 52nd Annual Meeting of the Society for Neuroscience (Neuroscience 2023), NANO01.09, S. 9 - 10. 52nd Annual Meeting of the Society for Neuroscience (Neuroscience 2023), Washington, DC, USA, 11. November 2023 - 15. November 2023. (2023)

Kurtz David, V.; Alladi, V.; Sinha, S.; Bucher, S.; Brandenburger, A.; Louie, K.; Dewan, A.; Glimcher, P.; Tymula, A.: Inefficient Divisive Normalization: Human Choosers Employ Divisive Normalization Even When They Should Not. In 52nd Annual Meeting of the Society for Neuroscience (Neuroscience 2023), NANO58.13, S. 544. 52nd Annual Meeting of the Society for Neuroscience (Neuroscience 2023), Washington, DC, USA, 11. November 2023 - 15. November 2023. (2023)

Safavi, S.; Dayan, P.: A decision-theoretic model of perceptual multistability: perceptual switches as internal actions. In 52nd Annual Meeting of the Society for Neuroscience (Neuroscience 2023), NANO58.08, S. 538 - 539. 52nd Annual Meeting of the Society for Neuroscience (Neuroscience 2023), Washington, DC, USA, 11. November 2023 - 15. November 2023. (2023)

Bruijns, S.; Dayan, P.: Dissecting the Complexities of the Learning Curve With State-Based Models. In NeNa Conference 2022: Neurowissenschaftliche Nachwuchskonferenz (Conference of Junior Neuroscientists), T12, S. 25. 24th Conference of Junior Neuroscientists (NeNa 2023), Frankfurt a.M., Germany, 11. September 2023 - 13. September 2023. (2023)

Zeraati, R.; Khajehabdollahi, S.; Giannakakis, E.; Schäfer, T.; Martius, G.; Levina, A.: Role of single-neuron and network-mediated timescales in recurrent neural networks solving long-memory tasks. In Bernstein Conference 2023, CT 4. Bernstein Conference 2023, Berlin, Germany, 26. September 2023 - 29. September 2023. (2023)

Buendía, V.: On mesoscopic, finite-size populations of stochastic coupled oscillators. In III Conference of the Italian Society of Statistical Physics (SIFS 2023). III Conference of the Italian Society of Statistical Physics (SIFS 2023), Parma, Italy, 21. Juni 2023 - 23. Juni 2023. (2023)

Nath, S.; Brändle, F.; Schulz, E.; Dayan, P.; Brielmann, A.: Relating Objective Complexity, Subjective Complexity and Beauty. In Abstracts of the 65th TeaP, S. 262 - 263 (Hg. Merz, S.; Frings, C.; Leuchtenberg, B.; Moeller, B.; Neumann, R. et al.). 65th Conference of Experimental Psychologists: TeaP 2023: Tagung experimentell arbeitender Psycholog:innen, Trier, Germany, 26. März 2023 - 29. März 2023. ZPID, Trier, Germany (2023)

Zamfir, E.; Dayan, P.: Interactions Between Causal Attributions And Beliefs: Evidence From A Novel Computer Game Task. In 48. Jahrestagung Psychologie & Gehirn (PuG 2023), S31.2, S. 139. 48. Jahrestagung Psychologie & Gehirn (PuG 2023), Tübingen, Germany, 08. Juni 2023 - 10. Juni 2023. (2023)

Eschenko, O.: The role of noradrenergic transmission for saliency signaling and perception. In CIN-NIPS-Asia Pacific Systems Neuroscience Symposium 2023. CIN-NIPS-Asia Pacific Systems Neuroscience Symposium 2023, Tübingen, Germany, 10. März 2023 - 11. März 2023. (2023)

Burgess, H.; Barnby, J.; Dean, R.; MacKenzy, L.; Thomas, R.; Dayan, P.; Richards, L.: Neurocog.js; A new tool for running cognitive experiments in both lab and online environments. In 51st Annual Meeting of the Society for Neuroscience (Neuroscience 2022), 164.24. 51st Annual Meeting of the Society for Neuroscience (Neuroscience 2022), San Diego, CA, USA, 12. November 2022 - 16. November 2022. (2022)

Bellucci, G.: Trading off subjective values and social expectations for interpersonal trust. In 15th Biannual Conference of the German Society for Cognitive Science (KogWis 2022), S. 144. 15th Biannual Conference of the German Society for Cognitive Science (KogWis 2022), Freiburg (Breisgau), Germany, 05. September 2022 - 07. September 2022. (2022)

Pombo, M.; Brielmann, A.; Pelli, D.: When judging beauty, order matters only if the stimuli are homogeneous. In The Visual Science of Art Conference (VSAC 2022). The Visual Science of Art Conference (VSAC 2022), Amsterdam, The Netherlands, 24. August 2022 - 27. August 2022. (2022)

