Peter Dayan
Impact in
- General Decision Sciences top 0.05%
- Cognitive Neuroscience top 0.01%
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- Memory and Neural Mechanisms
- Functional Brain Connectivity Studies
Papers in
-
- Neural dynamics and brain function 142
- Neural and Behavioral Psychology Studies 110
- Memory and Neural Mechanisms 57
- Visual perception and processing mechanisms 35
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- Neurotransmitter Receptor Influence on Behavior 41
- Co-authors
- Christopher J. Watkins (2 shared papers)Raymond J. Dolan (76 shared papers)P. Read Montague (19 shared papers)Nathaniel D. Daw (14 shared papers)Wolfram Schultz (1 shared paper)Yael Niv (11 shared papers)John P. O’Doherty (7 shared papers)L. F. Abbott (1 shared paper)
- Journals
- PLoS Computational Biology (35 papers)Neural Computation (18 papers)Journal of Neuroscience (16 papers)Proceedings of the National Academy of Sciences (13 papers)Nature Neuroscience (12 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Peter Dayan
418 papers receiving 54.0k citations
Peter Dayan's Hit Papers
Peers
Comparison fields: 5 of 225
- General Decision Sciences 3.3k
- Cognitive Neuroscience 31.2k
- Cellular and Molecular Neuroscience 11.9k
- Experimental and Cognitive Psychology 6.4k
- Applied Psychology 1.7k
Countries citing papers authored by Peter Dayan
This map shows the geographic impact of Peter Dayan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Peter Dayan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Dayan more than expected).
Fields of papers citing papers by Peter Dayan
This network shows the impact of papers produced by Peter Dayan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Peter Dayan. The network helps show where Peter Dayan may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Dayan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 451 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Q-learning Hit paper breakdown → | 1992 | 6829 |
| 2 | A Neural Substrate of Prediction and Reward Hit paper breakdown → | 1997 | 6253 |
| 3 | Technical Note: Q-Learning Hit paper breakdown → | 1992 | 2332 |
| 4 | Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems Hit paper breakdown → | 2001 | 2020 |
| 5 | Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control Hit paper breakdown → | 2005 | 1642 |
| 6 | Dissociable Roles of Ventral and Dorsal Striatum in Instrumental Conditioning Hit paper breakdown → | 2004 | 1585 |
| 7 | Cortical substrates for exploratory decisions in humans Hit paper breakdown → | 2006 | 1517 |
| 8 | A framework for mesencephalic dopamine systems based on predictive Hebbian learning Hit paper breakdown → | 1996 | 1422 |
| 9 | Uncertainty, Neuromodulation, and Attention Hit paper breakdown → | 2005 | 1192 |
| 10 | Model-Based Influences on Humans' Choices and Striatal Prediction Errors Hit paper breakdown → | 2011 | 1124 |
| 11 | Temporal Difference Models and Reward-Related Learning in the Human Brain Hit paper breakdown → | 2003 | 1108 |
| 12 | States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning Hit paper breakdown → | 2010 | 812 |
| 13 | Tonic dopamine: opportunity costs and the control of response vigor Hit paper breakdown → | 2006 | 795 |
| 14 | The Helmholtz Machine Hit paper breakdown → | 1995 | 718 |
| 15 | Goals and Habits in the Brain Hit paper breakdown → | 2013 | 669 |
| 16 | The Effect of Correlated Variability on the Accuracy of a Population Code Hit paper breakdown → | 1999 | 607 |
| 17 | Opponent interactions between serotonin and dopamine Hit paper breakdown → | 2002 | 602 |
| 18 | The "Wake-Sleep" Algorithm for Unsupervised Neural Networks Hit paper breakdown → | 1995 | 571 |
| 19 | Reward, Motivation, and Reinforcement Learning Hit paper breakdown → | 2002 | 557 |
| 20 | Computational psychiatry Hit paper breakdown → | 2011 | 538 |
About Peter Dayan
Peter Dayan is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Artificial Intelligence, Experimental and Cognitive Psychology and General Decision Sciences, having authored 451 papers that have together received 55.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (142 papers), Neural and Behavioral Psychology Studies (110 papers), Memory and Neural Mechanisms (57 papers), Mental Health Research Topics (45 papers), Neurotransmitter Receptor Influence on Behavior (41 papers), Neural Networks and Applications (36 papers), Visual perception and processing mechanisms (35 papers) and Decision-Making and Behavioral Economics (33 papers). The work is most often cited by research in General Decision Sciences (3.3k citations), Cognitive Neuroscience (31.2k citations), Cellular and Molecular Neuroscience (11.9k citations), Experimental and Cognitive Psychology (6.4k citations) and Applied Psychology (1.7k citations). Peter Dayan has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Christopher J. Watkins, Raymond J. Dolan, P. Read Montague, Nathaniel D. Daw, Wolfram Schultz, Yael Niv, John P. O’Doherty, L. F. Abbott, Angela J. Yu and Ben Seymour. Their work appears in journals such as PLoS Computational Biology, Neural Computation, Journal of Neuroscience, Proceedings of the National Academy of Sciences and Nature Neuroscience.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.