Dayan, P.; Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dolan, R.: Savouring and its Modulation by Prediction Errors. Colloquium Cognitive Systems: Universität Ulm , Ulm, Germany (2019)

Dayan, P.: Savouring and its Modulation by Prediction Errors. 17th Annual Meeting of the Society for NeuroEconomics (SNE 2019), Dublin, Ireland (2019)

Dayan, P.: Theoretical Neuroscience: Decision Making and its Discontents. 49th Annual Meeting of the Society for Neuroscience (Neuroscience 2019) , Chicago, IL, USA (2019)

Sharan, M.; Dinkel, H.: Building Blocks of Python Programming. EMBL Course: Computing Skills For Reproducible Research: Software Carpentry, Heidelberg, Germany (2019)

Sharan, M.; Dinkel, H.; Alves, R.: Building programs with Python I. EMBL Course: Computing Skills For Reproducible Research: Software Carpentry, Heidelberg, Germany (2019)

Sharan, M.; Dinkel, H.; Alves, R.: Building programs with Python II. EMBL Course: Computing Skills For Reproducible Research: Software Carpentry, Heidelberg, Germany (2019)

Sharan, M.; Dinkel, H.; Alves, R.: Using commandline git for version control. EMBL Course: Computing Skills For Reproducible Research: Software Carpentry, Heidelberg, Germany (2019)

Dayan, P.: The cortical dynamics of integrative decision making. 6th ESI Systems Neuroscience Conference 2019: The recurrent cortex: feedback, dynamics, and dimensionality , Frankfurt a.M., Germany (2019)

Dayan, P.: Unsupervised Yearning. David Marr, 50 years on (Marr 2019) at Artificial & Biological Cognition 2019, Cambridge, UK (2019)

Dayan, P.: Dysfunctional decision-making. Tübingen International Summer School (TISS 2019), Kloster Heiligkreuztal (2019)

Dayan, P.: Functional decision-making. Tübingen International Summer School (TISS 2019), Kloster Heiligkreuztal (2019)

Dayan, P.: Reinforcement learning. 2019 Computational Psychiatry Summer Course, New York, NY, USA (2019)

Dayan, P.: Theoretical approaches to function and dysfunction. 2019 Computational Psychiatry Summer Course, New York, NY, USA (2019)

Dayan, P.: Slothful serial: perilous parallel processing. Workshop Heuristics, Hacks and Habits: 41st Annual Meeting of the Cognitive Science Society (COGSCI 2019), Montréal, Canada (2019)

Dayan, P.: Decision-making and some of its Discontents. 9th IMPRS NeuroCom Summer School in Cognitive Neuroscience , Leipzig, Germany (2019)

Dayan, P.: Savouring and its Modulation by Prediction Errors. NEUREX Workshop: Neuroeconomics: Studying Decision Making in an Economic Context, Strasbourg, France (2019)

Dayan, P.: Pavlovian-Instrumental Interactions in Active Avoidance: The Bark of Neutral Trials. Modulation of Neural Circuits and Behavior Gordon Research Conference: Neuromodulatory Mechanisms Underlying Flexible Brain Functions and Behavior , Les Diablerets, Switzerland (2019)

Dayan, P.: The Cortical Dynamics of Integrative Decision Making. University of Freiburg: Bernstein Seminar, Freiburg i.Br., Germany (2019)

Dayan, P.: Learning in Natural Neural Systems. Eberhard-Karls-Universität Tübingen: Studium Generale: Maschinelles Lernen, Tübingen, Germany (2019)

Dayan, P.: The long and the short of serotonergic stimulation: The learning rate for rewards. NeuroRetreat 2019: Max Planck Institute of Psychiatry, München, Germany (2019)

Dayan, P.: The Good, The Bad, and Something Inbetween: Dopamine in Active Avoidance. Centro Champalimaud, Lisboa, Portugal (2019)

Dayan, P.: The long and the short of 5-HT stimulation: optogenetic activation of dorsal raphe serotonergic neurons changes the learning rate for rewards. COSYNE 2019 Workshop: Advances and convergences in 5-HT research , Cascais, Portugal (2019)

Dayan, P.: The Cortical Dynamics of Integrative Decision Making. Chen Institute Symposium 2019, Pasadena, CA, USA (2019)

Dayan, P.: Neural Reinforcement Learning 3: The Self and the Other. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)

Dayan, P.: Neural Reinforcement Learning 2: Choice. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)

Dayan, P.: Neural Reinforcement Learning 1: Prediction. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)

Dayan, P.: The long and the short of serotonergic stimulation: Selective effects on the learning rate of rewards. InstitutsSeminar Neurobiologie: Institute of Neurobiology, Eberhard-Karls Universität Tübingen, Tübingen, Germany (2018)

Buendia, V.; Zeraati, R.; Engel, T.; Levina, A.: Variable critical exponents induced by topology-dependent coalescence in a branching network. Bernstein Conference 2021 (2021)

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

Giannakakis, E.; Vinogradov, O.; Levina, A.: Recurrent connectivity regulates the ability of inhibitory STDP to produce E/I co-tuning in a spiking network. Bernstein Conference 2021 (2021)

Patzlaff, N.; Vinogradov, O.; Giannakakis, E.; Levina, A.: Examining network dynamics under inhibitory rewiring. Bernstein Conference 2021 (2021)

Pombo, M.; Brielmann, A.; Pelli, D.: Discounting the effect of memory on repeated measures of beauty judgment. Twenty-First Annual Meeting of the Vision Sciences Society (V-VSS 2021) (2021)

