_{Publications:
Department for Computational Neuroscience}

Kang, P.; Tobler, P.; Dayan, P.: Bayesian reinforcement learning: A basic overview. Neurobiology of Learning and Memory 211, 107924 (2024)

Neville, V.; Mendl, M.; Paul, E.; Seriès, P.; Dayan, P.: A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals. Cognitive, Affective and Behavioral Neuroscience 24 (2), pp. 370 - 383 (2024)

Sacu, S.; Dubois, M.; Hezemans, F.; Aggensteiner, P.-M.; Monninger, M.; Brandeis, D.; Banaschewski, T.; Hauser, T.; Holz, N.: Early life adversities are associated with lower expected value signaling in the adult brain. Biological Psychiatry Epub ahead (2024)

Jäger, A.-T.; Bailey, A.; Huntenburg, J.; Tardif, C.; Villringer, A.; Gauthier, C.; Nikulin, V.; Bazin, P.-L.; Steele, C.: Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training. Human Brain Mapping 45 (4), e26539 (2024)

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)

Muller, T.; Butler, J.; Veselic, S.; Miranda, B.; Wallis, J.; Dayan, P.; Behrens, T.; Kurth-Nelson, Z.; Kennerley , S.: Distributional reinforcement learning in prefrontal cortex. Nature Neuroscience 27 (3), pp. 403 - 408 (2024)

Schulz, L.; Bhui, R.: Political reinforcement learners. Trends in Cognitive Sciences 28 (3), pp. 210 - 222 (2024)

Batten, S.; Bang, D.; Kopell, B.; Davies, A.; Heflin, M.; Fu, X.; Perl, O.; Ziafat, K.; Hashemi , A.; Saez, I. et al.; Barbosa, L.; Twomey, T.; Lohrenz, T.; White, J.; Dayan, P.; Charney, A.; Figee, M.; Mayberg, H.; Kishida, K.; Gu, X.; Kishida, P.: Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange. Nature Human Behaviour Epub ahead (2024)

Chernov, G.: The Alternative Factors Leading to Replication Crisis: Prediction and Evaluation. Evaluation Review Epub ahead (2024)

Brielmann, A.; Berentelg, M.; Dayan, P.: Modelling individual aesthetic judgements over time. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 379 (1895), 20220414 (2024)

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

Kastner, D.; Holobetz, C.; Yokota, N.; Williams, G.; Lee, C.; Ton, J.; Romano, J.; Dayan, P.: Choice-wide behavioral association study: reliable and interpretable differences across learning. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal (2024)

Shani, D.; Dayan, P.: Integrating allocentric and egocentric representations for flexible navigation. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal (2024)

Tessereau, C.; Mellor, J.; Dayan, P.; Xuan, F.; Dombeck, D.: The hippocampus as an unpredicted map: Hippocampal traces of uncertainties induced by changes in reward distributions. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal (2024)

Moenke, G.; Schaefer, T.; Parto-Dezfouli, M.; Kajal, D.; Fuertinger, S.; Schmiedt, J.; Fries, P.: Systems Neuroscience Computing in Python (SyNCoPy): A Python Package for Large-scale Analysis of Electrophysiological Data. (submitted)

Barnby, J.; Bellucci, G.; Alon, N.; Schilbach, L.; Frith, C.; Bell, V.: Beyond Theory of Mind: A formal interoperable framework for social inference and representation. (submitted)

Biderman, D.; Whiteway, M.; Hurwitz, C.; Greenspan, N.; Lee, R.; Vishnubhotla, A.; Warren, R.; Pedraja, F.; Noone, D.; Schartner, M. et al.; Huntenburg, J.; Khanal, A.; Meijer, G.; Noel, J.-P.; Pan-Vazquez, A.; Socha, K.; Urai, A.; The International Brain Laboratory; Cunningham, J.; Sawtell, N.; Paninski, L.: Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools. (submitted)

Kastner, D.; Williams, G.; Holobetz, C.; Romano, J.; Dayan, P.: The choice-wide behavioral association study: data-driven identification of interpretable behavioral components. (submitted)

Alon, N.; Schulz, L.; Bell, V.; Moutoussis, M.; Dayan, P.; Barnby, J.: Overly deep hierarchical mentalizing produces paranoia: a new formal theory. (submitted)

Rachum, R.; Nakar, Y.; Tomlinson, B.; Alon, N.; Mirsky, R.: Emergent Dominance Hierarchies in Reinforcement Learning Agents. (submitted)

Shen, T.; Dayan, P.: Risking your Tail: Modeling Individual Differences in Risk-sensitive Exploration using Conditional Value at Risk and Bayes Adaptive Markov Decision Processes. (submitted)

Basgol, H.; Dayan, P.; Franz, V.: Violation of Auditory Regularities is Reflected in Pupil Dynamics. (submitted)

Fardet, T.; Giannakakis, E.; Paulun, K.; Levina, A.: Revising clustering and small-worldness in brain networks. (submitted)

Shen, T.; Dayan, P.: Risking your Tail: Curiosity, Danger and Exploration. (submitted)