Publikationen von P Schwartenbeck

Kalhan, S.; Schwartenbeck, P.; Hester, R.; Garrido, M.: People with a tobacco use disorder exhibit misaligned Bayesian belief updating by falsely attributing non-drug cues as worse predictors of positive outcomes compared to drug cues. Drug and Alcohol Dependence 256, 111109 (2024)

Schwartenbeck, P.; Baram, A.; Liu, Y.; Mark, S.; Muller, T.; Dolan, R.; Botvinick, M.; Kurth-Nelson , Z.; Behrens, T.: Generative replay underlies compositional inference in the hippocampal-prefrontal circuit. Cell 186 (22), S. 4885 - 4897 (2023)

Rens, N.; Lancia, G.; Eluchans, M.; Schwartenbeck, P.; Cunnington, R.; Pezzulo, G.: Evidence for entropy maximisation in human free choice behaviour. Cognition 232, 105328 (2023)

Kurth-Nelson, Z.; Behrens, T.; Wayne, G.; Miller, K.; Luettgau, L.; Dolan, R.; Liu, Y.; Schwartenbeck, P.: Replay and compositional computation. Neuron 111 (4), S. 454 - 469 (2023)

Horvath, L.; Colcombe, S.; Milham, M.; Ray, S.; Schwartenbeck, P.; Ostwald, D.: Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit Task. Computational Brain & Behavior 4 (4), S. 442 - 462 (2021)

Schwartenbeck, P.; Baram, A.; Mark, S.; Kurth-Nelson, Z.; Dolan, R.; Behrens, T.: Compositional Neural Representations in the Hippocampal Formation and Prefrontal Cortex Underlie Visual Construction and Planning. In: Conference on Cognitive Computational Neuroscience (CCN 2019), PS-1A.56, S. 550 - 553. Conference on Cognitive Computational Neuroscience (CCN 2019), Berlin, Germany, 13. September 2019 - 16. September 2019. (2019)

Schwartenbeck, P.; Éltetö, N.; Braun, A.; Bányai, M.; Dayan, P.: Hierarchically structured representations facilitate visual understanding. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA (2022)

Kalhan, S.; Schwartenbeck, P.; Hester, R.; Garrido, M.: People with a tobacco use disorder misattribute non-drug cues as worse predictors of positive outcomes compared to drug cues. (eingereicht)