Vinogradov, O.; Buendia, V.; Levina, A.: Minimal model of cultured neuronal networks population dynamics. Bernstein Conference 2021 (2021)

Yang, I.; Zeraati, R.; Zhang, Y.; Arrenberg, A.; Levina, A.: Evaluating the dynamical state of the visual brain during optic flow noise processing in zebrafish. Bernstein Conference 2021 (2021)

Zeraati, R.; Shi, Y.-L.; Steinmetz, N.; Gieselmann, M.; Thiele, A.; Moore, T.; Levina, A.; Engel, T.: Attentional modulation of intrinsic timescales in visual cortex and its underlying network mechanisms. Bernstein Conference 2021 (2021)

Pombo, M.; Brielmann, A.; Pelli, D.: How sequential dependencies affect the intraindividual variability of beauty judgment. 43rd European Conference on Visual Perception (ECVP 2021) (2021)

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

Wu, S.; Elteto, N.; Dasgupta, I.; Schulz, E.: Chunking as a rational solution to the speed-accuracy trade-off in a serial reaction time task. 43rd Annual Conference of the Cognitive Science Society (CogSci 2021) (2021)

Fardet, T.; Levina, A.; Paulun, N.: Revisiting and revising clustering in brain networks. Computational and Systems Neuroscience Meeting (COSYNE 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)

Zierenberg, J.; Wilting, J.; Priesemann, V.; Levina, A.: Tailored ensembles of neural networks optimize sensitivity to stimulus statistics. DPG-Frühjahrstagungen 2021 BP-CPP-DY-SOE (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)

Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O’Doherty, J.; Dayan, P.; Dolan, R.: Hippocampal-midbrain circuit enhances the pleasure of anticipation in the prefrontal cortex. 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2019), Montreal, Canada (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.; Hiao, L.-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)

Dayan, P.: "Liking" as a First Draft of the Affective Future. (submitted)

Antonov, G.; Gagne, C.; Eldar, E.; Dayan, P.: Optimism and Pessimism in Optimised Replay. (submitted)

Schwartenbeck, P.; Baram, A.; Liu, Y.; Mark, S.; Muller, T.; Dolan, R.; Botvinick, M.; Kurth-Nelson, Z.; Behrens, T.: Generative replay for compositional visual understanding in the prefrontal-hippocampal circuit. (submitted)

Bröker, F.; Love, B.; Dayan, P.: When unsupervised training benefits category learning. (submitted)

Fardet, T.; Levina, A.: Weighted directed clustering: interpretations and requirements for heterogeneous, inferred, and measured networks. (submitted)

Gagne, C.; Dayan, P.: Peril, Prudence and Planning as Risk, Avoidance and Worry. (submitted)

Zeraati, R.; Engel, T.; Levina, A.: A flexible Bayesian framework for unbiased estimation of timescales. (submitted)

Zeraati, R.; Shi, Y.-L.; Steinmetz, N.; Gieselmann, M.; Thiele, A.; Moore, T.; Levina, A.; Engel, T.: Attentional modulation of intrinsic timescales in visual cortex and spatial networks. (submitted)

Jain , Y.; Callaway, F.; Griffiths, T.; Dayan, P.; Krueger, P.; Lieder, F.: A Computational Process-Tracing Method for Measuring People’s Planning Strategies and How They Change Over Time. (submitted)

Vallier, M.; Mueller, M.; Bellucci, G.; Grange, M.; Lu, Y.; Duponchel, S.: Demographics and Employment of Max-Planck Society’s Postdocs. (submitted)

Kastner, D.; Miller, E.; Yang, Z.; Roumis, D.; Frank, L.; Dayan, P.: Spatial preferences account for inter-animal variability during the continual learning of a dynamic cognitive task. (submitted)

Castro-Rodrigues, P.; Akam, T.; Snorasson, I.; Camacho, M.; Paixão, V.; Barahona-Corrêa, B.; Dayan, P.; Simpson, H.; Costa, R.; Oliveira-Maia, A.: Explicit knowledge of task structure is the primary determinant of human model-based action. (submitted)

Kóbor, A.; Kardos, Z.; Takács, Á.; Éltetö, N.; Janacsek, K.; Tóth-Fáber, E.; Csépe, V.; Nemeth, D.: Initial experience has lasting effect on repeated risky decisions. (submitted)

Silston, B.; Wise, T.; Qi, S.; Sui, X.; Dayan, P.; Mobbs, D.: Neural encoding of socially adjusted value during competitive and hazardous foraging. (submitted)

Dezfouli, A.; Nock, R.; Arabzadeh, E.; Dayan, P.: Neural Network Poisson Models for Behavioural and Neural Spike Train Data. (submitted)

Mancinelli, F.; Roiser, J.; Dayan, P.: Subjective Beliefs In, Out, and About Control: A Quantitative Analysis. (submitted)

Dezfouli, A.; Nock, R.; Dayan, P.: Adversarial manipulation of human decision-making. (submitted)

Kastner, D.; Miller, E.; Yang, Z.; Roumis, D.; Liu, D.; Frank, L.; Dayan, P.: Dynamic preferences account for inter-animal variability during the continual learning of a cognitive task. (submitted)

Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dayan, P.; Dolan, R.: Hippocampal-midbrain circuit enhances the pleasure of anticipation in the prefrontal cortex. (submitted)

Zhao, S.; Chait, M.; Dick, F.; Dayan, P.; Furukawa, S.; Liao, H.-I.: Phasic norepinephrine is a neural interrupt signal for unexpected events in rapidly unfolding sensory sequences: evidence from pupillometry. (submitted)