Publikationen von P Dayan

Niv, Y.; Daw, N.; Joel, D.; Dayan, P.: Motivational effects on behavior: Towards a reinforcement learning model of rates of responding. Computational and Systems Neuroscience Meeting (COSYNE 2005), Salt Lake City, UT, USA (2005)

Zemel, R.; Natarajan, R.; Huys, Q.; Dayan, P.: Representational pursuit: Population codes for dynamic environments. Computational and Systems Neuroscience Meeting (COSYNE 2005), Salt Lake City, UT, USA (2005)

Yu, A.; Bentley, P.; Seymour, B.; Driver, J.; Dolan , R.; Dayan, P.: Expected and unexpected uncertainties control allocation of attention in a novel attentional learning task. 34th Annual Meeting of the Society for Neuroscience (Neuroscience 2004), San Diego, CA, USA (2004)

Gruber, A.; Dayan, P.; Gutkin, B.; Solla, S.: Dopaminergic enhancement of spatial working memory through single-unit modulation in a basal ganglio-cortical network model. 33rd Annual Meeting of the Society for Neuroscience (Neuroscience 2003), New Orleans, LA, USA (2003)

Zhaoping, L.; Dayan, P.; Herzog, M.: Positional variation in perceptual learning: quadratic ideal observation, recurrent pre-processing, and transfer. 25th European Conference on Visual Perception (ECVP 2002), Glasgow, UK (2002)

Popple, A.; Dayan, P.; Li, Z.: V1 model predicts texture segmentation bias. 31st Annual Meeting of the Society for Neuroscience (Neuroscience 2001), San Diego, CA, USA (2001)

Kakade, S.; Dayan, P.: Opponent interactions between serotonin and dopamine for classical and operant conditioning. 30th Annual Meeting of the Society for Neuroscience (Neuroscience 2000), New Orleans, LA, USA (2000)

Dayan, P.: Reinforcing connectionism: learning the statistical way. Dissertation, University of Edinburgh, Edinburgh, UK (1991)

Abdelrazik, A.; Dayan, P.: Deciding when to decide: How recency, urgency, risk, and bias shape human sequential decision-making: A case study across the obsessive-compulsive spectrum. (eingereicht)

Pan-Vazquez, A.; Zimmermann, C.; McMannon, B.; Fabre, J.; Louka, M.; Jia, T.; Sagiv, Y.; West, S.; Faulkner, M.; International Brain Laboratory et al.; Dayan, P.; Witten, I.: VTA dopamine neuron activity produces spatially organized stimulus and action value representations through conditioned reinforcement. (eingereicht)

Tessereau, C.; Dayan, P.: Coordinated behavioural and neural variability in hippocampal reward coding. (eingereicht)

Moses-Payne, M.; Zhang, R.; Mkrtchian, A.; Valton, V.; Gray, A.; Kieslich, K.; VanUrk, S.; Samborska, V.; Halahakoon, D.; Dayan, P. et al.; Robinson, O.; Roiser, J.: State-, Trait- and Recovery-Related Differences in Reinforcement Learning and Value-Based Decision Making in Major Depressive Disorder. (eingereicht)

Laessing, P.; Karvelis, P.; Rashid-Cocker, A.; Ruocco, A.; Koudys, J.; Kennedy, J.; Zai, C.; Dayan, P.; Diaconescu, A.: Two modes of aversive control in suicidality: joint computational modelling exposes regime-specific clinical signatures invisible to symptom-based stratification. (eingereicht)

Modirshanechi, A.; Eysenbach, B.; Dayan, P.; Schulz, E.: Unifying Goal-Conditioned RL and Unsupervised Skill Learning via Control-Maximization. (eingereicht)

Shen, T.; Dayan, P.: M^3: Meta-cognition and Meta-control with Markov Decision Processes. (eingereicht)

Zhou, H.; Nagy, D.; Dayan, P.; Wu, C.: Path-dependent program induction under resource constraints explains human sequence learning. (eingereicht)

Chebolu, S.; Zhang, P.; Ma, W.; Dayan, P.: Now or later: A reinforcement learning model of behavioural delay. (eingereicht)

Lloyd, K.; Cohen, J.; Dayan, P.: Strategic preparation in task-switching paradigms: which task set to prepare and when? (eingereicht)

Nazemorroaya, A.; Batten, S.; Grunfeld, I.; Torres, A.; Celaya, X.; Moreland, A.; Lattuca, C.; Wagle, A.; Nikjou, D.; Barbosa, L. et al.; Lohrenz, T.; Chiu, P.; Brewer, G.; McClure, S.; Witcher, M.; Bina, R.; Read Montague, P.; Dayan, P.; Bang, D.: Dopamine dynamics in human anterior cingulate cortex during Pavlovian-instrumental conflict. (eingereicht)

Rubino, V.; Dayan, P.; Wu, C.: Simplicity guides the discovery and use of compositionality. (eingereicht)