Publications:
Department for Computational Neuroscience

Journal Article (1)

1.
Journal Article
Moutoussis, M.; Bullmore, E.; Goodyer, I.; Fonagy, P.; Jones, P.; Dolan, R.; Dayan, P.: Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood. PLoS Computational Biology 14 (12), pp. 1 - 26 (2018)

Book Chapter (1)

2.
Book Chapter
Dayan, P.; Nakahara, H.: Models and Methods for Reinforcement Learning. In: Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Vol. 5: Methodology, 4. Ed., pp. 1 - 40 (Eds. Wixted, J.; Wagenmakers, E.-J.). Wiley, Hoboken, NJ, USA (2018)

Talk (4)

3.
Talk
Dayan, P.: Neural Reinforcement Learning 3: The Self and the Other. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)
4.
Talk
Dayan, P.: Neural Reinforcement Learning 2: Choice. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)
5.
Talk
Dayan, P.: Neural Reinforcement Learning 1: Prediction. Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence, Trieste, Italy (2018)
6.
Talk
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)

Working Paper (1)

7.
Working Paper
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)
Go to Editor View