Publications of P Dayan

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)

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)

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)

Zhao, S.; Dick, F.; Dayan, P.; Furukawa, S.; Liao, H.-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)

Bruijns, S.; Eckstein, M.; Dayan, P.: Low dimensional latent structure underlying the choices of mice. (submitted)

Hall-McMaster, S.; Wittkuhn, L.; Verra, L.; Hedrich, N.; Irie, K.; Dayan, P.; Gershman, S.; Schuck, N.: Entorhinal cortex signals dimensions of past experience that can be generalised in a novel environment. (submitted)

Laessing, P.; Karvelis, P.; Kennedy, J.; Zai, C.; Dayan, P.; Diaconescu, A.: Comparative Computational Modeling of Approach-Avoidance Biases in Suicidal Populations via Hierarchical Bayesian Inference. (submitted)

Mahajan, P.; Dayan, P.; Seymour, B.: Homeostasis After Injury: How Intertwined Inference and Control Underpin Post-Injury Pain and Behaviour. (submitted)