Nathaniel D. Daw
Affiliations: | New York University, New York, NY, United States | ||
| Princeton University, Princeton, NJ |
Area:
Reward, learning, and decision makingWebsite:
http://www.cns.nyu.edu/~daw/Google:
"Nathaniel Daw"Mean distance: 12.82 (cluster 23) | S | N | B | C | P |
Parents
Sign in to add mentor| Mark Gluck | research assistant | Rutgers, New Brunswick | ||
| David Touretzky | grad student | 2003 | Carnegie Mellon | |
| (Reinforcement learning models of the dopamine system and their behavioral implications.) | ||||
| Peter Dayan | post-doc | UCL | ||
Children
Sign in to add trainee| Yoel Sanchez Araujo | research assistant | Princeton | |
| Lindsay E. Hunter | grad student | Princeton | |
| Sarah A. Hutter | grad student | Princeton | |
| Yoel Sanchez Araujo | grad student | Princeton | |
| Oliver M Vikbladh | grad student | Princeton Neuroscience Institute | |
| Sarah Jo Venditto | grad student | 2017- | Princeton |
| Yotam Sagiv | grad student | 2018- | Princeton |
| Dylan Alexander Simon | grad student | 2007-2012 | NYU |
| Nicholas J Gustafson | grad student | 2013 | NYU |
| Aaron M. Bornstein | grad student | 2007-2013 | NYU |
| Hanneke EM den Ouden | post-doc | NYU | |
| Steve Fleming | post-doc | ||
| Ari E. Kahn | post-doc | Princeton | |
| Jian Li | post-doc | NYU | |
| Ross Otto | post-doc | NYU | |
| P Dylan Rich | post-doc | Princeton | |
| Hang Zhang | post-doc | 2011- | NYU |
| Ida Momennejad | post-doc | 2015- | Princeton |
| Marcelo Gomes Mattar | post-doc | 2016- | Princeton |
| Sam J. Gershman | research scientist | 2007-2008 | NYU |
Collaborators
Sign in to add collaborator| Nina Galbraith Curley | collaborator | NYU | |
| Song Qi | collaborator | ||
| G. Elliott Wimmer | collaborator | 2007- | Columbia |
| Sreejan Kumar | collaborator | 2019- |
BETA: Related publications
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Publications
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| Sagiv Y, Akam T, Witten IB, et al. (2024) Prioritizing replay when future goals are unknown. Biorxiv : the Preprint Server For Biology |
| Venditto SJC, Miller KJ, Brody CD, et al. (2024) Dynamic reinforcement learning reveals time-dependent shifts in strategy during reward learning. Biorxiv : the Preprint Server For Biology |
| Jahn CI, Markov NT, Morea B, et al. (2024) Learning attentional templates for value-based decision-making. Cell |
| Tafazoli S, Bouchacourt FM, Ardalan A, et al. (2024) Building compositional tasks with shared neural subspaces. Biorxiv : the Preprint Server For Biology |
| Bustamante LA, Oshinowo T, Lee JR, et al. (2023) Effort Foraging Task reveals positive correlation between individual differences in the cost of cognitive and physical effort in humans. Proceedings of the National Academy of Sciences of the United States of America. 120: e2221510120 |
| Kumar S, Dasgupta I, Daw ND, et al. (2023) Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. Plos Computational Biology. 19: e1011316 |
| Krausz TA, Comrie AE, Kahn AE, et al. (2023) Dual credit assignment processes underlie dopamine signals in a complex spatial environment. Neuron |
| LeDoux J, Birch J, Andrews K, et al. (2023) Consciousness beyond the human case. Current Biology : Cb. 33: R832-R840 |
| Zorowitz S, Chierchia G, Blakemore SJ, et al. (2023) An item response theory analysis of the matrix reasoning item bank (MaRs-IB). Behavior Research Methods |
| Nicholas J, Daw ND, Shohamy D. (2022) Uncertainty alters the balance between incremental learning and episodic memory. Elife. 11 |