Publications of P Dayan

Toro-Serey, C.; Tang, W.; Trambaiolli, L.; Dayan, P.; Haber, S.: ACC-striatal Projections are Uniquely Positioned to Interact With an Unusually Functionally Diverse Set of Cortical Areas. 60th Annual Meeting of the American College of Neuropsychopharmacology (ACNP 2021), San Juan, Puerto Rico (2021)

Bruijns, S.; Dayan, P.: Exploring learning trajectories with dynamic infinite hidden Markov models. 43rd Annual Conference of the Cognitive Science Society (CogSci 2021), Wien, Austria (2021)

Costa, K.; Scholz, R.; Lloyd, K.; Gardner, M.; Dayan, P.; Schoenbaum, G.: The orbitofrontal cortex is necessary for forming outcome-specific representations during learning Add to Itinerary. 50th Annual Meeting of the Society for Neuroscience (Neuroscience 2021) (2021)

Elteto, N.; Nemeth, D.; Janacsek, K.; Dayan, P.: Tracking the Unknown: Modeling Long-Term Implicit Skill Acquisition as Non-Parametric Bayesian Sequence Learning. 43rd Annual Conference of the Cognitive Science Society (CogSci 2021), Wien, Austria (2021)

Findling, C.; Dayan, P.; Pouget, A.: Subject-to-subject and session-to-session variability in behavioural strategy for the International Brain Lab task. 50th Annual Meeting of the Society for Neuroscience (Neuroscience 2021) (2021)

Gercek, B.; Meijer, G.; Benson, B.; Schaeffer, R.; Findling, C.; Banga, K.; Langdon, C.; Miska, N.; Schartner, M.; Socha, K. et al.; Whiteway, M.; Dayan, P.; Harris, K.; Pouget, A.: Neural correlates of an approximate prior in perceptual decision making. 50th Annual Meeting of the Society for Neuroscience (Neuroscience 2021) (2021)

Langdon, C.; Schartner, M.; Dewitt, E.; Harris, K.; Fiete, I.; Dayan, P.: Task-relevant population dynamics in the international brain lab dataset revealed by manifold analysis. 50th Annual Meeting of the Society for Neuroscience (Neuroscience 2021) (2021)

Schartner, M.; Langdon, C.; Miska, J.; Whiteway, M.; Huntenburg, J.; Harris, K.; Fiete, I.; Pouget, A.; Dayan, P.: Motor correlates of cognitive variables in the international brain laboratory task. 50th Annual Meeting of the Society for Neuroscience (Neuroscience 2021) (2021)

Schulz, L.; Fleming, S.; Dayan, P.: Metacognitive Computations for Information Search: Confidence in Control. 43rd Annual Conference of the Cognitive Science Society (CogSci 2021), Wien, Austria (2021)

Ershadmanesh, S.; Rajabi, S.; Rostami, R.; Moran, R.; Dayan, P.: Dopaminergic modulation of metacontrol. Bernstein Conference 2021 (2021)

Tano, P.; Dayan, P.; Pouget, A.: A Local Temporal Difference Code for Distributional Reinforcement Learning. Computational and Systems Neuroscience Meeting (COSYNE 2021) (2021)

Lekscha Sedlinská, T.; Brückner, L.; Hübner, M.; Rentsch, C.; Falke, D.; Mühle, C.; Suc, J.; Weinland, C.; Kornhuber, J.; Lenz, B. et al.; Dayan, P.: Temporal discounting and male depression. Kongress der Deutschen Gesellschaft für Psychiatrie und Psychotherapie, Psychosomatik und Nervenheilkunde e. V. (DGPPN 2020), Berlin, Germany (2020)

Bröker, F.; Love, B.; Dayan, P.: The varied effect of unsupervised information on human category learning. Bernstein Conference 2020 (2020)

Gagne, C.; Dayan, P.: Avoidant behavior and pathological worry as optimal policies and optimal offline planning given individually exaggerated risk preferences. Bernstein Conference 2020 (2020)

Lekscha Sedlinska, T.; Brückner, L.; Hübner, M.; Rentsch, C.; Falke, D.; Mühle, C.; Suc, J.; Weinland, C.; Kornhuber, J.; Lenz, B. et al.; Dayan, P.: Temporal discounting in major depression. Bernstein Conference 2020 (2020)

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)

Bruijns, S.; Dayan, P.: Anticipating Every Turn: Learning About Learning in Mice. 20th Conference of Junior Neuroscientists (NeNa 2019) , Schramberg, Germany (2019)

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)

Zhao, S.; Dick, F.; Dayan, P.; Furukawa, S.; Liao, H.; chait, M.: Phasic norepinephrine is a neural interrupt signal for unexpected events in rapidly unfolding sensory sequences: evidence from pupillometry. International Conference on Interdisciplenary Advances in Statistical Learning 2019, San Sebastián, Spain (2019)

Zhao, S.; Dick, F.; Dayan, P.; Furukawa, S.; Liao, H.; Chait, M.: Phasic norepinephrine is a neural interrupt signal for unexpected events in rapidly unfolding sensory sequences: evidence from pupillometry. Interdisciplinary Advances in Statistical Learning 2019, San Sebastián, Spain (2019)