Buendía, V.: The excitatory-inhibitory branching process: a parsimonious view of cor- tical asynchronous states, excitability, and criticality. In II Conference of the Italian Society of Statistical Physics (SIFS 2022), XXVI National Conference of Statistical Physics and Complex Systems. II Conference of the Italian Society of Statistical Physics (SIFS 2022), XXVI National Conference of Statistical Physics and Complex Systems, Parma, Italy, 20. Juni 2022 - 22. Juni 2022. (2022)

Klippert, A.; Montesano, A.; Dinkel, H.; Monheim, F.: Anishare: An Open-Source Software to Improve the Use of Surplus Laboratory Animals and Organs. In Laboratory Animals, 56 (Supplement 1), S2E1.1, S. 35 - 36. 15th FELASA Congress 2022, Marseille, France, 13. Juni 2022 - 16. Juni 2022. Laboratory Animals Ltd., London (2022)

Brielmann, A.; Berentelg, M.; Dayan, P.: A computational model predicts individual aesthetic judgments. In 64th Conference of Experimental Psychologists: TeaP 2022, S. 37 - 38 (Hg. Malejka, S.; Barth, M.; Haider, H.; Stahl, C.). 64th Conference of Experimental Psychologists (TeaP 2022): Tagung experimentell arbeitender Psycholog:innen, Köln, Germany, 20. März 2022 - 23. März 2022. Pabst, Lengerich, Germany (2022)

Schulz, L.; Schulz, E.; Bhui, R.; Dayan, P.: Towards a computational cognitive perspective of misinformation. In NeNa Conference 2021: Neurowissenschaftliche Nachwuchskonferenz (Conference of Junior Neuroscientists), T10, S. 11. 22nd Conference of Junior Neuroscientists (NeNa 2021), Tübingen, Germany, 07. Oktober 2021. (2021)

Bellucci, G.; Park, S.: How to trust when lonely? The effects of loneliness on behaviors and expectations in trusting interactions. In Journal of Neuroscience, Psychology, and Economics, 2022 (3), S. 18. 17th NeuroPsychoEconomics Conference 2021: “Bridging Neuroscience, Psychology, and Economics” , Amsterdam, The Netherlands, 10. Juni 2021 - 11. Juni 2021. Educational Publishing Foundation, Washington, DC, USA (2021)

Buendía, V.: Sincronización crítica en el cerebro: una perspectiva físico-estadística. In I Congreso FisEs '21 Joven. I Congreso FisEs '21 Joven, 05. Mai 2021 - 06. Mai 2021. (2021)

Dayan, P.; Lloyd, K.: Aversion or Inversion: The Curious Case of Dopamine and Punishment [Aversion ou inversion: le cas curieux de la Dopamine et la punition]. In NeuroFrance 2021, S28.2. NeuroFrance 2021, Strasbourg, France, 19. Mai 2021 - 21. Mai 2021. (2021)

Deserno, L.; Moran, R.; Lee, Y.; Michely, J.; Dayan, P.; Dolan, R.: Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference. In Biological Psychiatry, 89 (9 Supplement), S. S94. 2021 Annual Scientific Convention and Meeting of the Society of Biological Psychiatry (SOBP 2021), 29. April 2021 - 01. Mai 2021. Elsevier, New York (2021)

Dayan, P.: Impact beyond neuroscience (translational non-clinical). In FENS 2020 Virtual Forum, 1522. FENS 2020 Virtual Forum, Glasgow, UK, 11. Juli 2020 - 15. Juli 2020. (2020)

Rouault, C.; Dayan, P.; Fleming, S.: Forming global estimates of self-performance from local confidence. In 61st Conference of Experimental Psychologists: 61. TeaP 2019 (Tagung Experimentell Arbeitender PsychologInnen) (Hg. Lange-Küttner, C.). 61st Conference of Experimental Psychologists (TEAP 2019), London, UK, 15. April 2019 - 17. April 2019. Pabst, Lengerich, Germany (2020)

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, S. 103 - 104. 49th Annual Meeting of the Society for Neuroscience (Neuroscience 2019), Chicago, IL, USA, 19. Oktober 2019 - 23. Oktober 2019. (2019)

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)

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)

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, S. S108. 74th Annual Meeting of the Society of Biological Psychiatry, Chicago, IL, USA, 16. Mai 2019 - 18. Mai 2019. Elsevier, New York (2019)

Dayan, P.; Chen, K.; Gagne, C.; Lloyd, K.; Sui, X.: Risk in Sequential Decisions. 11th Bernoulli Lecture for the Behavioral Sciences: University of Basel, Basel, Switzerland (2023)

Lloyd, K.: Models of Action Selection: MDP. Computational Psychiatry Course Zurich 2023, Zürich, Switzerland (2023)